Journal of Biomedical Physics & Engineering
Volume:10 Issue: 5, Sep-Oct 2020

Health information is highly sensitive to all kinds of health care environments ranging from organization-based to personalized health. Nowadays, health information is exchanged readily for the consequence of the introduction of ubiquitous computing in healthcareindustry. Therefore, minimization of vulnerabilities and security risks are a must. Information privacy is a critical issue in all kinds of health information systems with some platforms (e.g. implementable medicaldevices, mobile-based apps, biosensors, smart home, etc.). This paper was aimed at providing a snapshot of existing frameworks protecting health information privacy in pervasive healthcare environments. Accordingly, terms such as pervasive health care, mobilehealth, ubiquitous health, health information and privacy were searched in technical databases and on the Internet search engines using free text both in English and Persian (February 2015). In summary, these frameworks have characteristics as managing data access, data collection, use and disclosure in common. Taken together, these frameworks would be applied in emerging health environments and associated frameworks addressing information privacy.

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease and global health crisis. Although real-time reverse transcription polymerase chain reaction (RT-PCR) is known as the most widely laboratory method to detect the COVID-19 from respiratory specimens. It suffers from several main drawbacks such as time-consuming, high false-negative results, and limited availability. Therefore, the automatically detect of COVID-19 will be required. This study aimed to use an automated deep convolution neural network based pre-trained transfer models for detection of COVID-19 infection in chest X-rays. In a retrospective study, we have applied Visual Geometry Group (VGG)-16, VGG-19, MobileNet, and InceptionResNetV2 pre-trained models for detection COVID-19 infection from 348 chest X-ray images. Our proposed models have been trained and tested on a dataset which previously prepared. The all proposed models provide accuracy greater than 90.0%. The pre-trained MobileNet model provides the highest classification performance of automated COVID-19 classification with 99.1% accuracy in comparison with other three proposed models. The plotted area under curve (AUC) of receiver operating characteristics (ROC) of VGG16, VGG19, MobileNet, and InceptionResNetV2 models are 0.92, 0.91, 0.99, and 0.97, respectively.  The all proposed models were able to perform binary classification with the accuracy more than 90.0% for COVID-19 diagnosis. Our data indicated that the MobileNet can be considered as a promising model to detect COVID-19 cases. In the future, by increasing the number of samples of COVID-19 chest X-rays to the training dataset, the accuracy and robustness of our proposed models increase further.

Thermoluminescence dosimetry(TLD) has been known as one of the most effective methods for dose estimation in diagnostic radiology. Orthopantomogram (OPG) imaging is used by many dentists, oral and maxillofacial surgeons as an effective tool for choosing an appropriate treatment plan. This study aims to measure the entrance skin dose and the dose values received by different head and neck organs in OPG imaging using TLD dosimeters (TLD-100). In this experimental study, the entrance skin dose and doses of various organs during imaging were measured by TLD dosimeters inside and on the surface of the Rando-Phantom. Doses to various organs, including thyroid, eye, esophagus, parotid and sublingual and submandibular salivary glands were measured. The measurements were repeated twice, and the dose values obtained in the two steps were compared. Based on the results obtained in this study, the minimum dose values were found in Esophagus; 65.81, and 59.31 µGy, respectively. The maximum organ dose value was found for left parotid glands, 3842.42, and 3399.58 for the two measurements, respectively. The results show that the dose values can vary based on devices, exposure conditions, and TLD positioning.

