Implementation of combinational deep learning algorithm for non-alcoholic fatty liver classification in ultrasound images

Background: Nowadays, fatty liver is one of the commonly occurred diseases for the liver which can be observed generally in obese patients. Final results from a vari-ety of exams and imaging methods can help to identify and evaluate people affected by this condition. Objective: The aim of this study is to present a combined algorithm based on neural networks for the classification of ultrasound �images from fatty liver affected patients. Material and Methods: In experimental research can be categorized as a diagnostic study which focuses on classification of the acquired ultrasonography images for 55 patients with fatty liver. We implemented pre-trained convolutional neural networks of Inception-ResNetv2, GoogleNet, AlexNet, and ResNet101 to extract features from the images and after combining these resulted features, we provided support vector machine (SVM) algorithm to classify the liver images. Then the results are compared with the ones in implementing the algorithms independently. Results: The area under the receiver operating characteristic curve (AUC) for the introduced combined network resulted in 0.9999, which is a better result compared to any of the other introduced algorithms. The resulted accuracy for the proposed network also caused 0.9864, which seems acceptable accuracy for clinical application. Conclusion: The proposed network can be used with high accuracy to classify ultrasound images of the liver to normal or fatty. The presented approach besides the high AUC in comparison with other methods have the independence of the method from the �user or expert interference. © 2021, Shriaz University of Medical Sciences. All rights reserved

Biomedical image denoising based on hybrid optimization algorithm and sequential filters

Background: Nowadays, image de-noising plays a very important role in medical analysis applications and pre-processing step. Many filters were designed for image processing, assuming a specific noise distribution, so the images which are acquired by different medical imaging modalities must be out of the noise. Objectives: This study has focused on the sequence filters which are selected by a hybrid genetic algorithm and particle swarm optimization. Material and Methods: In this analytical study, we have applied the composite of different types of noise such as salt and pepper noise, speckle noise and Gaussian noise to images to make them noisy. The Median, Max and Min filters, Gaussian filter, Average filter, Unsharp filter, Wiener filter, Log filter and Sigma filter, are the nine filters that were used in this study for the denoising of medical images as digital imaging and communications in medicine (DICOM) format. Results: The model has been implemented on medical noisy images and the performances have been determined by the statistical analyses such as peak signal to noise ratio (PSNR), Root Mean Square error (RMSE) and Structural similarity (SSIM) index. The PSNR values were obtained between 59 to 63 and 63 to 65 for MRI and CT images. Also, the RMSE values were obtained between 36 to 47 and 12 to 20 for MRI and CT images. Conclusion: The proposed denoising algorithm showed the significantly increment of visual quality of the images and the statistical assessment. © 2020, Shiraz University of Medical Sciences. All rights reserved

Physical and dosimetric aspect of euromechanics add-on multileaf collimator on varian clinac 2100 C/D

Background: Before treatment planning and dose delivery, quality assurance of multi-leaf collimator (MLC) has an important role in intensity-modulated radiation therapy (IMRT) due to the creation of multiple segments from optimization process. Objective: The purpose of this study is to assess the quality control of MLC leaves using EBT3 Gafchromic films. Material and Methods: Leaf Position accuracy and leaf gap reproducibility were checked with Garden fence test. The garden fence test consists of 5 thin bands A) 0.2 Cm width spaced at 2 Cm intervals and B) 1 Cm width spaced at 1 Cm intervals. Each leaf accuracy was analyzed with measuring the full-width half-maximum (FWHM). Maximum and average leaf transmission were measured with gafchromic EBT3 films from Ashland for both 6 MV and 18 MV beams. Results: Leaf positions were found to be in a range between 1.78 � 2.53 mm, instead of nominal 2 mm for the test A and between 9.09 � 10.36 mm, instead of nominal 10 mm for the test B. The Average radiation transmission of the MLC was noted 1.79 and 1.98 of the open 10x10 Cm 2 field at isocenter for 6 MV and 18 MV beams, respectively. Maximum radiation transmission was noted 4.1 and 4.4 for 6 MV and 18 MV beams, respectively. Conclusion: In this study, application of gafchromic EBT3 films for the quality assurance of Euromechanics multileaf collimator was studied. Our results showed that the average leaf leakage and positional accuracy of this type of MLC were in the acceptance level based on the Protocols. © 2019, Shiraz University of Medical Sciences. All rights reserved

Automatic Prostate Cancer Segmentation Using Kinetic Analysis in Dynamic Contrast-Enhanced MRI

