Journal of Biomedical Physics & Engineering
Volume:12 Issue: 2, Mar-Apr 2022

The dose values obtained from procedures of diagnostic radiology are relatively low. To accurately and precisely measure the dose values in this dose range, it is necessary to know the characteristics of dosimeters.

The aim of this study was to evaluate several thermoluminescent characteristics of GR-200, TLD-700H and TLD-100 for low dose measurement.

In this experimental study, linearity, repeatability, dose rate and photon energy dependence of different TLD materials were investigated in a 0.05-10 mGy range dose. It is noteworthy that the data obtained from TLD-100 were considered as reference and the data obtained from two other types of TLDs were compared with them.

For all three types of TLD materials, there are linear relations between absorbed dose values to TLDs and their responses. TLD-100 and TLD-700H have very low sensitivity than GR-200. For GR-200 and TLD-100, the coefficients of variation values (%) are 3.00% and 2.01%, respectively, that these values are within the tolerance limit (<7.5%). However, this value for TLD-700H is 10.85% which it is more than the reported tolerance limit. Furthermore, remarkable effects of dose rate and photon energy dependence on the responses of GR-200 are not observed in a 0.5-4 mGy dose range; nevertheless, remarkable effects of dose rate and photon energy dependence on the responses of TLD-100 and TLD-700H are found in this dose range.

The evaluated thermoluminescent characteristics for GR-200 are better than two other types of TLDs (TLD-100 and TLD-700H) for low dose values.

Recent research on photon detection has led to the introduction of a silicone photomultiplier (SiPM) that operates at a low voltage and is insensitive to magnetic fields. This work aims to model a scintillation camera with a SiPM sensor and to evaluate the camera reconstructed images from gamma ray projection data. The type of study in this research is experimental work and analytical. The scintillation camera, modelled from an SiPM sensor array SL4-30035, coupled with a scintillation material Caesium Iodide doped with Thallium (CsI(Tl)), is used in the experimental part. The performance of the camera was evaluated from reconstructed images by a back-projection technique of a radioactive source Caesium-137 (Cs-137). The experiments conducted with a 1 µCi Cs-137 radioactive source have revealed that the bias voltage (Vbias) of the SiPM needs to be set to 27.8 V at an operating temperature between 43 °C to 44 °C. The radioactive source has to be placed within a 1 cm distance from the sensor to obtain the optimum projection data. Finally, the back-projection technique for image reconstruction with linear interpolation pre-processing has revealed that the Ram-Lak filter produces a better image contrast ratio compared to others. This research has successfully modelled a scintillation camera with SiPM that was able to reconstruct images with an 86.4% contrast ratio from gamma ray projection data.

Establishing a predictive assay of radiosensitivity (as an appropriate, practical and cost-effective method) has been challenging. The purpose of this study is to evaluate the capability and relationship of various endpoints, including GammaH2AX, micronuclei; and apoptosis in determining the human tumor cell lines radiosensitivities compared with clonogenic survival. In an experimental in-vitro study, the response of carcinoma cell lines of HN5 and HeLa to 2 Gy of 6 MV photon beam was investigated via various assays. Survival fraction at 2 Gy (SF2) of HeLa and HN5 was indicated as 0.42 ± 0.06 and 0.5 ± 0.03 respectively, proposing more radioresistance of HN5. This finding was confirmed with “2 Gy apoptosis enhancement ratio” which was 1.77 and 1.42 in HeLa and HN5. The increased levels of DNA DSBs were observed after irradiation; significant in HeLa with enhancement rate of 19.24. The micronuclei formation followed an ascending trend post irradiation; but with the least difference between two cells. Although the relationship between micronuclei and clonogenic survival was moderate (R2 = 0.35), a good correlation was observed between apoptosis and clonogenic survival (R2 = 0.71). The results of studied endpoints agreed with the SF2, highlighting their capabilities in radiosensitivity prediction. In terms of the enhancement ratio, gammaH2AX foci scoring could be a valid indicator of radiosensitivity but not the exact surrogate marker of survival because no correlation was observed. Moreover, considering the chief determents comprising lack of time and money, the apoptotic induction might be an appropriate indicator with the best correlation coefficient.

The Mentha-Pulegium essential oil (MP-EO) contains different antioxidant compounds and reduces the indirect effects of dispersed ionizing radiation on biological systems.

The current study aimed to assess a possible radio-protective effect of MP-EO on peripheral blood mononuclear cells (PBMCs).

In this experimental study, MP-EO was firstly prepared and PBMCs were then irradiated in various groups with doses of 25 and 200 cGy of X-rays in the presence of IC10 of MP-EO. After incubation times of 48h and 72h, the survival, apoptosis, and necrosis percentages of PBMCs were determined by MTT assay and flow cytometry analyses; the radio-protective effect of MP-EO was examined.

