3.1.2. Effect of DMC and BDMC on CUR Solubility in the Selected Process Solvents

Before designing seeded cooling crystallizations, the solubility behavior of CUR was evaluated in presence of the main impurities DMC and BDMC in acetone, 50/50 acetone/2-propanol, 50/50 acetone/acetonitrile and acetonitrile. In Figure 6, the resulting solubility data are compared with the solubility values of pure CUR in the respective solvents.

**Figure 5.** Effect of anti-solvents methanol, ethanol, 2-propanol and acetonitrile on the solubility of CUR in acetone at 30 ◦C. Symbols represent experimental data, curves are just guide to the eyes. Dashed curves originate from experimentally determined solubility values in the respective 50/50 (wt/wt) acetone/anti-solvent mixtures. Thin solid lines represent ideal linear solubility behaviors.

**Figure 6.** Comparison of solubility curves determined for pure CUR (empty circles, grey curves), and CUR in presence of the main impurities (solid circles, colored curves). Symbols represent experimental data, fitted curves serve as guide to the eyes.

As seen the solubilities of CUR in presence of DMC and BDMC slightly exceed those of pure CUR in the four solvents. Moreover, comparison of the CUR solubility in 50/50 acetone/2-propanol and 50/50 acetone/acetonitrile shows that with the use of acetonitrile as anti-solvent, a higher supersaturation of CUR in the solution can be obtained resulting in a higher product yield. This observation confirms the behavior of pure CUR in the binary solvents discussed in Figure 5.


*Article* **Ultra-High-Resolution Photon-Counting Detector CT Arthrography of the Ankle: A Feasibility Study**

**Karsten Sebastian Luetkens 1,\*, Jan-Peter Grunz 1, Andreas Steven Kunz 1, Henner Huflage 1, Manuel Weißenberger 2, Viktor Hartung 1, Theresa Sophie Patzer 1, Philipp Gruschwitz 1, Süleyman Ergün 3, Thorsten Alexander Bley 1 and Philipp Feldle 1**

**Abstract:** This study was designed to investigate the image quality of ultra-high-resolution ankle arthrography employing a photon-counting detector CT. Bilateral arthrograms were acquired in four cadaveric specimens with full-dose (10 mGy) and low-dose (3 mGy) scan protocols. Three convolution kernels with different spatial frequencies were utilized for image reconstruction (ρ50; Br98: 39.0, Br84: 22.6, Br76: 16.5 lp/cm). Seven radiologists subjectively assessed the image quality regarding the depiction of bone, hyaline cartilage, and ligaments. An additional quantitative assessment comprised the measurement of noise and the computation of contrast-to-noise ratios (CNR). While an optimal depiction of bone tissue was achieved with the ultra-sharp Br98 kernel (*S* ≤ 0.043), the visualization of cartilage improved with lower modulation transfer functions at each dose level (*p* ≤ 0.014). The interrater reliability ranged from good to excellent for all assessed tissues (intraclass correlation coefficient ≥ 0.805).  Notably, the low-dose Br76 matched the CNR of the full-dose Br84 (*p* > 0.999) and superseded Br98 (*p* < 0.001) in all tissues. Based on the reported results, a photon-counting detector CT arthrography of the ankle with an ultra-high-resolution collimation offers stellar image quality and tissue assessability, improving the evaluation of miniscule anatomical structures. While bone depiction was superior in combination with an ultra-sharp convolution kernel, soft tissue evaluation benefited from employing a lower spatial frequency.

**Keywords:** photon-counting CT; arthrography; ankle; cartilage; radiation dosage

Academic Editor: Antonio Barile

**Citation:** Luetkens, K.S.; Grunz, J.-P.; Kunz, A.S.; Huflage, H.;

Weißenberger, M.; Hartung, V.; Patzer, T.S.; Gruschwitz, P.; Ergün, S.; Bley, T.A.; et al. Ultra-High-Resolution Photon-Counting Detector CT Arthrography of the Ankle: A Feasibility Study. *Diagnostics* **2023**, *13*, 2201. https://doi.org/10.3390/ diagnostics13132201

Received: 22 May 2023 Revised: 13 June 2023 Accepted: 27 June 2023 Published: 28 June 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

#### **1. Introduction**

The tibiotalar cartilage bears up to five times the body's weight [1], posing a risk factor for osteoarthritis, especially if these forces increase [2]. At the same time, traumatic osteochondral lesions and ligament injuries of the ankle, as well as resulting unphysiological load distributions, are frequent [3–5]; thus, assessing the stability of chondral lesions represents a crucial diagnostic imaging task, as chondral delamination and subchondral pathologies may not be visible in direct arthroscopy but can impact therapeutic concepts [6,7].

Magnetic resonance imaging (MRI) is widely recognized as the reference standard for cross-sectional imaging of soft tissue pathologies [8,9]; however, as the ankle's cartilage consists of only a thin hyaline chondral layer, averaging 1.1 mm (range 0.4–2.1 mm) [10–13], the depiction of discreet injuries continues to pose a challenge in MRI with reported sensitivities as low as 50% at 1.5 T and 75% at 3.0 T for osteochondral ankle injuries [12,14]. On the other hand, computed tomography (CT) arthrography represents a powerful, well-established, and preferable alternative for discerning osteochondral lesions, e.g., for the elbow [15]. Comparing CT to MR arthrography of the ankle joint at 1.0 and 1.5 T with regards to cartilage lesions, Schmid et al. reported a superior level of observer agreement and reliability favoring the former [10]. Similarly, Pöhler et al. demonstrated an advantage for CT arthrography versus 3.0 T MR arthrography regarding the assessment of lesion depth in artificially induced osteochondral lesions of the talar dome while maintaining a comparable accuracy [16].

Recently, the emergence of photon-counting detector CT (PCD-CT) catalyzed further advances in depicting minute structures with unsurpassed radiation dose efficiency for CT thus far [17,18]. PCD architecture eliminates the need for a two-step conversion process of incoming X-ray photons as opposed to the current energy-integrating detector systems [19,20]. As the generated electric impulses are proportional to every photon's particular energy above a certain threshold, low-energy photons are no longer down-weighted, and contrast-to-noise ratios are significantly improved [21,22]. The current and first PCD-CT generation allows for an in-plane resolution of as little as 0.11 mm in ultra-high-resolution (UHR) mode without dose penalty, facilitating the visualization of microstructures in particular [23].

While numerous studies have analyzed the impact of PCD technology on bone imaging [24,25], to the authors' best knowledge, no thorough investigation was conducted regarding PCD-CT arthrography thus far. Aiming to address the current research gap, this study evaluates the feasibility of ankle arthrograms with the novel detector technology, establishing a clinically reproducible scan protocol in the process. We hypothesized that the PCD-CT arthrography with UHR collimation would aid the assessment of minuscule anatomical structures, such as thin cartilage layers and ligamentous stabilizers.

#### **2. Materials and Methods**

#### *2.1. Cadaveric Specimens*

The anatomical institute of the local university allocated four fresh-frozen, nonformalin-fixated cadaveric specimens to the radiology department for this investigation. During their respective lifetimes, the body donors had consented to posthumous use of their remains for study and research purposes. No additional selection criteria were imposed. The institutional review board of our university waived the need for further written informed consent and granted permission for this study.

#### *2.2. Arthrography Procedure*

A board-certified radiologist with nine years of experience in musculoskeletal imaging performed bilateral ankle arthrographies in all four cadaveric specimens. Using an ultrasound for guidance (Acuson Sequoia, Siemens Healthineers, Erlangen, Germany), each tibiotalar joint was infiltrated with a 20-gauge needle (Sterican®, Braun SE, Melsungen, Germany) on the medial side of the anterior tibial tendon in analogy to a clinical procedure. A combination of 50% iodinated contrast agent (Imeron 300®, Bracco S.p.A., Milan, Italy) and 10 mg per ml of a local anesthetic (Mecain®, Puren Pharma GmbH & Co. KG, Munich, Germany) was injected via the articular access. The injection volume was selected as high as feasible, ranging between 7 and 9 mL. Using fresh-frozen specimens instead of formalin-fixated cadavers allowed for realistic tissue properties and, subsequently, an overall procedure representative of ankle arthrograms in vivo. No particular challenges or limitations were encountered during the arthrography procedures.

#### *2.3. Image Acquisition and Reconstruction Parameters*

Directly following injection, the ankle joints were scanned using a first-generation cadmium-telluride-based PCD-CT system (Naeotom Alpha, Siemens Healthineers). All examinations were performed in UHR scan mode using a collimation of 120 × 0.2 mm. With tube potential set to 120 kVp, a full-dose and low-dose scan were acquired in each specimen with effective tube currents of 125 and 38 mAs. Resulting volume CT dose indices (CTDIvol) amounted to 10.0 and 3.0 mGy. Detailed scan parameters are provided in Table 1. Ankles were individually scanned and reconstructed in three standardized orientations (axial, coronal, and sagittal) with an increment of 0.6 mm and a field of view of 100 mm. Matrix parameters were selected automatically to obtain optimal settings; thereby, the

sharpest available non-UHR kernel (Br76), a medium-sharp UHR kernel (Br84), as well as the sharpest UHR kernel (Br98) were employed (Table 2). Preset window settings were 1400 and 300 HU (window width and center); however, observers were permitted to modify these according to personal preferences.

**Table 1.** Acquisition protocols. Scan parameters and resulting radiation dose of photon-counting CT arthrograms.

CTDIvol: volume computed tomography dose index; eff. mAs: effective milliampere-seconds; kVp: kilovoltage peak; mGy: milligray; mm: millimeter; sec: second.

**Table 2.** Reconstruction parameters. Spatial frequencies of the employed convolution kernels at different values of the modulation transfer function. Reported data according to vendor information.

Br98/84/76: vendor-specific kernel names; cm: centimeter; MTF: modulation transfer function; ρ: indicator of spatial frequency.

#### *2.4. Subjective Image Evaluation*

Seven radiologists with four to nine years of experience in musculoskeletal imaging evaluated all datasets independently using certified diagnostic monitors (RadiForce RX660, EIZO, Hakusan, Japan) in combination with standard clinical PACS software (Merlin 7.0.226222, Phönix-PACS, Freiburg, Germany). Readers were blinded to all protocolrelated information. After determining whether images were suitable for diagnostic use in dichotomous fashion, observers were separately tasked with grading the image quality for bone, cartilage, and ligaments, employing a seven-point rating scale (1 = very poor; 2 = poor; 3 = fair; 4 = satisfactory; 5 = good; 6 = very good; 7 = excellent).

