Frontiers in Biomedical Technologies
Volume:10 Issue: 2, Spring 2023

Fatty liver is the most common chronic liver disease, and finding the appropriate method for detecting the problem is necessary. The current study aimed to quantity liver steatosis using Computed Tomography (CT), ultrasound images, and Alanine Aminotransferase (ALT) blood test.

In this work, 163 Non-Alcoholic Fatty Liver Disease (NAFLD) patients implemented CT and ultrasound images on their abdomen regions. The liver and spleen density were calculated using CT images (as the standard method), and then the patients were divided into mild, and moderate to severe groups. During the sonography, an M-value histogram of the liver and the right kidney was drawn and their ratio (liver/kidney) was considered as a Hepatorenal Index (HRI). Mann-Whitney test was used to evaluate the relationships between HRI and ALT values.

The mean and standard deviation of the liver density in CT scans were obtained as 51 ± 4 HU. The HRI had better performance (Area Under the Curve, AUC: 0.94) than the ALT (AUC: 0.88) in determining liver steatosis. In addition, there was a significant difference between the mild, and moderate to severe groups (P < 0.001) in HRI and ALT values.

Based on the results, HRI is an excellent factor to distinguish between mild, and moderate to severe fatty liver. Notably, HRI is reproducible and operator-independent.

The process of Magnetic Resonance Imaging (MRI) image registration is one of the important branches in MRI image analysis, which is a necessary pre -processing to use the information in these images. The purpose of this paper is to present a new approach for MRI image registration that can maintain the total number of initial matches and have the highest precision.

The Clustered Redundant Keypoint Elimination Method-Scale Invariant Feature Transform (CRKEM-SIFT) algorithm has recently been introduced to eliminate redundancies and upgrade the correspondence precision. The disadvantages of this algorithm include the high execution time and the number of incorrect correspondences. In this paper, to increase the accuracy and speed of MRI image registration, the CRKEM method is first used over the Speeded Up Robust Features (SURF) algorithm. Then, Spatial Relations Correspondence (SRC) and Alpha-Trimmed Spatial Relations Correspondence (ATSRC) methods are suggested to improve correspondences. These suggested methods, unlike conventional methods such as Random Sample Consensus (RANSAC(, which only eliminates incorrect correspondences, detect incorrect correspondences based on spatial relationships and turn them into correct correspondences. Converting incorrect correspondences to correct ones can increase the number of correct correspondences and ultimately increase the precision of correspondences.

The simulation results show that the suggested CRKEMSURF-ATSRC approach improves the mean by 28.92% in terms of precision and 37.58% in SITMMC compared to those of the SIFT-ARANSAC method.

The suggested SRC and ATSRC methods use the spatial relations of the initial correspondences to convert the incorrect correspondences into correct ones. The number of initial correspondences is maintained in these suggested approaches. These methods are better than other methods of improving correspondences such as RANSAC, and Graph Transformation Matching (GTM). These suggested methods can be used as a new and efficient approach to improve the correspondence of medical images.

Numerous studies have described the effect of Electromagnetic Fields (EMFs) in the promotion of Bone Marrow Stem Cell (BMSC) differentiation. We aimed to investigate the influence of frequency (10 and 100 Hz) and different pulse shapes (sine, rectangular, and triangular) of EMF on rats' BMSCs.

The BMSCs in 6 groups were exposed to EMF for 1 h/ 7 days. The BMSCs viability was estimated by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) test. The cresyl violet labeled the Nissl bodies, and the silver nitrate staining was done to evaluate the BMSCs nucleoli AgNORs.

The MTT test verified that EMF and pulse shape did not affect cell viability. In Nissl bodies staining most of the large neurons were related to the rectangular 10 Hz EMF group. The majority of the differentiated BMSCs were astrocytes, microglia, and oligodendrocyte in the triangular 100 Hz EMF group. Although the silver nitrate staining confirmed the effect of 10 Hz EMF, pulse shape alteration did not affect AgNOR parameters. In conclusion, we presented a low-magnetic flux density EMF (400 μT) to assess the responses of BMSCs nuclei.

The findings showed that BMSCs differentiation was frequency-dependent. Further investigations are recommended for recognizing the function of EMF on BMSCs.

According to the side effects of invasive cancer treatments, Sonodynamic Therapy (SDT) as a noninvasive method for breast adenocarcinoma was considered. Sonosensitizer agents’ encapsulation can improve the accumulation of these drugs in the tumor tissue and reduce treatment side effects. Hence, mice breast adenocarcinoma SDT with Hematoporphyrin (HP) and HP-encapsulated Mesoporous Silica Nanoparticles (HP-MSNs) was carried out.