Intensity Modulated Radiation Therapy (IMRT) is extensively used in the treatment of malignancies. Clarkson’s method is one of the leading methods for dose calculation at open points present in irregular fields. The aim of this study is to generalize the Clarkson’s method for dose calculation at points under compensator filters in IMRT method and its application in IMRT quality control as well. In this experimental study, compensator filters were designed in two forms: flat filter and block piled-up compensator. The measurements for the compensator filters and open fields in 5 and10 cm depths at energy levels (6, 10 and 18 MV) and in fields with different dimensions were performed using “Mapcheck2” dosimeter. The aim of performing calculations is to derive the theoretical dose by the generalized Clarkson’s equation and comparing it with data resulted from the measurement for confirming the Clarkson’s equation presented. These results demonstrate the data derived from the generalized Clarkson’s method are in good agreement with the data resulted from measurement; the highest error of the proposed equation was 3% for flat filter, and less than 5% for block-piled-up filter. Higher error in the block-piled-up filter compared with the flat filter was due to the presence of leakage between these blocks. The results of this study demonstrated that the presented equation is reliable and valid, and the proposed equation can be applied for dose calculation at all points under the compensator filter or the shielded areas.

Proton magnetic resonance spectroscopy (1HMRS) is a noninvasive method to quantify pain. A 1HMRS spectrum is a group of peaks at different radiofrequencies, showing proton nuclei in various chemical environments. These MR spectra provide information about metabolite concentrations, and make MRS a useful procedure to monitor metabolic fluctuations due to disease, and to track the efficacy of treatment. This study aims to identify correlations between clinical symptoms in patients with tension-type headache (TTH) and concentrations of brain metabolites. In this observational study, twenty-four patients (4 men and 20 women) with chronic TTH were included. To evaluate their clinical symptoms, the number of trigger points, headache frequency and headache intensity were recorded. The levels of anxiety and depression were recorded with the Beck Anxiety Inventory (BAI) and Beck Depression Inventory II (BDI- II). Concentrations of brain metabolites were determined in the anterior cingulate cortex, thalamus and primary somatosensory cortex of left hemisphere with 1HMRS. There was a negative correlation between trigger point count and choline/creatine (Cho/Cr) ratio in the primary somatosensory cortex [r= −0.509, n= 24, p= 0.01]. There were no correlations between other clinical symptoms of TTH and concentrations of brain metabolites. Patients with more trigger points had a lower Cho/Cr ratio, which may indicate alterations in brain metabolic activity.

Gadolinium oxide nanoparticles as positive contrast material of magnetic resonance imaging (MRI) have attracted a great attention due to the appropriate magnetic properties. One of the most desirable features of these nanoparticles is their ability of doping with other lanthanides which can change their properties. This study aimed to investigate the effect of neodymium doping on MRI relaxivity of the gadolinium oxide nanoparticles. In this experimental study, the oleic acid coated gadolinium oxide nanoparticles and the neodymium doped nanoparticles were prepared by polymer pyrolysis method. X-ray diffraction test and scanning electron microscopy were used for characterization of the particles. 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay was performed to investigate the in vitro cell toxicity of the nanoparticles. The r1 and r2 relaxivities were extracted from the T1 and T2 weighted MR images, respectively. The average size of the cytocompatible spherical-like shape nanoparticles was 40 nm. The neodymium doped nanoparticles produced a significant decrease in the r1 relaxivity, and a 1.7 fold increase in the r2 relaxivity compared to the gadolinium oxide nanoparticles. Doping of neodymium into the gadolinium oxide nanoparticles suppresses the r1 relaxivity and enhances the r2 relaxivity of the nanoparticles.

As an alternative form of cancer therapy, photothermal therapy (PTT) and sonodynamic therapy (SDT) using nanomaterials are in development. Nanomaterials can act as energy absorber as well as anti-cancer agent. In this study, the effects of laser and ultrasound irradiation with Se-PEG-Cur nanoparticles were investigated on melanoma cancer. In this experimental study, nanoparticles of selenium-polyethylene glycol-curcumin (Se-PEG-Cur) were synthesized, and their UV-vis absorption, particle size, zeta potential and photothermal conversion efficiency were determined. Se-PEG-Cur was then introduced as a novel 808-nm laser light absorbing agent as well as ultrasound (US) wave for treatment of C540 (B16/F10) cancer cells. Also, ROS generation in C540 (B16/F10) cancer cells was measured upon PTT and SDT using Se-PEG-Cur. Mean size, zeta potential and photothermal conversion efficiency of Se-PEG-Cur were obtained as ~300 nm, 42.7 mV and 16.7%, respectively. Cell viability upon irradiation of the laser light or US waves with 100 µg mL-1 Se-PEG-Cur were decreased to 33.9 and 22.9%, respectively. Intracellular ROS detection indicated that dual PTT and SDT in the presence of Se-PEG-Cur induced the highest ROS production. Se-PEG-Cur was therefore introduced as an absorbing agent of both laser light and US waves for cancer treatment.