#### *2.5. Objective Image Evaluation*

Normed regions of interest were placed in the talus, talar cartilage, posterior tibiotalar ligament, and subcutaneous fat, noting mean density and standard deviation thereof. Due to its homogeneous texture, the standard deviation within subcutaneous fat was defined as image noise. Individual contrast-to-noise ratios were calculated for osseous tissue (CNRBone), cartilage (CNRCartilage), and ligaments (CNRLigament) with the following formula:

$$\text{CNR} = \frac{\text{mean attenuation} \left(\text{bone/cartilage/ligament}\right) - \text{mean attenuation} \left(\text{fat}\right)}{\text{standard deviation} \left(\text{fat}\right)}$$

#### *2.6. Statistical Analysis*

All statistical analyses were performed with dedicated software (SPSS Statistics Version 28, IBM, Armonk, NY, USA). For evaluating normal distribution in continuous variables, Kolmogorov–Smirnov tests were conducted. Categorical variables were reported as absolute and relative frequencies, with median values and 10–90 percentile ranges, while normally distributed metric data were presented as means ± standard deviations. Mean rank distribution in paired non-parametric variables was assessed comparatively using

Friedman tests and Bonferroni-corrected pairwise post-hoc analyses. Null hypotheses were rejected, and statistical significance was assumed if computed *p*-values were not greater than 0.05. Interrater agreement was tested using the intraclass correlation coefficient (ICC) for absolute agreement in a two-way random effects model. Following Koo and Li [26], ICC scores were interpreted as being associated with poor (<0.50), moderate (0.50–0.75), good (0.75–0.90), or excellent (>0.90) reliability.

#### **3. Results**

#### *3.1. Subjective Image Quality Assessment*

All datasets were deemed suitable for diagnostic assessment in a clinical routine by each of the observers. Table 3 summarizes the pooled image quality scores assigned for bone, cartilage, and ligaments. The optimal depiction of bone tissue was achieved in full-dose scans with the ultra-sharp Br98 reconstruction kernel (median value 7, range 6–7). All full-dose datasets were rated superior to the respective low-dose scans (*p* < 0.001). Figure 1 includes a side-by-side comparison of the six employed acquisition–reconstruction combinations, while highlighting hyaline cartilage lesions of various degrees. In contrast to osseous tissue, the assessment of cartilage benefited from applying reconstruction kernels with a lower spatial frequency within each dose level (*p* ≤ 0.014). No significant difference was ascertained between full-dose Br98 versus low-dose Br84 and Br76 reconstructions for hyaline cartilage (*p* ≥ 0.186) and ligaments *(p* ≥ 0.283). Figure 2 illustrates the depiction of an intact posterior tibiofibular ligament. A pairwise comparison matrix comprising all assessed combinations of scan protocol and reconstruction settings is displayed in Table 4. Interrater reliability for bone microarchitecture visualization was excellent, indicated with an ICC of 0.938 (95% confidence interval 0.902–0.962; *p* < 0.001), while observer agreement was good for judging cartilage (0.887; 0.779–0.940; *p* < 0.001) and ligaments (0.805; 0.661–0.889; *p* < 0.001). Figure 3 exemplifies a full thickness defect located at the medial talar shoulder and a partial thickness lesion on the lateral side.

**Table 3.** Subjective image quality assessment. Pooled diagnostic assessability scores drawn from the subjective ratings of seven independent radiologists. Results are given as median values with 10–90 percentile ranges in parentheses.

Br98/84/76: vendor-specific kernel names; ICC: intraclass correlation coefficient.

**Table 4.** Comparison matrix for subjective image analysis. Mean image quality ranks of protocol– kernel combinations were compared individually for bone/cartilage/ligaments in pairwise analyses.

The Bonferroni procedure was performed to correct *p* values for multiple comparisons. "+": superior assessability; "–": inferior assessability; "=": no statistically significant difference; Br98/84/76: vendor-specific kernel names.

**Figure 1.** Photon-counting arthrographies in a cadaveric specimen performed with the full-dose (10 mGy; **A**–**C**) and low-dose scan protocol (3 mGy; **D**–**F**). Reconstructions were performed with the ultra-sharp kernel Br98 (**A/D**), medium UHR kernel Br84 (**B/E**), and non-UHR kernel Br76 (**C/F**). Please note the full thickness cartilage defect at the lateral aspect of the talus (**red circle**) versus the pseudodefect of the tibial plafond known as the "Notch of Harty" (**blue circle**). A superficial cartilage lesion of the central tibia is better visualized using means of full-dose arthrography (**red arrow**).

**Figure 2.** Depiction of an intact posterior tibiofibular ligament (**blue asterisk**) in axial (**A**) and coronal orientation (**B**). Photon-counting CT arthrography was performed with a CTDIvol of 10 mGy. The acquired dataset was reconstructed with the ultra-sharp Br98 kernel, which possesses the highest spatial frequency of all convolution kernels available for ultra-high-resolution imaging on a photoncounting detector.

#### *3.2.  With regards to CNR, the non-UHR Br76 kernel superseded both assessed UHR kernels based on measurements in bone, cartilage, and ligaments (*p* < 0.007). No dose-dependent difference was ascertained for any of the tissues with Br98 (*p* > 0.999); moreover, low-dose Br76 matched the quantitative metrics of full-dose Br84 (*p* > 0.999) and even superseded Br98 (*p* < 0.001) in all cases. Detailed signal and noise characteristics are provided in Table 5, while a pairwise comparison matrix thereof is exhibited in Table 6.

**Table 5.** Quantitative image quality assessment. Signal and noise characteristics are reported as mean ± standard deviations.

Br98/84/76: vendor-specific kernel names; CNR: contrast-to-noise ratio; HU: Hounsfield units.

**Table 6.** Comparison matrix for quantitative image analysis. Contrast-to-noise ratios (CNR) were calculated based on attenuation and noise measurements in the talus, talar cartilage, posterior tibiotalar ligament, and adjacent subcutaneous fat. Mean CNR ranks of protocol–kernel combinations were compared individually for bone/cartilage/ligaments in pairwise analyses.

The Bonferroni procedure was performed to correct *p* values for multiple comparisons. "+": higher contrast-tonoise ratio; "–": lower contrast-to-noise ratio; "=": no statistically significant difference; Br98/84/76: vendorspecific kernel names; CNR: contrast-to-noise ratio.

#### **4. Discussion**

This experimental multi-observer study investigated the feasibility and image quality of a photon-counting detector CT arthrography of the ankle joint with an ultra-highresolution detector collimation. Employing two different dose levels and three convolution kernels with varying modulation transfer functions, the depictions of bone, cartilage, and ligaments were separately assessed. Our results indicate that bone depiction is superior in combination with an ultra-sharp reconstruction technique, whereas soft tissue evaluation benefits from employing lower spatial frequencies. As to be expected, higher noise levels and lower CNR were determined in dedicated low-dose studies; however, all assessed datasets were found to be of diagnostic quality.

The presented findings are in line with recent publications regarding the depiction of osseous tissue with photon-counting technology in clinical applications [17,27]. As reported previously, the incorporated low-energy threshold reduces electronic background noise, which would otherwise increase significantly in low-dose applications [28]; thereby, one of the major disadvantages of a CT arthrography compared to an MRI, i.e., radiation dose, can be minimized. As the diagnostic value of CT arthrography is generally considered to be at least equivalent to an MRI after articular contrast injection [29,30], small joint imaging focused on thin layers of hyaline cartilage in particular continues to pose a major challenge to MRI arthrograms [31]. While MRI remains the modality of choice in bone marrow imaging [32,33], CT does provide advantages in assessing the subchondral bone, which facilitates diagnostic evaluation in patients suffering from osteoarthritis. Accordingly, the only previous study investigating PCD-CT arthrography reported reliable morphological assessability of cartilage loss in a porcine knee model [34].

With regards to acquisition time, an MRI also cannot compete with CT-based approaches, plausibly posing an obstacle in pain-ridden patients. As opposed to MR arthrography, the option to perform an ultrasound-guided injection of the contrast media directly within the CT suite further minimizes the overall examination time. Although a significant

amount of contrast agent in the articular cavity can still be detected for up to 120 min, following the administration thereof, an acceleration of the overall procedure optimizes contrast conditions [35].

Representing a noteworthy alternative to PCD-CT arthrography of peripheral joints, with regards to achievable spatial resolution, cone-beam CT arthrography gained increasing recognition in recent years. An experimental study evaluating arthrograms of the wrist suggested superiority of a cone-beam CT approach over a conventional energy-integrating detector CT arthrography [36]. While the present investigation does not contain a direct comparison of PCD-CT and cone-beam CT arthrography, the reported dose levels for maintaining diagnostic image quality in both studies were somewhat equivalent. These findings suggest similar dose efficiencies among both techniques, mandating further investigations in patients.

The following limitations of this study ought to be considered. First, the study cohort comprised only four cadaveric specimens; however, subjective ratings were performed by seven radiologists, aiming to alleviate this restriction to some extent. Second, to offset typical drawbacks of formalin-fixated body donor studies, e.g., the deterioration of bone quality and altered soft tissue conditions, solely fresh-frozen cadavers were included. Third, due to the experimental study design, PCD-CT arthrography findings did not incur therapeutic consequences; consequently, no comparison of diagnostic performance with other imaging modalities could be drawn. Fourth, the influence of possible motion artifacts and off-center positioning on the image quality were not assessed, warranting further evaluation in a clinical patient population. Lastly, since CNR differs with radiation exposure level, the optimal kernel choice may differ for other clinical applications.

#### **5. Conclusions**

Photon-counting detector CT arthrography of the ankle with ultra-high-resolution collimation offers stellar image quality and tissue assessability. While bone depiction was found to be superior in combination with an ultra-sharp convolution kernel, the soft tissue evaluation benefited from employing reconstructions with a lower spatial frequency.

