# International Workshop on Medical Ultrasound Tomography

14.-15. Oct. 2019, Wayne State University, Detroit, Michigan, USA

### PROCEEDINGS

Edited by Christian Böhm, Torsten Hopp, Nicole Ruiter, Neb Duric

Christian Böhm et al. (Eds.)

//

International Workshop on Medical Ultrasound Tomography 2019

C. Böhm, T. Hopp, N. Ruiter, N. Duric (Eds.)

### International Workshop on Medical Ultrasound Tomography

14.-15. Oct. 2019, Wayne State University, Detroit, Michigan, USA | Proceedings

## International Workshop on Medical Ultrasound Tomography

14.-15. Oct. 2019, Wayne State University, Detroit, Michigan, USA | Proceedings

Edited by Christian Böhm Torsten Hopp Nicole Ruiter Neb Duric

#### **Impressum**

Karlsruher Institut für Technologie (KIT) KIT Scientific Publishing Straße am Forum 2 D-76131 Karlsruhe

KIT Scientific Publishing is a registered trademark of Karlsruhe Institute of Technology. Reprint using the book cover is not allowed.

www.ksp.kit.edu

*This document – excluding the cover, pictures and graphs – is licensed under a Creative Commons Attribution-Share Alike 4.0 International License (CC BY-SA 4.0): https://creativecommons.org/licenses/by-sa/4.0/deed.en*

*The cover page is licensed under a Creative Commons Attribution-No Derivatives 4.0 International License (CC BY-ND 4.0): https://creativecommons.org/licenses/by-nd/4.0/deed.en*

Print on Demand 2021 – Gedruckt auf FSC-zertifiziertem Papier

ISBN 978-3-7315-1054-3 DOI 10.5445/KSP/1000124805

## Preface

This volume represents the second in a series of proceedings from biannual international workshops held under the heading of Medical Ultrasound Tomography (MUST). The inaugural workshop - MUST 2017 - was held in Speyer, Germany. Presented here are the proceedings from MUST 2019, a workshop that was held in Detroit, MI, USA on the grounds of Wayne State University.

We thank the Dean of the College of Engineering, Dr. Farshad Fotouhi, for his academic and financial support, and for providing access to the meeting venue. We also thank Dr. Juri Gelovani, the leader of the Molecular Imaging Program at the Karmanos Cancer Institute for use of program funds to support the logistical costs of the workshop. Without the support of Drs. Fotouhi and Gelovani, this meeting would not have been possible.

This workshop was notable for its historical context.  Dr. Glover was the first scientist to publish in-vivo sound speed images of the breast over 40 years ago!

Ultrasound Tomography is an emerging technology for medical imaging that is rapidly approaching clinical utility. Multiple research groups around the globe are engaged in research, spanning theory to practical clinical applications and commercialization. This twoday MUST workshop was held October 14-15, 2019. It was designed to be interactive and bring together the growing ultrasound tomography community, for the purpose of discussing and exchanging new ideas and research results, with each other and with researchers from related fields. The invited talks are listed below.

The program of the two-day workshop included six invited talks, 21 oral presentations and 15 posters. The presentations covered the history and future trends of Ultrasound Tomography, the clinical motivation and status of breast imaging as well as commercial developments.

Dedicated discussion sessions with the audience covered the current challenges and future directions of ultrasound tomography. The conference was attended by 42 participants from 10 countries who actively contributed to a very successful workshop.

Oral and poster presenters were asked to submit a one-page abstract before the workshop, which was reviewed by the scientific committee. Authors of accepted abstracts as well as the invited speakers were asked to submit a full paper. This book comprises the written versions of most of the contributions presented during the workshop and thereby provides an overview of the state of the art in medical ultrasound tomography.

We would like to sincerely thank all the colleagues involved in the scientific and local committee for their commitment.

Neb Duric, Kierstin Fiscus and Juri Gelovani Wayne State University, USA

Roman Maev University of Windsor, Canada

Torsten Hopp and Nicole Ruiter Karlsruhe Institute of Technology, Germany

Christian Boehm ETH Zurich, Switzerland

Mark Anastasio University of Illinois, USA

Detroit, July 2020

## Special Acknowledgements

The members of the scientific and local organizing committees are indebted to Kierstin Fiscus for her untiring efforts in support of MUST 2019. She carried the bulk of the organizational burden before during and after the workshop. She facilitated the interactions between the organizing committees, and coordinated communications with individual attendees. Kierstin worked behind the scenes to coordinate hotels, caterers and restaurants in support of the workshop. Furthermore, she played a central role in gathering materials for these proceedings. Her professionalism facilitated all aspects of the organizational work and her good humor and cheerfulness made the whole process enjoyable. All in all, her support was vital to the success of MUST 2019.

Thank you Kierstin!

## Workshop Organization

## Scientific Committee

Neb Duric Wayne State University, US Delphinus Medical Technologies, US

Torsten Hopp Karlsruhe Institute of Technology, Germany

Nicole V. Ruiter Karlsruhe Institute of Technology, Germany

Christian Boehm ETH Zurich, Switzerland

Mark Anastasio University of Illinois, US

## Local Organizing Committee

Juri Gelovani Wayne State University, US

Neb Duric Wayne State University, US Delphinus Medical Technologies, US

Roman Maev University of Windsor, Canada

Kierstin Fiscus Wayne State University, US

## Session Chairs

Nicole V. Ruiter Karlsruhe Institute of Technology, Germany

Neb Duric Wayne State University, US Delphinus Medical Technologies, US

Peter Littrup Delphinus Medical Technologies, US

Christian Boehm ETH Zurich, Switzerland

Mohammad Mehrmohammadi Wayne State University, US

Torsten Hopp Karlsruhe Institute of Technology, Germany

# Workshop Impressions

## **Table of Contents**

#### **Systems** 49

#### **Poster papers and abstracts** 189

# Keynote and Invited Talks

## Ancient Ultrasound Tomography and MRI Perspectives of Breast Cancer

Gary Glover, Ph.D.1

1*Stanford University, CA, USA*

#### Biography

Gary H. Glover received his PhD in Electrical Engineering from the University of Minnesota in 1969. He joined GE's Corporate Research & Development (CR&D) Labs in Schenectady, New York and studied solid state devices, computed ultrasound tomography and X-ray computed tomography until 1976, when he moved to GE's Medical Systems in Milwaukee to help transition fan-beam CT technology from CR&D. In 1980, he began the development of MRI as one of a team of five, and was thus instrumental in defining both the CT and MR products for GE. He joined Stanford's Radiology Department as Professor in 1990 and founded the Radiological Sciences Laboratory, dedicated to advancing biomedical imaging. His field of research is in MRI physics in general, and specifically in the development and application of functional MRI (fMRI) methods since 1993. His students' recent contributions include optimized techniques for acquisition and analysis of fMRI data, characterization of the dynamics of brain networks, development of real-time fMRI biofeedback methods, and multimodal neuroimaging using fMRI combined with EEG, fNIRS, fPET and functional MR Elastography, as well as with neuromodulatory transcranial electrical and magnetic stimulation.

He is a member of the US National Academy of Engineering and a Fellow of the American Institute for Medical and Biomedical Engineering (AIMBE) as well as the International Society for Magnetic Resonance in Medicine (ISMRM), for which he is also Past President. He holds a number of other awards including RSNA's Outstanding Researcher Award and ISMRM's Gold Medal, as well as Distinguished Investigator of the Academy of Radiology and the International Academy of Biomedical Engineers.

He has authored approximately 50 patents and published some 400 papers on his research.

## Transcranial Ultrasound Brain Imaging (TUBI) Solution for Point-of-Care Diagnosis of Traumatic Brain Injuries

E. Malyarenko1

1 *University of Windsor, Ontario, Canada, E-mail<EMAIL_ADDRESS>
## Abstract

Portability, safety, speed, cost, user friendliness, and accuracy of the final diagnosis are the most important aspects of any clinical diagnostic equipment. Although dramatic progress has been made in the area of medical diagnostic imaging, contemporary equipment still often relies on ionizing radiation and is bulky, costly, and difficult to use. Hence the quest for miniaturization and safety continues, as well as the efforts to solve new challenging diagnostic problems and a few highly professional research groups working pretty hard in this field during last decade worldwide, including us.

In this presentation, the author will provide an overview of current R&D status in this field and in more details introduce our latest results in developing Transcranial Ultrasound Brain Imaging (TUBI) complex solution for accurate and rapid on-site diagnosis of certain types of Traumatic Brain Injuries, e.g. Brain Hematomas, without resorting to current gold standard imaging tools, such as computed tomography (CT) and magnetic resonance imaging (MRI).

This presentation will address a fundamental problem in ultrasonic imaging: the inverse problem, that is, the need to recover parameters/image of target objects hidden from external observation by a barrier (e.g. acoustically non-transparent obstacle like the human skull). Ultrasonic waves propagating through multilayer thick skull bone undergo multiple reflections, strong beam distortions, phase aberration, and get considerably attenuated. Target abnormalities behind the skull bone can be static (e.g. bone fragments and blood clots) and dynamic (e.g. vasculature blood flow disruptions such as hemorrhage and aneurysm), making the detection of head trauma even more difficult. Our solution involves new highly efficient real-time image formation algorithms, improving the transcranial image contrast for better pathology detection, and mathematical morphology-based interpretation for both static and dynamic target abnormalities that will ultimately produce high quality digital images of the human brain. Our final strategic goal is the clinical development and modification of the TUBI solution into an effective portable device for emergency personnel, sonographers, and physicians.

## Clinical Implications of Screening Breast Ultrasound: Past, Present and Future

Rachel Brem, M.D.1

1 *George Washington University School of Medicine & Health Sciences, D.C., USA*

## Abstract

This presentation will discuss the importance and clinical implications of dense breast tissue, how screening breast ultrasound can improve the detection of breast cancer, the challenges of implementing screening breast ultrasound and what the future holds in terms of technological improvement in breast ultrasound in detecting mammographically occult breast cancer as well as the increasingly important role of ultrasound and ultrasound based technologies in individualized breast cancer risk assessment.

### Biography

Dr. Rachel Brem is the Director of Breast Imaging and Intervention at The George Washington University Medical Center, Professor of Radiology and the Vice Chairman of the Department of Radiology. In 2015 Dr. Brem was named the Program Leader for Breast Cancer at the GW Cancer Center. Dr. Brem completed her undergraduate studies at Brandeis University followed by medical school at Columbia University where she graduated with honors. Dr. Brem completed both her Diagnostic Radiology Residency and Breast Imaging Fellowship at the John Hopkins Medical Institutions. Since completion of her training Dr. Brem was on the faulty at John Hopkins as the Director of Breast Imaging. Currently she is the Director of Breast Imaging and Interventional Center at the George Washington Medical Institution and Professor of Radiology. Dr.  She currently directs multi-institutional clinical trials evaluating novel approaches to improved diagnosis of breast cancer and is the recipient of numerous honors and awards including Best Cancer Doctors (Newsweek), Castle Connolly Best Doctors for Cancer and Top Doctor, Jewish Woman International's Ten Women to Watch, the prestigious fellowship in the American College of Radiology and the Society of Breast Imaging. She is an internationally recognized expert on Breast Cancer who is sought to speak on the subject nationally and internationally. Dr. Brem has extensively published, and is also committed to mentoring of students and residents. She is on the scientific advisory board of The Prevent Cancer Foundation as well as FORCE (Facing our risk of cancer, for women who are BR CA positive) and is a member of the Board of the Katzen Cancer Research Center. She currently serves on the Board of Directors of Delphinus Medical Technologies and Dilon Technologies and served on the Board of Directors of iCAD, inc from 2002-2019.

Dr. Brem is the Director of the George Washington University Mobile Mammography program (Mammovan), a mobile van that brings mammography to underserved communities to optimize the care of all women.

Dr. Brem was part of the formation of the Brem Foundation to Defeat Breast Cancer in 2004 with a group of committed patients and friends who have worked diligently to support translational research as well as education and clinical care in the underserved community. The Brem Foundation has recently been instrumental in passing dense breast legislation in the District of Columbia which has the highest death rate from cancer nationally.

## A History of US Transmission Tomography Emphasizing Some Approaches Out of the Mainstream

P. L. Carson1,2

1 *Department of Radiology, Unversity of Michigan, Ann Arbor, Michigan, USA E-mail<EMAIL_ADDRESS>
2 *Department of Biomedical Engineering, Unversity of Michigan, Ann Arbor, Michigan, USA*

## Abstract

As head of the second group to present on ultrasound transmission tomography (UTT), I switched from emphasizing speed of sound (SOS) imaging to attenuation and pulse echo imaging. Confocal, 19 mm diameter transducers in translate-rotate geometry performed better in those roles than did small diameter transducers used in the Mayo Clinic and General Electric efforts designed primarily for SOS imaging. While bent ray SOS imaging was being explored in the mainstream, phase insensitive receivers were considered for less edge enhancement and other artifacts in attenuation imaging. This simpler approach to quantitative attenuation imaging has only recently been revived for medical imaging. Other body parts than breast were considered, as well as imaging of other tissue characteristics. In the mid 80's, clinical trials of commercial automated breast imaging systems were judged by radiology leaders to be unsuccessful and research funding of quantitative imaging and "over-sold" tissue characterization went down with those systems. S. Johnson's Techniscan worked consistently through two down decades and UCT improved considerably with good bent-ray and then full wave migration or inversion imaging. Acquired by QT Ultrasound, the 3D full wave reconstructions have now been performed with the system. Competition from the simpler, but well sampled ring array of Delphinus Medical Technologies has moved UTT close to clinical acceptance. We began work on limited angle transmission tomography in the mammographic geometry, leading to use of pulse echo information to fill in missing data. The concept of bulk attenuation coefficient was introduced to minimize domination of attenuation images by losses at major boundaries delineated in pulse echo and transmission modes. With less than full apertures, the distinction between transmission and pulse echo imaging becomes less distinct. Tomography of bulk tissue properties by pulse echo systems is again worth consideration, as is combination of transmission data with other ultrasound modes and thermoacoustic imaging for increased image quality and information.