96 female breast adenocarcinoma grafted Balb/C mice were randomly divided into 16 groups (n = 6): control, sham, HP, HP-MSN, Ultrasound (US), SDT+HP, and SDT+HP-MSN groups. Sonosensitizer agents were injected intraperitoneally (2.5 or 5 mg/kg, 0.2 ml) 24h before an US radiation (1MHz, 1 or 2 W/cm2, 60 sec). The tumor growth parameters were evaluated 30 days after SDT.

The inhibition ratio was enhanced by 23, 18, 18, and 16% relative to the control group in HP-MSN (5 mg/kg), HP-MSN (2.5 mg/kg) HP (5 mg/kg) and US (2 W/cm2) groups, respectively, at 18 days after the injection time; whereas, the analysis of findings revealed an antitumor effect in SDT with HP-MSN groups. The Tumor Growth Inhibition (TGI) percentages were 45, 42, and 42% for the SDT (2 W/cm2) + HP-MSN (5 mg/kg), SDT (1 W/cm2) + HP-MSN (5 mg/kg), and SDT (2 W/cm2) + HP (2.5 mg/kg) groups, respectively, on the 18th day post-injection, and T2 and T5 times were higher than that of control and sham groups (P<0.05). The estimated 44-day survival time in the Kaplan-Meier test was 95% in the SDT (2 W/ cm2) + HP-MSN (5 mg/kg) treated group, which had moderately differentiated cells in tumor grading.

Based on the findings, SDT with HP-encapsulated MSNs (5 mg/kg) has an antitumor effect on breast adenocarcinoma.

The Boundary Element (BE) and Finite Element (FE) methods are widely used numerical techniques to solve the Electroencephalography (EEG) forward problem. However, the FE Method (FEM) has difficulty in simulating current dipoles due to singularity, and the BE method (BEM) cannot simulate inhomogeneous and anisotropic conductivity profiles. Recently, a hybrid BE-FE method has been proposed to benefit from the advantages of both BEM and FEM in solving the EEG forward problem. Generally, the type of mesh may significantly influence the results of numerical EEG forward solvers and should be carefully studied.

In this paper, the performance of the hybrid BE-FE method is compared with an approach of FEM (partial integration) using three types of meshes. The ground truth is the analytical EEG forward solutions obtained from inhomogeneous and isotropic/anisotropic four-layer spherical head models with dipoles of radial and tangential directions at four eccentricities.

The minimum mean of Relative Difference Measure (RDM) obtained from Partial Integration (PI)-FEM is 0.0596 at 70% source eccentricity while by using the hybrid BE-FE method it is improved to 0.0251 at the same eccentricity. On the other hand, the maximum mean of Magnitude Ratio (MAG) obtained from PI-FEM is 0.6216 at 50% source eccentricity while it is improved to 0.9734 at the same eccentricity.

The results show that the hybrid BE-FE method outperforms PI-FEM in solving the EEG forward problem using three types of meshes regarding RDM and MAG error criteria.

Skyshine radiation dose equivalent dose rate is known as scattered radiation by the room above air to points at the ground level points outside the Linear Accelerator (LINAC) room. Our aim was to estimate skyshine around the LINAC-based radiotherapy by a 4MV LINAC photon beam.

Monte Carlo (MC) MCNP code calculation was conducted to skyshine at the control room, 60Co treatment room, physics, and simulator rooms. National Council on Radiation Protection and Measurements (NCRP) 151 was also used and it reported analytical formulation methods for photon beam calculation. A Flattering Filter (FF) equipped and Flattening Filter-Free (FFF) LINACs photon beams were derived and differences and agreements were discussed.

The results showed high skyshine for FF equipped relative to FFF LINACs. This effect may be attributed to photon beam hardening by FF in the LINAC head and higher transmission through the ceiling shield and more presence of photons on the roof above the air. NCRP 151 method results were higher than MC simulated photon beam skyshine dose equivalent dose rate and it may be the cause of the inflexible analytical method in contrast to MC simulation. Finally, FFF and FF-equipped LINACs result in skyshine compared and they compared to NCRP 151 report. MC simulation performed reasonably in estimation in different conditions.

Our results showed that FF-equipped skyshine is higher than FFF LINAC and NCRP 151 is an inflexible method that does not take some effective parameters into account and calculates skyshine higher.

Diagnosis of musculoskeletal abnormalities is critical because of the large number of people affected by these disorders worldwide. The recent advances in deep learning techniques show that convolutional neural networks can be a useful tool for the computer-aided detection of radiographic abnormalities. This study focuses on diagnosing musculoskeletal abnormalities in the lower extremities using X-Ray images by deep architecture neural networks.

