Journal of Biomedical Physics & Engineering
Volume:10 Issue: 3, May-Jun 2020

Gadolinium (Gd3+) is a chemical element belonging to the lanthanide group and commonly used in magnetic resonance imaging (MRI) as a contrast agent. However, recently, gadolinium has been reported deposition in the body after a patient receives multiple injections. Gadolinium is a potent block and competes with calcium diffusion into the presynaptic. There has not been a precise mechanism of gadolinium blocking calcium channel as a channel of calcium diffusion to presynaptic until now.

This study aims to investigate the mechanism of calcium influx model and the effect of neurotransmitter release to the synaptic cleft influenced by the presence of Gd3+.

Monte Carlo Cell simulation was used to analyze simulation and also Blender was used to create and visualize the model for synapse. The synapse modeled by a form resembling the actual synapse base on a spherical shape.

The presence of gadolinium around the presynaptic has been disturbing diffusion of calcium influx presynaptic. The result shows that the presence of gadolinium around the presynaptic has caused a decrease in the amount of calcium influx presynaptic. These factors contribute to reducing the establishment of the active membrane, then the amount of synaptic vesicle docking and finally the amount of released neurotransmitter.

Gadolinium and calcium compete with each other across of calcium channel. The presence of gadolinium has caused a chain effect for signal transmission at the chemical synapse, reducing the amount of active membrane, synaptic vesicle docking, and releasing neurotransmitter.

Breast cancer screening techniques have been developing rapidly in the field of imaging systems. One of these techniques is thermography, which is an alternative modality for mammography to detect breast lesions. Thermography utilization has been progressively developing as various models and methods of object processing improvement. Currently, the Fluke TIS20 infrared camera, with a resolution of 320 × 240, has not been used to measure precisely small objects such as early breast cancer lesions. Retrieval and processing of single images lead into imprecise object measurements and false positive results.

Problems have been arisen due to the limitations of the camera resolution, object retrieval techniques and suboptimal image processing. The aim of this study was to detect accurately breast cancer lesions in rats, which were induced by carcinogenic compounds.

In this experimental study, development of models was conducted based on increasing image by optimizing the ability of low-resolution infrared (IR) cameras to identify s mall objects precisely. Image pixel density increased by adjusting the distance of the objects from the camera and multiple images of objects gradually shifting were used to measure object dimensions precisely.

The results showed that cancerous lesions as small as 1.27 mm could be detected. This method of lesion detection had a sensitivity and specificity of 93% and 77 % respectively.

Small objects (cancerous lesions) were measured by increasing image resolution through splitting pixels into subpixels and combining several images using Partitioned Iterated Function Systems (PIFS).

Kidney stones in the urinary system are formed from complex minerals that can interfere with the function of the kidney. This formation occurs gradually and can be observed from the appearance of the kidney stones cross-section which are cut along its longitudinal axis resembling a tree cambium. A deeper study on the composition of these layers will provide etiological and pathophysiological information on the mechanism of the formation and development of kidney stones. In addition, an accurate analysis on the composition of the kidney stone can provide a scientific basis to determine the choice of medical treatment and efforts to prevent from forming of kidney stones in humans.

This study aimed to analyze the organic material that makes up kidney stones in each layer.

In this analytical study, the components and morphological properties of five kidney stones in each layer were characterized using Fourier transform infrared-attenuated total reflection (FTIR-ATR) and Scanning Elecron Microscope-Element Distribution Analysis (SEM-EDS).

FTIR-ATR displayed the typical absorption peaks for each stone constituent component. The components of each layer showed the same peak value for each absorption peak which consisted of calcium oxalate monohydrate, struvite, ammonium ion calcium oxalate monohydrate, calcium oxalate monohydrate-calcium phosphate and uric acid. Meanwhile, the difference in the percentage and composition of the elements in each stone can be observed by SEM-EDS.

From this study, it can be concluded that each layer of the kidney stones has a different percentage and composition of elements.

Many studies have used Cerebral Blood Volume (CBV) for gliomas grading and there has been in good agreement between CBV and tumor grade. Almost all of those studies have emphasized the importance of leakage correction due to the underestimation/overestimation of CBV caused by T1/T2* leakage effect in enhanced cases of tumors, especially high grade ones.

The aim of this study is to investigate two methods of CBV estimation in two groups of gliomas with the same grade and different appearance on post contrast T1 images (Enhanced vs. Non-enhanced ones).

