**3. Results**

The following sections present detailed results from the previous chapter's analytical and empirical analysis. Trade-off studies, which are explained in the next section, provide the basis of the final design choice.


3. Switched Generalized Function Projective Synchronization between Two Hyperchaotic Systems

In this section, we investigate the adaptive SGFPS between systems (4) and (5) with fully unknown parameters.

Suppose that system (4) is the drive system whose four variables are denoted by subscript 1 and system (5) is the response system whose variables are denoted by subscript 2. Then the drive and response systems are described by the following equations, respectively,

$$\begin{cases} \dot{x}\_1 = a\_1(y\_1 - x\_1) \\ \dot{y}\_1 = b\_1 x\_1 - x\_1 z\_1 - c\_1 y\_1 + w\_1 \\ \dot{z}\_1 = x\_1 y\_1 - d\_1 z\_1 \\ \dot{w}\_1 = -k\_1 y\_1 - r\_1 w\_1 \end{cases} \tag{6}$$

and

$$\begin{cases} \dot{x}\_2 = a\_2 x\_2 - y\_2 z\_2 + w\_2 + u\_1 \\\\ \dot{y}\_2 = x\_2 z\_2 - b\_2 y\_2 + u\_2 \\\\ \dot{z}\_2 = x\_2 y\_2 - c\_2 z\_2 + x\_2 w\_2 + u\_3 \\\\ \dot{w}\_2 = -y\_2 + u\_4 \end{cases} \tag{7}$$

where a1, b1, c1, d1, k1, r1, a2, b2 and c2 are unknown parameters to be identified, and ui(i = 1, 2, 3, 4) are controllers to be determined such that the two hyperchaotic systems can achieve SGFPS, in the sense that

$$\begin{cases} \lim\_{t \to \infty} \|e\_1\| = \lim\_{t \to \infty} \|x\_2 - \phi\_1(x)z\_1\| = 0\\ \lim\_{t \to \infty} \|e\_2\| = \lim\_{t \to \infty} \|y\_2 - \phi\_2(x)w\_1\| = 0\\ \lim\_{t \to \infty} \|e\_3\| = \lim\_{t \to \infty} \|z\_2 - \phi\_3(x)x\_1\| = 0\\ \lim\_{t \to \infty} \|e\_4\| = \lim\_{t \to \infty} \|w\_2 - \phi\_4(x)y\_1\| = 0 \end{cases} \tag{8}$$

where φi(x)(i = 1, 2, 3, 4) are scaling functions.

So the SGFPS error dynamical system is determined as follows

$$\begin{cases} \dot{e}\_1 = a\_2 x\_2 - y\_2 z\_2 + w\_2 - \dot{\phi}\_1(x) z\_1 - \phi\_1(x) (x\_1 y\_1 - d\_1 z\_1) + u\_1 \\\\ \dot{e}\_2 = x\_2 z\_2 - b\_2 y\_2 - \dot{\phi}\_2(x) w\_1 - \phi\_2(x) (-k\_1 y\_1 - r\_1 w\_1) + u\_2 \\\\ \dot{e}\_3 = x\_2 y\_2 - c\_2 z\_2 + x\_2 w\_2 - \dot{\phi}\_3(x) x\_1 - \phi\_3(x) a\_1 (y\_1 - x\_1) + u\_3 \\\\ \dot{e}\_4 = -y\_2 - \dot{\phi}\_4(x) y\_1 - \phi\_4(x) (b\_1 x\_1 - x\_1 z\_1 - c\_1 y\_1 + w\_1) + u\_4 \end{cases} (9)$$

Without loss of generality, the scaling functions can be chosen as φ1(x) = m11x1 +m12, φ2(x) = m21y1+m22, φ3(x) = m31z1+m32 and φ4(x) = m41w1+m42, where mij (i = 1, 2, 3, 4; j = 1, 2) are constant numbers. And substituting systems (6) and (7) into system (9), yields the following form:

$$\begin{cases} \dot{e}\_1 = a\_2 x\_2 - y\_2 z\_2 + w\_2 - m\_{11} a\_1 (y\_1 - x\_1) z\_1 - \phi\_1(x) (x\_1 y\_1 - d\_1 z\_1) + u\_1 \\\\ \dot{e}\_2 = x\_2 z\_2 - b\_2 y\_2 - m\_{21} (b\_1 x\_1 - x\_1 z\_1 - c\_1 y\_1 + w\_1) w\_1 - \phi\_2(x) (-k\_1 y\_1 - r\_1 w\_1) + u\_2 \\\\ \dot{e}\_3 = x\_2 y\_2 - c\_2 z\_2 + x\_2 w\_2 - m\_{31} (x\_1 y\_1 - d\_1 z\_1) x\_1 - \phi\_3(x) a\_1 (y\_1 - x\_1) + u\_3 \\\\ \dot{e}\_4 = -y\_2 - m\_{41} (-k\_1 y\_1 - r\_1 w\_1) y\_1 - \phi\_4(x) (b\_1 x\_1 - x\_1 z\_1 - c\_1 y\_1 + w\_1) + u\_4 \end{cases} \tag{10}$$

Our goal is to find the appropriate controllers ui(i = 1, 2, 3, 4) to stabilize the error variables of system (10) at the origin. For this purpose, we propose the following controllers for system (10)

$$\begin{cases} u\_1 = -\bar{a}\_2 x\_2 + y\_2 z\_2 - w\_2 + m\_{11} \bar{a}\_1 (y\_1 - x\_1) z\_1 + \phi\_1(x) (x\_1 y\_1 - \bar{d}\_1 z\_1) - l\_1 e\_1 \\\\ u\_2 = -x\_2 z\_2 + \bar{b}\_2 y\_2 + m\_{21} (\bar{b}\_1 x\_1 - x\_1 z\_1 - \bar{c}\_1 y\_1 + w\_1) w\_1 + \phi\_2(x) (-\bar{k}\_1 y\_1 - \bar{r}\_1 w\_1) - l\_2 e\_2 \\\\ u\_3 = -x\_2 y\_2 + \bar{c}\_2 z\_2 - x\_2 w\_2 + m\_{31} (x\_1 y\_1 - \bar{d}\_1 z\_1) x\_1 - \phi\_3(x) \bar{a}\_1 (y\_1 - x\_1) - l\_3 e \\\\ u\_4 = y\_2 + m\_{41} (-\bar{k}\_1 y\_1 - \bar{r}\_1 w\_1) y\_1 + \phi\_4(x) (\bar{b}\_1 x\_1 - x\_1 z\_1 - \bar{c}\_1 y\_1 + w\_1) - l\_4 e\_4 \end{cases} \tag{11}$$

where L = diag(l1, l2, l3, l4) is a positive gain matrix for each state controller. In practical applications the synchronization process can be sped up by increasing the gain matrix L.