**Author Contributions:** Conceptualization, K.S.L. and J.-P.G.; data curation, K.S.L., V.H., T.S.P., T.A.B. and P.F.; formal analysis, K.S.L., J.-P.G., A.S.K., P.G. and P.F.; funding acquisition, J.-P.G.; investigation, K.S.L., A.S.K., H.H., M.W., V.H. and T.S.P.; methodology, K.S.L., J.-P.G., H.H., P.G., T.A.B. and P.F.; project administration, J.-P.G. and S.E.; resources, P.G., S.E. and T.A.B.; supervision, J.-P.G., A.S.K., T.A.B. and P.F.; validation, M.W., S.E. and P.F.; visualization, K.S.L. and H.H.; writing—original draft, K.S.L.; writing—review and editing, J.-P.G., A.S.K., H.H., M.W., V.H., T.S.P., P.G., S.E., T.A.B. and P.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** The Department of Diagnostic and Interventional Radiology receives funding from the German Research Foundation (DFG) for photon-counting CT studies. JPG [Z-3BC/02] and PG [Z-02CSP/18] were individually funded by the Interdisciplinary Center of Clinical Research Würzburg, Germany. Furthermore, this publication was supported by the Open Access Publication Fund of the University of Würzburg.

**Institutional Review Board Statement:** For this retrospective study, permission was obtained from the Institutional Review Board of the University of Würzburg, Germany (IRB number 20201117 04). All procedures were in accordance with the ethical standards of the institutional and national research committee and with the 1975 Declaration of Helsinki.

**Informed Consent Statement:** For this retrospective study, permission was obtained from the Institutional Review Board of the University of Würzburg, Germany.

**Data Availability Statement:** The datasets generated and/or analyzed during this study are not publicly available as CT data and DICOM headers contain patient information. Data can be obtained upon reasonable request from the corresponding author.

**Conflicts of Interest:** JPG, ASK, and TAB serve as research consultants for Siemens Healthineers, receiving speaker honoraria in the process. The authors of this manuscript declare no further conflicts or relationships with any companies, whose products or services may be related to the subject matter of the article.

#### **Abbreviations**

#### **References**

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Early Cancer Diagnosis

#### **Chapter 11**

### Forty Years of Arctic Primary Care Research on the Early Diagnosis of Cancer

*Knut Holtedahl*

#### **Abstract**

Usually, before a patient with cancer can be treated in a hospital, a general practitioner (GP) must suspect the diagnosis and refer the patient. GPs often worry that they could have done better for some of their cancer patients. Had there been an unreasonable delay of diagnosis? In the arctic, rural/urban city of Tromsø, this question became the subject of several scientific articles. Symptoms was an evident gateway to thinking about cancer in patients. In later years, there has been an explosion of good research studies about early diagnosis both in primary and secondary care. Through a northern gaze, the reader will be guided through a journey covering forty years of primary care-based research aiming at earlier diagnosis of cancer. Summing up, suggestions are given for: How to react upon signals from the body? And for the GP: 1. Explain unusual symptoms. 2. Add results from clinical findings and testing to symptoms. 3. Refer when the probability based on symptoms and findings exceed 3%. 4.  5. Think of early diagnosis of cancer as an important, challenging and interesting part of your effort to serve the patients who consult you!

**Keywords:** Neoplasm, Oncology, Early diagnosis, Primary care, General practice, Family practice, Public Health

#### **1. Introduction**

Care for people with cancer: the task is universal, but conditions vary in different areas of the world. Tromsø, in the beginning of the 1970s, was a small city with a recently established university, the northernmost university in the world. The oncological department was yet to come, and surgeons and internists dealt with patients in collaboration with oncologists in the bigger, southern cities.

Then there were the general practitioners (GPs). In the homes, some of the patients were ill with cancer. Time to talk, some relief, morphine for pain, and repeated visits, this was enriching for the GP and sometimes comforting for the patient and the family. Tromsø covered a large, arctic island community, part urban and part rural, with closeness to sea and mountains, where summer brings the midnight sun and winter features northern light and pastel colours and snow. For a GP, home visits were many, always on duty nights, and sometimes also on ordinary working days to patients calling the surgery. Means of transport, on sunny days and through winter wind and snow, were private cars, but also all kinds and

sizes of boats and exceptionally a seaplane or a helicopter. Occasionally, medical things were put in a rucksack in order to go skiing to the patient – a mode of home visit that was more common and over greater distances in the previous generation of GPs. Many Norwegian GPs would recognise descriptions and photos in Berger & Mohr's beautiful book about a fortunate man [1]. The book follows an English rural GP, dedicated to his practice and his patients, trying to combine empathy and lessons from life with wide-ranging theoretical learning that can help his patients. Landscapes may differ, but the GP's tasks were much the same.

In these homes, as well as in the surgeries, many questions came to mind. This article will concentrate on a question which arose naturally in this primary care context: Can cancer be diagnosed earlier? Many researchers have contributed to the present-day knowledge and understanding. Some early studies were performed in Tromsø. They may be a suitable starting point for a somewhat personal story about the modern development of early diagnosis primary care research. Altogether, in 2021, there are some answers to the question.

#### **2. Early diagnosis of cancer, in primary care**

GPs see some patients requiring urgent hospitalisation, turning out to have incurable cancer. Often, GPs will ask themselves whether they have reacted reasonably quickly to worries and symptoms presented? Could something have been done better? What about the young woman with a seemingly innocent lump on her neck, turning out to be an oral cancer? Or the man with long-standing abdominal pain who got a follow-up appointment but never returned? He died from a stomach cancer.  The third time, she was contacted and asked to come for an appointment, and yes, the blood came from a cervical cancer.

GPs benefit from much trust. People expect their GP to understand and react professionally, without delaying a diagnosis like cancer and the time before treatment may start. A patient seen by an oncologist or a surgeon would commonly be rapidly diagnosed. However, how would the specialist know about that patient if the GP did not refer, or only did so after the cancer had spread?

#### **3. Why writing now?**

Hopefully, senior medical students and young doctors in vocational training could learn something useful from this story. Younger GPs -including GPs working in rural areas where they often know their patients well – might become more confident in their clinical practice, and some might open to the possibility of transforming good questions into research. Contributing to the knowledge base is important for the exercise of medicine. Some of this knowledge should be produced in primary care, in order to get the whole picture of diagnostic challenges. Primary care must be an integrated part of the research community.

Finally, it would be nice if some readers think they get a better idea about when to see their GP if the thought of cancer bothers them, and about what to expect from the GP. The language here is simple enough for lay people to follow.

As this story develops, some results have been quoted and short commentaries given. For detailed methodologies and more extensive discussions, the reader may consult the articles in the literature list.

#### **4. The leap into research: 1977-1984**

In Norwegian medical schools, general practice was not taught as a specific topic until around 1970. General practice was not among the more prestigious disciplines in medicine, and GPs were not frequently authors of scientific papers.

Still, most students graduating from medical schools found work in general practice. During the 1950s and 60s, some brave British GPs like John Fry and John Howie ventured into more systematic studies. Even before them, the productive Robert Braun in Austria had made diagnostic checklists for general practice. In Norway, Bent Bentsen gathered practice registration material in his own surgery [2].

At this time, academic departments of general practice appeared in several countries, introducing relevant student teaching and new research agendas. A formal specialty of general practice was acknowledged in more and more countries.

One interesting initiative occurred in Norway: The national medical association decided to encourage this revival and financed the first professorship in general practice in Oslo. And: They gave practice compensation payment for up to six months for GPs wanting to take a research leave after presentation of a project.

This encouragement resulted in a project description and an application from Tromsø. Did some cancer patients have their diagnosis delayed by incorrect handling in primary care? A friendly librarian at the University library searched their recently acquired databases for articles combining keywords 'cancer' and 'general practice'. Articles were found, saying for instance that an early diagnosis was often important for patient prognosis [3, 4]. And there it was, the word matching many previous thoughts: DELAY. Diagnostic delay. Somebody had been interested in this, and had written about it [5, 6], a couple of them in general practice [7, 8]!

#### **5. Delay**

All GPs in Tromsø agreed to find medical journals for patients diagnosed with cancer, and one GP researcher went through all journals, taking structured notes. On request, the Norwegian Cancer registry furnished a list of all 108 patients in Tromsø municipality having been diagnosed with cancer in 1976. The following was noted from the medical journals: Age, sex, civil state, rural/urban habitat, weeks from first symptom to first consultation, weeks from first consultation to diagnosis. Also, laboratory tests and X-rays taken the last year, and an admittedly subjective but criteria-based evaluation of what seemed like reasonable actions for that type of cancer, in the situations described in the journals. Did the medical history appear sparse, adequate, penetrating? Was the clinical examination insufficient, good local/regional, or extensive? Did the researcher think there was diagnostic delay, based on the conclusion in the medical journal notes, the type of cancer and the number of weeks noted for the two intervals examined? If so, was this due to what the patient did, or to what the GP did? Given the conclusion the GP described at the end of the consultation, did the researcher think that the GP could have done a better job there and then, and thereby reduced a possible delay?

The University hospital also gave access to their archives. The same kind of anonymous structured notes were taken from their machine written journals, altogether 25 archives from primary or secondary care, for a population of 45000 inhabitants.

#### **Figure 1.**

*Diagnostic delay of cancer in medical journal study, 108 patients in Tromsø, Norway, 1976.*

#### **5.1 Results**

Three quarters of the patients could have had their diagnosis made earlier: Half of all patients saw their GP rather late in the course of the disease. In half of the cases the GP or the hospital doctor could have improved the diagnostic work-up. The overlap left one fourth of all patients with no kind of delay. Long waiting lists in primary or secondary care also played a part (**Figure 1**).

What could have been done better? For 43 of the 108 patients, one or more of these were noted: Apparently no follow-up when needed, insufficient medical history, insufficient clinical examination, lack of relevant laboratory examination or of x-ray referral, no or late referral to secondary care.

#### **5.2 Short reflection**

What was lacking, was good old GP work, with a potential of improvement through vocational training and continuous education!

#### **6. Symptoms: seven warning signals of cancer**

Symptoms patients had presented at consultation, also were recorded from the medical journals. Medical journals are not reliable sources of everything going on in a consultation, but symptoms seem to be among the well documented topics [9]. Many symptoms had been noted in medical journals from both primary and secondary care.