In the presence of 80 µg/ml (IC10) MP-EO, the mean survival percentage of irradiated PBMCs by radiation doses of 25 and 200 cGy was significantly increased after 48h of incubation compared with the control. At 72h of incubation, the mean survival percentage of irradiated PBMCs was significantly increased only at 25 cGy. The percentage of apoptosis and necrosis of PBMCs was significantly reduced in the presence of the MP-EO at both incubation times and radiation doses; therefore, the highest reduction was at 200 cGy and 48h incubation compared to the control.

MP-EO as a natural, non-toxic, and cost-effective compound can exhibit a favorable in-vitro radio-protective effect by increasing the survival and decreasing the percentage of apoptosis and necrosis of irradiated PBMCs.

Multiple sclerosis (MS) disease causes structural and functional damage to brain. Structural imaging of the MS-induced damage cannot adequately describe the functional impairment of the brain in MS patients. Therefore, it seems that advanced functional imaging analysis such as functional magnetic resonance imaging (fMRI) data is needed for better management of this disease. The aim of present study was to evaluate the effective connectivity within the Papez circuit in MS patients using resting-state fMRI. In this cross-sectional analytical study, 22 healthy individuals and 24 patients with MS underwent resting-state fMRI. After pre-processing of the obtained data, the time series of Cingulate gyrus (CG), Para hippocampus gyrus (PHG), anterior thalamic nuclei (ATN), Mammillary body (MB), and Hippocampus (HPC) were extracted as the main Papez circuit components. The obtained time series were statistically analyzed as an input of the dynamic causal model in order to evaluate the effective connectivity in the Papez circuit. The power of effective connectivity between each pair of tested nodes in Papez circuit was significantly lower in MS patients than healthy subjects. Also, the effective connectivity level of MS patients in direction of HPC→ATN was higher in men than women. In addition, effective self-connection in CG→CG and MB→MB regions in healthy subjects were higher in women than them in men. The present study reveals significant difference in effective connectivity of the Papez nodes in MS patients than control group, which can be exploited to diagnosis and predict or evaluate the treatment response of these patients.

Motor Imagery (MI) Brain Computer Interface (BCI) directly links central nervous system to a computer or a device. Most MI-BCI structures rely on features of a single channel of Electroencephalogram (EEG). However, to provide more valuable features, the relationships among EEG channels in the form of effective brain connectivity analysis must be considered. This study aims to identify a set of robust and discriminative effective connectivity features from EEG signals and to develop a hierarchical machine learning structure for discrimination of left and right hand MI task effectively. In this analytical study, we estimated effective connectivity using Granger Causality (GC) methods namely, Generalized Partial Directed Coherence (GPDC), Directed Transfer Function (DTF) and direct Directed Transfer Function (dDTF). These measures determine the transient causal relation between different brain areas. Then a feature subset selection method based on Kruskal–Wallis test was performed to choose most significant directed causal connection between channels. Moreover, the minimal-redundancy-maximal-relevance feature selection method is applied to discard non-significance features. Finally, support vector machine method is used for classification. The maximum value of the classification accuracies using GC methods over different frequency bands in 29 subjects in 60 trial is approximately 84% in Mu (8−12 Hz) - Beta1 (12−15 Hz) frequency band using GPDC method. This new hierarchical automated BCI system could be applied for discrimination of left and right hand MI tasks from EEG signal, effectively.

Handgrip or Grip strength (GS) is a common method used to evaluate muscle strength and affected by different factors, including age, gender, and arm’s positions.

This study aims to investigate the effect of both the gender and arm’s positions on the handgrip strength and the fatigue resistance (FR), which is the time needed for the handgrip strength to drop to 75% (FR75), 50% (FR50), and 25% (FR25) of its maximum strength during sustained maximal handgrip effort.

In this experimental study, 59 male and 41 female participants were asked to grip forcefully on a dynamometer for the longest period. GS and FR75, FR50, and FR25 values were recorded for 7 different arm positions. Factorial ANOVA was used to find the main effect of gender and position and the interaction between them. Sidak and Tukey’s HSD tests were used to find the gender and arm position effects, respectively.

The results showed a significant effect for gender and arm position on GS and FR and a significant interaction effect for GS that was significantly higher in males than females for all positions. The gender difference in FR depends on arm’s positions and the level at which the FR was measured. GS was higher when arm adduction with 90 ͦ forward at the elbow as compared to arm abduction with 180 ͦ at the shoulder and 90 ͦ at the elbow.