The update laws for the unknown parameters a1, b1, c1, d1, k1, r1, a2, b2 and c2 are given as follows

$$\begin{cases} \dot{a}\_1 = -m\_{11}(y\_1 - x\_1)z\_1e\_1 - \phi\_3(x)(y\_1 - x\_1)e\_3 + (a\_1 - \bar{a}\_1) \\ \dot{b}\_1 = -m\_{21}x\_1w\_1e\_2 - \phi\_4(x)x\_1e\_4 + (b\_1 - \bar{b}\_1) \\ \dot{c}\_1 = \phi\_4(x)y\_1e\_4 + m\_{21}y\_1w\_1e\_2 + (c\_1 - \bar{c}\_1) \\ \dot{d}\_1 = \phi\_1(x)z\_1e\_1 + m\_{31}z\_1x\_1e\_3 + (d\_1 - \bar{d}\_1) \\ \dot{k}\_1 = \phi\_2(x)y\_1e\_2 + m\_{41}y\_1^2e\_4 + (k\_1 - \bar{k}\_1) \\ \dot{r}\_1 = \phi\_2(x)w\_1e\_2 + m\_{41}w\_1y\_1e\_4 + (r\_1 - \bar{r}\_1) \\ \dot{a}\_2 = x\_2e\_1 + (a\_2 - \bar{a}\_2) \\ \dot{\bar{b}}\_2 = -y\_2e\_2 + (b\_2 - \bar{b}\_2) \\ \dot{\bar{c}}\_2 = -z\_2e\_3 + (c\_2 - \bar{c}\_2) \end{cases} \tag{12}$$

where a¯1, ¯b1, c¯1, ¯ d1, ¯ k1, r¯1, a¯2, ¯b2 and c¯2 are the estimate values for these unknown parameters, respectively. Then, we have the following main result.

Theorem 1. For a given continuous differential scaling function matrix φ(x) = diag{φ1(x), φ2(x), φ3(x), φ4(x)}, and any initial values, the SGFPS between systems (6) and (7) can be achieved by the adaptive controllers (11) and the parameter update laws (12).

Proof. Choose the following Lyapunov function,

$$\begin{split} V &= \frac{1}{2} (e\_1^2 + e\_2^2 + e\_3^2 + e\_4^2 + (\bar{a}\_2 - a\_2)^2 + (\bar{b}\_2 - b\_2)^2 + (\bar{c}\_2 - c\_2)^2) \\ &+ \frac{1}{2} ((\bar{a}\_1 - a\_1)^2 + (\bar{b}\_1 - b\_1)^2 + (\bar{c}\_1 - c\_1)^2 + (\bar{d}\_1 - d\_1)^2 + (\bar{k}\_1 - k\_1)^2 + (\bar{r}\_1 - r\_1)^2) \end{split} \tag{13}$$

Taking the time derivative of V along the trajectory of the error dynamical system (10) yields

V˙ = ˙e1e1 + ˙e2e2 + ˙e3e3 + ˙e4e4 + (¯a2 − a2)a¯˙ 2 + (¯b2 − b2)¯˙ b2 + (¯c2 − c2)c¯˙2 + (¯a1 − a1)a¯˙ 1 + (¯b1 − b1)¯˙ b1 + (¯c1 − c1)c¯˙1 + ( ¯ d1 − d1) ¯˙ d1 + (¯ k1 − k1)¯˙ k1 + (¯r1 − r1)r¯˙1 =e1(a2x2 − y2z2 + w2 − m11a1(y1 − x1)z1 − φ1(x)(x1y1 − d1z1) + u1) + e2(x2z2 − b2y2 − m21(b1x1 − x1z1 − c1y1 + w1)w1 − φ2(x)(−k1y1 − r1w1) + u2) + e3(x2y2 − c2z2 + x2w2 − m31(x1y1 − d1z1)x1 − φ3(x)a1(y1 − x1) + u3) + e4(−y2 − m41(−k1y1 − r1w1)y1 − φ4(x)(b1x1 − x1z1 − c1y1 + w1) + u4) + (¯a2 − a2)a¯˙ 2 + (¯b2 − b2)¯˙ b2 + (¯c2 − c2)c¯˙2 + (¯a1 − a1)a¯˙ 1 + (¯b1 − b1)¯˙ b1 + (¯c1 − c1)c¯˙1 + ( ¯ d1 − d1) ¯˙ d1 + (¯ k1 − k1)¯˙ k1 + (¯r1 − r1)r¯˙1 (14)

Substituting Equation (11) into Equation (14) yields

$$\begin{aligned} \dot{V} &= -l\_1 e\_1^2 - l\_2 e\_2^2 - l\_3 e\_3^2 - l\_4 e\_4^2 \\ &- (\bar{a}\_1 - a\_1)^2 - (\bar{b}\_1 - b\_1)^2 - (\bar{c}\_1 - c\_1)^2 - (\bar{d}\_1 - d\_1)^2 - (\bar{k}\_1 - k\_1)^2 - (\bar{r}\_1 - r\_1)^2 \\ &- (\bar{a}\_2 - a\_2)^2 - (\bar{b}\_2 - b\_2)^2 - (\bar{c}\_2 - c\_2)^2 \\ &< 0 \end{aligned} \tag{15}$$

Since the Lyapunov function V is positive definite and its derivative V˙ is negative definite in the neighborhood of the zero solution for system (10). According to the Lyapunov stability theory, the error dynamical system (10) can converge to the origin asymptotically. Therefore, the SGFPS between the two hyperchaotic systems (6) and (7) is achieved with the adaptive controllers (11) and the parameter update laws (12).

This completes the proof.

#### 4. Numerical Simulation

In this section, to verify and demonstrate the effectiveness of the proposed method we consider a numerical example. In the numerical simulations, the fourth-order Runge-Kutta method is used to solve the systems with time step size 0.001. The true values of the "unknown" parameters of systems (6) and (7) are chosen as a1 = 12, b1 = 23, c1 = 1, d1 = 2.1, k1 = 6, r1 = 0.2, a2 = 8, b2 = 40, c2 = 14.9, so that the two systems exhibit hyperchaotic behavior, respectively. The initial values for the drive and response systems are x1(0) = 8.3, y1(0) = 10.8, z1(0) = 17.4, w1(0) = −11.1, x2(0) = −0.2, y2(0) = −0.1, z2(0) = 16.9 and w2(0) = −0.7, and the estimated parameters have initial conditions 0.1. Given that the function factors are φ1(x)=2x1 − 0.3, φ2(x)=2y1 + 0.5, φ3(x)=0.5z1 + 0.03, φ4(x) = −0.5w1 + 0.03, and the gain matrix L is given as diag{10, 10, 10, 10}. The simulation results are shown in Figures 3–5. Figure 3 demonstrates the SGFPS errors of the drive system (6) and response system (7). From this figure, it can be seen that the SGFPS errors converge to zero, *i.e.*, these two systems achieved SGFPS. And Figures 4 and 5 show that the unknown system parameters approach the true values.

Figure 3. The time evolution of SGFPS errors for the drive system (6) and response system (7) with controllers (11) and parameter update laws (12), where e1 = x2 −(2x1 − 0.3)z1, e2 = y2−(2y1+0.5)w1, e3 = z2−(0.5z1+0.03)x1, e4 = w2−(−0.5w1+0.03)y1.

