Volume 26 (2020): Issue 3 (September 2020)

Purpose: The purpose of the study was to investigate the dependence of tissue inhomogeneity correction factors (ICFs) on the photon beam quality index (QI).

Materials and Methods: Heterogeneous phantoms, comprising semi-infinite slabs of the lung (0.10, 0.20, 0.26 and 0.30 g/cm³), adipose tissue (0.92 g/cm³) and bone (1.85 g/cm³) in water, were constructed in the Eclipse treatment planning system. Several calculation models of 6 MV and 15 MV photon beams for quality index (TPR20,10) = 0.670±k*0.01 and TPR20,10 = 0.760±k*0.01, k = -3, -2, -1, 0, 1, 2, 3 respectively were built in the Eclipse. The ICFs were calculated with the anisotropic analytical algorithm (AAA) for several beam sizes and points lying at several depths inside of and below inhomogeneities of different thicknesses.

Results: The ICFs increased for lung and adipose tissues with increasing beam quality (TPR20,10), while decreased for bone. Calculations with AAA predict that the maximum difference in ICFs of 1.0% and 2.5% for adipose and bone tissues, respectively. For lung tissue, changes of ICFs of a maximum of 9.2% (6 MV) and 13.8% (15 MV). For points where charged particle equilibrium exists, a linear dependence of ICFs on TPR20,10 was observed. If CPE doesn’t exist, the dependence became more complex. For points inside of the low-density inhomogeneity, the dependence of the ICFs on energy was not linear but the changes of ICFs were smaller than 3.0%. Measurements results carried out with the CIRS phantom were consistent with the calculation results.

Conclusions: A negligible dependence of the ICFs on energy was found for adipose and bone tissue. For lung tissue, in the CPE region, the dependence of ICFs on different beam quality indexes with the same nominal energy may not be neglected, however, this dependence was linear. Where there is no CPE, the dependence of the ICFs on energy was more complicated.

Introduction: Achieving high positional and dosimetric accuracy in small fields is very challenging due to the imbalance of charged particle equilibrium (CPE), occlusion of the primary radiation source, and overlapping penumbra regions. These factors make the choice of the detector for Stereotactic Radiosurgery (SRS) patient-specific quality assurance (PSQA) difficult. The aim of the study is to compare the suitability of EBT3 Gafchromic film against CC01 pinpoint chamber for the purpose of SRS and stereotactic Radiotherapy (SRT) dose verification.

Material and Method: EBT3 Gafchromic film was calibrated against Treatment Planning System (TPS) doses (1 Gy – 35 Gy). CC01 pinpoint chamber and EBT3 film was used to verify Patient-Specific point doses of 21 intracranial lesions each planned with Static, Dynamic Conformal Arc (DCA), and Volumetric Arc Therapy (VMAT) using Varian TrueBeam Accelerator 6MV Flattening Filter (FF) and 6MV Flattening Filter Free (FFF) beams. The lesion sizes varied from 0.4 cc to 2.9 cc. The lesions were categorized into <1cc, 1cc-2cc and 2cc-3cc.

Results: High variations in measured doses from TPS calculated dose were observed with small lesion volumes irrespective of the dosimeter. As the sizes decreased high uncertainty was observed in ion chamber results. CC01 was observed under-responding to film in small lesion sizes (<1cc), where nearly 50% of results under-responded in comparison with Film results. Film results were more or less consistent for static and DCA plans. Static and DCA plans were consistent passing more than 73% of the plans of the smallest lesion size category. VMAT showed very poor PSQA agreement for all three volumes (32.1% for <1cc, 14.3% for 2cc-3cc and 39.3% for 2cc-3cc). No significant difference was observed between 6MVFF and 6MVFFF beams from the chi-squared test.

Conclusion: EBT3 Film was observed to be a more suitable detector for small lesion sizes less than 1cc, compared to CC01. As the volume increases, the response of CC01 and EBT3 film have no significant difference in performing PSQA for intracranial SRS/SRT. VMAT techniques for intra cranial SRS shows deviation from TPS planned dose for both EBT3 film and CC01 and should not be preferred choice of verification tools.

Uranium concentrations of human blood and soil samples have been studied at different ages and occupations in Babylon, Iraq. The technique of nuclear track detectors CR 39 with nuclear fission track analysis has been used to determine the uranium concentrations in this study. Results have shown that the concentrations of uranium ranged from 0.56 ± 0.06 to 1.24 ± 0.29 ppb with an average of 0.83 ± 0.18 ppb in blood samples. On the other hand, the concentrations of uranium in soil samples ranged from 0.93 ± 0.20 to 2.59 ± 0.15 ppm with an average of 1.72 ± 0.19 ppm. Moreover, the highest averages of concentration have been found in the city center of Babylon, reaching 1.09 ± 0.22 ppb and 2.10 ± 0.23 ppm in blood and soil samples, respectively. The results have further proved that gender and occupations have an effect in increasing the concentrations of uranium. In addition, the concentrations in blood samples are generally lower than the concentration in soil samples.

The aim of this work was twofold: first, to propose signal processing methods for assessing the temporal and spectral changes of parameters (mean absolute value, the energy and standard deviation as temporal parameters, total and mean power as frequency parameters) of the surface myoelectric signal of the various patient groups like normal, myopathic and neuropathic during muscles contraction of biceps. Secondly, to analyze this electrical manifestation of neuromuscular disorders by the implementation of time-frequency analysis using continuous wavelet that allows us to qualify this method to evaluate, appreciate the pathology and determine its degree of severity which was unable by extracting mentioned parameters. Our results showed that this approach presents satisfactory performances especially to follow patients with the least severe pathology.

Electromyogram signal (EMG) provides an important source of information for the diagnosis of neuromuscular disorders. In this study, we proposed two methods of analysis which concern the bispectrum and continuous wavelet transform (CWT) of the EMG signal then a comparison is made to select which one is the most suitable to identify an abnormality in biceps brachii muscle in the main purpose is to assess the pathological severity in bifrequency and time-frequency analysis applying respectively bispectrum and CWT. Then four time and frequency features are extracted and three popular machine learning algorithms are implemented to differentiate neuropathy and healthy conditions of the selected muscle. The performance of these time and frequency features are compared using support vector machine (SVM), linear discriminate analysis (LDA) and K-Nearest Neighbor (KNN) classifier performance. The results obtained showed that the SVM classifier yielded the best performance with an accuracy of 95.8%, precision of 92.59% and specificity of 92%. followed by respectively KNN and LDA classifier that achieved respectively an accuracy of 92% and 91.5%, precision of 92% and 85.4%, and specificity of 92% and 83%.

Alcoholism is one of the most widely occurring addiction in the world. In this paper, we proposed the method of addiction detection based on polysomnography. We have got the sleep records which were described by numerical parameters calculated from standard processed records of polysomnography signals. The database used in the experiments consisted of 172 examinations: 50% of healthy and alcohol-addicted patients, and 50% males and females, with normal-like age distribution. For the diagnosis, we have used the decision system built on an artificial neural network.

In our investigations, we have optimised the input set of parameters and the network structure. To verify the correctness of the diagnosis we have used the “leave one out” validation method.

Finally, we have obtained over 97% correctness of alcohol addiction diagnoses for different, optimised sets of data for men and women. we got the 8 parameters described men and 11 for women where only 5 has been common. What must be underlined such a positive result was obtained by dividing the data base. For the whole base, we have got only about 89% correct diagnoses.