*Keywords:* Medical Imaging, Review, Quantitative Acoustics

Figure 1: Clockwise from top left: From first UTT paper: Diagram of experimental system; schematic of analytic reconstruction technique; Algebraic reconstruction of acoustic "absorptions" within that approximate cross section; photo of transverse cross section through canine heart.

## 1 Earliest UTT

The term Ultrasonic CT or UCT is used with systems detecting the transmitted waves as is an x-ray CT. Taken literally, ultrasound computed tomography could be applied to the earliest pulse echo ultrasound images, if you don't limit the term to digital computing. I prefer ultrasound transmission tomography (UTT) for the transmission modes, ultrasound reflection tomography (URT) for the reflection modes and UCT in general. All borrowed images are adapted with permission from the adjacent references.

Greenleaf, Johnson and colleagues at the Mayo Research Foundation presented the first UTT constructions in July, 1973 (Figure 1) [1]. They modified a rectilinear radioisotope scanner for the rotate translate geometry with an 8 bit transient recorder and a 5 MHz transmitting and a 2.25 MHz receiving transducer. Reconstruction with the Algebraic reconstruction technique (ART) [2] produced ultrasound absorption images that were soon recognized as images of the broadband attenuation coefficient.

Figure 2: Left: Diagram of transmission tomography of the refactive index and plot of the deviation of the beam at the receiver, D*h/r*, as a function of the fractional distance to the edge of imaged refracting cylinder [4]. Right: Image of the refractive index of a section through a heart, in vitro (left). A photograph of the approximate section of the heart (right).

The first time of flight images (Figure 2) were presented in 1975, showing strong promise for UTT [3]. Gary Glover at GE Global Research produced a comparable SOS imaging system ready for human studies, with results discussed later with other human studies.

With the help of the head of medical physics at the University of Colorado, William Hendee, I and, particularly, a medical student Gary Thieme, and others, built a treatment planning CT scanner using a Co60 source. I had just started medical ultrasound research and the extension to ultrasonic CT seemed possible. We started with Howry and Holmes' translate/rotate pulse echo water tank scanner from the 1950's, unaware of Greenleaf and Johnson's work until their presentation at the Seminar on Ultrasonic Tissue Characterization in May, 1975 [4]. As their best scanner was optimized for speed of sound (SOS) imaging, we began emphasizing attenuation imaging. The confocal, 19 mm diameter transducers, were expected to be better for spatial resolution in pulse echo and attenuation imaging of the breast, with less attenuation artifact in the latter [5]. Also for originality, we chose to explore the possibility of imaging through bone. Perry and Altschuler at NCAR in Boulder ran on one of the fastest commercial mainframes, a mathematically rigorous least-mean-squares method, similar in philosophy to that described by Marr's polynomial solution of an orthogonal set of Radon Transforms [6]. They achieved a bit more fidelity [5] than our filtered backprojection reconstruction shown in Fig. 3. Images of a lamb shank were of similar quality.

Figure 3: Clockwise from top left: (a) Water-path scanning mechanism adapted to UTT imaging; (b) Phantom comprised of a balloon of castor oil, one of Dow Corning 710 silicone oil and an aluminum rod; (c) Sketch of cross section of the phantom; (d) Broadband attenuation coefficient image through approximately the same cross section. Rectangular ROIs are show for water quantification; (e) We got semiquantitative information as shown in the histograms.

## 2 Reducing Effects in Attenuation Images of Diffraction at Tissue Boundaries

Avinash Kak at Purdue and a series of graduate students contributed many innovations over a decade. His earliest work on using just signal processing to reduce artifacts in the attenuation images were not very successful [7]. However, an earlier publication aimed at imaging the attenuation coefficient of tissue types rather than heavily edge-enhancing refraction/diffraction effects at borders [8,9], showed good paths forward (Fig. 4). The broadband correction in Fig. 4d) seems to do most poorly in that regard, showing the edge effects with high fidelity.

Figure 4: (a) Center frequency shift by Gaussian fit; (b) Energy ratio in lower/upper frequency windows; (c) Narrow band assumption; (d) Broadband correction.

The student Azimi worked with Kak on multiple scattering effects in diffraction tomography [10], a method of solving the wave equation with weak scattering assumptions, discussed later. In Fig. 5, with a weak scattering approximation (left) you get beautiful images of 2, 6l cylinders, but if you include the presence of multiple scattering [11], you end up with the substantial artifacts (Fig. 5b), even for cylinders with breast tissue-like, 1.05, index of refraction. Anderson and Kak introduced the long popular SART algorithm with application to SOS UTT [12]. They state "we compute the individual correction terms..." for beam profile and length of path through a pixel. "The terms are then saved until all rays in that view have been considered. The average correction to each picture element is computed and added to form the updated image". They note that the method is applicable for curved ray paths in US and microwave tomography.

Figure 5: (a) Weak scattering using Born or Rytov approximation; (b) Doubly scattered fields included in the projection data.

Fig. 6 a)-c) shows reconstructions of the numeric Shepp-Logan Phantom. The single iteration of Art shows a very course noise from amplification of statistical fluctuations 6a). The reconstruction is much smoother and accurate using a single iteration of simultaneous ART 6b). Convolution back projection, however, gave an image 6c) very similar to that of the numerical phantom. At least both of the art methods used a longitudinal Hamming window, meaning along the path of the ultrasound ray. Zero weighting was at the boundaries of the Reconstructed overall object 6d). A.J. Devaney and others made early contributions to this approach [13-16].

Figure 6: (a) Single iteration ART; (b) Single iteration SART; (c) Convolution backprojection; (d) Longitudinal Hamming window.

Using phase insensitive receivers to minimize phase cancellation artifacts and resulting edge enhancement in attenuation imaging was pioneered by Jim Miller and his students and postdocs particularly Klepper [17]. They produced a very prescient analysis of the various mechanisms for artifacts in attenuation images with transmission tomography and ranked them according to their probable importance in the reconstructed images. These and their proposed solutions for the varios types of artifacts are summarized well in Table 1 from their publication.

Figure 7: (a) Attenuation image, phase sensitive, focused, 19 mm piezoelectric receiver; (b) Phase-insensitive processing, with simulated linear array of 40 point-like elements.

Chenevert et al. showed that phase insensitive processing with point-like elements in a simulated 40 element linear array could eliminate many attenuation artifacts in a cylindrical geometry [18]. This demonstration was accomplished, for each transmitter position of a 19 mm diameter, single element transducer, by scanning a small needle hydrophone across the image plane path of the transmitted beam. The image in b) is quite good reconstruction of this phantom, which was designed to be difficult, given the straight edges of the upper left quadrant insert.

Modern phase insensitive Imaging is being done [19], achieving less edge enhancement of most of objects when the PVDF detectors are used with phase insensitive electronics. PVDF polymer detectors are not quite as sensitive as PZT, particularly on transmit. For reception, however, they are pretty comparable Zeqiri et al. are getting some interesting results with large detectors.

## 3 Other Algorithms

A classification of UTT reconstruction algorithms was published in 2013 [20] as:

	- Straight Ray
	- ART, Filtered Back Projection
	- Bent Ray
	- Weak Scattering
	- Distorted Wave Born Analysis
	- Inverse Scatter Tomography (IST)

### 3.1 Diffraction Tomography

In diffraction tomography, weak scattering is usually assumed in the form of the Born or Rytov approximation. An approximate solution to the wave equation was given by Mueller et al. [21] as: Write the function *F*(*r*), where *k* is the wave number 2p*/*l and *c* and *c*0 are the local and surrounding medium speeds of sound, respectively.

$$^{\text{un}}F(\bar{r}) = k^2 \left( 1 - \frac{c\_0^2}{c^2(\bar{r})} \right). \text{ (1) } \quad \text{... write the wave equation as} \quad \left( \nabla^2 + k^2 \right) \Psi = F(\bar{r}) \Psi. \text{(2) }^{\text{un}}F$$

where y is the particle velocity potential. "By definition the function *F*(*r*¯) is zero for *|r*¯*| > a*, the radius of the assumed circular object. We shall further assume that its mean is zero. This can always be achieved by appropriate choice of *cO*. Eq. (2) can be transformed ... by introducing

$$
\mu = \ln \Psi \text{ (3)} \quad \text{and substituting into (1)} \quad \nabla^2 \mu + (V\mu)^2 + k^2 = F(\mu). \text{ (4)}
$$

If one considers *F*(*r*¯) as a small perturbation one can formally solve (2) and (4) by a perturbation method. The first order approximation obtained by this method from (2) is known as Born's approximation ... and ... from (4) as Rytov's approximation ..."

Allowing for somewhat stronger interactions, the distorted wave Born approximation offers some improvement over simple Born or Rytov approximations [22]. A much more in-depth review of reconstruction algorithms is included in [23].

Table 1: Mechanisms for artifacts in attenuation images with transmission tomography, ranked according to their probable importance in the reconstructed images.

## 4 Human Studies

The first human study of UTT was reported by Glover at GE [24]. The results in Table 2 show a trend of increasing speed of sound with expected connective tissue content. Later data shows some fibroadenomas with Cancer-like speeds of sound.

The first human study of SOS and relative attenuation coefficient, *µ* in numerous women [25] showed modestly promising results from imaging of 150 women with a total of 30 breast cancers from which 19 were analyzed in Fig. 8b. Attenuation was not a strong discriminant as might be expected from the image in Fig. 8a.

This publication was followed by results on 78 women, including 40 cancers, with complete data from 175 scans [26]. They concluded that "Images of the local speed of ultrasound show high values in regions of muscle, breast parenchyma, medullary carcinoma and connective tissue and show low values in regions of fat. Images of acoustic attenuation show high values in regions of connective tissue and borders of scirrhus carcinoma and low values in regions of fat." If UTT of the relatively rare medullary carcinoma does indeed contribute to its B-mode discrimination from benign solid masses such as fibroadenoma, that might allow noninvasive diagnosis to avoid biopsying many, subsequently benign, solid masses.

Figure 8: (a) Images of a carcinoma in upper left; (b) Attenuation and SOS plot for relevant tissues in breast with a mass.

In 40 participants with unequivocal lesions, from the 95 studied, the differences between SOS and *µ* in the mass and their values in the remaining central mammary tissues provided the discrimination in Fig. 9a [27]. These results were similar to those of the two earlier human studies that utilized the raw SOS and *µ* of the mass [25,26]. Actual SOS and *µ* ranges were very similar to those earlier studies, suggesting that normalization relative to,

Table 2: Study on 16 patients with breast lesions and 4, young asymptomatic women [24]. Reprinted with permission.

Table 3: Reprinted with permission from [26]. The increase in specificity and positive predictive value over mamography might be expected just from doing B-mode ultrasound.

Figure 9: Results from [27]. Discrimination of three mass types by two linear discriminate functions of four tissues in the involved breast. The three masses are Benign solid - label 2, cystic - 3, and cancer - 5.

or inclusion of tissues other than the mass might not be necessary. This question was not clearly answered in this small study, but might be considered further with quantitative 3D imaging. Comparison with the contralateral breast for anatomy and tissue properties is certainly used in visual diagnoses. When SOS and *µ* in ten tissue regions of the participants' two breasts were evaluated by linear discriminate analysis, one nonmass tissue region contributed slightly to the discrimination. In order of importance in the discrimination of 3 key mass types were the tissue regions: a) the SOS in the mass including all of the border region seen in the attenuation image, b) SOS in the normal parenchyma of the involved breast, c) *µ* in the mass as defined on SOS image, i.e., usually not including the enhanced edge in the *µ* image, d) *µ* in the entire involved breast (Fig. 9b).

A good, recent plot of *µ* as a function of SOS, Fig. 10, is from a study with a commercial prototype scanner, now commercially available in an upgraded form. The images [28] are much better than previously. There is good separation between cancers in the red rectangles and other tissues, giving some hope for UTT as a screening, diagnostic and prognostic tool. This hope is particularly true if done in combination with pulse echo or other advanced reflection mode imaging comparable to current clinical ultrasound that provides better screening in dense breasts than digital mammography [29]. Despite diffraction artifacts providing edge enhancement in the attenuation images, *µ* seems to be a bit better discriminator than with earlier systems. Cysts, green circles, and compex cysts, blue circles, are well separated by *µ*. The general trends are still similar those of the earlier systems and investigators.

With the Delphinus system, substantial lesion characterization analysis was performed on reflection, SOS and *µ* images of 107 benign masses and 31 cancers [30]. Lesion boundaries and reflectivity were added tot he usual UTT measures. PPV was 91% for a sensitivity of 97%.

Figure 10: Discrimination of various masses in 125 participants using a commercial prototype system employing full wave inverse scatter reconstructions. Small colored square outlines are for cases shown as examples in [20].