At that time, in most patient waiting rooms, there were posters quoting 'Seven warning signals of cancer' (**Table 1**). The posters advised patients to tell their doctor if they experienced any such symptoms. The first mention of 'the danger signals of cancer' occurred in a pamphlet developed during World War I, in a desire to

Seven 'classical' warning signals of cancer

Abbreviations used in text:

1. Sore

#### **Table 1.**

*Seven 'classical' warning signals of cancer.*

stretch medical resources and to emphasise disease prevention. Three such signals were soon distributed to the public, and by 1929 they had been translated into 22 different languages, despite no scientific studies validating the signals. By 1951, the number of signals had increased to seven (Personal communication, Gerry de Harven, American Cancer Society). By 1982, 'danger signals' had changed names to 'warning signals', and a minor revision made the first letter in each signal form the word CAUTION. The Norwegian translation was a quite accurate translation from the American original.

#### **6.1 Results**

One or more of the seven symptoms had been presented by 68 of the 108 patients with cancer. However, 35 patients presented other symptoms, a quite varied list. Most symptoms, including those on the list, were common and it could only be assumed whether the symptom stemmed from the cancer. Still, with a known cancer location, many recorded symptoms seemed to fit with the diagnosis. Some symptoms seemed to be better known than others by the public: lumps and irregular bleeding more quickly than other symptoms led to GP consultations. Overall, non-warning symptoms did not lead to slower consultation than warning signals.

#### **6.2 Short reflection**

It was possible that the list had a mission in reminding the GPs of being vigilant. The public may be more aware of some symptoms than of others. The role of warning signals seemed to merit further studies.

#### **7. Publish!**

The Journal of the Norwegian Medical Association published this study. A first article detailed the background, method, results and conclusions, and a second article gave casuistic examples of what the GP might improve [10, 11].

By now, a regular contact at the university library had been established. What had been written previously about early cancer diagnosis, was eagerly studied. In a British article from 1966, Grey [12] described how cancer can bring patients to GPs and the possible reactions of the doctor. Whole person medicine is the GP's starting point in consultations. From there, the medical history, the clinical examination and various tests and referral possibilities is the way to go. Patient delay, GP delay, hospital delay and even government delay from insufficient financing of health services, were described with casuistic examples.

Patient delay had been discussed considering social psychological factors in two articles from the US [13, 14]. Some hospital based articles described delay in relation to specific forms of cancer [15]. Jenkins' article on delay and Macadam's article focusing on gastrointestinal cancer were contemporary investigations from general practice [16, 17].

New questions were triggered by the original study. How frequent were the warning symptoms among patients consulting in general practice? - according to GP registrations, and according to patients interviewed after their consultation? In a general population? Had newly diagnosed cancer patients consulted for warning signals more often than other GP patients? Over the next three years, these questions were studied with a basis in general practice in Tromsø.

#### **8. Warning signals in patients who consult**

Fourteen GPs from four group practices, almost all GPs in Tromsø, registered anonymously for six months consecutive patients on an A6 card immediately after the consultation, marking initials, sex and date of birth. A cross in a square, one for each symptom, identified patients who presented one or more of the seven warning signals.

#### **8.1 Results**

In 11606 patients, 649 symptoms were recorded. Three of the signals, 'lump', 'bleeding' and 'indigestion' (**Table 1**) occurred far more often than the other signals. On average, warning signals were presented in 5.4% of all consultations, more frequently in women than in men. This was expected because of the possibility of lumps in breasts. The rate of warning signals increased with age, except for 'lump' which was frequent in children and young persons, and 'bleeding', frequent in younger women.

#### **8.2 Short reflection**

At that time, Norwegian GPs saw approximately 20 patients a day. If one in twenty patients presents a warning signal of cancer, it meant that on average, one such patient would consult a GP every day. That did not mean that many of them had cancer, but it meant that GPs had to think of that possibility at least once most of our working days!

#### **9. Warning signals in the general population**

The posters in waiting rooms and in the municipal bus aimed at informing patients and the general population. The symptoms should initiate a visit at their GP's surgery. How frequent were these symptoms? Did people really go see their doctor?

Two medical students in Tromsø volunteered to do a door-to-door survey in two areas of Tromsø, one with small houses and many elderly inhabitants, and one with a more suburban mix of higher concrete buildings and rows of houses. Every other entrance or house were visited in early evenings by one or the other student. Local papers had informed about the study. The presentation procedure and questioning had been standardised. People who consented to participate, were asked whether they during the last three months had experienced any of the seven symptoms which were read to them one by one. The A6 cards from the consultation study served to record the answers.

Moreover, one of the students was engaged to sit for one day at the waiting room of each of the four group practices while the consultation study was being done. When a patient came out of a GP's office, the students would ask for a brief interview and record symptoms the patient thought they had presented to the doctor. The answers were compared to the GP's registration for the same consultation.

#### **9.1 Results**

In 299 persons from the general population, one fourth said they sometimes during the last three months had felt one of the symptoms read aloud to them. There was no difference between age groups. Half of these people had visited the GP for this reason, more so in the highest age group. These were higher proportions than what used to be found in studies about why people see a doctor [18], suggesting that the warning signals do promote visits to the GP. 'Indigestion', 'lump' and 'cough/hoarseness' were frequent. During the four interview-days in the surgeries, more patients than GPs thought that the patient had presented this kind of symptoms, 28% versus 10%.

#### **9.2 Short reflection**

The symptoms in question no doubt are present in people's mind, far more frequently than when they signify cancer. Increased consultation may become a burden for the health services; on the other hand, the symptoms have been shown to be relevant for cancer, and an increased tendency for consultation may be a good thing when cancer can cause the symptom. The GPs seem to have stricter criteria for recognising warning signals than people consulting them.

#### **10. The first control groups: case–control study**

If you investigate a group of patients, it is difficult to have a clear idea of what caused or expressed disease without a similarly constituted control group. The consultation registrations took place during six months in 1981–1982. A new retrospective study of medical journals was planned. For these six months, the Norwegian cancer registry again furnished a list of patients diagnosed with new cancer in Tromsø. For each of the 65 cancer patients, a control patient was found among the group of patients having consulted before any diagnosis of cancer had been made in

#### **Figure 2.**

*Two kinds of study design: case–control study (looking back in time), and Cohort study with prospective recording of cancer (looking forward).*

the cohort (**Figure 2**). Matching criteria were same sex and the closest possible date of birth. This time, criteria were made for early versus late symptoms in the cancer patients, to see the potential prognostic gain from early diagnosis.

#### **10.1 Results**

Two third of cancer patients had presented early warning signals, and about 35% of control patients had presented corresponding symptoms. The difference was statistically significant both for males and females.

#### **10.2 Short reflection**

When early warning signals are more frequent in cancer patients than in other consulting patients, a window of diagnostic opportunity exists for GPs.

Altogether five articles were now sent to the Norwegian medical journal [19], including a discussion of the content of the list of warning signals, and possibilities given by observations of the person-related data. Also, some more common diagnostic traps facing the GPs were discussed (**Table 2**).

Later, a list of Tromsø cancer patients diagnosed during the first eighteen months after the symptom registrations, was provided by the Cancer registry. Eighty of these cancer patients could be found among the recorded consulting patients. A new matching with 80 control patients based on the same criteria as in the previous study, was performed. Additionally, three GPs performed an inter-observer agreement study concerning what warning signals were found by each of them in the medical records.

#### **10.3 Results**

Warning signals were registered from the journals of 78% of cancer patients, before patient or doctor knew that the patient would get a cancer diagnosis, and in 26% of control patients. Again, this was a significant difference. Warning signals recorded only at consultation occurred in 20 cancer patients and 13 control patients. This difference did not reach statistical significance [20]. Agreement about the presence of warning signals in the journals, measured with kappa statistics, was

Traps for GPs in early diagnosis of cancer

#### **Table 2.**

*Traps for GPs in early diagnosis of cancer.*

good both for cancer patients and control patients, with some variation between different symptoms and less good in control patients [21].

#### **10.4 Short reflection**

The greater frequency of warning signals in cancer patients, found in the retrospective medical journal study, was not evident in the prospective recording of cancer patients. However, the tendency was in the same direction. Overall, based on all the studies, a majority of cancer patients experienced a cancer-related symptom which was communicated to a doctor some time before diagnosis. Furthermore, it seemed possible to rely quite well on registrations of symptoms from medical journals.

#### **11. Strengthening the academic basis in the north: 1984–1991**

During the 1980s, the topic of early diagnosis gained visibility in vocational training – in the North, and soon nationally. A GP colleague in Oslo started a PhD thesis in the same cancer field [22] and initiated a book about different cancer topics for GPs [23]. The next couple of years, GPs attended continuing education seminars and studied books that gave better insight in clinical epidemiology [24] and statistics [25]. Based on the investigations in the north, a thesis [26] and a practical manual for GPs [27] were written. The Arctic University had a Department of Community medicine, led by a GP professor, and several GPs started teaching and research in combined academic and clinical positions.

At this time, a big step in technology also created important changes: The typewriter had previously necessitated total re-writing of manuscripts needing changes. Now, the two-diskette-slot personal computer had appeared and developed into a movable computer with a 20-megabyte hard-disk and one diskette slot, opening a new world of free writing that could easily be corrected again and again.

#### **12. A theoretical basis: understanding how probabilities may change**

It had become quite certain that the probability of diagnosing cancer in a patient presenting a warning signal, was greater than in a patient without such symptoms.

However, with the many non-cancer patients presenting similar symptoms, it was clear that the probability of cancer was still very low. In order to refer a patient, a GP should be able to convince specialists that investigations in hospital would have a reasonable chance of revealing a cancer, preferably an early-stage cancer. Working with the Tromsø data, it was calculated how many of the patients with one or more warning signals had turned out to have cancer: this proportion, known to GPs as the *positive predictive value* (PPV), was 3.7%. Perhaps not very impressive in a referral letter, but we will get back to this figure.

A chapter in a book about decision analysis showed how the 18th century Bayesian thinking allow to update the probabilities of a hypothesis when evidence is added [28]. This is the way a GP works! The patient presents a symptom. The GP already knows something about the patient: age, sex, perhaps something about heredity and profession. Then the GP starts to explore the problem: a further medical history, a focused clinical examination. Cumulated additional information may allow upgrading the probability of cancer, or in many cases, dismiss such a hypothesis without bothering the patient or the specialist or the system with unnecessary procedures. The new information may not be independent of what we already know, but the GP may then apply Bayes' axioms of conditional probability to arrive at a reasonable update of the previous probability.