In this retrospective study, eight glioma patients with histopatologically confirmed grade III were equally divided into two groups (with enhancement (group 1) and without enhancement (group 2)), and retrospectively studied. Imaging was performed on a 3 tesla MR Scanner and included gradient-echo DSC, 3D T1-weighted dataset and FLAIR images. The conventional method of CBV measurement (Integration over the whole curve of CTC- method 1) and the GVF fitting (method 2) was done using Matlab.

The observed mean rCBV in the tumor ROI was 2.85 and 2.12 for group 1 with method 1 and 2, respectively. Mean rCBV in the tumor ROI for group 2 was 1.24 and 1.11 with method 1 and 2, respectively.

In conclusion, this pilot study demonstrated that with combined use of pre-bolus and accounting for T2* effect, CBV could be considered as a criterion for the categorization of glioma tumors.

Perfusion imaging, one of MRI’s techniques, is widely used to test damaged tissues of the body. The parameters used in this technique include cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT). The MRI scanner contains a device called a “phantom”, which controls the accuracy of various imaging models.

Our goal is to design and produce a microphantom to control the perfusion-imaging model in MRI scanners.

Firstly, in an analytical study type, we designed the phantom based on Murray’s minimum work rule using AutoCAD software. Next, the phantom was fabricated using lithography and then imaged using a Siemens Magnetom 3T Prisma MRI scanner at the National Brain Laboratory. Finally, the velocity and pressure in the capillary network was simulated using COMSOL software.

CBF, CBV, and MTT curves for the capillary network were obtained at different times. In addition, the simulations showed that the velocity and pressure in the capillary network were between 0.0001 and 0.0005 m/s and between 5 and 25 mm/Hg, respectively.

The fabricated microphantom was used to simulate the movement of blood within tissues of the body. Different parameters of perfusion imaging were measured inside the phantom, and they in the phantom were similar to in the body.

High Dose Rate (HDR) brachytherapy sources with high photon energy have been widely used in treating tumors. Dosimetric parameter of these brachytherapy sources should be determined according to the AAPM TG-43 recommendation. Gafchoromic films are reliable tools for this evaluation.

The aim of this study is to evaluate and compare dose accuracy of the two-brachytherapy sources in a dedicated phantom.

In this analytical study, two common sources, including Cobalt and Iridium, were loaded into the dedicated phantom. The two-dimensional dose distribution around the source was calculated by TPS system for certain activities and geometries around the sources. Then, the experimental dose measured by Gafchromic film dosimetry was reported for different angles ranging from 0 to 180 degrees.

The difference between calculated and measured doses was less than 6 percent (-5 to +6 percent) for all of the channels and angles. These errors are smaller and mainly more than zero (Dfilm>DTPS) for angles less than 20 and larger than 110 degrees. There is no statistically significant discrepancy in dose calculation by treatment planning system.

Although the estimated error in dose calculation is not significant, there is still an opportunity to increase the treatment precision. The correlation between the error and the angle should be considered in further plans of brachytherapy. The present study showed comparable errors compared to results of other research studies.

Mycobacterium tuberculosis (MTB) is a pathogen causing tuberculosis (TB) in human, and TB can cause enormous social and economic disruptions. Lateral flow test strips (LFTSs) are inexpensive, portable, disposable, rapid, and easy-to-use analytical tools.

LFTSs were prepared for the detection of MTB. LFTSs were fabricated using a new specific probe for MTB H37Rv, based on IS6110 sequence gene, and tailed with poly deoxyadenine (dA).

In this experimental study, to create test and control zones, streptavidin (STP) and a 150-mer dA were dotted on a nitrocellolose membrane. Gold nanoparticles (GNPs) were conjugated with poly deoxythymidine sequence and placed on the conjugate pad. The composition of immersion buffers for sample pad and conjugate pad, running solution, solutions of GNPs-S-dT150 and STP were introduced. DNA genome of MTB and Mycobacterium bovis in clinical samples was amplified with PCR, and then detected by the LFTSs. During the assay, samples were firstly hybridized in two steps and then placed on a conjugate pad in a manner that positive and negative samples provided two and one red lines, respectively, on the detection pad.

After PCR reaction with biotinylated primer, hybridization process with specific MTB probe-dA70-100 toke 10 min, and running process on the strip was performed within 5 min.

We showed that LFTS can discriminate a particular bacteria strain from others. The LFTSs can be redesigned for detection of other pathogenic genomes.