Adhesive intestinal obstruction is a common and potentially lethal complication after surgical interventions in the abdomen. Radiologic imaging is the main diagnostic method. This study aims to analyse the diagnostic value of spiral computed tomography with a novel method (n = 54). In this multidirectional cohort study, we present the data with non-parallel (historical) control. This study included the analysis of results of patients with a diagnosis of intestinal obstruction (n = 54) who were admitted to the surgical departments of the City Clinical Hospitals (Ufa city) from 2013 to 2019; the patients’ examination methods included computed tomography with conventional enhancement. The proposed novel enhancement method was implemented by ingesting a mixture containing 50 ml of the contrast Unigexol (300 mg) in 1.0 L cold mineral carbonated water, and Computed tomography (CT) was performed during 40 min after ingesting the contrast meal. Further, the patients with suspected obstruction in the colon were administered a pre-prepared contrast enema with a decoction of leaves of smoke-tree (100 g), chamomile flowers (100 g) and calendula flowers (100 g). Additionally, CT was performed. Obstruction was conservatively stopped in 24 (44.4%) patients of the main group. Remaining 30 (55.6%) patients from the main group were operated with minimal surgical access in the early stages. Owing to early diagnosis of intestinal obstruction and application of the phytocomposition during the examination, exerting various effects such as antispasmodic, analgesic, disinfectant, bactericidal, cicatrising, choleretic, tanning and decongestant, unnecessary surgical interventions were prevented.

Intensity Modulated Radiation Therapy (IMRT) technique is an advanced method of radiotherapy leading into the development of Flattening Filter-Free (FFF) medical linear accelerators (Linacs). Monte Carlo simulation has been a standard method for calculation of particle transport due to precise geometry and material specifications. This study is to obtain the design optimization of Flattening Filter Free (FFF) for 6 MV Linac machine. In this simulating study, EGSnrc user code was used to simulate particles emitted from head of linac 6MV Varian to achieve the most suitable filter in FFF linac design. Monte Carlo simulation results of the PDD and profile, on the 10 × 10 cm2 field, were compared with the measurements. Differences in small profile beams from Monte Carlo simulation were also evaluated between FF and FFF linac. The spectrum on Monte Carlo simulation in isocenter was compared with Treatment Planning System (TPS) for each filter variation. The slight differences of average spectrum are simulated using 2 mm copper filter and FakeBeam with -1.52 ± 3.82% and -3.13 ± 3.61%. Whereas, for PDD and profiles, each variation has an average difference of 7.10 ± 0.70% and -5.99 ± 1.39%. FakeBeam filter is a proper filter for the use of linac design 6MV Varian. It is necessary to decrease the kinetic energy of electrons to perform MC simulations on FFF linac.

Noise reduction is a method for reducing CT dose; however, it can reduce image quality. This study aims to propose a selective mean filter (SMF) and evaluate its effectiveness for noise suppression in CT images. This experimental study proposed and implemented the new noise reduction algorithm. The proposed algorithm is based on a mean filter (MF), but the calculation of the mean pixel value using the neighboring pixels in a kernel selectively applied a threshold value based on the noise of the image. The SMF method was evaluated using images of phantoms. The dose reduction was estimated by comparing the image noise acquired with a lower dose after implementing the SMF method and the noise in the original image acquired with a higher dose. For comparison, the images were also filtered with an adaptive mean filter (AMF) and a bilateral filter (BF). The spatial resolution of the image filtered with the SMF was similar to the original images and the images filtered with the BF. While using the AMF, spatial resolution was significantly corrupted. The noise reduction achieved using the SMF was up to 75%, while it was up to 50% using the BF. SMF significantly reduces the noise and preserves the spatial resolution of the image. The noise reduction was more pronounced with BF, and less pronounced with AMF.