## 5 Available for Diagnosis

The two primary, commercially available UTT systems are shown in Fig. 11. Both are FDA approved for diagnosis and are in clinical trials for breast cancer screening. No information is expected from those trials until they are completed. Both systems now employ or are beginning to employ full wave inversion reconstructions.

Recent advanced capabilities in commercially available, or soon to be available options include Delphinus's stiffness imaging in multimode displays (Fig. 12) and QT Ultrasound's 3D full wave inversions in times at or approaching clinical utility (Fig 13) [32]. Examples suggest that the stiffness does provide some additional information [33].

With a 1.75D array receiver, QT Ultrasound achieved, in 2017, 3D reconstructions of an entire breast (Fig. 13) in ⇠35 min, with a scan time of 7 min [32]. When the image plane is at steep angle of incidence to the skin, when near the end of the breast and for relatively flat breasts, diffraction causes large artifacts near the edges of the breast. The outline of the

Figure 11: Two commercially available UTT systems. Left: Delphinus SoftVue [31] system with 2048 element ring array operating at up to 2.5 MHz; Right: QT Ultrasound's system with a large, planar transmitter, a 1536 element transmitter and receiver array operating at 0.3 to 1.3 MHz and three conventional curved linear arrays conventional pulse echo imaging [32].

Figure 12: New "stiffness" imaging mode on the Delphinus system. In both cases, SOS and composit reflection mode and SOS-corrected stiffness and attenuation are shown on the top left and right, respectively. Red arrows point to the mass in each. (a) The infiltrating ductal carcinoma is red, i.e., stiff. Left and right bottom are the magnified SOS image and state of the art pulse echo image with a conventional hand held transducer. (b) The complex cyst is somewhat stiff (arrow) and the cysts are not colored, i.e., not stiff nor attenuating. Left and right bottom images are reflection mode and magnified SOS, respectively. Figure adapted from [33].

breast is shrunk in the 2D reconstructions and information is lost, particularly in the critical subareolar area.

In an axial plane of the 3D-reconstruction (top of the lower pair of images) much greater fidelity and detail is revealed in the skin, subcutaneous fat, areolar tissues and nipple. While very little motion of the breast is allowed for these coherent, 3D, full wave reconstructions, that stability is achieveable with a stabilizer/extender post shown in Fig. 11b. Stabilizing tape is required in some or all cases that produced artifacts at the blue arrows in the top images of Fig. 13. Even with data acquired in individual slices in a ring array, reasonable 3D reconstructions appear possible [34]. The small elevational motion of the array stirs the water and the breast less than a rapid rotation as well the elevational motion. Use of custom-formed, semisolid coupling gels instead of water could be a good stabilizer.

Figure 13: The 90 mm yellow arrows show how, when the image plane is at steep angle of incidence to the skin, the outline of the breast is shrunk in the 2D reconstructions (top right and bottom of the second row) compared with the 3D images (top left and upper image of the bottom row). Reproduced with permission from [32].

## 6 Other Diverse Systems and Applications

Other diverse systems and applications, too numerous to cover fully here, have been evaluated for breast UTT, many of which are covered elsewhere in these proceedings. Use of a focusing mirror instead of opposed arrays could save some cost [35] and resulted in amazing SOS-corrected reflection mode images in the fatty-breast examples [36]. Both SOS and reflection images were at 7.5 MHz nominal frequency. Phase ambiguity might destroy the SOS quality in dense and heterogeneously dense breasts. It is worth mentioning the nearhemispherical bowl transducer arrays developed for photoacoustic imaging of the breast, superficial tissues and small animals [37,38]. With simple rotation of the bowl about its central axis, and the correct spiral distribution of transducer elements, all of k-space can be sampled with a limited number of elements. This geometry may be equally optimal for UTT.

With high signal to noise ratio and dynamic range and full wave migration, it is becoming possible with UTT to image body parts containing bone. Excellent examples have been obtained with commercial systems in planes containing modestly calcified bone [39] and the adult brain is not far away.

Figure 14: Ultrasound in the mammographic geometry. (a) Combined DBT and pulse echo ultrasound system; (b) Standalone dual sided test system for future inclusion with DBT. Photoacoustics was included in this system. (c) Scanning pattern with one or opposed matrix or linear arrays.

## 7 Limited Angle Ultrasound Tomography

Our work with GE Global Research, Niskayuna, NY, began with pulse echo imaging of the breast in the mammographic geometry for completely coregistered ultrasound and mammograpy or DBT. It was found that good coverage of the entire breast at frequencies even below 9 MHz could not be achieved by one sided imaging with conventional transducers. Dual sided pulse echo and transmission imaging were evaluated for eventual use with 2D CMUT arrays covering both sides of the entire breast. The CMUT arrays could not be produced with a high enough yield, but the principles were demonstrated with conventional 1.25D arrays (GE M12L). 90% coverage was achieved and better ways of acoustic coupling envisioned to achieve 98-100% coverage. That is better than typically achievable with the breast dependent in water.

Figure 15: Limited angle transmission tomography of a challenging, compressed breast phantom, shown quantitatively on the left. Bent-ray reconstruction with and without use of a priori information obtainable from reflection mode images [40] are shown on the right, followed by full wave inversion reconstructions with and without use of the a priori information.

For transmission tomography, as well as pulse echo, in the mammographic geometry, the maximum breast thickness with modest compression is 9 cm, compared with a maximum path length of *>*20 cm for the prone water path. The shorter path length allows higher frequencies for penetration and some reduction in phase ambiguities due to less long adjacent paths with different speeds of sound. With long, opposed linear arrays moving away from the chest wall, as in the single transducer case of [41], good 2D transmission tomography image slices should be achievable *in vivo*, but breast stability for 3D full wave inversion will be difficult unless solid compression paddles can be made to work

Reasonable limited angle reconstructions require use of *a priori* information [42], and such use will be helpful in imaging through and around bone [43].

## 8 Discussion

Speed of sound tracks rather closely with CT density, so it will be interesting to see whether breast CT can fulfill the role of SOS. Breast CT by itself will not have the added information provided by ultrasound in addition to SOS. That is, *µ*, physical density, quasistatic and shear wave complex elasticity, reflection and vascularity imaging, relatively safe and simple contrast agent imaging, slip boundary imaging under manipulation and thermoacoustic quantitative imaging. Only with transmission imaging can you have all those ultrasound modes with high spatial and quantitative resolution as well as subwavelength aberration correction of those ultrasound and multimodality imaging modes.

## References

## Ultrasound Imaging with FWI: From Breast to Brain

Llu´ıs Guasch, Ph.D.1

1*Imperial College London, Department of Earth Science and Engineering, London, United Kingdom, E-mail<EMAIL_ADDRESS>
## Abstract

Full-waveform inversion (FWI) is an imaging technique developed in the field of seismology that exploits all available information in the data, phase and amplitude, by solving a local optimisation problem based on the numerical solution of the wave equation. This technology was first translated to medical breast imaging over a decade ago. It has dramatically improved the potential of ultrasound as an imaging tool for breast cancer diagnosis due to its ability to produce high-resolution images and to provide quantitative information of several tissue properties such as acoustic speed, density, impedance or attenuation.

Despite its many challenges, breast imaging with FWI benefits from the low tissue heterogeneity of the target and from adequate instrument access to provide sufficient illumination. Brain imaging, on the other hand, presents a more challenging problem due to the presence of the skull. The high-contrast bone tissue surrounding the imaging target, i.e. the brain, requires full 3D data acquisition as well as some a priori knowledge of the geometry and acoustic properties of the skull. Under the right circumstances, however, brain imaging with FWI is possible and has the potential to impact the diagnosis and monitoring of a wide range of neuropathologies like stroke, brain cancer or head trauma.

#### Biography

Dr Llu´ıs Guasch is a Research Fellow at Imperial College London. He performs his research across the Earth Science and Engineering, and the Bioengineering departments. He holds a B.Sc. in physics from the University of Barcelona and a Ph.D. in Geophysics from Imperial College London. His work in seismic imaging has let to a successful start-up company, S-Cube, where he is one of the founders and the COO, as well as author of the two patents that drive the technology and commercial development of the company. During the last four years his research has been focused on medical imaging, and currently leads an academic multi-disciplinary group that works on translating seismic imaging technologies to ultrasound imaging for clinical applications.

## Full-ring Photoacoustic Tomography: Light and Sound to Enhance Diagnosis of Breast Cancer

Mohammad Mehrmohammadi, Ph.D.1,2,3

## Abstract

Photoacoustic imaging has shown a steadily growth in diagnostic imaging of various pathologies including cancer. Through excitation of the tissue with light, conversion of the light energy to thermal energy, minor but rapid thermoelastic expansion followed by generation of acoustic waves, PA provides a complementary platform to acquire optical signature of breast tumors using the same hardware used for US imaging. In recent years, PA tomography (PAT) imaging of breast cancer has shown a steady growth. We have developed a PAT system based on a ring geometry (both excitation and detection) that can potentially address limitations of existing PAT system. Within this presentation, an overview of PAT application in breast cancer detection and staging as well as initial results from our developed full-ring PAT system will be presented.

# Systems

## The New Generation of the Breast Ultrasound Tomography Imaging System in HUST

J. Song1, K. Liu1, Q. Zhang1, L. Zhou1, Q. Zhou1, Z. Quan1, Y. Wu1, X. Fang1, M. Yuchi1, and M. Ding1

1 *Huazhong University of Science and Technology, Wuhan, China E-mail<EMAIL_ADDRESS>
## Abstract

#### Background

In 2017, our team developed the prototype of the ultrasound tomography system. To this end, we have designed and implemented a new generation of the ultrasound tomography system to meet the clinical requirement.

#### Material and Method

The new system mainly includes a patient bed, image reconstruction servers and a display workstation. A ring array probe is adopted, which have 2048 elements with the center frequency 3.0 MHz and the radius 110 mm. The system has 512 independent transmit and receive channels. The excitation voltage can be up to +/-100V. After digitization, the RF signals are transmitted to the reconstruction servers, and the GPU completes the image reconstruction. The display station receives and displays the reconstructed images and provides an interface for data management and debugging.

#### Results

The acquisition time for one slice can be set between 2 s to 8 s depending on different imaging modes. The reconstruction time of the reflection image of 2048x2048 pixels is 4s, and the reconstruction time of the sound speed image and the attenuation image of 1024x1024 pixels are 20s and 25s.

#### Conclusion

Preliminary tests have shown that the performance of the new system has been significantly improved. The future work is to optimize the system based on clinical results.

## Progress Towards an Open-Source, Low-Cost Ultrasound Computed Tomography Research System

Morgan J. Roberts1, Eleanor Martin1, Ben T. Cox1, and Bradley E. Treeby1

1*Department of Medical Physics and Biomedical Engineering, University College London, London, UK, E-mail<EMAIL_ADDRESS>
## Abstract

Ultrasound Computed Tomography (UCT) systems are typically custom-built, and the high cost and long lead time can be a significant barrier to research groups becoming active in the field. This work details progress towards FlexUCT: a design framework for a low-cost benchtop UCT system that will allow novel data acquisition protocols and reconstruction algorithms to be tested on a physical system, thereby facilitating progress towards fast and accurate UCT. The design, assembly and testing of 4-element prototypes are described. Field scans of the prototypes have been performed to characterise the beamwidth, element radiation pattern and acoustic cross talk, and the pulse echo behaviour was evaluated.

*Keywords:* Ultrasound Computed Tomography, Low Cost Hardware, Open Source, US Transducer

## 1 Introduction

Ultrasound Computed Tomography (UCT) is a biomedical imaging technique that involves sending pulses of ultrasound into the tissue, often the breast, from different angles, and measuring the reflected and transmitted pulses with an array of detectors [1]. UCT has the advantages of being non-ionising, operator-independent, and pain-free since it requires no breast compression [2].

However, for researchers seeking to start working on UCT the barrier to entry is high, because to properly test novel data acquisition protocols and image reconstruction methods, custom hardware is required in order to have sufficient control over the experimental setup to meet the specific research needs, and custom systems can be prohibitively expensive and often have a long lead time. Lowering this barrier will increase participation in the field, which is likely to result in more and faster progress towards improved image reconstruction algorithms and data acquisition protocols.

This paper describes the initial developmental stages of FlexUCT, an open source design framework for a benchtop UCT research system. The framework uses a toolbox of flexible, low-cost manufacturing techniques which allow the user to choose their own values for key design parameters, such as aperture size and element dimensions, without affecting the assembly processes. The framework is designed to have simple user requirements for manufacture, requiring only standard workshop hand tools, a mill and a 3-D printer, which are commonly available in most research institutions. Our future goal is to distribute the complete specification needed to build a custom UCT research system, including parametric CAD models, 3D-printing design files, Gerber files for PCB manufacture, a bill of materials and a full assembly procedure. Here, we present the design, assembly, and evaluation of the first FlexUCT prototypes.

## 2 Design and Modelling

### 2.1 Aperture Configuration

To develop flexible manufacturing techniques, our approach was to first design a typical full-aperture UCT ring, but to build this in smaller 4-element segments. This allows rapid iteration with lower material costs, and also ensures that the manufacturing techniques can be used to realise modular apertures as well as fixed apertures. The KIT and MUBI UCT systems demonstrate that multiple modular segments can be assembled to realise 2D [3] and 3D [4] apertures, which could provide greater flexibility to FlexUCT users by allowing changes to the aperture configuration without manufacturing new hardware, and by allowing easy replacement of faulty elements.