Three more articles resulted: two were about diagnostic indexes allowing quantitative judgement about the relationship between symptoms and cancer [29, 30]. The third article gave examples of revising probabilities of cancer: Based on data from the 1982 study, positive predictive value (PPV) was calculated from consultation data and then revised adding new information from the medical journals [31]:

#### **12.1 Results/examples**

A 60–69 years-old male with 'indigestion' had a PPV of 2.3% for colorectal cancer. Adding information about a positive test for occult blood, PPV rose to 13.3%.

 Adding the information that this man was a daily smoker, PPV increased to 8.5%. If the man was a non-smoker, PPV decreased to 3.3%. The increase is smaller than for the occult blood example. This is because it may be assumed that 'indigestion' and occult bleeding are independent of each other, while 'cough/hoarseness' and daily smoking are less independent.

#### **12.2 Short reflection**

Such indexes can be calculated on the basis of empirical data. However, they also fit well with the more approximate way a GP works when analysing a patient problem. It is a way of thinking that implies both quantitative and qualitative considerations, and which most GPs apply intuitively and approximatively.

It is nice to be able to give examples based on data collected in primary care. However, we were still only in 1990 when these articles were published. Registrations in databases like Medline were in its infancy. The scientific journal, owned by Springer Verlag, ceased to appear the year after, and the articles in "Allgemeinmedizin" are not searchable in current databases. If you want to read the articles, you may use the Arctic University web-link given in the references. Also, for this and other examples of older articles in the reference list, a university library may help.

#### **13. Academia: on the right track, with mixed feelings of enthusiasm and professional loneliness: 1992–1999**

After rich years of full-time general practice, teaching and research at the university became a full time task for this author, although still with one day a week in the group practice in general practice. The 1990s was a period of increasing activity in primary care reunions, nationally and internationally, and many doctors presented primary care-based research. In some seminars and workshops, colleagues were asked to bring a cancer case of their own to discuss in small groups. This was motivating for the participants, who soon eagerly discussed how to improve their early diagnosis of cancer. Such group work later became part of the compulsory program in vocational training for the specialty of general practice in Norway. However, not everything was easy. The Arctic university was a young university, which admitted its first medical students in 1973. For the first decades, the competition for research grants was difficult with limited earmarking for primary care and competition with the more established universities. When grants were obtained, applicants for research positions were few. It was difficult to tempt colleagues living in the more populated south of Norway to apply for positions in the beautiful, but longer-winter north.

However, international primary care publications dealing with the early diagnosis of cancer, were relatively few during the 1990s. In workshops and congresses for GPs, interest in the subject was vivid, but with some exceptions [32, 33], the interest was only modestly reflected in studies from general practice. The focus on the early diagnosis topic weakened for a while at our department. General practice is a good place to get research ideas and produce evidence about many different clinical questions [34].

#### **14. The times they are a-changin' – fortunately: research boost and Ca-PRI - from year 2000 and onward**

Soon, however, a remarkable change occurred: Some GP based researchers, especially in the UK, but also in Denmark, Sweden, Belgium, the Netherlands, Australia, published interesting studies about the early diagnosis of cancer. They often drew upon large number of patients found in GP based databases and in official registries, and focused on major types of cancer [35, 36], in addition to cancer in general [37–40]. A GP can never know what kind of cancer the next patient presents, and it is useful to be prepared to diagnose just any cancer, frequent or rare. However, the frequent ones are more frequent and merit a closer look.

At this time in the north, all the almost 4000 GPs in Norway were invited to participate in an audit-type, one-sheet questionnaire study with much of the same intent as in previous studies, but this time recording cancer prospectively after an initial symptom registration in consecutive GP patients [41] (Cohort study, **Figure 2**). About 10% of the invited GPs volunteered to take part. In these studies, cancer suspicion was examined more closely.

#### **14.1 Results**

GPs' correct cancer suspicions were found to be six times more frequent than their erroneous lack of suspicion. Patient comorbidity and multiple consultations seemed to be underestimated by GPs as factors associated with cancer.

The discussion dealt with how GPs in their diagnostic attentiveness could consider ways of thinking, interpersonal awareness and relevant information related to symptoms and other factors [42]. The study also showed how a comprehensive GP approach should include knowledge derived from clinical examination and test results. This could increase sensitivity, i.e. findings correctly identifying patients with cancer, and help correctly suspect a diagnosis of cancer, in some cases with 'low-risk-but-not-no-risk' symptoms, or even without any relevant symptom [43].

#### **14.2 Short reflection**

The study suggests how knowledgeable, empathic medical work in primary care can make a positive difference for early cancer diagnostics.

Also, Johansen [44] interviewed GPs about the essential question "How does the thought of cancer arise in a general practice consultation?"

#### **14.3 Results**

Several contexts of attention were found: Practising basic knowledge, interpersonal awareness, intuitive knowing and fear of cancer. Such fear could affect both patient and doctor. Intuitive knowing was described as a tacit feeling of alarm which could be difficult to verbalise, but nevertheless was helpful. Intuition was supposed to build on the three other elements: knowledge, awareness, fear.

#### **14.4 Short reflection**

The complex quality of diagnostic analysis is demonstrated here through a qualitative approach. The study was performed around the same time as the previous, quantitative study. The results show how different methodological approaches may create complementary knowledge.

In 2008 our department was invited to participate in the creation of a permanent workshop promoting research about cancer in primary care; The Cancer and Primary Care Research International Network (Ca-PRI) [45]. This forum has proved to be an inspiration for many researchers in primary care, generating ideas and developing new ways and new standards for producing good knowledge about all aspects of cancer, with early diagnosis and cancer care as backbones. The important role of primary care in providing research-based knowledge about cancer, has been highlighted [46]. Now, in 2021, a first nationwide formal GP research practice network is about to be established in Norway.

To-day, it would be impossible to reproduce the delay findings based on the subjective criteria from the 1970s. A more modern approach emphasises the different intervals and milestones from first symptom to start of treatment, and encourages shortening of the different intervals with patients, GPs, hospital doctors and the administrative system as stakeholders. Not only the intervals from symptom to consultation, and from consultation to diagnosis counts: the time from diagnosis to first treatment is important as well [47]. The intervals have been clarified and standardised for research purposes [48, 49], and the Ca-PRI workshop is an active hot-spot for ideas and discussions.

In the last decade, many countries have organised different kinds of 'fast track' for patients suspected to have cancer [50]. This has helped shortening the time from symptom to treatment, which is in itself a good thing, and there is hope that it could also contribute to lowering cancer mortality.

*Forty Years of Arctic Primary Care Research on the Early Diagnosis of Cancer DOI: http://dx.doi.org/10.5772/intechopen.98580*

One welcome result of Ca-PRI connections was a six-country study of a new cohort of general practice patients, focusing on abdominal symptoms. Consultation data were collected in 2011, and cancer was registered prospectively after six months or more. A question to the GPs about cancer suspicion now distinguished between different reasons for such suspicion: symptoms, clinical findings, intuition.

#### **14.5 Results**

Unexpectedly, in statistical analyses intuition ranged higher than symptoms or clinical findings in the association with a subsequent new cancer [51]. The study further demonstrated that a wide range of symptoms may signal abdominal cancer, with 'rectal bleeding' reaching the highest association with cancer. PPV above 3% was found for visible bleeding in the urine or from rectum, and for weight loss that was associated with a more specific abdominal symptom [52].

An analysis of the subgroup with colorectal cancer demonstrated clinically important differences between colon and rectal cancer, and between proximal and distal colon cancer. Proximal colon cancer often has scarcity or slow debut of symptoms, slow development of anaemia and fewer positive findings on clinical examination, which may explain more urgent but less fast track referrals and less implication of the GP in the initiation of diagnosis. The challenges of the GP's work is discussed in the article [53].

#### **14.6 Short reflection**

Again, GPs' clinical competence seems to be essential for the work with early diagnosis of cancer. A process of better understanding of diagnostic approaches towards symptom poor cancer is ongoing and will need further research.

The results from these studies seem to suggest why GPs working professionally quite often may arrive at correct cancer suspicions [42]. At the same time, the subjective assessment of probability will always be influenced by ideas about similarity or representativeness or other prior notions which easily may bias conclusions [54]. It would have been too much to expect that GPs could correctly suspect all subsequent cancers. One fourth of cancer cases in the six-country study were not suspected by the GP, but with good clinical training it should be possible to lower this proportion in the future.

In the UK, the NICE guidelines [55] give GPs a rational way to deal with probabilities. Patients suspected of cancer should be referred when the positive predictive value reaches 3%. This may be a surprisingly low risk threshold, but a single symptom by itself usually has a lower PPV [56]. The seemingly low PPV of 3.7% for any warning signal in relation to cancer that was reported in 1991 [26] might well justify a referral in some cases. Later studies referred to here, seem to support this.

#### **15. Summing up/conclusion**

#### **15.1 Avoiding patient delay**

What can the layman do to react rationally to signals from the body? First, it is important to know your own body. A few common symptoms should always have an explanation, especially if your age or habits put you in a risk group for a certain cancer. Bleeding unexpectedly from a body orifice is perhaps the most important of such symptoms. Often one can understand that some innocent condition caused it, but if not, see your GP. The same way of thinking goes for a lump that is new or changing in size, for a mole growing or changing in colour, or a sore that does not heal. Cancer lodged deep in the body is more difficult, needing a certain size before signalled in the body. Cancer in an early stage is rarely painful. Pain may still be a relevant symptom, but you should know that pain is more than other symptoms caused by numerous non-cancerous conditions. Sometimes the best you can do is to observe and react to unexpected changes in the body, especially when they do not go away when you think they should.

#### **15.2 Promoting early diagnosis in general practice**

This article follows some of the stepstones leading up to present-day thinking about the early diagnosis of cancer. Some findings are in line with wise thoughts written even more than 40 years ago: Cox [57] worked in medical education and had been a professor of surgery before that. He wrote that "..beliefs about how likely different events and outcomes are derived from some facts, some habits and some hopes." Cox listed five important factors which are quoted backwards, in order to start with the most basic: Fifth, decisions are based on subjective probabilities, not objective probabilities. Fourth, probabilities are about this individual 50 year-old male with both his cough and his unique genetic, family, socioeconomic mix and disease history, not only any 50 year-old male with a cough. Third, what clinicians need is a probability given that symptom, not incidence figures. Second, clinicians think in probabilities in rather course categories, such as common, possible, rare. And first, when a probability is very low, its exact quantity is not important.