Current diagnostic methods for enamel caries detection are unable to detect caries lesions (incipient caries lesion) at a very early stage. This study aims to determine the remineralizing effect of three fluorinated compounds on demineralized subsurface tooth enamel using Raman spectroscopy characterization. In this experimental study, sixty impacted 3rd molars, with intact anatomical crowns recently extracted and without structural defects, were sectioned longitudinally in a mesio-distal direction using a diamond disc, obtaining two working surfaces (buccal and lingual). The 120 working surfaces obtained were immersed for 96 h in a demineralization solution at 37°C in order to demineralize the enamel surface. All samples were randomly divided into three groups (n=30 each) and their surfaces were treated with silver diamine fluoride (SDF), Difluoride silane (DSF), and acidulated phosphate fluoride (APF), and with no treatment undertaken in the control group (CG). The samples were immersed in alternating solutions for demineralization and remineralization at pH 4.4 and pH 7.0, respectively. The results were analyzed with Principal Component Analysis (PCA) in order to determine the variance. The most important difference (91.7%) is observed in APF group between PCA1 respect to PCA2, followed by DSF (91.5%) and SDF (76.3%) respectively. Therefore, a greater remineralization in the dental enamel can be observed by the three experimental groups. The APF and DSF have the effect of recovering the mineralization of dental enamel, except for the SDF. Functional groups OH- and PO43- were identified in all subsurface.

The foot is the most complex body’s structure; it is highly susceptible to disorders because of its loading pattern. The complexity of the foot structure geometry implies the use of reverse engineering tools to obtain a model that can accurately mimic the biomechanical behavior of the foot. The objective of this study is to establish a state-of-the-art ankle-foot finite element (FE) model with anatomically realistic geometry and structure in order to get the model that will suit all cases for future studies on stress injuries and foot insole designs under different loading conditions. In this analytical study, tomography images were imported in DICOM format, after that, the object was exported in the form of three-dimensional structures in STL file format to define and assemble the structures. After that, the computer simulation on numerical model was done. One-way Analysis of variance (ANOVA) test was performed, and a threshold (p<0.05) was used to indicate the significance of results. The results showed no significant differences (P>0.05) between the values of the plantar pressure corresponding to neutral standing condition with other foot models in literature. The stresses transferred to the bone structure show that the relatively higher stress was located in the fifth, fourth and third tarsometatarsal, where the maximum von Mises stress in the bone structure was 2155.4 kPa. The state-of-the-art ankle-foot FE model with anatomically realistic geometry and structure will be very helpful for future studies on stress injuries and foot insole designs under different loading conditions.

131I source is widely used in the treatment of hyperthyroidism and thyroid cancers. 131I emits both beta and gamma-rays. Radiation protection is considered for gamma rays emitted by 131I. It seems no special shield against 131I source to be designed. This research aims to evaluate determination of optimum shields in nuclear medicine against 99Tcm and 131I sources by dosimetric method. Additionally, Monte Carlo simulation was used to find the optimum thickness of lead for protection against 131I source. This is an experimental research in the field of radiation protection. A calibrated model of GraetzX5C Plus dosimeter was used to measure exposure rates passing through the shields. The efficiency of the shields was evaluated against 99Tcm and 131I. Furthermore, Monte Carlo simulation was used to find the optimum thickness of lead for protection against 131I source. The findings of the dosimetric method show that the minimum and maximum efficiencies obtained by the lead apron with lead equivalent thickness of 0.25 mm and the syringe holder shields with thickness of 0.5 mm lead were 50.86% and 99.50%, respectively. The results of the simulations show that the minimum and maximum efficiencies obtained by lead thicknesses of 1 mm and 43 mm were 19.36% and 99.79%, respectively. The optimum shields against 99Tcm are the syringe holder shield, the tungsten syringe shield, and the lead partition, respectively. Furthermore, based on simulations, the thicknesses of 11-28 mm of lead with efficiencies between 90.6% to 99% are suggested as the optimum thicknesses to protect against 131I source.