Figure 4. The time evolution of the estimated unknown parameters of system (6).

Figure 5. The time evolution of the estimated unknown parameters of system (7).

#### 5. Conclusions

In this paper, we have investigated switched generalized function projective synchronization between two new different hyperchaotic systems with fully unknown parameters, which extended the switched modified function projective synchronization scheme. In this synchronization scheme, a state variable of the drive system synchronizes with a different state variable of the response system up to a generalized scaling function matrix. Due to the unpredictability of the switched states and scaling function matrix, this synchronization scheme can provide additional security in secure communication. By applying the adaptive control theory and Lyapunov stability theory, the appropriate adaptive controllers with parameter update laws are proposed to achieve SGFPS between two different hyperchaotic systems. A numerical simulation was conducted to illustrate the validity and feasibility of the proposed synchronization scheme.

#### Acknowledgments

This work was supported by the Youth Foundation of Yunnan University of Nationalities under grant No.11QN07, the Natural Science Foundation of Yunnan Province under grants No.2009CD019 and No.2011FZ172, the Natural Science Foundation of China under grant No.61263042.

#### Conflicts of Interest

The authors declare no conflict of interest.

#### References

Reprinted from *Entropy*. Cite as: Zhou, X.; Jiang, M.; Cai, X. Synchronization of a Novel Hyperchaotic Complex-Variable System Based on Finite-Time Stability Theory. *Entropy* 2013, *15*, 4334–4344.

*Article*


*Article* **Medical and Legal Aspects of Child Sexual Abuse: A Population-Based Study in a Hungarian County**

**Andrea Enyedy 1, Panagiotis Tsikouras 2,\* and Roland Csorba 3,4**

Received: 1 March 2018; Accepted: 5 April 2018; Published: 9 April 2018

**Abstract:** Background: Very few studies focus on childhood sexual abuse in middle European countries. Aim: The purpose of our study is to describe the medical and legal characteristics of children who experience sexual abuse and explore common features that may result in strategies for prevention. Methods: Between 2000 and 2015, 400 girls and 26 boys under the age of 18, suspected of being sexually abused, visited one of the four hospitals in a Hungarian county. Results: Mean age at onset was 10.81 years for boys, 13.46 years for girls. In 278 cases (65.3%), the perpetrator was known to the victim, and a stranger was suspected in 148 cases (34.7%). In 79 cases (30.7% of boys and 17.7% of girls), a family member was the accused perpetrator. In more than one-third (boys) and in one-fifth (girls) of cases, sexual abuse had occurred on multiple occasions.  In case of girls, sexual abuse included coitus in 219 (54.8%), oral genital, genital touching, genital to genital contact in 164 (41.0%), anal abuse in 14 (3.5%) cases, physical injury was incurred in 15 cases. Legal proceedings followed the CSA in 205 (48.1%) cases. Conclusion: The results highlight the urgent need to address the issue of sexual abuse in Hungary and minimize its impact. Prevention requires a systematic and lifelong approach to educating children about personal space safety and privacy to reduce vulnerability and is the responsibility of parents and professionals.


3.4.1. Model Descriptions

Artificial neural network is one of the most popular machine learning techniques for nonlinear approximations because of its ability to deal with a large number of functions with a high degree of accuracy (Chen et al. 2003). The idea of ANN came from the structure of the animal brain, more specifically, from the human neural system. It is based on the idea of how brain works, how the neurons in the brain receive information from the input neurons, analyse it, and finally identify the object or pattern. Fundamentally, the mechanism has three layers—input layer, hidden layers, and output layer. Each layer consists of neurons or nodes. The hidden part may consist of many layers, however, for the time series analysis and forecasting, the single hidden layer feed forward network is the most widely used model structure (Zhang et al. 1998). A simple three layer neural network has the following mathematical form

$$Y\_t = \mathcal{W}\_0 + \sum\_{j=1}^q \mathcal{W}\_j \cdot \mathcal{g} \left(\mathcal{W}\_{0,j} + \sum\_{i=1}^p \mathcal{W}\_{i,j} \cdot Y\_{t-i}\right) + \mathfrak{e}\_{t\_I} \tag{9}$$

where, *Wi*,*j* and *Wj* for *i* = 1, 2, ... , *p*, *j* = 1, 2, ... , *q* are known as connection weights. The parameter *p* and *q* are the number of input and output nodes respectively. The network involves an activation function which plays a very important role because it converts the input signals to be used for the neurons or nodes in the next layer, eventually the output neuron. The most widely used activation functions are the logistic and hyperbolic functions (Khashei and Bijari 2010), which are shown in Equations (10) and (11)

$$\text{sig}(\mathbf{x}) = \frac{1}{1 - \varepsilon^{-\mathbf{x}}} \tag{10}$$

$$\tan^{-1}(x) = \frac{1 - e^{-2x}}{1 + e^{-2x}}.\tag{11}$$

Most of the modelers prefer the hyperbolic tangent function as the activation functions because of its faster convergence, and it makes the optimization easier. Hence, we used this activation function in our model. There is no systematic rule of choosing the number of neurons or nodes, *q* in the hidden layer (Khashei and Bijari 2010). In most of the cases it is data-dependent and chosen on the basis of trial and error.

### 3.4.2. Artificial Neural Network for *S* & P 500 Index

The model proposed for S & P 500 in this section is a three layer model—input, hidden, and the output layer. The input layer consists of a total of seven nodes which are daily *Open, Close, High, Low, Average, Volume,* and *Return*. The variable *Average* is the average of daily *Open, Close, High,* and *Low*. The *Volume* was converted to million units. Daily return was calculated by this formula *rt* = log *St St*−1 , where *St* is the adjusted closed price and day one return, *r*0 was considered zero. The output layer has only one node that corresponds to the predicting variable *Adjusted Close* price. The number of the nodes in the hidden layer was chosen based on the error measures in Equation (1) for different combinations of the hidden nodes, which are displayed in Table 3. From this Table 3, we see that model ANN(7-15-1) has the lowest APE, AAE, ARPE, and RMSE and the highest adjusted *R*2 value.

**Table 3.** Error measures for different network structures.

The original dataset had 1257 observations, but the dataset used in this method was modified in this way—all the predictor and predicting variables have the same length of 1256, however, the predictor variables started from day 1 to the 1256th day and the predicting variable day 2 to the 1257th day. Then, the dataset was divided into two parts to run the model. The test dataset contained the last 63 actual stock prices (adjusted close) which were compared to the predicted prices. The best model was selected on the basis of the adjusted *R*2 and four error measures (Table 3). The model architecture is shown in Figure 5 and the result of this model is discussed in Section 4.3.

**Figure 5.** Artificial neural network architecture.


**1. Introduction**

158 Imaging of the Breast – Technical Aspects and Clinical Implication

Venkatakrishnan, V., Yavuz, M., et al. (1999) *Experimental and theoretical spectral optimization*

Walter, D.J., Wu, X., et al. (2004) *Dual kVp material decomposition using flat-panel detectors.* In,

Watanabe, M., Sato, E., et al. (2008) *Energy-discriminating K-edge x-ray computed tomography*

Zentai, G. (2011) *Signal-to-Noise and Contrast Ratio Enhancements by Quasi-Monochromatic Imaging.* IEEE Transactions on Instrumentation and Measurement Vol. 60, 908-915.