The CURE prototype [5] has previously shown that 256 transducers are sufficient for basic UCT imaging in a 2D ring configuration, and since 3D apertures require an order of magnitude more transducers, meaning complicated and expensive multiplexing would have to be used, it was decided to use a 2D ring array configuration with 256 equispaced transducers as shown in Figure 1. This matches the number of available transmit/receive channels for the ULA-OP, UARP, and Verasonics Vantage systems, which are three commonly available platforms for ultrasound data acquisition [6]. In principle the system could be rotated to obtain measurements at a finer angular spacing. A ring diameter of 220mm was chosen, based on an assessment of breast diameter from 200 women in America showing that a ring of this size would accommodate 95% of the population [7], which is shown in Figure 1 with the PZT element dimensions.

Figure 1: Left: Full-aperture UCT ring, designed with 256 equispaced transducer elements embedded in a common backing layer, and with a diameter of 220 mm. Right: A single PZT element defined by the key dimensions shown, with solid pattern electrodes.

### 2.2 PZT Element Dimensions

The centre frequency of a PZT element is dominated by its half-wave resonance, which is controlled by its thickness when driven as a width expander [8], and should be as high as possible for good resolution, but low enough to prevent excessive absorption. For a plane wave travelling in the +*z* direction, the solution to the lossy Helmholtz equation is *p* = *P*0*e*a*z e j*(w*tkz*) [9], where *p* is the acoustic pressure, w is the angular frequency, *k* is the wavenumber, and *t* is time. This shows that as a wave propagates through an absorbing medium over a distance *z*, the plane wave amplitude *P*0 decays according to exp(a*z*). In tissue, the frequency dependent acoustic absorption coefficient a(*f*) follows a power law relationship described by a(*f*) = a0*| f | y*, where a0 = 0*.*75 dB.MHz*y* .cm1 and *y* = 1*.*5 for breast tissue [8]. Using these material properties, a mean breast diameter of *z* = 140 mm, and an assumed noise floor of 5%, a centre frequency of *f* = 2 MHz results in an acceptable decay, which corresponds to a PZT element thickness of 1 mm with a sound speed of 4010 m.s1 [10].

The elevation height of an element affects the beamwidth and therefore the image slice thickness. To avoid variations in the effect of volume averaging, the slice thickness would ideally be constant over the imaged region [2]. To choose an appropriate elevation height, simulations were performed using the acoustic field propagator from the k-Wave toolbox in MATLAB [11] [12]. For a range of element sizes, the transmitted field in the elevation plane was computed at a frequency of 2 MHz for a ring of diameter 220 mm. As the receive sensitivity will have the same spatial dependence, the transmit-receive sensitivity was found by multiplying the transmitted field with a copy of itself flipped about the central point of the array. The resulting transmit-receive sensitivity is shown in Figure 2. The full-width-halfmaximum of the beam at the centre of the array was then extracted. As the element elevation height increases, the beamwidth at the centre decreases as expected, but beyond the 10 mm element size, the improvement in beamwidth comes at the expense of a much wider and longer near field which could affect the image reconstruction at the edges of phantoms larger than 100 mm. An element elevation height of 10 mm was chosen as a good balance between slice thickness at the centre of the array and slice uniformity across the region of interest.

For UCT, the elements would ideally be as narrow as possible so that they are very diverging in the scan plane and achieve full coverage of the breast. However, it is important for this system to be easily and repeatably assembled by hand, so the element width was chosen to be 1 mm, so that the electrode area is large enough to easily terminate signal leads by hand-soldering. The final element dimensions can be seen in Figure 1.

Figure 2: Elevation plane transmit-receive sensitivity plots for rectangular bar elements driven at 2 MHz, for a range of elevation heights. Pressure is displayed on a logarithmic scale, referenced to the maximum pressure at the centre of the ring, and thresholded to a 6 dB range. The element width was 1 mm for all simulations.

### 2.3 Acoustic Properties of Tungsten-Epoxy Composites

To fabricate matching and backing layers, tungsten particles can be embedded in an epoxy resin polymer matrix to form a 0-3 composite. A study was performed to establish the relationship between tungsten-epoxy weight ratio and the acoustic properties of the resulting composite under a specific set of repeatable conditions, since previous work has only been completed at much higher frequencies [13], and work by Grewe et al. suggests that the relationship is affected by tungsten particle size and mixing techniques [14].

Tungsten-epoxy samples were manufactured with tungsten weight ratios ranging from 72.5% to 95%. To calculate the characteristic impedance of the samples, their sound speed was measured in deionised water using the through-transmission substitution method [15], and their density was calculated using a simplified hydrostatic weighing method [16]. Figure 3 shows the measured sound speed and characteristic impedance, alongside the predicted acoustic properties of the samples calculated using the Devaney model, which gives expressions for the effective bulk and shear moduli of a random distribution of elastic spheres embedded in an elastic matrix, using multiple scattering theory [17]. The shape of the predicted sound speed profile is qualitatively similar to the experimental data, showing a sound speed minimum at a tungsten weight ratio of 87.5%, but the model does not match the data quantitatively since it doesn't account for absorption, and since it also depends heavily on the values used for the bulk and shear moduli of the epoxy matrix and tungsten particles. The experimental results are important because they can be interpolated to manufacture tungsten-epoxy matching and backing layers with a desired characteristic impedance.

Figure 3: Experimental data showing the relationship between the tungsten weight ratio of a tungsten-epoxy composite and its phase velocity and characteristic impedance at 2 MHz. The acoustic properties from the Devaney model [17] are also shown.

### 2.4 CAD Design

The prototype transducers were designed in CAD software, shown in Figure 4. PZT elements with a single tungsten-epoxy matching layer on their front face are embedded in a 12 mm tungsten-epoxy backing layer, which is mounted on an acrylic cable-guide plate, which has holes to align the individual signal leads with the rear electrode on each element. The individual signal leads combine into a flat ribbon cable, which is secured to the cableguide plate with a strain relief clip. A common ground electrode connects to a 1.5⇥1 mm unmatched area on the front electrode of each PZT element.

### 3 Assembly Methods

### 3.1 Quarter-Wave Matching Layer

For a layer of tungsten-epoxy used to match PZT with impedance *Zp* = 30*.*5 MRayl to water with impedance *Zw* = 1*.*5 MRayl, the impedance of the matching layer should be *Zl* = p30*.*5⇥1*.*5 = 6*.*76 MRayl. This can be achieved by using a tungsten weight ratio of *WT* = 86*.*9%, which has a sound speed of 1317 m.s1, meaning that the target quarter wave matching layer thickness is l*/*4 = 165 *µm* at 2 MHz.

Figure 4: CAD rendering of prototypes, with the key components labelled. The right hand diagram is an elevation plane cross section down the centre of one of the PZT elements. Note that the common ground electrode on the front face of the PZT elements is not shown.

Previous low cost transducers have used a 3D-printed mould to control the matching layer thickness by supporting the PZT element on 'standoffs' which are exactly l*/*4 [18]. Preliminary work showed that as frequency increases, matching layer thicknesses becomes less repeatable, because the required thickness approaches the layer height of the 3-D printed standoffs, meaning that the technique is not suitably flexible. Alternatively, it has been shown that metal foils can be used as a stencil to deposit solder pastes with a uniform and controlled geometry for circuit board assembly [19], and that blade coating can be used for depositing thin films with a controllable thickness [20].

In order to replicate a hybrid of these techniques, a stencil was manufactured by using a 1 mm end mill to create 1 ⇥ 8*.*5 mm slots in 0.2 mm steel shim stock. A jig was milled from acrylic with 1 mm slots to receive the PZT elements and hold their top face flush with the surface. The stencil was placed on top of the elements using registration pins, and the tungsten-epoxy composite was spread over the slots using a blade. On removal of the stencil, the tungsten-epoxy composite covered the PZT element with a controlled geometry, and was left to cure at room temperature. This process is shown in Figure 5.

To test the repeatability of the technique, 45 samples were deposited and the thickness was measured with digital callipers. The mean sample thickness was 150.9 *µ*m, and the standard deviation was 15.4 *µ*m, placing the 165 *µ*m target thickness within one standard deviation of the mean. Future work will be done to establish the relationship between the stencil thickness and the final cured thickness of the deposited layers, but this preliminary study suggests that the proposed method can deposit matching layers repeatably with a suitable thickness.

### 3.2 PZT Element Alignment Mould

It is important that the front faces of the elements are aligned tangent to the ring geometry. If they are skewed, then the breast may not be homogeneously insonified, which can cause artefacts [21]. Moulds with slots to retain each element were manufactured from polyvinyl

Figure 5: Left: Proposed method used to deposit matching layers. A) PZT Elements are placed into slots in a jig, with their top face flush with the surface. B) A steel stencil is placed on top, and the tungsten-epoxy composite is added. C) The tungsten-epoxy composite is spread over the stencil with a scraper. D) The stencil is removed. Right: Proposed method to manufacture an alignment mould. A) 1⇥1⇥13 mm slots are milled into a strip of 1.5 mm PVA. B) The resulting PVA alignment strip. C) Strip and 3D-printed alignment form before bending. D) The PVA alignment strip is bent and welded onto the alignment form.

alcohol (PVA) in order to align the PZT elements relative to one another. PVA is a water soluble polymer and can easily be removed without damaging the elements by dissolving the moulds. Kerfs were milled from a 3D-printed flat PVA strip, which was then bent and welded to a 3D printed PVA form, shown in Figure 5. The benefit of using milled slots is that the internal corners are much sharper than those achieved using 3D-printing alone, allowing a much tighter fit to be achieved. To test the PZT element orientation accuracy when using milled slots rather than 3D-printed slots, both methods were used to prepare a 4-element sample, and a microCT scan was performed on each using a XT H 225 scanner (Nikon). A slice was taken through the CT image to show the cross sections of the PZT elements, which can be seen compared to microscope photographs of the samples in Figure 6. This shows that the element alignment achieved using milled slots is more uniform than that achieved using 3D-printing alone.

Figure 6: Analysis of the PZT element orientation using microscope photographs (Left) and microCT scans (Right). Two samples were investigated that use different assembly methods to create slots that the PZT elements are placed in. The 3D-printed slots are shown on the left, and the milled slots are shown on the right.

### 3.3 Further Assembly

Once the deposited matching layers had cured, the PZT elements were fixed in the alignment moulds using a water soluble PVA glue. The flat ribbon cable was then fixed into place with a 3D-printed PLA strain relief clip, and the individual signal leads were distributed through the holes in the cable guide plate, shown in Figure 7. The leads were then soldered to the element electrodes.

A mould for curing the backing layer was 3D-printed from PVA filament. The backing layer mould, cable guide plate, and alignment mould were then all bolted down to a rigid base plate, shown in Figure 7. A tungsten-epoxy composite with a tungsten weight ratio of 92.5% was mixed thoroughly, pushed into the backing layer mould, and allowed to cure at room temperature, bonding directly onto both the rear electrode of the PZT and the cable guide plate, whilst encapsulating the signal leads. A weight ratio of 92.5% is the highest impedance composition available using hand mixing, since beyond this high pressures and temperatures are required to bind the composite together [22]. This was chosen in order to investigate whether the resulting sensitivity is high enough for use in UCT.

Figure 7: Left: Casting the backing layer. A) Elements are placed in alignment moulds and leads are soldered onto electrodes. B) Backing layer mould fixed into place. C) Tungsten-epoxy backing layer pressed into mould. D) PVA moulds dissolved, leaving elements embedded in backing layer. Right: Coating the transducer. A) Flat ribbon cable threaded through a slot in the coating mould. B) Mould coated with Aptflex F7. C) Transducer placed in the mould and filled up with Aptflex before leaving to cure. D) Finished second generation prototype after PVA mould has been dissolved away.

The PVA moulds were all removed by dissolving them in warm water. In order to waterproof the transducers and to insulate them electrically, a two-component polyurethane coating with an acoustic impedance of 1.5 MRayl was used (Aptflex F7, Precision Acoustics) to minimise the pressure reflection coefficient at the coating-water boundary, preventing internal reverberations within the coating layer. A 3D-printed PVA mould was used to create a coating layer with a consistent thickness, which was again removed by dissolving in water. One of the finished transducers can be seen in Figure 7.

## 4 Experimental Evaluation

### 4.1 Field Scan Procedure

Field scans were performed on the prototypes to investigate the pressure distribution on the front of the elements and the beam orientation in the scan plane for each element. Measurements were taken in a tank of deionised water using an X-Y stepper motor positioning system (Precision Acoustics), and the water temperature was monitored using a J-type thermocouple (National Instruments). The transducer was directly connected via a custom 3Dprinted backshell to the Vantage-256 (Verasonics), with no electrical impedance matching, and all four channels were driven by a 3 cycle tri-state pulse with a frequency of 2 MHz and an amplitude of 30 V. Signals were acquired at a sampling frequency of 0.2 GHz using a calibrated 200 *µ*m needle hydrophone (Precision Acoustics) connected to an InfiniiVision DSOX3024A digital oscilliscope (Keysight) via a submersible preamplifier and DC coupler (Precision Acoustics) in a 170⇥170 scanning grid located 27 mm from the transducer surface, with a uniform point spacing of 0.3 mm. The voltage signals were deconvolved using the hydrophone response to give the pressure time series in the measurement plane, which were bandpass filtered. A Tukey window was applied, and the 3D volume of the maximum pressure in the field was calculating by backprojecting using the angular spectrum method [23].