The dataset contains 61,098 musculoskeletal radiographic images, including 42,658 normal and 18,440 abnormal images. Each image belongs to a single type of lower extremity radiography, including the toe, foot, ankle, leg, knee, femur, and hip joints, which were prepared with standard projection without artifacts and with high quality. A novel deep neural network architecture is proposed with two different scenarios that perform the lower extremity lesion diagnosis functions with high accuracy. The foundation of the proposed method is a deep learning framework based on the Mask Regional Convolutional Neural Network (R-CNN) and Convolutional Neural Network (CNN). The model with the best results incorporated the Mask R-CNN algorithm to produce the bounding box, followed by the CNN algorithm to detect the class based on that.

The proposed model can identify different types of lower limb lesions by an Area Under the Curve (AUC) of the Receiver Operating Characteristics (ROC) curve 0.925 with an operating point of 0.859 of sensitivity and a specificity of 0.893.

The results indicated that the consecutive implementation of Mask R-CNN and CNN has a higher efficiency than Mask R-CNN and CNN separately in lesion detection of lower limb X-ray images.

Therapeutic electrical stimulation of deep brain structures, such as the subthalamic nucleus and the Globus Pallidus (GP), is widely accepted as a treatment tool for patients with Parkinson's Disease (PD). Electrical stimulation of the cerebral cortex with electrodes or transcranial stimulation can increase motor function among PD patients. The present study aimed to evaluate the effects of non-invasive cortical stimulation with simulation of transcranial Direct Current Stimulation (tDCS) technique on parts of the basal ganglia among PD patients.

tDCS was simulated using two different electrode placement methods (anodal stimulation of the primary motor cortex (M1) and anodal stimulation of the Dorsolateral Prefrontal Cortex (DLPFC)) and We evaluated the excitation procedure in the target area based on the excitation current distribution in GP and Subthalamic Nucleus according to the patient's condition in both electrode methods. All simulations were performed using head Magnetic Resonance Imaging (MRI) images of four people with PD. Also, according to the excitation current distribution obtained from the previous step, we studied how the excitation current distributed in the target areas is affected by using a model of the basal ganglia so that based on the membrane potential of each excitation in these areas, in all four patients, we compare both electrode-installation methods in a functional way. The effectiveness of brain stimulation was also studied using a basal ganglia model. Considering the membrane potential of GP and Subthalamic Nucleus regions, the effectiveness of each electrode placement method was evaluated in the Basal Ganglia )BG( model.

According to the results, direct current stimulation was propagated through electrodes placed on the scalp throughout the model. Also, anodal stimulation of the M1 had a better stimulation of GP and subthalamic nucleus than anodal stimulation of the DLPFC.

Although, the procedures for performing tDCS and invasive brain stimulation in PD are different, the results show that this treatment can be appropriate and improve motor function in patients with PD.

Photon-field shaping in radiation therapy with cerrobend block or Multi-Leaf Collimator (MLC) leads to an increase in the scattered dose to the out-of-field Organ At Risk (OAR). This study aimed to measure and compare the healthy organs absorbed dose outside the cerrobend block and MLC shielded field.

Computed Tomography (CT) images were taken of a heterogeneous Thorax phantom while the target volume and organ at risk, including the spinal cord, contralateral lung, and heart were contoured. Conformal Treatment planning was performed (POP fields, total dose 40 Gy, 5 fx/week, and 2 Gy/fx) on the Prowess Panter Treatment Planning System (TPS). Irradiation was performed with 6 and 18 Mv X-ray of Siemens Oncor medical linear accelerator, once for the block-shielded field and again for the MLC-shielded field. At each energy, the radiation dose to the contoured out-of-field organs was measured by an ionization chamber and compared.

At both 6 and 18 MV energies, the out-of-field dose in the MLC-shielded fields was significantly lower than in the block-shielded ones (P < 0.001). The out-of-filed dose for contoured organ at risk was not significantly different at 18 MV compared with 6 MV. The dose calculated by the treatment planning system showed that the healthy organs absorbed doses in all conditions were significantly lower than the dosimetry results.

The use of MLC to shield the lung cancer treatment filed reduces the out-of-field OARs dose compared to cerrobend block. This reduction is greater at 18 MV photon beam but this difference is not statistically significant.

32-time scan duration reduction of 18F-Fluorodeoxyglucose )18F-FDG( Positron Emission Tomography (PET) images through the generation of standard scan duration images using a multi-slice cycle-consistent Generative Adversarial Network (cycle-GAN) was studied. Also, the effect of the image augmentation methods on the performance of the cycle-GAN model was evaluated.