Researchers believe that smoking might increase the severity of infections caused by SARS-CoV-2 by altering the viability and integrity of the BBB, while promoting the expression of ACE2 in endothelial cells, glia, and neurons. Moreover, as smoking increases the blood circulatory level of VWF and decreases the levels of thrombomodulin, it can lead to dysregulated blood homeostasis and hence, increased risk of thrombosis which significantly increases the risk of stroke and cardiovascular disorders. However, despite current controversies and remarkable study limitations, a recent systematic review and meta-analysis claims that the findings of 18 recent COVID-19 clinical and epidemiological studies show that smokers were statistically less likely to be hospitalized. The authors state that their observations might be due to the effects of nicotine. We believe that the lower number of hospitalized smokers than expected, if confirmed by further studies, can be due to the higher concentration of deposited energy of alpha particles emitted from radionuclides such as Po-210 in cigarette tobacco. The anti-inflammatory effects of localized radiation energy deposition of alpha particles as well as the effect of low doses of radiation on reducing the risk of thrombosis, are possibly involved in the lower number of hospitalized smokers than expected.

This study aims to make a phantom to verify dose distribution and compare two techniques of radiation therapy, including 3D conventional radiotherapy (3D-CRT) and modulated photon radiotherapy (IMRT). For treatment of brain cancer, physicians have to prescribe radiation therapy to involved patients so that organs at risk receive unwanted dose causing them to be damaged. To know precise dose delivered into them and evaluate treatment-planning system (TPs), it is necessary to do dosimetry in the phantom owing to difficulties of dosimetry in human.It is important to make a phantom with characteristics similar to humans and ability to compute dose and dose distribution in desired organs and tissue. Thus, there is possibility to compute dose in different parts, including doses delivered in ears, eyes, stem brain and optic nerve. Furthermore, this phantom has to provide this opportunity to investigate whether some techniques of radiation therapy such as 3D-CRT or IMRT depend on the size or location of tumors.To this end, a low workload, easy-to-set-up, lightweight, and transportable phantom was designed, and made from Polylactic acid (PLA) in dimensions 23×24×32 cm3. The phantom consists of brain, tumors in different dimeters, including 2, 4, 6 cm and also parts for eyes and ears to locate TLDs. Head, brain and tumors are able to open so that they can be filled with polymer gel dosimetry making possible record dose distribution in three-dimensions (3D) and sharp dose gradients.

Pattern recognition has shown remarkable success in decoding motor information from electromyogram (EMG) signals. To decrease the computational complexity in EMG pattern recognition, it may be useful to reduce the dimensionality of the model input. This paper investigates the effect of reducing the dimensionality of EMG features in a regression-based motion intent estimation model. Ten able-bodied subjects participated in this analytic study. EMG signals from the right forearm and angle of the left wrist in three degrees of freedom (DoF) were measured, concurrently. The TD features were extracted from eight EMG channels, resulting in a total of 32 features. Three dimensionality reduction methods including principal component analysis (PCA), non-negative matrix factorization (NNMF), and canonical correlation analysis (CCA) were applied to the EMG features. Reducing the dimension of the EMG features below a certain threshold degraded the performance of the EMG pattern recognition model. Otherwise, dimensionality reduction did not change the performance. These thresholds for the PCA, NNMF, and CCA methods were 25, 26, and 13, respectively. Based on the results, CCA substantially outperformed PCA and NNMF, as it allowed a significant reduction of the EMG features size, from 32 to 13, with no adverse impact on the performance.