rss_2.0Polish Journal of Medical Physics and Engineering FeedSciendo RSS Feed for Polish Journal of Medical Physics and Engineering Journal of Medical Physics and Engineering 's Cover of the polarity effect of Roos parallel plate ionization chamber in build-up region<abstract> <title style='display:none'>Abstract</title> <p><italic>Purpose:</italic> Despite widespread studying of the polarity effect of Roos parallel plate ion chamber in electron beams as mentioned in several protocols, no investigations have up till now studied this effect in photon beams in the build-up region. It is important to examine its polarity effect in the build-up region for photon beams, so this is the first work that focuses in to evaluate the polarity effect of the Roos chamber in the surface and build-up region and comparing its effect with other chambers.</p> <p><italic>Methods:</italic> In this study, the Roos chamber was irradiated by a Theratron 780E <sup>60</sup>Co beam to a known polarity effect. The Polarity effects of 5×5 up to 35×35 cm<sup>2</sup> field sizes at positive and negative polarizing voltages were measured in the build-up region from surface to 0.7 cm in a solid water phantom.</p> <p><italic>Results:</italic> The polarity ratios (PRs) were obtained at 1.020 ± 0.00 and 1.015 ± 0.00 for field sizes 5 × 5 up to 35 × 35 cm<sup>2</sup>, respectively. For the same fields, the percentage of polarity effects (%PEs) was obtained at 1.99% ± 0.00% and 1.47% ± 0.02%, respectively. The results found that the %PEs decrease with increased field sizes and depths. Moreover, the %PEs exhibited a decrease with an increased percentage surface dose (%SD). The uncertainty of %PE was estimated as 0.01% for all measurements in this study.</p> <p><italic>Conclusions:</italic> As a result, the average %PE of the Roos chamber described here is equal to 0.756% ± 0.013% for all depths and field sizes for the <sup>60</sup>Co γ-ray beam. It has introduced a less percentage of polarity effect than other chambers.</p> </abstract>ARTICLE2022-08-23T00:00:00.000+00:00Automation of slice thickness measurements in computed tomography images of AAPM CT performance phantom using a non-rotational method<abstract> <title style='display:none'>Abstract</title> <p><italic>Purpose:</italic> The current study proposes a method for automatically measuring slice thickness using a non-rotational method on the middle stair object of the AAPM CT performance phantom image.</p> <p><italic>Method:</italic> The AAPM CT performance phantom was scanned by a GE Healthcare 128-slice CT scanner with nominal slice thicknesses of 0.625, 1.25, 2.5, 3.75, 5, 7.5 and 10 mm. The automated slice thickness was measured as the full width at half maximum (FWHM) of the profile of the middle stair object using a non-rotational method. The non-rotational method avoided rotating the image of the phantom. Instead, the lines to make the profiles were automatically rotated to confirm the stair’s location and rotation. The results of this non-rotational method were compared with those from a previous rotational method.</p> <p><italic>Results:</italic> The slice thicknesses from the non-rotational method were 1.55, 1.86, 3.27, 4.86, 6.58, 7.57, and 9.66 mm for nominal slice thicknesses of 0.625, 1.25, 2.4, 3.75, 5, 7.5, and 10 mm, respectively. By comparison, the slice thicknesses from the rotational method were 1.53, 1.87, 3.32, 4.98, 6.77, 7.75, and 9.80 mm, respectively. The results of the nonrotational method were slightly lower (i.e. 0.25%) than the results of the rotational method for each nominal slice thickness, except for the smallest slice thickness.</p> <p><italic>Conclusions:</italic> An alternative algorithm using a non-rotational method to measure the slice thickness of the middle stair object in the AAPM CT performance phantom was successfully implemented. The slice thicknesses from the nonrotational method results were slightly lower than the rotational method results for each nominal slice thickness, except at the smallest nominal slice thickness (0.625 mm).</p> </abstract>ARTICLE2022-08-23T00:00:00.000+00:00Automatic diagnosis of severity of COVID-19 patients using an ensemble of transfer learning models with convolutional neural networks in CT images<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> Quantification of lung involvement in COVID-19 using chest Computed tomography (CT) scan can help physicians to evaluate the progression of the disease or treatment response. This paper presents an automatic deep transfer learning ensemble based on pre-trained convolutional neural networks (CNNs) to determine the severity of COVID -19 as normal, mild, moderate, and severe based on the images of the lungs CT.