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Purpose: Self-regulation can refer to a dimension of temperament (i.e., effortful control), to a set of cognitive processes involved in higher-order control (i.e., executive functions), or to the physiological regulation of the stress response. Effortful control describes the ability to voluntarily manage attention and inhibit or activate behavior as a need to adapt. The purpose of this study was to investigate the psychometric properties of the self-regulation questionnaire.

Materials and Methods: The statistical population of this research are the students who were living in Sanandaj city in 2019. The samples consisted of 231 students (92 females and 139 males) who were selected using cluster random sampling method and received a self-regulation questionnaire.

Results: The results of exploratory and confirmatory factor analysis confirmed the structure of the four self-regulating factors as one of the executive functions. Also, the convergent validity of the self-regulation questionnaire was assessed through the simultaneous implementation of the Bouffard questionnaire. The reliability coefficients of the self-adjusted questionnaire for planning, monitoring, controlling, reflection, and total questionnaires were obtained by Cronbach's alpha coefficient of 0/82, 0/61, 0/77, 0/78, and 0/90, respectively.

Conclusion: Finally, concerning desirable validity and reliability coefficients, ease of implementation, scoring, and interpretation, as well as short response time, it can be stated that this questionnaire is very important in cognitive assessments to examine self-regulation as one of the executive functions.

Purpose: Proton Beam Therapy (PBT) is an emerging radiotherapy technique using beams of proton to treat cancer. As the first report addressing the topic, the principal aim is to highlight the present status of PBT research and development in Iran as a developing country.

Materials and Methods: To do so, the demand for PBT in Iran and Iran National Ion Therapy Center (IRNitc) was investigated and introduced. Then, Scopus and PubMed were searched for studies that dealt with PBT research in Iran and subsequently 6 major subfields of interest were identified. Furthermore, international collaborations were extracted from the bibliographic data. To combine both research and development sides, a SWOT analysis was performed through collecting viewpoints of 48 radiotherapy experts about PBT, and then strengths, weaknesses, opportunities, and threats of it were examined.

Results: Iran contributes to approximately 1% of global PBT sciences. Proton dose calculation using Monte Carlo simulation is the dominant subject of interest for Iranian researchers. Italy is recognized as the major foreign partner in PBT researches. Clinical advantages over conventional radiotherapy modalities are the main strength of PBT development in Iran while the high installation cost remains the most weakness. Finally, 10 general considerations for the launching of a PBT facility in Iran were presented based upon both Iranian experts’ viewpoints and IAEA recommendations.

Conclusion: This research reveals that while PBT research and development in Iran are still in their infancy, there are promising trends in both the research and development sides of PBT.

In the electroporation we can use different electrode types such as needle and plate electrode with different arrangements. One of the new electrode types is single bipolar electrode which the anode and cathode components are in the same needle for decreasing the invasiveness of electroporation procedure. For treatment planning purposes we can use different cell killing probability models such as Peleg-Fermi model. The aim of this study is, investigate the impact of geometric electrode parameters such as conductive pole length, insulated pole length and pulse voltage in bipolar electrode on the cell killing probability distribution in electroporation by COMSOL Multiphysics. The target tissue volume with cell killing probability >80% increased with conductive pole length, and voltage and decreased with insulated pole length. This paper has highlighted the importance of conductive and insulated pole length and voltage in bipolar electrode on the cell killing probability distribution and electroporated volume in the EP.

Purpose: Targeted magnetic drug delivery is one of the methods of cancer treatment. In this method, magnetic factors are conducted inside the body by a variable external magnetic field and deliver the drug agents to the tumor area. The present study aimed to investigate the performance of the drug magnetic conduction by using Differential Current Coil (DCC) and the effect of gravity force on it.  

Materials and Methods: In mathematical modeling, magnetic, hydrodynamic and gravity forces were assumed to affect the movement of magnetic nanoparticles inside the vessels. Helmholtz coils with a circular cross-section and different currents were simulated in the software environment. The trajectory of nanoparticles within the static fluid, Y-shape channel and multi-branch vascular network was calculated. The relations between the magnetic force applied on the magnetic nanoparticles and the parameters of coil flow, radius and relative permeability of the nanoparticles were investigated.

Results: The magnetic flux generated in the coils was calculated and the particles moved in the direction of the magnetic gradient. The diagram of magnetophoresis force changes with the physical parameters was calculated. Particle trajectory and correct exit rate were obtained in simulated vessels. The output changes in the state of with-the-effect and without-the-effect of gravity were about 1.5 to 3%. The output changes of the correct and incorrect branches were calculated by changing the angle of the branches.

Conclusion: From the approximate reduction of 2% of the correct output, it can be concluded that the effect of gravity on the conductivity of the system can be neglected. Besides, it seems that as the injection point is closer to the conduction point, the amount of the correct output will increase more.

Purpose: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is characterized by impaired social interactions. Early detection can prevent the progression of the disease. So far, much research has been done to better diagnose autism. Investigation of brain structure using Magnetic Resonance Imaging (MRI) provides valuable information on the evolution of the brain of patients with autism.  

Materials and Methods: In this study, we equally selected T1-MRI data from 20 control subjects and 20 patients, aged under 13 years (male and female, right hand and left hand). MRI research has shown that the brain of autistic children has grown locally and globally. In this paper, for the brain volumetric evaluation of autistic patients, the MRI data was segmented and then analyzed with a statistical method, which has been investigated more generally, in both the cortical and subcortical areas.