His further discussion is well worth reading, too. However, his article suffers the same lack of visibility as many early papers: the journal in question has been digitalised only from 2002. Again, try a university library.

Hence, how is this to be summed up for to-day's GPs?

1.Explain unusual symptoms

The vocational training of doctors should make them acquainted with the literature about warning signals, or alarm symptoms, as they are also called. Some symptoms like unexpected bleeding always need an explanation: Although often having a benign cause, it is important to exclude serious disease like cancer. Sometimes the distinction between symptoms and signs is blurred: In the early cancer context, anaemia is most often a sign discovered through the GP's blood tests rather than something the patient feels.

2.Add results from clinical findings and testing to symptoms

Most patients with cancer consult when their cancer can still be treated with a curative intent. This is motivating for a GP's work. In an early stage, less than half of cancer patients present with a warning signal in the consultation, but more than half have a warning signal and/or some other cancer relevant but low-risk symptom. Adding findings from clinical examination and testing, the GP will be able to suspect cancer in about four of five cases a short time after a patient consults [43].

3.Refer when the probability based on symptoms and findings exceed 3%

Usually, a GP needs some other information pointing in the same direction as the symptom, or replacing the symptom, to revise a PPV above the 3% NICE

level. If you do your GP job and examine carefully, you may even add your intuitive suspicion, which has been shown to be of importance.

4.Consider 'fast track' when you seriously suspect cancer

Patients with a warning signal have a greater probability to be referred to cancer patient pathways. The difficult challenge for GPs is to pursue more vague symptoms and refer relevant patients when a suspicion persists. Ordinary, comprehensive GP clinical work, attentive to details and to who the patient is, can facilitate this.

5.Last, but not least: Think of early diagnosis of cancer as an important, challenging, and interesting part of your effort to serve the patients who consult you!

### **Acknowledgements**

Primarily, to all good GP colleagues who over the years helped with registrations. Also, to my university colleagues who gradually helped me understand scientific reasoning and method. Finally, to my co-authors over the years, to referees who gave constructive criticism to scientific manuscripts and to everybody who helped facilitate the research.

### **Funding**

The publication charges for this article has been funded by a grant from the publication fund of UiT The Arctic University of Norway.

### **Conflict of interest**

The author declares no conflict of interest.

### **Author details**

Knut Holtedahl Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway

\*Address all correspondence to<EMAIL_ADDRESS>
© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### **References**

[1] Berger J, Mohr J. A fortunate man. London: Canongate; 1967.

[2] Bentsen B. The accuracy of recording patient problems in general practice. J Medic Educ. 1976;51:311-6.

[3] Editorial: The image of cancer. Lancet. 1975;1(7919):1284.

[4] Miller DG. What is early diagnosis doing? Cancer. 1976;37(S1):426-32. doi:10.1002/1097-0142(197601)37: 1+<426::Aid-cncr2820370704> 3.0.Co;2-p

[5] Pack G, Gallo J. The culpability for delay in the treatment of cancer. American Journal of Cancer. 1938;33:443-62.

[6] Leach J, Robbins G. Delay in the diagnosis of cancer. JAMA. 1947;135:5-8.

[7] McWhinney I. The early diagnosis of cancer. Five years' experience in general practice. J R Coll Gen Pract. 1962;5:404-14.

[8] Starey CJ. The diagnosis and treatment of cancer in a general practice. J Coll Gen Pract. 1966;12(1):32-42.

[9] Feinstein AR, Pritchett JA, Schimpff CR. The epidemiology of cancer therapy. IV. The extraction of data from medical records. Ann Intern Med. 1969;123:571-90.

[10] Holtedahl KA. [Diagnosis of cancer in general practice. I. Can diagnosis be made earlier?]. Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke. 1980;100(19- 21):1219-23. English summary. . Available from: https://hdl.handle. net/10037/12542.

[11] Holtedahl KA. [Diagnosis of cancer in general practice. II. What can the

general practitioner improve? Case reports as a teaching aid]. Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke. 1980;100(19-21):1224-6. Available from: https://hdl.handle.net/10037/ 12539.

[12] Gray DJP. The role of the general practitioner in the early detection of malignant disease. Transactions Hunterian Soc (London). 1966;25:121-75.

[13] Cobb B, Clark RL, Jr., Mc GC, Howe CD. Patient-responsible delay of treatment in cancer; a social psychological study. Cancer. 1954;7(5):920-6. doi:10.1002/ 1097-0142(195409)7:5<920::aidcncr2820070516>3.0.co;2-r

[14] Hackett TP, Cassem NH, Raker JW. Patient delay in cancer. The New England journal of medicine. 1973;289(1):14-20. doi:10.1056/ NEJM197307052890104

[15] Howson JY. Observations on the delay period in the diagnosis of pelvic cancer. Med Clin North Am. 1948;32:1573-81. doi:10.1016/ s0025-7125(16)35623-1

[16] Jenkins S. Diagnostic delay in neoplastic disease. J R Coll Gen Pract. 1978;28(197):724-8.

[17] Macadam DB. A study in general practice of the symptoms and delay patterns in the diagnosis of gastrointestinal cancer. J R Coll Gen Pract. 1979;29(209):723-9.

[18] White KL, Williams TF, Greenberg BG. The ecology of medical care. The New England journal of medicine. 1961;265:885-92. doi:10.1056/ NEJM196111022651805

[19] Holtedahl KA. [Cancer diagnosis in general practice III-VII. The general

*Forty Years of Arctic Primary Care Research on the Early Diagnosis of Cancer DOI: http://dx.doi.org/10.5772/intechopen.98580*

practitioner's recording of cancer warning signals in their patients. IV. Recording of interviews on cancer warning signals. Patients in general practice and in the general population. V. Patients with and without cancer. Who consults the physician for the 7 warning cancer signals? VI. The content of the warning signals. Is persistent pain relevant as a warning signal? VII. Alarm bell symptoms, alarm bell data and pitfalls. Some useful reminders for the general practitioner's work in cancer diagnosis]. English summary. Tidsskrift for den Norske laegeforening. 1984;104(12):799-812. Available from: https://hdl.handle.net/10037/12543 ; https://hdl.handle.net/10037/12544 ; https://hdl.handle.net/10037/12545 ; https://hdl.handle.net/10037/12547 ; https://hdl.handle.net/10037/12548.

[20] Holtedahl KA. The value of warning signals of cancer in general practice. Scand J Prim Health Care. 1987;5(3):140-3. doi:10.3109/<PHONE_NUMBER>9013994

[21] Holtedahl KA. Inter-observer variation on registration of signals of cancer. Scand J Prim Health Care. 1987;5(3):133-9. doi:10.3109/<PHONE_NUMBER>9013993

[22] Nylenna M. Diagnosing cancer in general practice: from suspicion to certainty. Br Med J (Clin Res Ed). 1986;293(6542):314-7. doi:10.1136/ bmj.293.6542.314

[23] Nylenna M, Gundersen S, Johannessen JV, (eds). Kreft i almenpraksis [Cancer in General Practice]. Oslo: Landsforeningen mot kreft, Universitetsforlaget; 1985. In Norwegian.

[24] Sackett Dl, Haynes R, Tugwell P. Clinical epidemiology. A basic science for clinical medicine. . First edition. (Second edition 1991) ed. Boston: Little, Brown and Company; 1985.

[25] Bland M. An introduction to medical statistics. Oxford: Oxford University Press; 1987.

[26] Holtedahl KA. Diagnosis of cancer in general practice. A study of delay problems and warning signals of cancer, with implications for public cancer information and for cancer diagnostic strategies in general practice (Thesis) University of Tromsø, Norway: ISM skriftserie nr. 16, 1991. : http://hdl. handle.net/10037/2325

[27] Holtedahl KA. Early diagnosis of cancer in general practice. A manual. Berlin: Springer Verlag; 1990.

[28] Chapter 4. The use of diagnostic information to revise probabilities. In: Weinstein MC, Fineberg, H.V, editor. Clinical decision analysis. Philadelphia: W.B. Saunders Company; 1980.

[29] Holtedahl KA. A method of calculating diagnostic indexes for possible cancer symptoms in general practice. Allgemeinmedizin. 1990;19:74- 9. Available from: http://hdl.handle. net/10037/12484.

[30] Holtedahl KA. More diagnostic indexes from general practice for some important forms of cancer. Allgemeinmedizin. 1990;19:80-5. Available from: https://munin.uit.no/ handle/10037/12487.

[31] Holtedahl KA. Probability revision in general practice: the cases of occult blood in stool in patients with indigestion, and daily smoking in patients who cough. Allgemeinmedizin. 1990;19:35-8. Available from: http://hdl. handle.net/10037/12453.

[32] Mansson J, Bjorkelund C, Hultborn R. Symptom pattern and diagnostic work-up of malignancy at first symptom presentation as related to level of care. A retrospective study from the primary health care centre area of Kungsbacka, Sweden. Neoplasma. 1999;46(2):93-9.

[33] Buntinx F, Wauters W. The diagnostic value of macroscopic haematuria in diagnosing urological cancers: a meta-analysis. Family Practice. 1997;14:63-8.

[34] Holtedahl K. Research and practice combined--ideas for a life in general practice. Fam Pract. 2008;25(2):132-6. doi:10.1093/fampra/cmn002

[35] Bruyninckx R, Buntinx F, Aertgeerts B, Van Casteren V. The diagnostic value of macroscopic haematuria for the diagnosis of urological cancer in general practice. Br J Gen Pract. 2003;53(486):31-5.

[36] Hamilton W, Round A, Sharp D, Peters TJ. Clinical features of colorectal cancer before diagnosis: a populationbased case-control study. Br J Cancer. 2005;93(4):399-405. doi:10.1038/ sj.bjc.6602714

[37] Hamilton W. The CAPER studies: five case-control studies aimed at identifying and quantifying the risk of cancer in symptomatic primary care patients. Br J Cancer. 2009;101:S80-S6.