The results confirmed the significant effect of the gender and arm’s positions on the maximal handgrip strength and fatigue resistance during sustained maximal handgrip effort.Keywords

Artificial intelligence plays an important role in medicine. Specially, expert systems can be designed for diagnosis of disease. Artificial intelligence can be used for diagnosis of disease. This study proposes an expert system for diagnosis of Multiple Sclerosis based on clinical symptoms and demographic characteristics. Specially, it recommends patients to refer to a specialist for further investigation. In this empirical study, some symptoms of Multiple Sclerosis are mapped to fuzzy sets. Moreover, several rules are defined for prediction of Multiple Sclerosis. The fuzzy sets and rules form the knowledge base of the expert system. Patients enter their symptoms and demographic information via a user interface and Mamdani method is used in inference engine to produce the appropriate recommendation. The precision, recall, and F-measure are used as criteria to analyze the efficiency of the expert system. The results show that the designed expert system can recommend patients for further investigation as effective as specialists. Specially, while the proposed expert system recommended referring to a doctor for some healthy users, most of the MS patients are diagnosed. The proposed expert system in this study can analyze the symptoms of patients to predict the Multiple Sclerosis disease. Therefore, it can investigate initial status of patients in a rapid and cost-effective manner. Moreover, this system can be applied in situations and places, which human experts are unavailable.

Due to the increased prevalence of diabetes and the irreparable complications of this disease, it is important to measure and monitor the blood glucose levels of diabetic patients. The only way to treat type 1 diabetes is monitoring insulin, and in this type of diabetes, insulin should be injected into the body in order to reduce the patient’s blood glucose as prescribed by the physician at certain times. In addition, the only way to treat type 2 diabetes is through diet and exercise daily.

We aim to use an ordinary differential equation model with two-delays to control the rate of changes in blood glucose levels throughout the day, based on the amount of food that the person consumes.

In this analytical study, we extended an ODE model which is parameterized by data collected in this study to capture dynamics of glucose and insulin. We used global sensitivity analysis method to assess model robustness with respect to parameter perturbations.

Our results have shown that utilizing the dynamics of changes in blood glucose levels throughout the day can be used to prevent hypoglycemia and hyperglycemic in the diabetic patients.

Dynamic modeling can help us to prevent hypoglycemia and hyperglycemia in the diabetic patients.

In the present study, we investigated the application of pulsed magnetic field (MF) (3.5 T, 1 Hz, 8 square-wave/160 µs) permeabilization on murine breast adenocarcinoma cells when administering bleomycin (BLM) in vivo.

This cross-over study aims to find a noninvasive method to facilitate penetration of hydrophilic anti-cancer drugs through the cancerous cells membrane into the cytosoll in order to minimize the side effects of the chemotherapy treatments of tumors.

In this cross-over study, a total of 50 female Balb/c mice were tumorized via homograft. After about 2 weeks, magnetic pulses (3.5 T, 1 Hz, 8 square-wave/160 µs) were applied to tumor-bearing mice 3 min after intratumoral BLM solution injection. Tumor volume was measured every 48 h during 22 days.

The results showed that the difference between the BLM plus 3.5 T MF group versus the sham control or sham MF groups was significant. Uptake of BLM molecules by tumoral cells in the BLM plus 3.5 T MF group versus the BLM control group was 7- folds higher that this result was statistically insignificant (p <0.05, SEM=266.8676, analysis of variance).

Significant cell permeabilization to BLM requires greater MF strength or exposure time. Further investigation is necessary.

It has recently been reported that differences in life expectancy can be linked to income. In Norway, a registry-based study that included all Norwegian residents aged ≥ 40 years (2005-2015) was performed. This study showed substantial and increasing gaps in life expectancy by income level during the interval between 2005-2015. Compared to the United States, the largest life expectancy differences were for individuals in the lower to middle part of the income distribution, although differences were observed at all income levels. Despite its undeniable strengths and although this paper can be considered as a significant contribution to this field, it has some shortcomings. The first shortcoming of this study is due to ignoring the effects of population exposures to natural and man-made ionizing and non-ionizing radiation on life expectancy. Another shortcoming arises from ignoring the strong impact of education on lifestyle. In summary, what is observed in this study might be at least to some extent, due to education-related changes in lifestyle and not necessarily income (despite the mutual links between education and income).

Coronavirus disease (COVID-19) as an emerging disease decreases security among people from different countries. Sense of security can be raised via quick diagnosis of COVID-19, and its management and control using clinical decision support systems (CDSS) to prevent further spread of the disease. So, the aim of this study is to identify and introduce the applications of a CDSS in the diagnosis, management, and control of COVID-19. This cross-sectional study was conducted to identify and introduce the applications of CDSS in the diagnosis, management, and control of COVID-19. Based on the results of some meetings with infectious disease specialists and a general practitioner as well as reviewing the related literature, information about COVID-19 and CDSS was obtained. Then based on the information obtained, a questionnaire was designed electronically and distributed in a two-round Delphi method among 19 experts in the three fields of medical informatics, health information management, and infectious disease specialists. According to the literature and expert opinions, 35 applications of CDSS applications were identified in the four main groups of “diagnosis”, “medication”, “monitoring”, and “health services”. Eventually, a collective agreement was reached on 30 applications in the first and second rounds of Delphi. Among all the applications, the highest means were assigned to “monitoring the vital signs” and “helping diagnose infections and damaged lung tissue through CT scan”. Introducing these applications can provide general, basic knowledge of the design and implementation of clinical decision support systems in the real world to prevent irreversible complications and even many people’s death.