Background: Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) provides functional information on the microcirculation in tissues by analyzing the enhancement kinetics which can be used as biomarkers for prostate lesions detection and characterization. Objective: The purpose of this study is to investigate spatiotemporal patterns of tumors by extracting semi-quantitative as well as wavelet-based features, both extracted from pixel-based time-signal intensity curves to segment prostate lesions on prostate DCE-MRI. Methods: Quantitative dynamic contrast-enhanced MRI data were acquired on 22 patients. Optimal features selected by forward selection are used for the segmentation of prostate lesions by applying fuzzy c-means (FCM) clustering. The images were reviewed by an expert radiologist and manual segmentation performed as the ground truth. Results: Empirical results indicate that fuzzy c-mean classifier can achieve better results in terms of sensitivity, specificity when semi-quantitative features were considered versus wavelet kinetic features for lesion segmentation (Sensitivity of 87.58% and 75.62%, respectively) and (Specificity of 89.85% and 68.89 %, respectively). Conclusion: The proposed segmentation algorithm in this work can potentially be implemented for automatic prostate lesion detection in a computer aided diagnosis scheme and combined with morphologic features to increase diagnostic credibilit

Effects of resveratrol and methoxyamine on the radiosensitivity of iododeoxyuridine in U87MG glioblastoma cell line

The purpose of this study was to evaluate the combination effect of resveratrol and methoxyamine on radiosensitivity of iododeoxyuridine in spheroid culture of U87MG glioblastoma cell line using colony formation and alkaline comet assays. Spheroids on day-20 with 350 µm diameters were treated with 20 µM resveratrol and/or 6 mM methoxyamine and/or 1 µM iododeoxyuridine for one volume doubling time (67 h), and then irradiated with 2 Gy gamma-radiation (60Co) in different groups. After treatment, viability of the cells, colony forming ability and DNA damages were obtained by blue dye exclusion, colony formation and alkaline comet assay, respectively. Our results showed that methoxyamine and resveratrol could significantly reduce colony number and induce the DNA damages of glioblastoma spheroid cells treated with iododeoxyuridine in combination with gamma-rays. Therefore, methoxyamine as base excision repair inhibitor and resveratrol as hypoxia inducible factor 1-alpha inhibitor in combination with iododeoxyuridine as radiosensitizer enhanced the radiosensitization of glioblastoma spheroid cells. © 2016, © 2016 by the Society for Experimental Biology and Medicine

A basic dosimetric study of PRESAGE: The effect of different amounts of fabricating components on the sensitivity and stability of the dosimeter

Over the past few years there has been much interest in the development of three-dimensional dosimeters to determine the complex absorbed dose distribution in modern radiotherapy techniques such as IMRT and IGRT. In routine methods used for three-dimensional dosimetry, polymer gels are commonly used. Recently, a novel transparent polymer dosimeter, known as PRESAGE, has been introduced in which a radiochromic color change is observed upon radiation. PRESAGE has some advantages over usual polymer gel dosimeters. It has been noted that the sensitivity of PRESAGE can be changed when different amounts of the components are used for its fabrication. This study has focused on the assessment of dosimetric characteristics of PRESAGE for various amounts of components in its formulation. To achieve this, PRESAGE dosimeters were fabricated using various amounts of their constituting components. Then the dosimeters were irradiated to 60Co gamma photons for a range of radiation doses from 0 to 50 Gy. Consequently, the light absorption changes of the dosimeters were measured by a spectrophotometer at different post-irradiation time periods. It was generally observed that as the concentration of the radical initiator is increased, the PRESAGE dosimeter sensitivity is increased while its stability is decreased. Furthermore, it was noted that with the high concentration of the radical initiator and leuco dye, the sensitivity of PRESAGE is decreased. © 2010 Institute of Physics and Engineering in Medicine

Estimation and evaluation of pseudo-CT images using linear regression models and texture feature extraction from MRI images in the brain region to design external radiotherapy planning

Aim: The aim of this study is to construct and evaluate Pseudo-CT images (P-CTs) for electron density calculation to facilitate external radiotherapy treatment planning. Background: Despite numerous benefits, computed tomography (CT) scan does not provide accurate information on soft tissue contrast, which often makes it difficult to precisely differentiate target tissues from the organs at risk and determine the tumor volume. Therefore, MRI imaging can reduce the variability of results when registering with a CT scan. Materials and methods: In this research, a fuzzy clustering algorithm was used to segment images into different tissues, also linear regression methods were used to design the regression model based on the feature extraction method and the brightness intensity values. The results of the proposed algorithm for dose-volume histogram (DVH), Isodose curves, and gamma analysis were investigated using the RayPlan treatment planning system, and VeriSoft software. Furthermore, various statistical indices such as Mean Absolute Error (MAE), Mean Error (ME), and Structural Similarity Index (SSIM) were calculated. Results: The MAE of a range of 45�55 was found from the proposed methods. The relative difference error between the PTV region of the CT and the Pseudo-CT was 0.5, and the best gamma rate was 95.4 based on the polar coordinate feature and proposed polynomial regression model. Conclusion: The proposed method could support the generation of P-CT data for different parts of the brain region from a collection of MRI series with an acceptable average error rate by different evaluation criteria. © 2020 Greater Poland Cancer Centr