[38] Jones R, Latinovic R, Charlton J, Gulliford MC. Alarm symptoms in early diagnosis of cancer in primary care: cohort study using General Practice Research Database. BMJ. 2007;334:1040- 4. doi:10.1136/bmi.39171.637106.AE

[39] Lyratzopoulos G, Neal RD, Barbiere JM, Rubin GP, Abel GA. Variation in number of general practitioner consultations before hospital referral for cancer: findings from the 2010 National Cancer Patient Experience Survey in England. Lancet Oncol. 2012;13(4):353-65. doi:10.1016/ S1470-2045(12)70041-4

[40] Rubin G, Vedsted P, Emery J. Improving cancer outcomes: better access to diagnostics in primary care could be critical. Br J Gen Pract. 2011;61(586):317-8. doi:10.3399/ bjgp11X572283

[41] Ingebrigtsen SG, Scheel BI, Hart B, Thorsen T, Holtedahl K. Frequency of 'warning signs of cancer' in Norwegian general practice, with prospective recording of subsequent cancer. Fam Pract. 2013;30(2):153-60. doi:10.1093/ fampra/cms065

[42] Scheel BI, Ingebrigtsen SG, Thorsen T, Holtedahl K. Cancer suspicion in general practice: the role of symptoms and patient characteristics, and their association with subsequent cancer. Br J Gen Pract. 2013;63(614): e627-35. doi:10.3399/bjgp13X671614

[43] Scheel BI, Holtedahl K. Symptoms, signs, and tests: The general practitioner's comprehensive approach towards a cancer diagnosis. Scand J Prim Health Care. 2015;33(3):170-7. doi: 10.3109/02813432.2015.1067512

[44] Johansen ML, Holtedahl KA, Rudebeck CE. How does the thought of cancer arise in a general practice consultation? Interviews with GPs. Scand J Prim Health Care. 2012;30(3):135-40. doi:10.3109/0281343 2.2012.688701

[45] The Cancer and Primary Care Research International Network (Ca-PRI) [Internet]. [cited 13 June 2021]. Available from: https://www. ed.ac.uk/usher/cancer-primarycare-research-international-network.

[46] Rubin G, Berendsen A, Crawford SM, Dommett R, Earle C, Emery J, et al. The expanding role of primary care in cancer control. The Lancet Oncology. 2015;16(12):1231-72. doi:http://dx.doi.org/10.1016/ S1470-2045(15)00205-3

[47] Hanna TP, King WD, Thibodeau S, Jalink M, Paulin GA, Harvey-Jones E, et al. Mortality due to cancer treatment delay: systematic review and metaanalysis. BMJ. 2020;371:m4087. doi:10.1136/bmj.m4087

*Forty Years of Arctic Primary Care Research on the Early Diagnosis of Cancer DOI: http://dx.doi.org/10.5772/intechopen.98580*

[48] Olesen F, Hansen RP, Vedsted P. Delay in diagnosis: the experience in Denmark. Br J Cancer. 2009;101 Suppl 2:S5-8. doi:10.1038/sj.bjc.6605383

[49] Weller D, Vedsted P, Rubin G, Walter FM, Emery J, Scott S, et al. The Aarhus statement: improving design and reporting of studies on early cancer diagnosis. Br J Cancer. 2012;106(7):1262-7. doi:10.1038/ bjc.2012.68

[50] Holtedahl K. Challenges in early diagnosis of cancer: the fast track. (Editorial). Scand J Prim Health Care. 2020;38(3):251-2. doi:10.1080/02813432. 2020.1794415

[51] Holtedahl K, Vedsted P, Borgquist L, Donker GA, Buntinx F, Weller D, et al. Abdominal symptoms in general practice: Frequency, cancer suspicions raised, and actions taken by GPs in six European countries. Cohort study with prospective registration of cancer. Heliyon. 2017;3(6):e00328. doi:10.1016/j. heliyon.2017.e00328

[52] Holtedahl K, Hjertholm P, Borgquist L, Donker GA, Buntinx F, Weller D, et al. Abdominal symptoms and cancer in the abdomen: prospective cohort study in European primary care. Br J Gen Pract. 2018;68(670):e301-e10. doi:10.3399/bjgp18X695777

[53] Holtedahl K, Borgquist L, Donker GA, Buntinx F, Weller D, Campbell C, et al. Symptoms and signs of colorectal cancer, with differences between proximal and distal colon cancer. A prospective cohort study of diagnostic accuracy in primary care. BMC Family Practice. 2021. DOI: 10.1186/s12875-021-01452-6

[54] Tversky A, Kahneman D. Judgment under Uncertainty: Heuristics and Biases. Science. 1974;185(4157):1124-31. doi:10.1126/science.185.4157.1124

[55] Suspected Cancer: Recognition and Referral (NICE guideline 12). London

2015. Available from: https://www.ncbi. nlm.nih.gov/pubmed/26180880.

[56] Shapley M, Mansell G, Jordan JL, Jordan KP. Positive predictive values of >/=5% in primary care for cancer: systematic review. Br J Gen Pract. 2010;60(578):e366-77. doi:10.3399/ bjgp10X515412

[57] Cox KR. The GP and the cancer patient. What does a GP do about the person who might have cancer? Australian Family Physician. 1978;7(June ):757-68.

### Section 9


*4.1.2 Expansion*

*Cell Growth*

**Figure 2.**

autophagosome precursors called phagophores. In mammalian cells, phagophores can be formed at PAS sites proximal to ER, mitochondria, or plasma membrane [13, 14]. In yeast however, PAS structures are perivacuolar in nature, leading phagophores to originate at locations proximal to the vacuole with membrane contributions with other cellular locations like discussed below. While mammalian cells can display many PAS structures at steady state, yeast often display one of these struc-

*Lipid biosynthesis and trafficking during autophagosome biogenesis and fusion. The relative lipid contributions via lipid trafficking or lipid biosynthesis from each organelle are shown. (A) upon autophagy induction, membrane is sequestered from pools of lipid donors such as the ER, mitochondria, Golgi, endosome and vacuole to form the pre-autophagosomal structure (PAS) or isolation membrane (IM). (B) PI in the PAS is converted to PI3P via Vps34 and Atg8-PE is enriched, allowing for IM expansion and closure. (C) Additional lipid membrane from Atg9-Atg27 vesicle trafficking allows for further expansion of the IM. (D) Autophagosome (AV) maturation is completed once PI3P is converted into PI by myotubularin phosphatases such as Ymr1. The mature AV can fuse to the vacuole which has converted PI3P into PI(3,5)P2 via Fab1 kinase. PI(3,5)P2 permits fusion of AV and endosomes. Vacuole lipid homeostasis is further aided by Snx4 trafficking of PS and Atg27*

Initially, activated or triggered by upstream inhibition of mTOR, core autophagy proteins collect at the PAS structure. These core factors include the ULK1 complex, ATG13, FIP200, ATG101, (yeast Atg1, Atg13, Atg17, Atg29 and Atg31) [13, 14]. The mobilization of these factors ultimately leads to the PAS recruitment and activation of the PI3K/Vps34 kinase complex which allows for the generation of PI3P at this site (from PI) (**Figure 2A**) [13, 14, 30, 31]. This enzyme activity drives forward phagophore initiation/nucleation, allowing additional recruitment of other proteins like WIPI proteins (Atg18 in yeast). WIPI proteins are key PI3P effectors. PI3K regulator proteins like ATG14 (Atg14 in yeast) are also recruited to the PAS, allowing for the modulation of initiation/nucleation of phagophore formation [13, 14]. ATG14 is also able to mediate homotypic fusion of single-membrane vesicles at the PAS, allowing more traditional membrane vesicles delivered to the PAS to fuse and contribute to the nucleation and growth of the phagophore [13, 14]. In this way, the phagophore has been found to accept lipid inputs from the ER, ER exit sites (ERES), the Golgi, the plasma membrane and recycling endosomes for its growth

**92**

tures at any given time.

*from the endosome and vacuole.*

and expansion (**Figure 2A**) [13, 14].

The lipidation of Atg8 (LC3) onto PE lipid molecules in the growing phagophore membrane is key for autophagosome formation. Other Atg proteins like ATG16L1 (yeast Atg16) as well as ATG12-ATG5 are required for Atg8 lipidation with PE. Interestingly, some of these required Atg factors like ATG16L1 partly reside in the recycling endosome and have been found to localize to the PAS in a PX-BAR/ SNX protein-dependent manner (for example, SNX18) [13, 14]. While not considered core Atg proteins, PX-BAR/SNX proteins are membrane remodeling proteins that have also been found to be required for autophagosome formation.

While the exact lipid composition of the phagophore/autophagosome is still under debate, because of the findings described above, PI3P is thought to be one of the most abundant lipid species present in these structures. In fact, recent findings identify the ATG protein ATG2A as a lipid shuttle factor that facilitates PI3P-dependent autophagosome growth [42–44]. Other phosphoinositides such as PI4P, PI(4,5)P2 and PI(3,5)P2 have also been suggested to play a role in the expansion of the phagophore [13, 14]. Apart from these, as mentioned above, sphingosine-1-phosphate (S1P) and ceramide, also contribute to autophagy. And while, Atg8/LC3 lipidation resulting in LC3-PE is important for the expansion and closure of the autophagosome, the intracellular membranes that are the source of this PE still remain to be identified. PE is produced from phosphatidylserine (PS) in mitochondria, which might be one of the sources of PE (**Figure 2A**). PE might also be shuttled from the ER, plasma membrane and recycling endosomes. It has been recently shown by Ma et al. [39], that PS trafficking by sorting nexin Snx4 in yeast is required for maintaining the correct lipid composition of the vacuole for autophagosome fusion in yeast (**Figure 2C**). Thus, maintenance of organelle lipid identity through proper trafficking and lipid homeostasis are crucial for autophagy as well.