### 4.2 Elevation Plane Beam Orientation Analysis

To evaluate the orientation of the beams in the elevation plane of the pressure field, the scanning procedure was repeated four times, successively driving each element in isolation. The beam orientation was calculated for each element by drawing a line between the locations of the maximum pressure at two points in the far field, and calculating the angle between this line and the horizontal. This can be seen in Figure 8, which shows the pressure on a logarithmic scale. Although there is a common downwards skew due to misalignment of the scan plane with the transducer, the standard deviation of the beam angles is s = 0*.*57, which corresponds to a 1.1 mm vertical deviation over a horizontal distance of 110 mm to the centre of the ring. This is sufficiently small to suggest that the milled alignment strip is a suitable low-cost method for aligning the PZT elements relative to one another with high repeatability. The measured beamwidth at the centre of the ring is 9.5 mm, which is slightly greater than the 7.1 mm predicted from the k-Wave simulations, which suggests that the effective element elevation height is smaller than 10 mm.

Figure 8: Elevation beam pattern for each of the elements. The centreline of the beam in the far field has been estimated, and the angle of the centreline to the horizontal has been calculated. Pressure is displayed on a logarithmic scale, referenced to a point on the beam axis in the far field, and thresholded to a 6 dB range.

### 4.3 Element Radiation Pattern and Cross Talk

The front view in Figure 9 shows that each element has a weakly radiating region at the bottom. This is because a 1.5 mm⇥1 mm area was left unmatched to allow a common ground lead to be terminated to the front electrode. This resulted in poor ultrasound transmission from this region, which is likely the reason for the smaller effective elevation height. The width of the radiation pattern varies along the length of the element, which is due to nonuniform coverage caused by a burr on the stencil. Additional lateral non-uniformity in the radiation pattern may be introduced by deformation due to surface tension at the edges of the matching layer during curing. To address these factors in future work, the stencil slots will be enlarged and a slightly thicker matching layer will be deposited and lapped down to size after curing.

Figure 9: Left: Maximum source pressure showing the radiation pattern of the elements. A weakly radiating region can be seen at the bottom of each element. Right: Maximum pressure in the scan plane of the elements, showing that the undriven elements do not radiate when a single element is driven in isolation.

The pressure fields shown in Figure 9 show that the crosstalk between elements is negligible since none of the non-driven elements are radiating, indicating that there is no electrical interaction between elements, and that there is no acoustic interaction between elements through their common backing layer.

### 4.4 Pulse Echo Behaviour

To assess whether there were any internal reverberations in the transducers, they were placed in a tank of deionised water facing the wall of the tank, connected to the Vantage-256 (Verasonics), and driven with a 3 cycle tri-state pulse at a frequency of 2 MHz and an amplitude of 30 V. In this setup the tank wall acts as a reflective target. A representative time series is shown in Figure 10, which features a high amplitude burst from electrical pickup, followed by a low amplitude reflection, followed by two high amplitude reflections. The high amplitude reflections are known to arrive from the front and back of the tank wall, because as the distance between the transducer and the target is increased, the arrival times of these pulses increase. The low amplitude pulse was stationary in time when the transducer was moved, indicating that there may be internal reverberations within the transducer. The sound speed of the backing layer was measured to be *c* = 1407 m.s1 and the distance of one round trip within the backing layer is *d* = 2⇥12 mm = 0*.*024 m. Using this data would result in a pulse arrival time of d*t* = 0*.*024*/*1407 = 17*.*1 *µ*s, and the actual pulse arrival time from Figure 10 is 18.5 *µ*s. Allowing for the uncertainty in the backing layer thickness and sound speed, this suggests that the low amplitude reflection is from the backing-Aptflex boundary at the rear face of the backing layer.

Figure 10: Left: Pulse-echo signal showing electrical pickup up until 10 *µ*s, a low amplitude reflection from the rear face of the backing layer at 18.5 *µ*s, and two high amplitude reflections from the front and rear face of the tank wall at 42 *µ*s. Middle: Extracted time series for the internal reflection (top) and echoes from reflective target (bottom). Right: Amplitude spectrum for the internal reflection (top) and echoes from reflective target (bottom).

The internally reflected pulse and the first pulse to arrive from the external target were both extracted and windowed before applying a Fourier transform. Figure 10 shows that the amplitude spectrum of the internally reflected pulse contains most of its energy up to 1.2 MHz, whereas the amplitude spectrum of the pulse arriving from the external reflective target contains most of its energy at the transducer resonance frequency of 2 MHz. High frequencies are attenuated more strongly when propagating through absorbing media like tungsten-epoxy composites, so it is to be expected that the internally reflected pulse would contain most of its energy at these lower frequencies.

The internal reflections within the prototype transducers are a problem for UCT, since an incoming acoustic pulse will have an initial arrival time when it first reaches the PZT, but will have a second arrival time when it propagates past the PZT, reflects from the rear face of the backing and returns to the PZT. If the second arrival has a high enough amplitude, this could present an artefact during the image reconstruction.

## 5 Conclusions and Future Work

In this work, the first FlexUCT prototypes have been assembled and evaluated. Novel lowcost methods to deposit matching layers with a repeatable thickness and align PZT elements during manufacture were used to build robust, functioning 4-element transducers, which required no special equipment other than a mill, 3D-printer, and standard workshop equipment. In future, the elevation beamwidth of the transducers will be reduced by increasing their effective elevation height with a better strategy for making electrical connections to the front face of the elements, and internal reverberations in the transducers will be addressed by increasing the absorption of the backing layer. In the future, the release of an open-source design framework for a low-cost benchtop UCT system will enable more research into the optimal configuration for acquiring the minimum amount of data needed for fast, accurate UCT.

## 6 Acknowledgements

The authors would like to thank Francesco Iacoviello (Chemical Engineering, UCL) for running the microCT scan. This work was supported by the National Physical Laboratory, European Union's Horizon 2020 research and innovation programme H2020 ICT 2016-2017 under Grant Agreement No. 732411 (as an initiative of the Photonics Public Private Partnership), the Engineering and Physical Sciences Research Council (EPSRC), UK, Grant Nos. EP/L020262/1, EP/S026371/1, and EP/P008860/1, and the EPSRC Centre For Doctoral Training in Intelligent Integrated Imaging In Healthcare (i4health).

## References

[1] C. Li, N. Duric, and L. Huang, "Clinical breast imaging using sound-speed reconstructions of ultrasound tomography data," in *Medical Imaging 2008: Ultrasonic Imaging and Signal Processing*, vol. 6920, p. 692009, International Society for Optics and Photonics, 2008.

## A Low-cost Ultrasound Computed Tomography System using Diagnostic Linear Arrays

P. Patel1, B. Cox1, and B. Treeby1

1 *University College London, London, United Kingdom, E-mail<EMAIL_ADDRESS>
## Abstract

Ultrasound Computed Tomography is clinical imaging modality whose potential to complement mammography as a non-ionising, economical breast screening or diagnosis tool has recently driven renewed interest and rapid development. Costly, custom-built detector arrays with a variety of geometries have been proposed including bowl-shaped, rings, and planar arrays. Here, we investigate whether a simple low-cost system based on diagnostic linear arrays can be used to perform USCT. A proof-of-concept system was constructed using clinical-grade linear arrays, an off-the-shelf data acquisition system, and in-house image reconstruction software.

Figure 1: A schematic of the USCT.

The designed USCT system (see Figure 1) houses two linear array transducers, opposing each other, rotating on a frame about a phantom. The arrays fit to the frame via a detachable mount, allowing for an adjustable array separation and hence reducing the effects of diffraction for phantoms of varying dimensions. The main operating components are located beneath the water tank and hence it can be placed under a patient bed for clinical applications in the future. The entire system excluding the transducers and phantoms is designed from recycled plastic and stainless steel, making it economical and simple to manufacture. The probes are connected to a Verasonics ultrasound system which allows for independent channel and element control. Control of the rotation motor and scan sequencing was via Matlab. Four phantoms were scanned (two PVCP and two wire phantoms). At each rotation angle, a plane wave was emitted from an array and both the back-scattered and transmitted signals were detected. Time-of-flight and amplitude values were extracted from each measured time series and, and 2D images of the sound speed and attenuation were reconstructed using both straight- and bent-ray reconstruction algorithms.

The systems components and promising preliminary results are to be presented. This will include sound speed and attenuation maps from multiple signal processing and reconstruction algorithms, data from multiple scans with varying angles of rotation as well as a comparative analysis of the above scan parameters. The system characteristics (e.g. resolution) from the wire phantom will also be discussed.

## Towards 3D Brain Imaging in Small Animals using Full-Waveform Inversion

T. Robins1, C. Cueto1, O. Calderon Agudo1, L. Guasch1, M. Warner1, and M.-X. Tang1

1 *Imperial College London, London, United Kingdom, E-mail<EMAIL_ADDRESS>
## Abstract

Full-waveform inversion (FWI) is an iterative image-reconstruction technique used in exploration seismology to produce high-quality tomographic images for acoustic properties of the subsurface by minimising the misfit between acquired and modelled data FWI has also been shown to have some exciting applications in ultrasound imaging of soft tissue, including breast cancer diagno- sis, however the method has yet to be applied to brain-imaging in small animal models where hard tissue is present and 3D reconstruction is required. Here we demonstrate the feasibility of 3D small-animal transcranial tomography using FWI in silico and implement our FWI algorithm to reconstruct an in vitro acoustic brain phantom in 2D using data acquired with independently translated medical transducers.

In this study a pair of 96-element linear probes (P4-1, ATL) were each assigned a set of 3-axis motors for independent translation, allowing for a larger imaging region and for 3D acquisitions to be performed. To test this experimental setup, an in silico mouse brain and skull acoustic model was created and placed between two 1152-element plane arrays, each representing the translation of a linear array over 12 positions (with 2.5 mm spacing), as shown in Fig1.a. A synthetic 3D dataset of this scene was produced so that the velocity model could be reconstructed using a robust 3D FWI algorithm. To mitigate cycle skipping due to the skull tissue, a starting model consisting of the mouse skull and homogenous water (1500 ms1) was used. To demonstrate this method using real data, we acquired a 2D dataset of a half-scale 2.5D brain phantom made using a polyvinyl alcohol cryogel to mimic brain tissue. By translating both probes vertically when acquiring data, a two-plane array consisting of 960 elements was formed, from which a subset of 240 were selected as sources. Element delays and positions were calibrated by time of flight optimisation using a watershot dataset and the velocity model was reconstructed using our 2D FWI algorithm.

Fig1.b shows FWI results of the mouse brain and skull model. When compared to the ground truth, a relative error of 0.110 % has been achieved (starting model relative error = 2.562 %). In Fig1.c-d the photo of the brain phantom and the reconstructed velocity model can be seen to closely match. In future work we will introduce rotation to further improve our transducer scanning sequence and apply our method to image ex-vivo brain and skull tissue.

Figure 1: a) Experimental setup of 3D synthetic mouse brain model, b) Saggital and transverse views of velocity model recovered using FWI with velocity samples (red) plotted against ground truth, c) Photo of brain phantom, d) Brain phantom velocity model recovered using FWI.

## The Efficiency of an All-reflective Omnidirectional Illumination for Photoacoustic Tomography with a Ring Ultrasound Transducer

S. S. Alshahrani1, N. Alijabbari1, A. Pattyn1, and M. Mehrmohammadi1,2,3

1 *Wayne State University, Department of Biomedical Engineering, Detroit, USA E-mail<EMAIL_ADDRESS>
2 *Wayne State University, Department of Electrical and Computer Engineering, Detroit, USA*

3 *Barbara Ann Karmanos Cancer Institute, Detroit, USA*

### Abstract

Breast cancer is a common cancer and a major health concern affecting the lives of many women worldwide. According to the World Health Organization (WHO) breast cancer has an estimated annual incidence rate of 2.1 million and is responsible for about 15% of all cancer related deaths around the world. We have previously introduced a novel photoacoustic tomography (PAT) system for breast cancer imaging, in which the object is illuminated omnidirectionally by using a cone and a conical ring mirrors. A ring ultrasound (US) transducer is used to acquire PA signals and to form the PAT images. The design of the system is intended to acquire data from entirety of a pendant breast up to the chest wall, without compressing the tissue, thus allowing for deeper detection of endogenous chromophores associated with breast cancer.

This work presents the characterization of the full-ring illumination / acquisition system through three different studies. In the first study, three different illumination methods, fullring, diffused-beam, and point source illumination, and their efficacy for PAT imaging are compared. The results indicate that the full-ring illumination method is capable of providing a more uniform fluence irrespective of the vertical depth of the cross-section imaged, while the point source and diffused illumination methods provide a higher fluence at regions closer to the point of entry, which diminishes with depth. The omnidirectional ring illumination can provide a more uniform illumination pattern within the tissue and enable PAT imaging at deeper distances in the targeted cross-sectional area. In the second study, a set of experiments were conducted to determine the optimum position of ring-illumination with respect to the position of the acoustic detectors to achieve the highest signal-to-noise ratio.  The results demonstrate that the system is capable of imaging blood up to a cross-sectional depth of 30 mm. These three studies demonstrate the utility and advantages of the full ring-illumination system in imaging breast mimicking objects and paves the way for future development of the system towards a clinically translatable breast PAT scanner and can be part of a future diagnostic system.