Medical Imaging 2004: Physics of Medical Imaging, SPIE, San Diego, CA, USA, Vol.

*system.* In, SPIE Penetrating Radiation Systems and Applications IX, SPIE, San

*for digital mammography.* SPIEVol. 3659, pp. 142-149.

Diego, California, Vol. 7080, pp. 70800B-1-5.

5368, pp. 29-39.

#### **1.1 Imaging technique, employing feeble alternating current**

Currently, a variety of electrical impedance diagnostic systems is used both in academic studies and in clinical practice. A significant part of such systems employs electrodes which reside in a single array and two-dimensional mathematical conductivity reconstruction algorithms in the array of the electrodes. Electrical impedance mammograph belongs to the class of 3D tomography systems. Thus, all the measurements are made on the surface of the object under investigation. The change of surface potential difference (compared with the homogeneous case), as a rule, is caused by the presence of a local heterogeneous area in the object. It is mainly concentrated in the area which is a projection of the local heterogeneous area on the surface of the object. Therefore, the main objective of electrical impedance mammography is to visualize the reconstructed three-dimensional electrical conductivity distribution of the object basing on the results of electrical measurements on its surface. For this purpose various modifications of mathematical method of "back projection" are employed. Mathematical methods provide also crosssectional slices of conductivity.

The usage of alternating current for this purpose is justified from several positions. Extreme complication of electrical conductivity measuring in biological systems at direct (i.e. unidirectional) current is conditioned by high degree of polarization of cellular membranes. Moreover, the flow of direct current through biological tissues is accompanied by irreversible chemical reactions at the electrodes, through which the object is connected with the external part of the circuit. Therefore, only alternating electric current of sufficiently high frequency is employed in medical diagnostics.

#### **1.2 Tissue-specific peculiarities of electrical conductivity**

In biological tissue, electric current affects the components and structures that have a net electric charge and / or an electric dipole moment. This influence is carried out in an environment characterized by the presence of numerous interface regions. An example of such interface regions are cell membranes. In the space, surrounding cell membranes from both sides, the changes are carried by electric charges, mainly in the form of ions and the sources of dipole moment in the form of polar water molecules and mobile polar

Standards for Electrical Impedance Mammography 161

Electrical conductivity index (IC), calculated during the electrical impedance examination, is a quantitative value, which characterizes the status of the breast. The results of 1,632 electrical impedance mammograph examinations, obtained from healthy women from different age groups, were analyzed. The women were selected for the examination according to the following criteria: absence of complaints on the mammary glands, a normal menstrual cycle, uncomplicated perimenopausal period, absence of chronic somatic and gynaecological diseases and absence of hormonal contraceptives taking or hormone replacement therapy. The women were distributed by age in years as follows: 20-30 (380 women), 31-40 (428), 41-50 (449) and 51-60 (375). All the examinations described in the chapter were carried out with the help of the electroimpedance computer mammograph "MEIK" v.5.6 (0.5 mА, 50 kHz), developed and manufactured by PKF "SIM-Technika",

Fluctuations of electrical conductivity index in 1,632 studies were as follows: lower limit – 0.01 conventional units, upper limit – 0.68 conventional units. In order to identify the structure of electrical impedance index distribution there were elaborated 8 ranges of criteria at a step of 0.09 and the quantity of studies was calculated in each range (Table 1).

Electrical conductivity index Number of studies 0.00 – 0.09 67 0.10 – 0.19 279 0.20 – 0.29 471 0.30 – 0.39 435 0.40 – 0.49 299 0.50 – 0.59 75 0.60 – 0.69 6 Total 1632

Fig. 1 shows the frequency histogram of electrical conductivity index data. Mean electrical

Taking into consideration a bell-shaped curve, close mean, median and mode values one can speak about standard (Gauss) distribution of the quantitative value, in this case, of electrical conductivity index. Typically, mean value and standard deviation are used to describe standard distribution. More detailed data can be obtained using 3th, 10th, 25th, 40th, 75th, 90th and 97th percentiles (Figure 2). In this case, the information on the shape of criterion

Table 1. Arrangement of electrical conductivity index frequencies.

distribution graph is not required.

conductivity index constituted 0.29, median value – 0.29 and mode - 0.26.

**5. Types of mammary gland structure from the perspective of electrical**

**impedance mammography**

interpretation.

Russia.

macromolecules. Moreover, the polarization ability of the cell membrane itself due to protein and lipid structures determines its exceptional electrical properties. Thus, the electrical properties of biological tissue as a colloid-disperse system in an alternating electric field are determined by the concentration and «the behaviour» of chemical compounds in it.


**6. Declarative debugging of missing answers in** *CFLP*(D)

The declarative debugging of *missing answers* also assumes an intended interpretation IP of the *CFLP*(D)-program P, starts with the observation of an *incompleteness symptom* and ends with an *incompleteness diagnosis*. A more precise definition of this *debugging scenario of missing answers* is as follows:


**3. Early recognition of perforation by simple bedside examination**

In a patient who has undergone small bowel endoscopy the diagnosis of small bowel perforation should be suspected if the patient has acute pain in the abdomen. The severity of pain will progressively increase. The patient will lie still as any movement will exacerbate the pain. Even the respiration will be shallow for this reason. This differentiates it from other acute pathologies like acute pancreatitis in which the patient is restless and changes posture to find relief. The physical examination will reveal a sick look, tachycardia, and features of dehydration along with the signs of peritonitis. Perforation causes third space loss of body fluid. This along with bacteremia and systemic inflammatory response leads to hypotension and decreased urine output. The abdomen will be very tender and guarding will be present. A board-like rigidity may be felt. Loss of liver dullness on percussion will further confirm the presence of free air in the peritoneal cavity. Bowel sounds will be absent due to paralytic ileus caused by peritonitis. After 4–6 hours of perforation (gastro-duodenal perforation), the peritoneal cavity acid becomes diluted and there is a decrease in pain and guarding. It may seem that the patient is improving but, in reality, is deteriorating [12].

Making the diagnosis of perforation may be difficult in the early period because of subtle signs and symptoms. The classical peritoneal signs may fail to elicit in a morbidly obese patient. Thus a high index of suspicion should be kept in mind for patients complaining of undue pain following endoscopy. Any patient with difficult endoscopy should have close post procedure monitoring for early detection of complications. Tachycardia, dehydration, or decreased urine output should alarm the clinician. Repeated abdominal examination can detect any new abdominal signs. Lessons can be learnt from trauma surgery. In a hemodynamically stable patient with an anterior abdominal stab wound with the peritoneal breach, serial abdominal examination is a standard technique for picking the peritonitis early.