Radiation induced bystander effects (RIBEs) occurs in unirradiated cells exhibiting indirect biological effect as a consequence of signals from other irradiated cells in the population.

In this study, bystander effects in MCF-7 breast cancer cells and hFOB 1.19 normal osteoblast cells irradiated with gamma emitting HDR Brachytherapy Ir-192 source were investigated.

In this in-vitro study, bystander effect stimulation was conducted using medium transfer technique of irradiated cells to the non-irradiated bystander cells. Cell viability, reactive oxygen species (ROS) generation and colony forming assay was employed to evaluate the effect.

Results indicate that the exposure to the medium irradiated MCF-7 induced significant bystander killing and decreased the survival fraction of bystander MCF-7 and hFOB from 1.19 to 81.70 % and 65.44 %, respectively. A significant decrease in survival fraction was observed for hFOB 1.19 bystander cells (p < 0.05). We found that the rate of hFOB 1.19 cell growth significantly decreases to 85.5% when added with media from irradiated cells. The ROS levels of bystander cells for both cell lines were observed to have an increase even after 4 h of treatment. Our results suggest the presence of bystander effects in unirradiated cells exposed to the irradiated medium.

These data provide evidence that irradiated MCF-7 breast cancer cells can induce bystander death in unirradiated MCF-7 and hFOB 1.19 bystander cells. Increase in cell death could also be mediated by the ROS generation during the irradiation with HDR brachytherapy.

An accurate and fast radiation dose calculations method is the main part of treatment planning for successful radiation therapy.

This work aimed to create a novel GPU-based fast Monte Carlo Photon Dose Code (MCPDC) as a fast and accurate tool in dose calculation for radiotherapy treatment planning.

In this analytical study, MCDPC was written to implement photon MC simulation for energies 0.01 to 20 MeV and run on an NVIDIA GTX970. The code was validated using DOSXYZnrc results and experimental measurements, performed by a Mapcheck dosimeter. Using the innovative definition of photon and electron interactions, mean calculation time for the MCPDC was 5.4 sec for 5e7 source particle history, significantly less than that of DOSXYZnrc which was 400 min.

Considering the simulations in the anthropomorphic phantom with bone and lung inhomogeneity, more than 96.1% of all significant voxels passed the gamma criteria of 3%-3 mm. Compared to the experimental dosimetry results, 97.6% or more of all significant voxels passed the acceptable clinical gamma index of 3%-3 mm.

Very fast calculation speed and high accuracy in dose calculation may allow the MCPDC to be used in radiotherapy as a central component of a treatment plan verification system and also as the dose calculation engine for MC-based planning. MCPDC is currently being developed for electron dose calculation module and graphic user interface. In addition, future work on the applicability of the improved version of the MCPDC in transit dosimetry of megavoltage CT is in process.

Field matching problems in abutting electron fields can be managed by using spoilers.

The aim of this study was to design a Monte Carlo framework for the assessment of spoiler application in abutting electron fields.

In this experimental study, a Siemens Primus treatment head was simulated for a 5 MeV electron beam using BEAMnrc, DOSXYZnrc and EGSnrc user codes. Validation of beam model was done by measurement using a MP3-M water tank and a Semi-flex Chamber-31010 (PTW, Freiburg, Germany). An in-house routine was developed to calculate the combined isodose curves resulting from simulated adjacent fields. The developed framework was analyzed using PMMA and chromium spoilers.

The penumbra width increased from 27.5 mm for open fields to 42 mm for PMMA and 40 mm for chromium. The maximum junction dose reduced from 115% for open fields to 107% for PMMA and 108% for chromium. R90 reduced about 6 mm for PMMA and 3 mm for chromium. Uniformity index reduced from 93% to 77% for both spoilers. Surface dose increased from 79% to 89% for PMMA and 88% for chromium.

Using spoilers, penumbra width at the surface was increased, size and depth of hot spots as well as the therapeutic range were reduced and dose homogeneity at the junction of abutting electron fields was improved. For both spoilers, the uniformity index reduced, and surface percent dose increased. The results of this research can be used to optimize dose distribution in electron beam treatment using abutting fields.

Application of CT- scanning image information and radiation physical characteristics of the biomaterials are two measurable assays for presenting modified cells.

This study presented that CT number (HU) and linear attenuation coefficient contain useful information which can be determined during usual CT scanning for the prediction of breast cancerous cells existence based on hemoglobin concentration.