Conjugation of glucosamine with Gd3+-based nanoporous silica using a heterobifunctional ANB-NOS crosslinker for imaging of cancer cells

Bita Mehravi,1 Mohsen Ahmadi,1 Massoud Amanlou,2 Ahmad Mostaar,1 Mehdi Shafiee Ardestani,3 Negar Ghalandarlaki4 1Biomedical Engineering and Medical Physics Department, Faculty of Medicine, Shahid Beheshti University of Medical Sciences,Tehran, Iran; 2Department of Medicinal Chemistry, Faculty of Pharmacy and Drug Design and Development Research Center, Tehran University of Medical Sciences, Tehran, Iran, 3Department of RadioPharmacy, Faculty of Pharmacy, Tehran University of Medical Sciences, 4Department of Biological Science, School of Science, Science and Research Branch, Islamic Azad University, Tehran, Iran Background: The aim of this study was to synthesize Gd3+-based silica nanoparticles that conjugate easily with glucosamine and to investigate their use as a nanoprobe for detection of human fibrosarcoma cells. Methods: Based on the structure of the 2-fluoro-2-deoxy-D-glucose molecule (18FDG), a new compound consisting of D-glucose (1.1 nm) was conjugated with a Gd3+-based mesoporous silica nanoparticle using an N-5-azido-2-nitrobenzoyloxy succinimide (ANB-NOS) crosslinker. The contrast agent obtained was characterized using a variety of methods, including Fourier transform infrared spectroscopy, nitrogen physisorption, thermogravimetric analysis, scanning and transmission electron microscopy, and inductively coupled plasma atomic emission spectrometry (ICP-AES). In vitro studies included cell toxicity, apoptosis, tumor necrosis factor-alpha, and hexokinase assays, and in vivo tests consisted of evaluation of blood glucose levels using the contrast compound and tumor imaging. The cellular uptake study was validated using ICP-AES. Magnetic resonance relaxivity of the contrast agent was determined using a 1.5 Tesla scanner. Results: ANB-NOS was found to be the preferred linker for attaching glucosamine onto the surface of the mesoporous silica nanospheres. The r1 relaxivity for the nanoparticles was 17.70 mM-1s-1 per Gd3+ ion, which is 4.4 times larger than that for Magnevist® (r1 approximately 4 mM-1s-1 per Gd3+ ion). The compound showed suitable cellular uptake (75.6% ± 2.01%) without any appreciable cytotoxicity. Conclusion: Our results suggest that covalently attaching glucosamine molecules to mesoporous silica nanoparticles enables effective targeted delivery of a contrast agent. Keywords: gadolinium, glucosamine, mesoporous silica nanospheres, magnetic resonance imaging, N-5-azido-2-nitrobenzoyloxy succinimide, photoactivatio

Commissioning and quality assurance of Euromechanics add-on multileaf collimator

In this study, the beam characteristics of a Euromechanics add-on MLC that has been installed on a Varian CLINAC 2100 C/D linear accelerator are presented. This was the first installation of 60-leaf PMLC from Euromechanics Company worldwide and all mechanical and dosimetric parameters were measured before clinical use of this kind of MLC. Mechanical tests were executed for different gantry and collimator angles. Leaf position accuracy and leaf gap reproducibility were checked with four different tests. The leaf transmissions, collimator (Sc), phantom (Sp), total (Sc,p) scatter factors, output of the machine, beam profiles for off-axis ratios, central axis depth dose, flatness, symmetry and penumbra have been measured for different field sizes pre and post MLC installation in 6 and 18 MV-mode. To evaluate the effect of new data on clinical plans, different beam setup configurations conformed with MLC and custom blocks were planned on CT images of thorax a CIRS phantom model 002LFC in the same treatment planning system. Leaf position in picket fence test found to be in range between 4.89-5.02 cm instead of nominal 5 cm, however the results of this test with EPIDs image and PIPSpro software showed the higher deviation rather than the results reported from the tests with EBT3 films. The measured data showed that on average Sc,p and Sc were increased 0.22 (P = 0.86) and 0.34 (P = 0.86) for 6 MV and 0.37 (P = 0.84) and 0.42 (P = 0.88) for 18 MV beams for different field sizes, respectively. Good agreement was observed between the PDD and profile curves pre and post MLC installation that was expected based on no changes in beam energy and geometry of the collimators. Based on the mechanical and dosimetry results which have been achieved from our different standard tests, it was found no significant differences between pre and post MLC installation values. This indicates, installation and using this system is clinically acceptable. © 2020 IOP Publishing Ltd