Results: We extracted 110 cortical and subcortical brain areas. The statistical analysis show which areas are important in discriminant between ASD and healthy control groups. According to the results of MRI, an increase in overall growth is seen in the subcortical areas of the brain (amygdala and hippocampus) as well as the cerebellum, but in adults with autism, a decrease in brain volume is seen.

Conclusion: In this study, we analyze the T1-MRI data of ASD subjects for early detection of Autism disorder. Our results were shown in the 6 brain areas that have P-values under 0.005. These areas are important in the early detestation and treatment of ASD.

Purpose: The process of neurodegeneration in Alzheimer's Disease (AD) is irreversible using current therapeutics. An earlier diagnosis of the disease can lead to earlier interventions, which will help patients sustain their cognitive abilities for longer. Individuals within the early stages of AD, shown to have trouble making confident and sounds decisions. Here we proposed a computational approach to quantify the decision-making ability in patients with mild cognitive impairment and mild AD.

Materials and Methods: To study the quantified decision-making abilities at the early stages of the disease, we took advantage of a 2-Alternative Forced-Choice (2AFC) task. We applied the Drift Diffusion Model to determine whether the information accumulation process in a categorization task is altered in patients with mild cognitive impairment and mild AD. We implemented a classification model to detect cognitive impairment based on the Drift Diffusion Model's estimated parameters.

Results: The results show a significant correlation of the classification score with the standard pen-and-paper tests, suggesting that the quantified decision-making parameters are undergoing significant change in patients with cognitive impairment.

Conclusion: We confirmed that the decision-making ability deteriorates at the early stages of AD. We introduced a computational approach for measuring the decline in decision-making and used that measurement to distinguish patients from healthy individuals.

Purpose: Glioma tumor segmentation is an essential step in clinical decision making. Recently, computer-aided methods have been widely used for rapid and accurate delineation of the tumor regions. Methods based on image feature extraction can be used as fast methods, while segmentation based on the physiology and pharmacokinetic of the tissues is more accurate. This study aims to compare the performance of tumor segmentation based on these two different methods.

Materials and Methods: Nested Model Selection (NMS) based on Extended-Toft’s model was applied to 190 Dynamic Contrast-Enhanced MRI (DCE-MRI) slices acquired from 25 Glioblastoma Multiforme (GBM) patients in 70 time-points. A model with three pharmacokinetic parameters, Model 3, is usually assigned to tumor voxel based on the time-contrast concentration signal. We utilized Deep-Net as a CNN network, based on Deeplabv3+ and layers of pre-trained resnet18, which has been trained with 17288 T1-Contrast MRI slices with HGG brain tumor to predict the tumor region in our 190 DCE MRI T1 images. The NMS-based physiological tumor segmentation was considered as a reference to compare the results of tumor segmentation by Deep-Net. Dice, Jaccard, and overlay similarity coefficients were used to evaluate the tumor segmentation accuracy and reliability of the Deep tumor segmentation method.

Results: The results showed a relatively high similarity coefficient (Dice coefficient: 0.73±0.15, Jaccard coefficient: 0.66±0.17, and overlay coefficient: 0.71±0.15) between deep learning tumor segmentation and the tumor region identified by the NMS method. The results indicate that the deep learning methods may be used as accurate and robust tumor segmentation.

Conclusion: Deep learning-based segmentation can play a significant role to increase the segmentation accuracy in clinical application, if their training process is completely automatic and independent from human error.

Electric field intensity at each point is responsible for pore creation in the cell membrane during the electroporation process. These pores can increase the tissue electrical conductivity in the electroporation. Changes in electrical conductivity through the electroporation is a useful factor for imaging and tracking of electroporation inside the body. Electrical conductivity is set to become a vital factor for accurate estimation of the electric field and cell kill probability distribution in the course of electroporation for treatment planning purposes. Therefore, for more accurate treatment, tissue electrical conductivity changes due to electroporation should be considered in the treatment planning system. This paper describes the advantages of tissue electrical conductivity as a useful factor in the clinic.

The Autonomous Sensory Meridian Response (ASMR) is a unique phenomenon to provoke a sense of relaxation that has been proposed for a few years. This phenomenon suggests acoustic-visual stimuli  for cultivating a peaceful environment for the mind as well as a tingling sensation. Some studies suggest that this phenomenon is comparable with mindfulness; surprisingly, published articles in this regard are growing increasingly to examine how it happens scientifically. Some studies have been done on neuroimaging techniques, including functional Magnetic Resonance Imaging (fMRI), biological methods such as heart rate and skin conductance, and questionnaires to assess the impact of ASMR videos. In this paper, we intend to determine the effect of ASMR videos on EEG signals. The FFT absolute power analysis (Pre versus Post ASMR) revealed a declined delta band power generally. On the other hand, there are no significant changes in theta band power. The central region demonstrated a rise in alpha band power as well as a slight decrease in the occipital region. Moreover, such an increase was evident in post-ASMR in the beta1 (Sensorimotor wave (12-15 Hz)) band frequency, generally, especially in the frontal region. Besides, Gamma 1 has been increased in the central region, and Gamma 2 has also be increased in frontoparietal regions in both hemispheres. These results indicate the cognitive process as well as sensorimotor, tingling sensations features of ASMR.