### **4. Role of basic laboratory investigation like TLC and serum lactate in early diagnosis**

Laboratory workup will confirm the diagnosis of small bowel perforation apart from a careful history and physical examination. It is particularly helpful in elderly or seriously ill patients in whom signs and symptoms are less reliable. An elevated (>12,000/ cumm) or decreased white blood cells (< 4000/cumm) confirms inflammation or infection [13]. If TLC is normal, an increase in the number of neutrophils in differential counts or bandemia (> 10% band forms) is indicative of infection. The hemoglobin level will help in deciding the blood transfusion requirement. Serum electrolytes, blood urea nitrogen and, serum creatinine measurements will provide information about the fluid losses associated with third space loss, vomiting, delayed presentation, etc. Lactate level serves as a surrogate marker for tissue perfusion and correlates with anaerobic metabolism. A raised lactate level indicates bowel ischemia, shock, and sepsis. Lactate levels have been more specific than leukocyte count in diagnosing abdominal sepsis [14]. However, lactate levels can also be elevated in hepatic

**111**

**Figure 1.**

*Early Recognition and Management of Small Bowel Perforation*

failure, dehydration, and drug abuse. Metabolic acidosis will be present in sepsis. Coagulation profiles such as platelet count, prothrombin time, international normalized ratio, etc. are important in the preoperative assessment of patients with liver disease or those on anticoagulants. These may also be deranged due to sepsis. Other biochemical markers of inflammation include C-reactive protein and pro-calcitonin which when used in adjunct with complete blood count and other clinical signs help in making the diagnosis, assessing severity and prognosis, and guiding treatment.

**5. Role of X-ray abdomen and CT scan in confirming the diagnosis**

Plain radiography remains the most frequently ordered examination in patients with suspected perforation. Pneumoperitoneum is present in the rupture of any hollow viscous. It may also be observed following recent abdominal surgery, paracentesis, and pneumatosis intestinalis. Benign pneumoperitoneum may rarely develop following endoscopy due to transmural passage of insufflated air without bowel perforation [15]. Plain radiography can detect about 55–85% of patients with pneumoperitoneum [16]. It can detect as little as 1–2 ml of free air [17]. Upright lateral chest radiograph has better sensitivity than upright postero-anterior chest radiograph [18]. Upright positions including left lateral decubitus are uncomfortable in critically ill patients in the emergency setting. In such patients supine decubitus anteroposterior view of the thorax and anteroposterior or lateral view of

Free air can be visualized in different shapes, sizes, and locations in the abdominal cavity. On upright postero-anterior chest or abdominal radiography, free air is visualized as a translucent crescent below the diaphragm (**Figure 1**). These free-air signs can be categorized as bowel-related, right-upper-quadrant, peritoneal ligament- related, or other signs [20]. Rigler sign is the visualization of both sides of the bowel wall in a supine abdominal radiograph (**Figure 2**). The presence of normal gas

*X-ray abdomen showing A-Giant pneumoperitoneum appearing as an air-fluid level in the peritoneal cavity.*

*B-pneumoperitoneum on the left side may be confused with fundal gas.*

*DOI: http://dx.doi.org/10.5772/intechopen.96435*

the abdomen are generally requested [19].

*Early Recognition and Management of Small Bowel Perforation DOI: http://dx.doi.org/10.5772/intechopen.96435*

*Endoscopy in Small Bowel Diseases*

all indications (1.1 per 1000 procedures) [11].

with inflammatory bowel disease (IBD) as compared to non-IBD patients, with disease severity and steroid use being the two of the strong predictors for perforation [7–10]. In a systematic review, the total rate of perforation with enteroscopy in Crohn's disease was 4.27 per 1000 procedures (diagnostic and therapeutic procedures) and it was nearly 4 times that of diagnostic balloon assisted enteroscopy for

**3. Early recognition of perforation by simple bedside examination**

nal examination is a standard technique for picking the peritonitis early.

**4. Role of basic laboratory investigation like TLC and serum lactate**

Laboratory workup will confirm the diagnosis of small bowel perforation apart from a careful history and physical examination. It is particularly helpful in elderly or seriously ill patients in whom signs and symptoms are less reliable. An elevated (>12,000/ cumm) or decreased white blood cells (< 4000/cumm) confirms inflammation or infection [13]. If TLC is normal, an increase in the number of neutrophils in differential counts or bandemia (> 10% band forms) is indicative of infection. The hemoglobin level will help in deciding the blood transfusion requirement. Serum electrolytes, blood urea nitrogen and, serum creatinine measurements will provide information about the fluid losses associated with third space loss, vomiting, delayed presentation, etc. Lactate level serves as a surrogate marker for tissue perfusion and correlates with anaerobic metabolism. A raised lactate level indicates bowel ischemia, shock, and sepsis. Lactate levels have been more specific than leukocyte count in diagnosing abdominal sepsis [14]. However, lactate levels can also be elevated in hepatic

In a patient who has undergone small bowel endoscopy the diagnosis of small bowel perforation should be suspected if the patient has acute pain in the abdomen. The severity of pain will progressively increase. The patient will lie still as any movement will exacerbate the pain. Even the respiration will be shallow for this reason. This differentiates it from other acute pathologies like acute pancreatitis in which the patient is restless and changes posture to find relief. The physical examination will reveal a sick look, tachycardia, and features of dehydration along with the signs of peritonitis. Perforation causes third space loss of body fluid. This along with bacteremia and systemic inflammatory response leads to hypotension and decreased urine output. The abdomen will be very tender and guarding will be present. A board-like rigidity may be felt. Loss of liver dullness on percussion will further confirm the presence of free air in the peritoneal cavity. Bowel sounds will be absent due to paralytic ileus caused by peritonitis. After 4–6 hours of perforation (gastro-duodenal perforation), the peritoneal cavity acid becomes diluted and there is a decrease in pain and guarding. It may seem that the patient is improving but, in reality, is deteriorating [12]. Making the diagnosis of perforation may be difficult in the early period because of subtle signs and symptoms. The classical peritoneal signs may fail to elicit in a morbidly obese patient. Thus a high index of suspicion should be kept in mind for patients complaining of undue pain following endoscopy. Any patient with difficult endoscopy should have close post procedure monitoring for early detection of complications. Tachycardia, dehydration, or decreased urine output should alarm the clinician. Repeated abdominal examination can detect any new abdominal signs. Lessons can be learnt from trauma surgery. In a hemodynamically stable patient with an anterior abdominal stab wound with the peritoneal breach, serial abdomi-

**110**

**in early diagnosis**

failure, dehydration, and drug abuse. Metabolic acidosis will be present in sepsis. Coagulation profiles such as platelet count, prothrombin time, international normalized ratio, etc. are important in the preoperative assessment of patients with liver disease or those on anticoagulants. These may also be deranged due to sepsis. Other biochemical markers of inflammation include C-reactive protein and pro-calcitonin which when used in adjunct with complete blood count and other clinical signs help in making the diagnosis, assessing severity and prognosis, and guiding treatment.