# Clinical Studies

## Tissue Sound Speed: A Novel Imaging Biomarker for Measuring Tamoxifen Response

M. Sak1, N. Duric1,2, P. Littrup1, and G. Gierach3

1 *Delphinus Medical Technologies, Inc, E-mail<EMAIL_ADDRESS>
2 *Karmanos Cancer Institute*

3 *National Cancer Institute*

## Abstract

#### Purpose

Studies have shown that a decrease in mammographic percent density (MPD) or lowering of background parenchymal enhancement (BPE) on MRI after initiation of tamoxifen therapy predicts a favorable response in the preventive or adjuvant settings. However, performing serial mammograms poses radiation concerns, while serial MRIs carry high cost as well as risk of multiple Gadolinium doses. Previous studies have shown that tissue sound speed, derived from whole breast ultrasound tomography measurements, is a surrogate biomarker of MPD. Ultrasound is ideal for performing serial measurements because it is fast and poses almost no risks. The purpose of this study was to evaluate repeated measures of the sound speed biomarker at 3, 6 and 12-months following tamoxifen initiation.

#### Method and Materials

We performed a case-control comparison involving 74 participants referred by a health professional to undergo tamoxifen therapy (cases) and 150 matched participants with no history of breast cancer (controls). The cases were scanned with ultrasound tomography at baseline (i.e. before start of tamoxifen therapy), and then at 1-3, 3-6 and 12 months after tamoxifen initiation. Controls were scanned at baseline and 12 months. In the case group, sound speed was measured pre-treatment in the contralateral breast to avoid potential influences of tumorrelated changes on density. In the control group, a single randomized breast was scanned. A paired t-test was used to assess differences in sound speed and MPD over time and compared to baseline.

#### Results

There was a steady decline in sound speed over the 12-month period for women undergoing tamoxifen therapy (mean: -2.6 m/s, p = 0.005). Furthermore, significant sound speed reductions were observed as early as 3-6 months after tamoxifen initiation (mean: -2.3 m/s, p = 0.007); Figure 1. In contrast, the controls demonstrated no significant change in sound speed over a 12-month period.

### Conclusion

Breast sound speed decreases rapidly after tamoxifen initiation; further studies are needed to assess whether this can predict clinical response.

#### Clinical Relevance / Application

Ultrasound tomography may have utility in monitoring breast sound speed change as a potential biomarker of clinical tamoxifen response.

 The reduction in breast cancer risk is also associated with a decrease in breast density, particularly in premenopausal women. Favourable response in either the preventive or adjuvant settings have been shown to be associated with either decreases in mammographic percent density (MPD) or lowering of background parenchymal enhancement (BPE) [3,4].

The effects of decreased breast density (BD) are the most pronounced with the first 12-18 months [3]. Yet both mammography and MRI have shortcomings in regard to the repeated serial scans that would be needed to accurately track response to Tamoxifen on a time frame shorter than this. The use of radiation in mammography along with both the use of Gadolinium and the high cost of MRI would limit the period between repeated scans. Increased monitoring early on in treatment could therefore improve patient outcomes by identifying patients who are or aren't responding and adjusting course appropriately.

Studies have shown that average tissue sound speed, a factor derived from whole breast ultrasound tomography (UST) scans, is strongly correlated with mammographic breast density [5,6]. Ultrasound tomography overcomes many of the issues associated with mammography and MRI. Namely, UST is non-ionizing, does not use contrast and is much less expensive than MRI. This makes UST imaging an ideal modality for performing serial measurements.The aim of this work is to perform a preliminary evaluation on the repeated measures of UST average sound speed at short, regular intervals following Tamoxifen initiation.

## 2 Methods

### 2.1 Patient Recruitment

A total of 73 patients beginning treatment with Tamoxifen, either due to a history of breast cancer or those with a higher risk of developing breast cancer were selected to be part of this trial. These "case" patients were referred by health professionals mainly at the Karmanos Cancer Institute (KCI) in Detroit. A total of 140 "control" patients with negative mammographic screens who were not receiving Tamoxifen were also enrolled. These control patients were age and race matched with the case patients. The study was performed under an IRB approved protocol and was HIPPA compliant.

All case patients received a mammogram and UST scan at baseline (prior to start of Tamoxifen therapy) followed by repeated UST scans at 1-3, 3-6 and 12 months post baseline along with a repeat mammogram at 12 months in accordance with yearly screening protocols. All control patients received their two normal screening mammograms 12 months apart combined with UST scans at the same time. A single randomly chosen breast was analyzed for each control patient and each case patient with no history of breast cancer. For those case patients with recently diagnosed breast cancer, the contralateral breast chosen for analysis.

### 2.2 Breast Density Measurements

Mammographic percent density (MPD) was analyzed by one expert reader using the CUMU-LUS 4 Software. This software uses a semi-automated algorithm where the reader manually selects the breast and a threshold between the dense and fatty tissue. The software then measures the amounts of dense and total areas on the mammogram which are then used to calculate the percent density.

UST images were created using a prototype device at the Karmanos Cancer Institute that could produce between 40-100 sound speed images per breast. Whole volume averaged sound speed (VASS) was measured using the public domain software package ImageJ. Because the soundspeed of the background water bath is intermediate to that of the normal breast tissue, segmentation of the breast tissue was done using a semi-automated method that approximated the breast in each slice as an ellipse. After the segmentation was completed, the remaining pixels could be averaged to produce the VASS.

## 3 Results

There was a decline in VASS for case patients compared to control patients. On average, the VASS in the case group decreased by 2.6 m/s after 12 months compared to the baseline sound speed. This change was statistically significant as a paired t-test was performed and a p value of p = 0.005 was measured. The change in sound speed could be detected as early as 3-6 months post the initiation of Tamoxifen as an average decrease in sound speed of 2.3 m/s (p = 0.007) was noted. A slight increase in VASS of 0.3 m/s (p = 0.5) was noted for controls. These results can be visualized in Figure 1.

The changes in MPD were not as apparent. For cases, there was a decrease in average MPD of 2.3% after 12 months, but this was not statistically significant (paired t-test p = 0.11). For controls, there was also a decrease of 1.8% and this was statistically significant (p = 0.045). These results can be seen in Figure 2. The changes in VASS and MPD are summarized in Table 1.

Figure 1: Average change in VASS for both cases and controls.

## 4 Discussion

When using UST density measures, average changes in breast density could be detected in the case group much sooner than could be detected when using mammographic measures. The differences when measured by UST were also statistically significant compared to the

Figure 2: Average change in MPD for both cases and controls.

differences measured by mammography. This suggests that VASS may be a more sensitive measure of breast density and breast cancer risk than mammography. Previous results using only the baseline data suggests that UST sound speed potentially showed stronger breast cancer risk assessment than mammography and these findings may support that result [7].

There were inconsistencies in the density measures for the control group with UST sound speed slightly increasing but MPD showing a statistically significant decrease over the 12 months. Breast density is known to decrease with increasing age, so some small decrease in density is expected in both the case and control group.

? p-values are calculated from the paired t-test between the measured and the baseline values

Table 1: Summary of average changes in UST and mammographic density over time

Figure 3: Plot of Baseline VASS vs the change in VASS after 12 months for all Cases. The Spearman correlation coefficient was r*s* = -0.535

The average breast density of the patients in this study skews towards being less dense. Previous mammographic analysis of Tamoxifen's effect on breast density showed significant decreases in density in cases compared to controls. However, for those studies, the average baseline breast density was greater than 40% [3] while in this study, the baseline MPD for cases was 25% and 22% for controls. Since breast density started low, there was less of a potential decrease in breast density available to be made.

Patients with higher baseline breast density (measured with either VASS or MPD) generally showed the greatest decrease in breast density. There were moderate and negative correlations between the baseline density and the final change in density at 12 months. Figure 3 shows a plot of the baseline VASS and the change in sound speed after 12 months for the cases. A Spearman correlation of r*s* = -0.535 was measured for this and Table 2 lists the Spearman correlations for the other different possible groupings. Despite the limitations of the dataset, VASS appears to be a more sensitive measure of breast density and changes to breast density than mammography. However, further analysis is still required to determine whether these changes can be used to predict clinical response.

Table 2: Correlations between baseline density measure and change in density measure

## 5 Conclusion

Ultrasound tomography may have utility in serially monitoring sound speed change as a potential biomarker of clinical Tamoxifen response. Changes in breast density may be more sensitively detected using VASS than by using MPD. Further analysis is still required to know if these changes can be used to predict clinical response.

## References

## Tissue Sound Speed from Ultrasound Tomography as a Biomarker of Breast Cancer Risk: A Review of Recent Advances

N. Duric1,2, P. Littrup1, M. Sak1, and G. Gierach3

1 *Delphinus Medical Technologies, Inc, E-mail<EMAIL_ADDRESS>
2 *Karmanos Cancer Institute*

3 *National Institutes of Health*

## Abstract

Increased mammographic density is a strong population-based risk factor for breast cancer. However, the inclusion of breast density in clinical risk models leads to only a modest improvement in individual risk prediction. Ultrasound Tomography (UST) is an emerging breast imaging technique that has the potential to overcome some of mammography's limitations as a predictor of breast cancer risk.

We review the methods and results of previous UST studies investigating the use of tissue sound speed to characterize breast density and breast cancer risk. A number of different UST methods have yielded strong correlations between speed and breast density with Spearman correlation coefficients ranging from 0.71 to 0.96. and in some cases, even stronger correlations between sound speed and MRI measures of breast density with correlation coefficients of up to 0.96. In one breast cancer risk study, elevated sound speed was significantly associated with increased breast cancer risk (odds ratios (OR) per quartile=1.79, 95%, CI: 1.30, 2.48; ptrend=0.0004). In contrast, Mammographic density was associated with elevated breast cancer risk compared to controls, although the trend was not statistically significant (OR per quartile=1.28, 95%CI: 0.95, 1.73; ptrend=0.10). The OR-trend for sound speed was significantly different from that observed with mammography (p=0.01).

Recent clinical studies have demonstrated that sound speed not only corelates with mammographic density but is also related to breast cancer risk. UST has the potential to provide a more accurate, non-ionizing method for assessing breast density and breast cancer risk.

*Keywords:* Ultrasound Tomography, sound speed, breast cancer risk

## 1 Introduction

Many clinical studies have shown that breast density (BD), as measured by mammography, is a strong risk factor for breast cancer [1]. At the same time, women with high breast density are the least likely to benefit from mammographic screening where sensitivity can be less than 50% [2]. Thus, this high-risk population that could benefit the most from breast cancer screening, is, in fact, underserved.

Mammographic studies have established a relationship between mammographic density (MD) and breast cancer (BC) risk. When using MD quartiles, the women in the highest density quartile have a 3 to 6-fold increase in BC risk compared to women in the lowest density quartile [2-7]. While this risk factor is strong, its inclusion in clinical risk models has resulted in limited additional benefit. While a typical clinical risk model (e.g. Gail or Tyrer-Cuzick) predicts individual risk correctly 60% of the time, inclusion of MD raised the prediction accuracy to 61% - 64% [8]. Thus, MD remains a useful marker for characterizing populations but has only modest value in predicting individual risk. There is therefore a need for a mor sensitive measure of breast cancer risk.

The MD measurements are limited by several factors. First, mammography measures MD from 1 or more 2D projections of a highly compressed 3D volume. Any such projection reduces the information contained in the original undistorted volume. Secondly, it requires segmentation of mammograms to determine the percent of dense tissue contained within the beast. Such segmentation requires subjective or otherwise user defined thresholding. Thirdly, digital mammography is optimized for mass detection, not density measurements. And finally, MD is not a quantitative measure in the true sense. It does not yield pixel values that can tied to an external standard. These limitations form a likely set of reasons why MD's contribution to clinical risk models is modest. An alternate imaging approach that mitigates one or more of these limitations has the potential to improve upon MD as a BD risk marker.

Ultrasound Tomography (UST) is an emerging breast imaging technique that is being developed to overcome some of mammography's limitations and has the potential to aid in the screening of women with dense breasts [9-15]. In this paper, we review its role in assessing breast density and breast cancer risk. Unlike mammography, UST is a 3D imaging technique that does not compress the breast and creates a 3D imaging set so that information in the natural breast volume is preserved. Previous UST studies have shown that the speed of sound, a tissue property that is measured by UST, is closely linked to breast density [16-21]. In fact, some studies have suggested that sound speed is directly linked to physical tissue density [19].

## 2 Methods

Measuring breast density. Previous UST studies relating to BD were carried in cohorts of women undergoing mammographic exams with UST scans added as part of the studies [16- 21]. These studies were IRB approved and HIPPA compliant. UST scans were performed with the breast immersed in water with one or more transducers moving through the water to acquire the signals needed to perform a tomographic inversion.

The measurement of MD is usually carried out using segmentation software such Cumulus or Libra, which require some degree of subjectivity to carry out. In some studies, only the radiologist assessment of the BIRADS breast density category (a,b,c,d) is used. Automated methods, such as Quantra and Volpara have been introduced in recent years to facilitate the MD measurement and to attempt volumetric estimates by taking into account the thickness of the breast under compression.

As noted above, UST studies measure sound speed as a surrogate of BD. Extraction of sound speed information, as it relates to BD, has been carried out in several ways.