Four subsets of standard and 32-time short scan duration PET image pairs, each contacting image data of 10 patients were used to train and test (80 percent for training and 20 percent for testing) a multi-slice cycle-GAN separately. Another patient’s image data was used as the validation dataset for different training subsets. When training the cycle-GAN model for each subset, two approaches were followed: with and without image augmentation. Common image quality metrics of Peak Signal-to-Noise Ratio )PSNR (, Structural Similarity Index Measure )SSIM(, and Normalized Root Mean Squared Error )NRMSE( were used to assess the generation performance of the cycle-GAN model. Paired sample t-test statistical testing with a confidence interval of 0.95 was used to determine whether the differences between approaches were statistically significant or not.

For subsets 1-3, both training approaches improved the image quality of the short scan duration inputs (p < 0.001) while for subset 4 only the training approach with image augmentation was capable of improving the image quality. However, the training approach with image augmentation offered better results than the approach without image augmentation (p < 0.001).

Employing the training approach with image augmentation, the cycle-GAN model was capable of improving the image quality of 1/32nd short scan duration images through the generation of synthetic standard scan duration images. In the case of the training approach without image augmentation, except for subset 4, the model trained on all subsets 1-3 was capable of improving the image quality. Image augmentation does indeed improve the performance of the cycle-GAN model, especially in the case of insufficient available training datasets.

Musculoskeletal systems have a complex nature, and it is very difficult to control issues in these systems due to various characteristics such as speed and accuracy. Thus, investigating these musculoskeletal systems requires simple and analyzable methods. Also, due to sudden changes during the movement process, the speed and accuracy of the calculations should be proportional to the operating speed of the system. Predicting the system norms and fulfilling them for the system are the next challenges for relevant studies.

Accordingly, this study aimed to investigate the knee joint function, the joint condition in an incomplete Spinal Cord Injury (SCI), as well as its rehabilitation conditions by designing a simple mathematical model. This model was designed based on the interactions between Hamstring Muscles (HAM) and the vasti muscle group. Considering changes in the Central Pattern Generator (CPG) as a variable input, we analyzed the model output in fixed point, periodic and chaotic modes.

The results of the present study showed that the knee joint model output was a chaotic and fixed point for the healthy and incomplete SCI modes, respectively. Increasing the values of afferents was enhanced in the central pattern generating model to rehabilitate the model. According to the modeling results, by applying coefficients of 1.98, 2.21, and 3.1 to the values of afferents Ia, II and Ib, the incomplete spinal injury model changed permanently from the fixed point to the periodic position, indicating movement with rehabilitation in the knee joint.

Based on the results obtained from the knee joint mathematical model in comparison with the reference articles in relation to the expected results, it can be stated that this model has an acceptable output while being simple in calculations and has the ability to predict different norms. It can also be hoped that improved and more detailed results will be achieved in the study of musculoskeletal systems with the development of this model .

Nicotinamide Adenine Dinucleotide Phosphate (NADPH) oxidase is one of the probable sources of Reactive Oxygen Species generated by ionizing radiation. This study aimed to determine the expressions of Nox4 and radioprotective effects of magnesium sulfate and vitamin A following whole-body 2 Gy X-ray irradiation.

In this research, 6-7 weeks old Naval Medical Research Institute (NMRI) male mice were kept in a standard cage with an appropriate temperature and 12 on 12 off light cycle. Three concentrations of vitamin A and magnesium sulfate were intraperitoneally injected into mice 2 hours before irradiation. The dose rate was 50 cGy/min at Source Skin Distance (SSD) = 100 cm and a field size of 10 × 10cm2. The mice were anesthetized and sacrificed by cervical dislocation 24 hours after irradiation. Then, the expression of Nox4 was assessed by Real-Time Polymerase Chain Reaction (PCR(.

There were significant differences between the mean of gene expression in groups treated with vitamin A and magnesium sulfate compared to only radiation group (P < 0.05).

Based on the results of this study, it is likely that vitamin A and magnesium sulfate neutralize the harmful effects of free radicals due to their antioxidant properties.

Studies conducted on both normal and abnormal samples have shown transcranial brain stimulation to be effective in improving cognitive functioning. Meanwhile, the behavioral training of cognitive skills has been found to be effective as well. To enhance or rehabilitate core cognitive processes, neuropsychologists and clinicians usually use either one of these or a combination of both. In this study, we reviewed the literature to investigate the effects of brain stimulation alone or combined with cognitive training on attention and working memory. It was concluded that the combined method can be more effective than brain stimulation alone. However, there is no sufficient evidence to make a conclusive statement.