This experimental study used breast phantom containing major and minor vessels with diameters of 10 and 5 mm, respectively. The major vessels are filled by water, fat, hemoglobin (Hb) as a normal and 4× concentration of hemoglobin (4×Hb) as a cancerous breast cells, then scanned by single slice CT (GE, Hi Speed) 120 kVp, 100 mA for the determination of linear attenuation coefficient (µL).

The CT numbers were for water (-7 to +7 HU), Hb (22±6 HU) and 4×Hb (80±4 HU). The difference between Hb and 4×Hb was significant (p <0.000). Minimum µL was 0.1190±0.00680 cm-1 for fat and maximum was 0.1449±0.00794 cm-1 for 4×Hb.

The study of CT number and linear attenuation coefficient of different concentration of Hb provides a possibility for early predicting of breast cancerous cells existence (4×Hb).

The issue of medial image resolution enhancement is one of the most important topics for medical imaging that helps improve the performance of many post-processing aspects like classification and segmentation towards medical diagnosis.

Our aim in this paper is to evaluate different types of pixel selection models in terms of pixel originality in medical image reconstruction problems. A previous investigation showed that selecting far original pixels has highly better performance than using near unoriginal/estimated pixels while magnifying some benchmarks in digital image processing.

In our technical study, we apply two classical interpolators, cubic convolution (CC) and bi-linear (BL), in order to reconstruct medical images in spatial domain. In addition to the interpolators, we use some geometrical image transforms for creating the reconstruction models.

The results clearly demonstrate that despite the absolute preference of the original pixel selection model in the first research, we cannot see this preference in medical dataset in which the results of BL interpolator for both tested models (original and estimated pixel selection models) are approximately the same as each other and for CC interpolator, we only see a relatively better preference for the original pixel selection model.

The current research reveals the fact that selection models are not a general factor in reconstruction problems, and the structure of the basic interpolators is also a main factor which affects the final results. In other words, some interpolators in medical dataset can be affected by the selection models, while, some cannot.

In the present work, three versions of implementation of non-invasive bronchial asthma diagnostic system based on the author’s technique of noninvasive diagnosis of bronchopulmonary diseases are considered. The offered variants of diagnostic system can be used both in medical institutions and at patient’s home for the control of the patient’s condition with the purpose of monitoring the dynamics of the disease during treatment, as well as for preventive purposes. Three variants of implementation of the diagnostic system with various complexity are considered. The results of a radiofrequency scanning of a human chest phantom with included heterogeneity simulating the presence of sputum in the human chest is a consequence of bronchial asthma.

Better accurate stethoscope measurements have been needed to diagnose heart problems earlier, monitor patients, and provide initial clinical data for physicians. This study aims to evaluate an electronic stethoscope for automatic identification of heart rate by monitoring Beats Per Minute (BPM) in real-time. In this work, a new design with a low cost electronic stethoscope is designed and implemented as a simple circuit for a replacement with conventional stethoscopes. This presented a low cost stethoscopes consisting of a preamplifier, low-pass filter, high-pass filter, microcontroller and Bluetooth. This simulation and experimental study was carried out for electronic circuit design testing. The condenser microphone transmited the signal into the signal conditioning circuit, and amplified it from 10 to 30 times. The low- and high- pass filter circuit was with cutoffs of 180 Hz and 50 Hz, respectively. The result shows that the fourth-order Butterworth filter was the best filter, with a gain of 0.707 Volt, -3.01 dB, and 0.782 Volt, -2.137 dB, respectively. The real-time measurements using the system are not significantly different from the manual measurements, with around 2-5%, with a delay of 1.7 to 2 seconds. The results indicated that an electronic stethoscope system could provide suitable information for BPM value and could display heart sound signals.

The COVID-19 pandemic has affected people globally; nowadays several countries are facing a major change in daily life due to universal quarantining, closed schools, social isolation, and shelter-in-place orders. In addition, this pandemic caused an economic crisis. International Labour Organization (ILO) reported that not only COVID-19 is a serious threat to public health but also the economic and social disruption of this crisis threatens the long-term livelihoods and wellbeing of millions of people. In this short paper, we introduce our hypothesis on using artificial intelligence (AI) technology to predict which employees are most vulnerable to the infections caused by the novel coronavirus (SARS-CoV-2). Such a system can be used in a wide variety of work places such as libraries, banks, drugstores, and hotel receptions to reduce the risk of severe infections in employees as well as to ensure the safety of labor force and the sustainability of businesses and jobs.