**3. Biological significance of MRI variables in GBM**

gliomas. Radiolabeled 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG), methyl-[11C]-L-methio‐ nine ([11C]MET) and 3-deoxy-3-[18F]fluoro-L-thymidine ([18F]FLT) are taken up by prolifer‐ ating gliomas depending on their tumor grade as the consequence of an increased activity of membrane transporters for glucose ([18F]FDG), amino acids ([11C]MET), and nucleosides ([18F]FLT) as well as increased expression of cellular hexokinase ([18F]FDG) and thymidine kinase ([18F]FLT) genes, which specifically phosphorylate [18F]FDG and [18F]FLT, respec‐ tively [20]. Imaging of brain tumors with [18F]FDG was the first oncologic application of PET. [18F]FDG is actively transported across the blood-brain barrier (BBB) into the brain where it is phosphorylated and trapped into cells. Since 1982 [5,21], PET with [18F]FDG has been accepted and widely used in the grading of brain tumors; its uptake is generally high in highgrade tumors and it has a good prognostic value, because increased intra-tumoral glucose consumption correlates with tumor grade [22], biological aggressiveness and survival of patients in both primary and recurrent gliomas. Pathology and survival can be predicted by [18F]FDG-PET in gliomas [6]. In addition, a tumor-to-white matter ratio and tumor-to-gray matter ratio were found to increase the sensitivity of the grading evaluation [22]. Since intratumor heterogeneity of brain tumors is not adequately revealed in conventional MRI, because evaluation of the contrast enhancing lesion can either under-or overestimate the presence of active tumor, MRSI and PET are requested to gain additional information on metabolic and molecular tumor markers. In a tumor, the grading can be heterogenous with low-and highgrade areas, as it happens frequently in GBM. This may affect the choice of the site for stereotactic biopsy, which must direct towards tumor sites with the highest tumor grade. Therefore, suitable targets for biopsy will have positive contrast enhancement on T1-weighted MRI, a high choline-peak on MRSI and hypermetabolism on [18F]FDG-PET, the uptake of which is much higher in high-grade component of tumors. As a matter of fact, the [18F]FDG-PET improved the diagnostic yield of stereotactic biopsies by detecting metabolically active

70 Tumors of the Central Nervous System – Primary and Secondary

However, [18F]FDG-PET can have some diagnostic limitations, because of the high rate of physiologic glucose metabolism in normal brain tissue. In the brain cortex it is particularly high [24,25], so when a hypermetabolic lesion is close to the cortex or the subcortical white matter, the distinction of the tumor from the normal tissue may be difficult [22]. Moreover, it must be taken into account that [18F]FDG accumulation can be non-specific, because it is also observed in inflammatory or granulation tissues [26]. A later PET image acquisition [27] and a co-registration of PET images with MR images greatly improves the performance of [18F]FDG-PET [28]. Technologic advances have allowed to merge PET and MR images, combining the high resolution of MR imaging with the low-resolution functional capability of PET [23], defined as a reduction of intracellular oxygen pressure (pO2), because of decreased supply and of increased demand for oxygen. It predicts poor treatment response of malignant tumors. Two different forms of tumor hypoxia are recognized. Diffusion-limited chronic hypoxia may develop as a result of increased intercapillary distances, and acute hypoxia can result from occlusion of large tumor vessels [29]. Both forms of hypoxia have several implica‐ tions for the further evolution of tumors (induction of signaling cascades that promote angiogenesis, growth, and cell migration) [30]. Tumor hypoxia may also lead to necrosis, which is mandatory to establish the diagnosis of GBM. The **([18F]Fluoromisonidazole) ([18F]FMI‐**

areas of tumor [23].

Basically, three conditions can be detected with anatomy-based MRI: iso-hypo-intensity in TC1 (tumor, edema), hyper-intensity in TC2 (edema) and contrast enhancement (malignancy). The contrast enhancing regions (CERs) of untreated GBM correspond to the most histologically malignant areas of the tumor with architectural disruption, high cell density, proliferation, vessel density and angiogenesis with circumscribed necroses. Many other properties are revealed by physiology-based MRI. In CERs, in comparison with non-enhancing regions (NERs), physiologic MRI variables show higher values of rT1C, relative fast spin echo (rFSE), rCBV, relative peak height (rPH) and relative recovery factor (rRF), whereas rADC, relative fractional anisotropy (rFA) and fluid attenuated inversion recovery (rFLAIR) do not differ from NERs. All these observations have been shown and confirmed in recent studies of many cases of GBM planning pre-operatively tissue sampling sites and marking them on the anatomic images used by the surgical navigation work station. A comparison between MRI variables and histology of the samples corresponding to the MRI regions of interest (ROIs) in CERs and NERs has been made [32,33]. A correlation of histopathologic features and DWI and DSC variables prevailed in enhancing areas and rCBV and Cho/NAA index (CNI) above and rADC below a certain value could indicate the occurrence of tumor cells. Neoangiogenesis could be recognized and distinguished from simple endothelial hyperplasia, even though the permeability of the region is limited. Interestingly, also T2 rFSE and rFLAIR hyperintensity areas could show histopathologic features of malignancy. On the whole, it was demonstrated by gene microarray that the genetic expression patterns between CERs and NERs were different, with genes associated with mitosis, angiogenesis and apoptosis clustered in CER surgical samples [32].

occurrence or not of tumor cells. In particular, Epidermal Growth Factor Receptor (EGFR) amplification, the occurrence of EGFRvIII and Tumor Protein p53 (TP53) mutations were more frequent in CERs than in NERs, corresponding to a malignant histology. The genetic variability in the different samples was interpreted as due to polyclonality and not only to a genetic heterogeneity supported by the occurrence in the same tumor of different non-tumor cells of various species. Polyclonality means cell complexity, formed by tumor cells that differ among themselves for a series of phenotypic and molecular characteristics of cell proliferation, invasion, *etc.* [41,42]. This observation can be a warning against the use of small tumor samples to characterize the genotype of the entire tumor. Heterogeneity has been explained either by the hierarchic model mechanism [43] or by the stochastic mechanism [44] of tumor develop‐ ment. The two models, however, cannot be mutually exclusive, because their cells should derive from a common ancestor [45]. As for EGFR amplification, the possibility that its variation could depend on an asymmetrical distribution during mitoses must be mentioned [46,47], even if it is already included in the clone formation. The neurosphere assay produces neurospheres (NS), characterized by stemness antigens (Figure 9A,C,E), and adherent cells

Spatial Relationships of MR Imaging and Positron Emission Tomography with Phenotype, Genotype and...

http://dx.doi.org/10.5772/58391

73

However, their phenotype is not the same in the different tumor sites, differing for the quota of the two types of antigens. There must be a different capacity of the tumor areas to host or to generate GSCs and this is in line with the concept that a GSCs hierarchy exists for their potential [48-52]. GSCs have been interpreted as the top of a hierarchy of tumor cells for stemness and, therefore, for self-renewing, clonogenicity, *etc.* They occur in tumor niches and are under the control of microenviroments with their intrinsic and extrinsic signaling [53,54]. The niches can be perivascular or perinecrotic [53] and for a series of observations and considerations they must develop in the most malignant sites of the tumor [51,55]. Stemness and differentiation are the opposite poles of a spectrum in which a hierarchy exists of GSCs as for their potential [48-52]. Going from areas of the highest malignancy, such those of CERs, to differentiated ones, the stem-cell potential decreases [55]. In this way the distribution of GCS in GBM could be explained. The NS and AC degree of differentiation or stemness, demon‐ strated by the relevant antigens, represents an interesting subject of study that has been