## *4.1.3 ATG9 trafficking*

ATG9 (Atg9 in yeast) is a six-transmembrane protein that is required for autophagosome formation [45–52]. ATG9 trafficking is one of the most studied topics in the autophagy field, highlighting the important role it plays in autophagy—the autophagic phenotypes of null mutants are very penetrant. While this is the case, we still lack detailed information about the function of this protein during autophagy. Yeast studies have shown that Atg9 is localized to PAS as well as cytoplasmic vesicles of 30–60 nm diameter that bud-off of the late Golgi. It is believed that Atg9 shuttles between the PAS and its cytoplasmic vesicle pool upon autophagy induction (**Figure 2C**). At the PAS, Atg9 associates with Atg1, Atg2 as well as Atg18. Since Atg9 is a transmembrane protein, its trafficking directly affects the funneling or channeling of membrane to the PAS and the growing autophagosome. The Atg9 vesicles are thought to originate at the Golgi and contain fusion factors such as subunits of the TRAPIII (Trs85) complex that are responsible for fusion with the growing autophagosome [45, 46, 52]. Once Atg9 reaches the lysosome/vacuole as autophagosomes fuse, some studies suggest that the protein can be recycled out of the vacuolar membrane for reuse in new rounds of autophagosome formation. These studies are synergistic with findings that Atg9 traffics through endosomal compartments, as this might be an intermediary step important for recycling.

This recycling model is supported by the observation that mutations in the retromer complex, when combined with mutations in tethering factor Trs85, can abrogate trafficking of Atg9 to the PAS. Similarly the combination mutations with GARP subunits that are responsible for tethering vesicles to the Golgi from the endosome, with Trs85 result in defective autophagy. Atg9 trafficking is influenced by other autophagy proteins such as Atg27 and Atg23 [53–56]. Atg23 is a peripheral membrane protein that facilitates the anterograde trafficking of Atg9 from the Golgi to the PAS. Atg27, another transmembrane protein that facilitates formation of Atg9 vesicles at the late Golgi, is itself observed to be present in early/late endosomes, PAS, Golgi and vacuolar membrane. Atg27 can be retrieved from the vacuole in a process that is Snx4-dependent. Furthermore, earlier studies identified a C terminal tyrosine (YSAV) motif in Atg27 that is important for the proper delivery of Atg27 to the vacuole as well as to maintain Atg9 pools at the endosome that can be mobilized to different compartments during autophagy (**Figure 2C**). Taken together, the complexity of Atg9 trafficking synergizes with the hypothesis that a collection of different membranes such as endosome and Golgi all contribute to the lipid identity of the autophagosome.


**1. Introduction**

Void nucleation is the first step towards fracture in many different contexts, including quasi-static tearing, dynamic spall, creep rupture, irradiation creep, and wear debris generation. Voids are predominantly thought to nucleate at second phase particles, either when the particles crack or when the interface between the particle and matrix debonds [1]. Here, we focus on the earliest stages of void nucleation via particle delamination. Subsequent to nucleation, these voids grow until they induce fracture. While many studies have employed continuum models, such as finite element modeling [2–5], to evaluate the process of void nucleation, the atomistic mechanisms governing nucleation are less well studied. And yet, since void nucleation begins at the nanoscale, it is intrinsically an atomistic process [6]. Our goal in this work is to evaluate void nucleation in a model system with an incoherent, second-phase particle (*θ*-particle in Al) in an effort to reveal the underlying micromechanics and kinetically limiting processes.

Given its central role in fracture, continuum damage models commonly invoke void nucleation in their underlying formalisms. Perhaps the most popular approach is the porous plasticity model of Gurson, Tvergaard, and Needleman [7] which utilizes a yield

**Citation:** Zhao, Q.Q.; Boyce, B.L.; Sills, R.B. Micromechanics of Void Nucleation and Early Growth at Incoherent Precipitates: Lattice-Trapped and Dislocation-Mediated Delamination Modes. *Crystals* **2021**, *11*, 45. https://doi.org/10.3390/cryst11010045

Received: 21 November 2020 Accepted: 2 January 2021 Published: 7 January 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

criterion that is a function of the void volume fraction, *f* . In this model, the void volume fraction is governed by a differential equation of the form:

$$
\dot{f} = \dot{f}\_{\text{max}} + \dot{f}\_{\text{growth}}
$$

where . *f* nuc and . *f* growth account for the contributions from nucleation and growth events, respectively. Ideally, the term . *f* nuc would be derived from a fundamental, micromechanicsbased understanding of void nucleation. Given that this understanding is lacking, a more phenomenological approach is commonly utilized. For example, it is commonly assumed that void nucleation occurs at particles when a critical plastic strain, *εP c* , is reached, and that *εP c* varies from particle to particle according to a probability density function *F εP*/*εP c* where *εP* is the equivalent plastic strain [8,9]. The void volume fraction then increases in time as a result of void nucleation according to the expression:

$$\dot{f}\_{\text{nuc}} = F\left(\varepsilon^P / \varepsilon\_c^P\right) \dot{\varepsilon}^P$$

where . *ε P* is the equivalent plastic strain rate. Usually, *F εP*/*εP c* is assumed to be a normal distribution with mean *εP c* and standard deviation *sεc* [8], however there is no direct evidence which justifies this choice. Furthermore, *εP c* and *sεc* are treated as empirical parameters that are fitted against experimental data (e.g., stress-strain curves). While this and other similar phenomenological approaches have been applied pervasively across the literature, the Sandia Fracture Challenges have recently shown that these models often fare poorly when making blind fracture predictions [10–12]. This motivates a deeper look at the micromechanics of void nucleation, so that strong assumptions about what governs fracture (a critical strain?) and how the propensity for fracture varies across the population of particles (normally distributed?) can be lifted.

Unfortunately, the critical strain *εP c* is not easily studied using micromechanical simulations because plastic strain is really a homogenized, macroscale concept; at the microscale where discrete dislocations interact with particles, plastic strain is not a very relevant concept. On the other hand, some damage mechanics models employ a critical stress *σc* at which nucleation occurs [9], which is more consistent with micromechanics modeling (the stress state can be specified in molecular dynamics, for example). Here, we argue, however, that rather than focusing on a "critical stress" at which void nucleation occurs, it makes more sense to consider how the *nucleation rate* varies with stress state, temperature, etc. In other words, void nucleation can occur over a range of stresses, with the nucleation rate increasing as the stress is increased. This view is more consistent with other works on crack nucleation, which focus on the nucleation rate [13,14]. Within this view, the critical stress is the stress at which the nucleation rate goes to infinity, meaning that nucleation occurs instantaneously. We note that the nucleation rate for a given state is likely only welldefined in an average sense, because nucleation is a stochastic phenomenon. This means that at each state, there is a distribution of nucleation rates (which could be interpreted in probabilistic terms). We argue that the possibility of "subcritical" nucleation, i.e., with *σ* < *σc*, and the statistical aspects of nucleation could be important to the overall nucleation process. For these reasons, our focus here is on the stress and temperature dependence of the void nucleation rate.

An important nuance to the study of void nucleation is deciding when exactly a void is said to "nucleate." As soon as a crack appears within the particle-matrix interface? Or after a significant fraction of the interface has delaminated? We may expect that a clear nucleation event occurs whereby a crack "suddenly" appears along the interface, allowing us to disentangle this terminological ambiguity, although the appearance of a crack is often limited by the spatial and temporal resolution of the techniques employed. In the present approach, with atomic-scale and picosecond resolution, the initial emergence of a crack is still difficult to define: we observed steady growth of an interfacial crack starting

from a vacancy-sized nucleus. We were unable to determine the precise mechanism by which the vacancy-sized nucleus appeared, however. Furthermore, the appearance of the vacancy-sized nucleus did not control the kinetics of void nucleation. Instead, we found that it was the subsequent growth of the crack that governed the overall delamination (e.g., void nucleation) process. Hence, we find that it is the delamination rate, controlled by the growth of a crack, which governs the void nucleation rate. For this reason, we refer to our simulations as studying void nucleation and "early growth."

Void nucleation has been studied in perfect crystals [15–22], at grain boundaries [23,24], ahead of crack tips [25], and at second-phase particles [26–29] using molecular dynamics. In most cases, void nucleation results from interactions between several crystallographic defects, such as grain boundaries and twins/dislocations [23,24], pairs of intersecting stacking faults [21], and particles and dislocations [26,27,30]. The previous work on particlemediated void nucleation is most relevant here. Coffman et al. [31] studied void nucleation in Si under uniaxial tension with a cubic nanograin "particle" that delaminated from the surrounding matrix. They first performed atomistic simulations to calibrate a continuum fracture model (a cohesive zone model), and then compared atomistic and continuum predictions of void nucleation. In general, they found poor agreement between the models, motivating the need for further studies of void nucleation with atomistic resolution. Pogorelko and Mayer [26–29] and Cui and Chen [30] studied void nucleation at spherical particles in a variety of material systems, considering the influence of strain rate, temperature, simulation box size, and particle volume fraction on the delamination behavior under a fixed uniaxial strain rate. In simulations with face-centered cubic (FCC) matrices [26,27,29,30], nucleation was observed to occur in two stages: first a crack nucleated at the top and bottom poles along the loading axis (similar to the behavior predicted by continuum models [2]), and then after some subsequent growth dislocations were emitted from the crack tips. On the other hand, nucleation with body-centered cubic and hexagonal close-packed (HCP) matrices seemed to initiate from defects in the matrix rather than at the particle-matrix interface [28]. While the tensile strength of these systems has been characterized extensively using these simulation results, the nucleation rate could not be estimated because of the fixed-strain-rate boundary conditions.

Our study here had two goals: (1) to assess the stress and temperature dependence of the void nucleation and early growth rate with MD and (2) identify the micromechanical processes which govern the kinetics. In contrast to previous work [26–30], we perform simulations here with a fixed stress state (and temperature), so that our results can be used to estimate the stress and temperature-dependent rates. Our findings indicate that void nucleation may be rate limited by the kinetics of crack growth processes rather than the kinetics of crack nucleation (e.g., the time it takes for a crack to appear). Furthermore, we show two distinct delamination modes with drastically different growth kinetics. Finally, we conclude that a brittle delamination mode which we term *lattice-trapped delamination* may be an important contributor to void nucleation. While the stress range employed here (5.7 to 7.2 GPa) is high relative to quasi-static loading, it is in the range where shock spallation is observed under high loading rates [32,33]. Furthermore, through a thermal activation analysis of our data we are able to extrapolate our results down to lower stress conditions. The remainder of the work is organized as follows. In Section 2 we discuss our simulation setup and analysis methods, in Section 3 we present our results, in Section 4 we discuss the implications of our findings and compare results with existing theories, and finally conclude the manuscript in Section 5.