Risk Assessment. So far, only one study has been carried out for assessing UST sound speed as an independent risk factor for breast cancer [22].  The cases and controls were imaged with both ultrasound tomography (UST) and mammography. In cases, breast density was measured pre-treatment in the contralateral breast to avoid potential influences of tumor-related changes on MPD or sound speed. In controls, a randomly selected breast was imaged. The ultrasound tomography images were used to estimate the volume averaged sound speed of the breast, and the Cumulus software package was applied to mammograms to determine MPD. Odds Ratios (ORs) adjusted for matching factors and 95% Confidence Intervals (CIs) were calculated for the relation of quartiles of MPD and VASS with breast cancer risk.

## 3 Results

Breast density. Breast density. The three UST methods described above have yielded strong correlations between speed and MD with Spearman correlation coefficients ranging from 0.71 to 0.96 [16-21]. and in some cases, even stronger correlations between sound speed and MRI measures of BD with correlation coefficients of 0.96 [18]. Figure 1 shows examples of cases in the four different BIRADS density categories, showing the correlation between MD and UST sound speed.

Breast Cancer Risk. In the one BC risk study, elevated VASS was significantly associated with increased breast cancer risk in a dose-response fashion (OR per quartile=1.79, 95%CI: 1.30, 2.48; ptrend=0.0004) (Figure 2). In contrast, MPD was associated with elevated breast cancer risk compared to controls, consistent with previous studies, although the trend did not reach statistical significance (OR per quartile=1.28, 95%CI: 0.95, 1.73; ptrend=0.10). The OR-trend for VASS was statistically significantly different from that observed for MPD (p=0.01). Figure 2 illustrates the OR's of MD vs VASS. The ratio of highest to lowest density quartiles (Q4/Q1 )was found to be 8.6 for VASS vs 1.76 for MD.

Figure 2: Histogram of ORs by quartiles. MD data shown in blue, VASS data in orange.

## 4 Discussion

Recent clinical studies have demonstrated that sound speed not only corelates with MD but is also related to BC risk. We present two possible interpretation of these relations.

Sound speed is a proxy of MD. Since MD is known to be associated with BC risk and since sound speed itself is associated with BD, it stands to reason that VASS would be associated with BC risk. While the biological cause of the increased BC risk is not well understood, the driver of the relationship appears to be the dense tissue content of the breast.

Under this scenario, the stronger association of VASS with BC risk can be explained by the fact that UST mitigates some of the limitations of mammography, as described in the Introduction and provides a more comprehensive picture of the volumetric distribution of dense tissue. Furthermore, sound speed is a measure of physical density of tissue suggesting that it is the physical density, not MD, that drives the observed relationship between VASS and BC risk.

Sound speed is an independent marker of BC risk. The relationship between VASS and BC risk was observed independently of MD. In other words, it stands as a risk factor on its own without a need to tie it to breast density. Thus, it is plausible that sound speed carries additional biological information on BC risk beyond breast density.

The much stronger association of VASS with BC risk compared to MD (Q4/Q1 = 8.6 vs 1.76) suggests an almost 5-fold improvement in risk stratification. Such a large increase suggests that VASS may be a sensitive measure of an underlying biological factor that has yet to be identified.

In a clinical setting, UST would provide relatively comfortable exams without the use of ionizing radiation and at relatively low cost. In that context, determining VASS as a risk factor may be viable. Furthermore, the absence of radiation would make this risk assessment available to women for all ages. Interventions for women at high risk are most effective when performed at early ages so the use of UST for young women (below screening age) would provide timely data, guiding interventions that reduce their risk.

Future studies are needed to validate the findings presented above, investigate the underlying cause of the association between VASS and BC risk and to test the VASS parameter in a clinical risk model so that its impact om individual risk prediction can be assessed. Such studies may lead to the use of VASS as a biomarker of risk, as defined by the Food and Drug Administration (FDA) under its "context of use" guidelines. Finally, future studies may investigate additional parameters that UST can measure, such as tissue attenuation and stiffness that can be added to risk models to improve their accuracy.

## 5 Conclusion

Elevated breast density strongly increases breast cancer risk. UST has the potential to provide a more accurate, non-ionizing method for assessing breast density and its associated breast cancer risk.

## References

density measurements with ultrasound tomography: a comparison with film and digital mammography. Med Phys, 2013. 40(1): 013501.

## Breast Cancer Development at the Fat-Gland Interface (FGI): Importance of Coronal Imaging and Ultrasound Tomography

P. J. Littrup1-4, N. Duric2,3, M. Sak3, and R. Brem4

1 *Prof. of Radiology, Wayne State University, Detroit, MI, USA, E-mail<EMAIL_ADDRESS>
2 *Prof. of Oncology, Wayne State University, Detroit, MI, USA*

3 *Delphinus Medical Technologies, Inc., Novi, MI, USA*

4 *George Washington University School of Medicine & Health Sciences, D.C., USA*

## Abstract

#### Objective

We evaluated the locations of cancer and benign masses in relation to the fat-gland interface and anatomic quadrant locations with ultrasound tomography.

#### Methods

A total of 602 breast masses were evaluated from a clinical data set corresponding to a pretrial arm of a multicenter study evaluating UST. Anatomic breast quadrants also noted for each tumor, and the fat-gland interface was considered the site of origin if at least 1/8 of the mass circumference abutted fat. In a subset of 298 masses, a hand-traced region-of-interest allowed quantitative sound speed and percent density comparisons of tumor and peritumoral margins.

#### Results

Cancers were located at the fat-gland interface in 93.4% (169/181) of cases, and were completely surrounded by fat in 5.5% (10/181) or parenchyma in 1.1% (2/21)(p*<*0.001) of cases.

Moreover, 56.1% (97/173) of cysts and 25.0% (47/188) of fibroadenomas were fully surrounded by dense tissue, significantly more than cancers (1.1%)(p*<*0.001). The upper outer quadrant was the most common location of all masses, but no significant differences between mass were noted (p=0.06). Quantitative sound speed values showed significantly greater amount of fat surrounding cancers than fibroadenomas or cysts (p*<*0.001), while percent density showed that most cysts were completely surrounded by dense tissue and cancers were surrounded by both dense and fatty tissues.

#### Conclusion

Both the qualitative tumor location and quantitative peritumoral data corroborate the preferential location of cancers at the FGI, compared to benign masses or anatomic quadrants. This study supports possible integration into clinical practice with future dense breast screening by UST.

 Common mammographic teaching has emphasize greater visual attention to anatomic regions of historically higher cancer incidence [1,2], such as the upper outer quadrants having its greater parenchymal content, or epithelial distribution [2]. The dominant signs of breast cancer by mammography relate to a focal mass/asymmetry, a cluster of microcalcifications and/or architectural distortion.

Cancers newly diagnosed by mammography were seen as a mass/asymmetry in over 2/3 of cases, by calcifications in 29% and architectural distortion in only 4% [3]. Masses or asymmetries seen by mammography are generally then evaluated by ultrasound, which predominantly characterizes it as a cyst or solid mass for follow-up or biopsy, respectively. Yet, in women with overall increased breast density, mammography can miss up to 50% of cancers in the densest breasts and obscure both high contrast microcalcifications, as well as the higher density of some cancers.

Breast magnetic resonance (MR) imaging shows high sensitivity to both ductal carcinoma in situ (DCIS) and invasive cancers due to increased local blood flow and/or permeability to paramagnetic intravenous contrast agents. Limited breast MR work has suggested that the fat-glandular interface (FGI; figure 1) represents a preferable location for up to 94-99% of breast cancers [4,5]. Breast cancer localization at the FGI appears to be a high sensitivity parameter but has not been widely considered. The coronal plane can visualize the circumferential nature of the FGI, which is feasible with 3D acquisitions of breast MR with isotropic pixels, but was not addressed [4,5]. They also described benign solid masses, but cysts, the most common benign masses, were not included. In most women, fat makes up more of the breast than dense tissue, which often leaves part of that coronal circumference

Figure 1: Graphic coronal representations of a UST sound speed (SS) image, highlighting the FGI (yellow arrow): The significantly higher SS of central fibroglandular tissue (speckled) allows good separation from the surrounding fat (darker gray). Red arrow denotes a Cooper's peak. Magnified view (right) shows an irregular cancer (black) at a Cooper's peak with radiating spicules of architectural distortion (white lines).

without parenchyma, leaving only telltale residual fibrous bands (e.g., Cooper's ligaments) after involution.

### 1.2 The Well-Established Cancer Biology at the FGI

Breast cancer initiation and growth have strong associations with adjacent fat cells, or adipocytes, and their fat-secreted hormones, adipokines [6,7]. The FGI also helps define the boundary with the breast's subcutaneous adipose layer which may comprise the largest endocrine gland in the body [8]. Adipokines help mediate blood pressure, reproductive function, appetite, glucose homeostasis, angiogenesis and immune function [8]. The link between obesity and the rising incidence of multiple diseases appears to include breast cancer.

When the balance of adipokines tip toward an excessive pro-inflammatory state at the FGI, multiple adipokines, such as leptin, have been implicated in breast cancer initiation via aromatase expression [9,10]. Cancer cell lines and tumor growth become markedly accelerated in the presence of adipocytes [9]. Bidirectional crosstalk between cancer cells and adipocytes, moreover lead to the formation of cancer-associated adipocytes (CAA). These CAA's stimulate a phenotypic change to generate fibroblast-like cells known as adipocytederived fibroblasts through the secretion of the adipokine, fibronectin, and collagen. Tumor cells cultured with these fibroblasts then demonstrate increased invasive ability. CAA's also display overexpression of collagen VI while ECM-related molecules contribute to breast cancer progression. This FGI sequence may also lead to the presence of a dense collagenous stroma, or desmoplastic reaction around breast cancers (i.e., peritumoral region), particularly in estrogen receptor/progesterone receptor (ER/PR) positive tumors.

### 1.3 UST and the FGI

Ultrasound tomography (UST) development over 40 years [11-36] has accelerated with recent rapid progress of computing capacity and appears well-suited to evaluate the circumferential nature of the FGI in its native coronal plane. A ring array transducer has provided whole breast and focal mass evaluation by combining reflection signal acquisition with quantitative transmission properties of sound speed (SS) and attenuation (ATT). UST offers quantitative multi-parametric evaluation of breast tissues that are scanned and displayed in its highest resolution, coronal plane. Correlation of mammographic breast density to SS distributions of parenchymal tissues throughout the breast have been thoroughly explored [26-36], including improvements in SS resolution [34].  SS has also been shown to be a stronger BC risk factor than mammographic density [32].

Given the strong biological background for cancer initiation near the FGI, we sought to clarify tissue localization for cancers, solid benign masses and cysts, in relation to their standard anatomic quadrants and tissue components using UST and its innate coronal imaging plane. In a smaller subset, mass evaluations by UST was also able to compare and assess quantitative peritumoral measurements.

## 2 Methods

For qualitative anatomic and FGI locations, a total of 602 clinical breast masses were noted within 467 individual breasts from 408 patients, as part of a related study of UST for women with dense breasts (SoftVue, Delphinus Medical Technologies Inc., Novi, Michigan; Clinicaltrials.gov – NCT#02977247). This data set included a subset with quantitative region-ofinterest (ROI) analyses for the tumor and peri-tumoral regions noted below. Some women had more than one mass in each or both breasts. All masses were biopsy-confirmed by subsequent or prior histology, unless considered as a characteristic cyst by standard HHUS evaluation.

Mass location in coronal UST images was determined by a MQSA certified radiologist with extensive UST imaging experience. The relationship of a mass to the FGI was noted for a all 602 breast masses (181 cancers, 188 fibroadenomas, 173 cysts and 60 other benign findings), confirmed by biopsy, or by hand-held ultrasound for a simple cyst. The 60 other benign findings were excluded from the figures due to their smaller numbers and contained nonmass findings, such as focal fibrosis, micro-cystic changes and/or granulomatous mastitis.

The FGI was defined as the circumferential interface between the peripheral fat and parenchyma [4,5] as determined by examining sound speed (SS) images, which reliably differentiate the much lower SS (i.e., density) of fat [26-36] from the higher SS of fibro-glandular tissues. Mass location was determined from its best visualized coronal level and placed into 3 groups: (i) completely surrounded by dense high SS fibroglandular tissue, (ii) completely surrounded by low SS fat or (iii) partially surrounded by both (i.e., the FGI) [4]. Typically, if a mass showed ⇠ 1/8 of its circumference abutting fat in its greatest visualized coronal level, it was considered to be at the FGI (figure 2-Fibroadenoma). Conversely, a mass could be considered to abut parenchyma while being surrounded by fat and also labeled at the FGI (figure 2-Cancers). Masses were evaluated only on the coronal plane and therefore not fully evaluated in 3D for FGI location at this time due to lower out of plane resolution of SoftVue imaging (below). Mass location was only augmented by the lower resolution reconstructions in the axial/sagittal reconstructions as needed for additional confirmation of anterior/posterior aspects of the FGI. Masses were also categorized according to standard quadrant positions within the breast based on distance from the nipple and clock position of the finding. Differences in lesion locations were assessed using the chi-squared test.