Confocal microscopy is an advanced technique of optical imaging used to obtain high resolution images [56,57]. In tissue and cells derived from GBM, it is possible to distinguish the emission signal of different markers and to perform study of both co-localization and quantification of the luminous signal related to the protein marker expression. The cellular heterogeneity is a hallmark of GBM. Using differentiation and stemness markers it is possible to identify hypothetical immature or dedifferentiated elements in the whole tumor cell population, as well as in NS or AC by the neurosphere assay. Confocal images of glioma cells by double immunofluorescence allow to distinguish the expression pattern of the markers above mentioned. Their expression levels, related to the intensity of the emitted signal, show variable Nestin and glial fibrillary acidic protein (GFAP) positivity, depending on the tumor site. The method has a paramount importance in the study of the spectrum from stemness to

(AC), characterized by differentiation antigens (Figure 9B,D,F).

pursued by us by confocal microscopy (unpublished data).

differentiation.

The values of MRSI variables such as Cho/Cr and Cho/NAA showed a parallel variation as those of DWI and PWI. In spite of the possibility of a misregistration between biopsy sites and MRI uploaded to the neuronavigation device if a brain shift occurs, GBM histologic features could be usefully identified by physiology-based MRI [33].

Using the same technique, *i.e.* combining physiology-based MRI, MRSI and [18F]FDG-PET imaging with neuronavigation work station in a series of gliomas, mainly GBMs, we observed that the values of rCBV, ADC, Cho/Cr, CNI were useful for recognizing tumor areas and their phenotypic variations, as for both the number of cells and vascular pathologic structures (Figures 6,7). A possible source of error was the mismatch between the MRI registration and the sampling by the navigator, so that a dissociation between the variable values of the ROIs and histopathology occurred. For example, a ROI on central necrosis could erroneously correspond to a high rCBV value and histologically to the occurrence of tumor tissue in the sample. However, this was a rare event and it did not prevent from recognizing the biological significance of the imaging values contained in the ROIs, also by extrapolation among all the samples.

Malignant gliomas are hypermetabolic in comparison with normal brain. The glycolytic metabolism is increased as well as protein and membrane synthesis to maintain the rapidly dividing tumor cells. MRSI in spite of an intra-or inter-subject variability can identify the tumor. There are two patterns clearly distinct: one is that corresponding to the ROIs on necrotic regions and the other that on the enhancing ring. In the first one, two patterns have been in turn described: "necrosis" and "cystic necrosis" with variable Ch and high LL peak and with no peaks and variable LL, respectively. The ROIs on the ring show a high Cho and Cho/NAA ratio, whereas very variable are those on regions around the ring [34]. In our series Cho, Cho/ Cr and Cho/NAA values were constantly high in CERs in comparison with NERs.

Fusing MRI and [11C]MET-PET it was shown that the volume of the radio-compound uptake is greater than that of gadolinium enhancement on T1, even though smaller than T2 volume; it extends beyond in most cases [35,36] correlating with the proliferation markers [37,38], increased Cho/NAA and DTI abnormalities in the white matter [28,39]. However, there could be an underestimation of the tumor extension, because infiltrating cells do not proliferate [3,40].

The number of genetic alterations decreased from the most malignant areas of the tumor to the peripheral areas, correlating fairly well with the MRI variable values and indicating the occurrence or not of tumor cells. In particular, Epidermal Growth Factor Receptor (EGFR) amplification, the occurrence of EGFRvIII and Tumor Protein p53 (TP53) mutations were more frequent in CERs than in NERs, corresponding to a malignant histology. The genetic variability in the different samples was interpreted as due to polyclonality and not only to a genetic heterogeneity supported by the occurrence in the same tumor of different non-tumor cells of various species. Polyclonality means cell complexity, formed by tumor cells that differ among themselves for a series of phenotypic and molecular characteristics of cell proliferation, invasion, *etc.* [41,42]. This observation can be a warning against the use of small tumor samples to characterize the genotype of the entire tumor. Heterogeneity has been explained either by the hierarchic model mechanism [43] or by the stochastic mechanism [44] of tumor develop‐ ment. The two models, however, cannot be mutually exclusive, because their cells should derive from a common ancestor [45]. As for EGFR amplification, the possibility that its variation could depend on an asymmetrical distribution during mitoses must be mentioned [46,47], even if it is already included in the clone formation. The neurosphere assay produces neurospheres (NS), characterized by stemness antigens (Figure 9A,C,E), and adherent cells (AC), characterized by differentiation antigens (Figure 9B,D,F).

CERs and NERs has been made [32,33]. A correlation of histopathologic features and DWI and DSC variables prevailed in enhancing areas and rCBV and Cho/NAA index (CNI) above and rADC below a certain value could indicate the occurrence of tumor cells. Neoangiogenesis could be recognized and distinguished from simple endothelial hyperplasia, even though the permeability of the region is limited. Interestingly, also T2 rFSE and rFLAIR hyperintensity areas could show histopathologic features of malignancy. On the whole, it was demonstrated by gene microarray that the genetic expression patterns between CERs and NERs were different, with genes associated with mitosis, angiogenesis and apoptosis clustered in CER

The values of MRSI variables such as Cho/Cr and Cho/NAA showed a parallel variation as those of DWI and PWI. In spite of the possibility of a misregistration between biopsy sites and MRI uploaded to the neuronavigation device if a brain shift occurs, GBM histologic features

Using the same technique, *i.e.* combining physiology-based MRI, MRSI and [18F]FDG-PET imaging with neuronavigation work station in a series of gliomas, mainly GBMs, we observed that the values of rCBV, ADC, Cho/Cr, CNI were useful for recognizing tumor areas and their phenotypic variations, as for both the number of cells and vascular pathologic structures (Figures 6,7). A possible source of error was the mismatch between the MRI registration and the sampling by the navigator, so that a dissociation between the variable values of the ROIs and histopathology occurred. For example, a ROI on central necrosis could erroneously correspond to a high rCBV value and histologically to the occurrence of tumor tissue in the sample. However, this was a rare event and it did not prevent from recognizing the biological significance of the imaging values contained in the ROIs, also by extrapolation among all the

Malignant gliomas are hypermetabolic in comparison with normal brain. The glycolytic metabolism is increased as well as protein and membrane synthesis to maintain the rapidly dividing tumor cells. MRSI in spite of an intra-or inter-subject variability can identify the tumor. There are two patterns clearly distinct: one is that corresponding to the ROIs on necrotic regions and the other that on the enhancing ring. In the first one, two patterns have been in turn described: "necrosis" and "cystic necrosis" with variable Ch and high LL peak and with no peaks and variable LL, respectively. The ROIs on the ring show a high Cho and Cho/NAA ratio, whereas very variable are those on regions around the ring [34]. In our series Cho, Cho/

Fusing MRI and [11C]MET-PET it was shown that the volume of the radio-compound uptake is greater than that of gadolinium enhancement on T1, even though smaller than T2 volume; it extends beyond in most cases [35,36] correlating with the proliferation markers [37,38], increased Cho/NAA and DTI abnormalities in the white matter [28,39]. However, there could be an underestimation of the tumor extension, because infiltrating cells do not

The number of genetic alterations decreased from the most malignant areas of the tumor to the peripheral areas, correlating fairly well with the MRI variable values and indicating the

Cr and Cho/NAA values were constantly high in CERs in comparison with NERs.

could be usefully identified by physiology-based MRI [33].

72 Tumors of the Central Nervous System – Primary and Secondary

surgical samples [32].

samples.

proliferate [3,40].

However, their phenotype is not the same in the different tumor sites, differing for the quota of the two types of antigens. There must be a different capacity of the tumor areas to host or to generate GSCs and this is in line with the concept that a GSCs hierarchy exists for their potential [48-52]. GSCs have been interpreted as the top of a hierarchy of tumor cells for stemness and, therefore, for self-renewing, clonogenicity, *etc.* They occur in tumor niches and are under the control of microenviroments with their intrinsic and extrinsic signaling [53,54]. The niches can be perivascular or perinecrotic [53] and for a series of observations and considerations they must develop in the most malignant sites of the tumor [51,55]. Stemness and differentiation are the opposite poles of a spectrum in which a hierarchy exists of GSCs as for their potential [48-52]. Going from areas of the highest malignancy, such those of CERs, to differentiated ones, the stem-cell potential decreases [55]. In this way the distribution of GCS in GBM could be explained. The NS and AC degree of differentiation or stemness, demon‐ strated by the relevant antigens, represents an interesting subject of study that has been pursued by us by confocal microscopy (unpublished data).

Confocal microscopy is an advanced technique of optical imaging used to obtain high resolution images [56,57]. In tissue and cells derived from GBM, it is possible to distinguish the emission signal of different markers and to perform study of both co-localization and quantification of the luminous signal related to the protein marker expression. The cellular heterogeneity is a hallmark of GBM. Using differentiation and stemness markers it is possible to identify hypothetical immature or dedifferentiated elements in the whole tumor cell population, as well as in NS or AC by the neurosphere assay. Confocal images of glioma cells by double immunofluorescence allow to distinguish the expression pattern of the markers above mentioned. Their expression levels, related to the intensity of the emitted signal, show variable Nestin and glial fibrillary acidic protein (GFAP) positivity, depending on the tumor site. The method has a paramount importance in the study of the spectrum from stemness to differentiation.

tumors relapses within 2-cm margin around the enhanced region [58]; another adverse characteristic of infiltrating cells is that they do not proliferate [3,40], escaping thus detection

Spatial Relationships of MR Imaging and Positron Emission Tomography with Phenotype, Genotype and...

http://dx.doi.org/10.5772/58391

75

Tumor invasion is not uniform along its borders. It can be non-existent where the tumor sharply abuts against the normal nervous tissue (Figure 10A), as it may happen with the white matter, or it gradually progresses from the tumor outwards (Figure 10B).  The different invasion modalities have been codified [59] and a distinction between diffuse and local tumors has even been proposed [60], but it

**Figure 10.** A – Sharp tumor border. Ki-67/MIB.1, DAB, 100x; B – Invasion gradient toward the cortex. H&E, 100x; C –

Letting aside the mechanisms of tumor cell migration and invasion of which there is today a good knowledge [61-63], some information about neuropathologic findings on peritumor tissue are relevant. First of all, it has been demonstrated that patients with absence of tumor cells in the adjacent normal nervous tissue had better survival than those with tumor cells [64]. This is not in contrast with the observation that the removal of edematous peritumor tissue

Perineuronal satellitosis. H&E, 400x; D – Infiltration along corpus callosum. H&E, 200x.

was not confirmed by the observation of substantially different outcomes.

and being less sensitive to treatments.

**Figure 9.** Immunofluorescence (IF) for stemness antigens in NS. A – Nestin, 200x; C – CD133, 200x; E – Musashi1, 200x. IF for differentiation antigens in AC. B – GFAP, 400x; D – GalC, 400x; F – β-III Tubulin, 400x. Nuclei are counterstained with DAPI.


**Fractional-Order Integral and Derivative Operators and Their Applications**

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Prosthetic grafts should be reserved for situations where autogenous vein is not available to perform an access. The most commonly used prosthetic graft is e-PTFE based. Newer advances in medication bonding to decrease thrombosis and formation of intimal hyperplasia may be promising. In addition, various graft characteristics such as flared-end and stretch may provide better patency. Biologic grafts are being tested; however, at this point data are lacking to show superiority over prosthetic grafts. This area is a fertile ground for randomized clinical trials in the search for a man made or biologic graft that would equal

Chronic kidney disease (CKD), hemodialysis (HD), peritoneal dialysis (PD), arteriovenous fistula (AVF), polytetrafluoroethylene (PTFE), expanded PTFE (ePTFE), transposed

Primary Patency: Interval of time from access placement to any intervention necessary tomaintain patency of access. Assisted Primary Patency: Interval of time from access placement to time of intervention necessary to maintain the functionality of the access. Secondary Patency: Interval of time from access placement to access abandonment including

**Graft Graft Material Manufacturer**

Brunswick, NJ

Hudson, NH

Natick, MA

Hudson, NH

Hill, NJ

GA

Artegraft® Bovine Carotid Artery Heterograft Artegraft Inc., New

Atrium Adventa™ VXT Reinforced ePTFE Atrium Medical Corp.,

Boston Scientific ePTFE Boston Scientific Corp.,

Carboflo® Carbon impregnated ePTFE C.R. Bard Inc., Murry

CryoVein® Cryopreserved femoral vein CryoLife Inc., Atlanta,

Flixene™ Trilaminate membrane Atrium Medical Corp.,

lower levels of turbulence, leading to lower risk of stenosis.46

autogenous vein in patency and complication rates.

brachialbasilic vein (TBB), percutaneous angioplasty (PTA)

intervening surgical or endovascular manipulations

**5. Conclusions**

**6. Abbreviations**

**7. Definitions**

**8. Manufacturer and graft**

The views expressed in this article are those of the authors and do not necessarily reflect the official policy of the Department of Army, the Department of Defense, or the US government.

#### **10. References**

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[18] Kaufman JL, Garb JL, Berman JA, Rhee SW, Norris MA, Friedmann P. A prospective

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### *Edited by Maria Goretti Moreira Guimarães Penido*

The book provides practical and accessible information on all aspects of hemodialysis, with emphasis on day-to-day management of patients. It is quite comprehensive as it covers almost all the aspects of hemodialysis. In short it is a valuable book and an essential aid in the dialysis room.

Hemodialysis - Different Aspects

Hemodialysis

Different Aspects

*Edited by Maria Goretti Moreira Guimarães Penido*

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