Figure 2: Cancers, cyst and fibroadenoma: (Left) Sound speed (SS) images from 2 patients with scattered fibroglandular breast density and high SS cancers at the FGI. Both cancers have irregular margins on the magnified views, being nearly surrounded by fat along the residual fibrous bands of the FGI (arrowheads). Top right SS and magnified reflection view show dominant replacement by extremely dense breast parenchyma (white) with an embedded simple cyst. The well circumscribed 2.0 x 1.3 cm simple cyst has intermediate sound speed, similar to the gray water surrounding the breast. Bottom right images show a patient with heterogeneously dense breast parenchyma and a 1.6 x 1.2 cm fibroadenoma with a lucent halo of lower SS, sometimes also noted with mammography. While mostly embedded in parenchymal tissue, a smooth portion of the fibroadenoma bulges the FGI into the surrounding subcutaneous fat.

For a subset of 296 masses (78 cancers, 105 fibroadenomas, 91 cysts and 24 other benign findings), their boundaries were hand-traced by a radiologist with over 20 years experience as a certified breast imager using MIM software to generate regions of interest (ROI) encompassing the detected masses by UST. Mass margins were defined on the single best visualized/representative image upon a combination of sound speed and reflection image stacks to trace their contours, generating a surface area. Once tumor margins were defined, a peritumoral region was then digitally created to extend 20% of the tumor's diameter beyond all tumor margins, making it proportionate for every tumor. The quantitative parameters of SS and the peritumoral surface area could then be compared with the boundaries inside the traced mass ROI. The SS image was also segmented into two regions corresponding to dense and fatty tissues by using a k-means segmentation method. Combining the segmented SS image with the ROI masks allowed for calculations of the percent density (PD) [the area of dense tissue compared to the total area] for each region as well. Comparisons of mean values between the mass types were performed using an ANOVA analysis. Chi-squared test was used to assess significance of frequency differences.

### 3 Results

Coronal imaging by UST provided reliable circumferential evaluation of the FGI, allowing a consistent peripheral visual search pattern. Cancers were classified at the FGI in 93.3% (169/181) of the cases, were surrounded by fat in 5.5% (10/181) or parenchyma in 1.1% (2/181)(chi-squared, p*<*0.001) of cases (figure 3). Even when surrounded by fat, cancers were still associated with residual fibrous bands (i.e., Cooper's ligaments) of the atrophied parenchyma at the FGI. For fibroadenomas, 68.6% (129/188) were classified at the FGI while 39.8% (69/173) of cysts were found at the FGI. Moreover, 56.1% (97/173) of cysts and 25.0% (47/188) of fibroadenomas were fully surrounded by dense tissue, significantly more than cancers (1.1%) (chi-squared, p*<*0.001). Few cancers, fibroadenomas or cysts were completely surrounded by fat (i.e., 5.5%, 6.4% and 4.0%, respectively).

Figure 3: Relative distribution of 3 tissue locations for each tumor type (i.e., 3 locations = 100%). Significant opposing trends are noted for location incidence of Cancer, Fibroadenoma and Cyst at the FGI (shaded bars) versus being surrounded by dense breast parenchyma (white bars).

Figure 4 shows the four-quadrant distribution of cancers, fibroadenomas and cysts. Significantly greater cancer distribution of 42% (76/181) (chi-squared, p = 0.008) was noted in the upper outer quadrant compared to cancer rates in the other quadrants, yet a similar greater relative percentage of 34% (63/188) for fibroadenomas and 39.3% (68/173) of cysts were also more common in the upper outer quadrant than the other locations (Chi square p*<*0.01). All tumors were also least commonly located in the lower inner quadrant (p*<*0.05).

Figure 4: Relative distribution of 4 anatomic breast quadrants for each tumor type (i.e., 4 locations = 100%). All tumors were more commonly located in the upper outer quadrant and have their lowest incidence in the lower inner quadrant, but otherwise showed no mass-specific intra-quadrant differentiation.

Quantitative SS results for surface areas generated for the traced ROIs of the mass showed overlap between masses, but still a significant difference in mean SS (m/sec) for the actual mass ROIs between cancers (1527 m/s, 1521-1533 95%CI) fibroadenomas (1536 m/s, 1531- 1540 95% CI) and cysts (1535 m/s, 1529-1540 95% CI)(p = 0.046). Surrounding peritumoral regions showed significantly lower mean peritumoral SS for cancers (1477 m/s, 1470-1482 95% CI) than fibroadenomas (1496 m/s, 1490-1502 95% CI) as well as lower mean peritumoral SS for fibroadenomas than cysts (1518 m/s, 1512-1523 95% CI)(ANOVA p*<*0.001). The percent density (PD) of the peritumoral region for the different mass types also showed a progressive increase in the mean values when going from cancer to fibroadenoma to cyst (47% to 65% to 84% respectively, ANOVA p*<*0.001). Furthermore, the median peritumoral PD for cysts and cancers are 98.5% and 44.7%, quantitatively indicating that roughly half of all cysts are almost entirely surrounded by dense tissue, while significantly more fat surrounds cancers.

## 4 Discussion

Our results confirm the common breast imaging dictum of cancers being more common in the upper outer quadrant, but also showed a similar incidence for fibroadenomas and cysts. Similar to prior MRI findings [4,5], UST tissue localization also confirmed cancers had a very strong tendency to be located at the FGI and extend these findings by demonstrating that benign masses have a weaker tendency in that regard. Moreover, quantitative peritumoral SS characteristics of the tumor microenvironment with cancers provides insights to their greater likelihood of being partially surrounded by fat compared to benign masses and support the qualitative findings.

UST is a novel breast imaging technology being explored for its potential for improving breast cancer detection in women with dense breasts (NCT#02977247). The native coronal imaging plane by SoftVue UST may facilitate simpler qualitative detection and localization of cancers, which were much more likely to be found at the FGI (figures 1, 2). Conversely, it appears rare that cancers are entirely surrounded by fibroglandular tissues, or cysts surrounded by fat (i.e., 1.1% and 4.0%, respectively). Even though overall benign masses were significantly more likely to be surrounded by fibroglandular tissue than cancers, only cysts were predominantly surrounded by parenchyma (i.e., 56.1%). These findings are further corroborated by insights provided by the mean peritumoral analyses.

UST separation of breast parenchyma from fat by SS, using segmentation K-means segmentation techniques, have been well established and correlated with breast density by mammogram and parenchymal distribution by MR [26-36]. The mean SS results for mass ROIs and peritumoral regions are better understood when we note that the mean SS for the surrounding water bath is approximately 1500 m/s. Considering that simple cysts contain similar waterlike SS or density, smaller cysts appear more often to contain thicker proteinaceous fluid or inspissated debris that can markedly elevate SS.

Data from our peritumoral analyses lend insights to the average tissue composition surrounding masses. Progressively increasing mean SS in the peritumoral tissues of cancers, fibroadenomas and cysts [i.e., 1470-1482 m/s, 1490-1502 m/s and 1512-1523 m/s respectively (ANOVA p*<*0.001)], suggest a similar physiologic progression, from a mix of fatty tissues to dense fibroglandular tissue. For cancers, the 25th percentile to 75th percentile range of mean peritumor SS is 1455 – 1499 m/s, indicating a progression of tissue composition from predominantly fatty to fairly dense, features compatible with tissues found at the FGI. Conversely, the quantitative peritumoral SS range for cysts of 1503 - 1542 m/sec is also compatible with the qualitative assessment of cysts being entirely surrounded by parenchyma a majority of the time. Using the peritumoral PD measurements also supports the qualitative analysis. The 25-75th percentile range for cancer peritumor PD goes from 14% to 75% dense, while for cysts, the same percentile range is 75% to 100% dense. Once again, this shows that the regions surrounding cancers is much more likely to be a mix of dense and fatty tissue while cysts are far more likely to be almost entirely surrounded by only dense tissue.

The preferential tumor location for cancers at, or near, the FGI thus appears to be a highly sensitive finding for cancer origin and growth, but not necessarily specific in this clinical case selection. However, the knowledge of nearly all cancers being near the FGI suggests a reasonable circumferential search pattern that will also require the use of common BI-RADS criteria. In other words, mass margin irregularity noted near the FGI is highly suspicious. Conversely, a smoothly marginated mass near the FGI still requires consideration of fibroadenoma versus more uncommon but well-marginated cancers (e.g., mucinous, medullary, etc.).

Future use as a search tool near the FGI requires comparison with an actual screening series, but the quantitative aspects of UST mass and peritumoral analyses suggest future development with computer-aided diagnosis and detection. Finally, the quantitative tumoral:peritumoral information can be further utilized to better understand the complex biology of adipocytes, adipokines and cancers cells near the FGI.

Numerous weaknesses are inherent in an analysis of a subjective criteria, such as the location of whether a breast tumor resides at the FGI. Rather than a more graded approach [4], we therefore chose a simpler assessment whereby of the extremes of being entirely surrounded by fat or fibroglandular tissue was more straightforward. While the coronal plane is convenient for the circumferential assessment of the FGI, we also acknowledge that further work is needed on the 3D assessment of both anterior and posterior tumor margins near the FGI. As a 3D structure, figure 5 is offered as a graphic rendering to show that the FGI is dispersed throughout the breast volume , but a search can be simplified to an irregularity along the FGI margin.

Figure 5: Graphic representation of a pendulus breast (pink background) in what could be postulated as an extremely dense breast with the FGI represented by an inverted architectural dome having a multi-pointed hemispherical mesh (black and gray). The irregularity of a cancer is represented by a burr at one of these points, or Cooper's peak.

The FGI criteria was qualitative but produced significant mass differentiation that prior anatomic quadrant location did not. The peritumoral analyses was also incomplete for all 602 masses, being available for only 298. However, these quantitative analyses of mean SS values required no subjective component and were highly significant and supported the qualitative assessments of the FGI. Further work is also needed for further confirmation with biological and/or molecular correlates.

In summary, both the qualitative and subjective opinion of a radiologist noting cancers' preferential location at the FGI corroborates similar MR findings but emphasizes the coronal UST location as a circumferential view of the FGI. Moreover, quantitative SS results for individual masses and peritumoral regions also corroborates the well-known biological significance of fat being adjacent to cancers and their associated rate of growth. These FGI analyses showed significantly better mass differentiation than anatomic location, which confirmed that all masses are more common in the upper outer quadrant. This study supports its possible integration into clinical practice and future dense breast screening.

## 5 Conclusion

The coronal view by UST confirmed that cancers are much more likely to be found at the FGI (p*<*0.01) compared to fibroadenomas and cysts. UST is a novel new technology that has the potential for improved breast cancer detection. This study supports increased accuracy of UST imaging as it becomes integrated into clinical practice.

## References

Adipocyte-derived fibroblasts promote tumor progression and contribute to the desmoplastic reaction in breast cancer. Cancer Res 2013; 73(18):5657-68.

# Methods

## USCT data challenge 2019

C. Boehm1, T. Hopp2, and N. Ruiter2

1 *ETH Zurich, Switzerland, E-mail<EMAIL_ADDRESS>2 *Karlsruhe Institute of Technology, Germany*

## Abstract

Recent years have witnessed the active development of scanning systems and reconstruction algorithms for ultrasound computed tomography (USCT) with applications to breast imaging for early cancer detection. Despite these advances in hardware and software development, we encounter the need for reference data to develop, test and compare different imaging methods. With the goals of encouraging scientific exchange and collaborations, providing benchmarks of reconstruction algorithms, and standardizing USCT data formats, we have released open-source data sets of simulated waveforms that mimic measurements of a USCT scanning aperture using numerical breast phantoms. This is part of ongoing efforts centered around the USCT platform for data exchange and collaboration [1, 2].

*Keywords:* ultrasound computer tomography, numerical modelling, data challenge

### 1 Introduction

Within the past decade, substantial progress in the development and design of USCT systems has been made, and several systems have readily provided first clinical results [3, 4, 5]. Simultaneously, a wide range of image reconstruction methods using both transmission and reflection data has been developed. Overviews of different modelling and inversion techniques can be found in [6] and [7]. One of the main challenges is to find good trade-offs between the quality of the image, on the one hand, and the time-to-solution, on the other hand. Popular reconstruction methods include ray-based time-of-flight inversion [8, 9, 10], reflection imaging using synthetic aperture focusing techniques [11] and reverse time migration [12], Born modelling [13, 14], as well as waveform tomography and full-waveform inversion in time and frequency domain [15, 16, 17, 18, 19, 20, 21, 22].

While this list is far from being complete, the variety of imaging and reconstruction algorithms readily stresses the need for suitable reference data to benchmark and compare different methods. To meet the demand for freely available data sets within the USCT research

Figure 1: Sound speed map of the analytical (left) and the segmented breast phantom (right) used in the simulations.

community, a digital platform hosting several data sets has been initiated. In the initial phase this included raw data donated by three different USCT systems [1, 2]. In the course of this new data challenge, we added simulated A-scans using numerical phantoms that enable researchers to compare and benchmark different reconstruction algorithms with a ground truth.

The long term goals of this initiative are (1) to build up an open-source reference USCT data base that is freely available for the entire community, (2) to enable reproducible comparisons of image reconstruction algorithms and USCT systems, (3) to establish user friendly interfaces, standards and data formats between different USCT apertures, reconstruction algorithms, software and data formats, and (4) to identify properties of systems, experimental setups, data, and algorithms towards optimal images.

In the rest of the paper we briefly summarize the specification of the numerical phantoms used in this data challenge, comment on the scanning aperture and simulation setup, and propose a flexible data format for USCT scans.

## 2 Numerical phantoms