</p> <p><italic>Material and methods:</italic> In this study, two different deep transfer learning strategies were used. In the first procedure, features were extracted from fifteen pre-trained CNNs architectures and then fed into a support vector machine (SVM) classifier. In the second procedure, the pre-trained CNNs were fine-tuned using the chest CT images, and then features were extracted for the purpose of classification by the softmax layer. Finally, an ensemble method was developed based on majority voting of the deep learning outputs to increase the performance of the recognition on each of the two strategies. A dataset of CT scans was collected and then labeled as normal (314), mild (262), moderate (72), and severe (35) for COVID-19 by the consensus of two highly qualified radiologists.</p> <p><italic>Results:</italic> The ensemble of five deep transfer learning outputs named EfficientNetB3, EfficientNetB4, InceptionV3, NasNetMobile, and ResNext50 in the second strategy has better results than the first strategy and also the individual deep transfer learning models in diagnosing the severity of COVID-19 with 85% accuracy.</p> <p><italic>Conclusions:</italic> Our proposed study is well suited for quantifying lung involvement of COVID-19 and can help physicians to monitor the progression of the disease.</p> </abstract>ARTICLE2022-07-28T00:00:00.000+00:00Application of therapeutic linear accelerators for the production of radioisotopes used in nuclear medicine<abstract> <title style='display:none'>Abstract</title> <p>This review paper summarizes the possibilities of the use of therapeutic linear electron accelerators for the production of radioisotopes for nuclear medicine. This work is based on our published results and the thematically similar papers by other authors, directly related to five medical radioisotopes as <sup>99</sup>Mo/<sup>99m</sup>Tc, <sup>198</sup>Au, <sup>186</sup>Re, <sup>188</sup>Re, <sup>117m</sup>Sn, produced using therapeutic linacs. Our unpublished data relating to the issues discussed have also been used here. In the experiments, two types of radiation were included in the analysis of the radioisotope production process, i.e. the therapeutic twenty-megavolt (20 MV) X-rays generated by Varian linacs and neutron radiation contaminating the therapeutic beam. Thus, the debated radioisotopes are produced in the photonuclear reactions and in the neutron ones. Linear therapeutic accelerators do not allow the production of radioisotopes with high specific activities, but the massive targets can be used instead. Thus, the amount of the produced radioisotopes may be increased. Apart from linear accelerators, more and more often, the production of radioisotopes is carried out in small medical cyclotrons. More such cyclotrons are developed, built, and sold commercially than for scientific research. The radioisotopes produced with the use of therapeutic linacs or cyclotrons can be successfully applied in various laboratory tests and in research.</p> </abstract>ARTICLE2022-07-28T00:00:00.000+00:00Normal tissue objective (NTO) tool in Eclipse treatment planning system for dose distribution optimization<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> The purpose of this study was to determine the best normal tissue objective (NTO) values based on the dose distribution from brain tumor radiation therapy.</p> <p><italic>Material and methods:</italic> The NTO is a constraint provided by Eclipse to limit the dose to normal tissues by steepening the dose gradient. The multitude of NTO setting combinations necessitates optimal NTO settings. The Eclipse supports manual and automatic NTOs. Fifteen patients were re-planned using NTO priorities of 1, 50, 100, 150, 200, and 500 in combination with dose fall-offs of 0.05, 0.1, 0.2, 0.3, 0.5, 1 and 5 mm<sup>-1</sup>. NTO distance to planning target volume (PTV), start dose, and end dose were 1 mm, 105%, and 60%, respectively, for all plans. In addition, planning without the NTO was arranged to find out its effect on planning. The prescription dose covered 95% of the PTV. Planning was evaluated using several indices: conformity index (CI), homogeneity index (HI), gradient index (GI), modified gradient index (mGI), comprehensive quality index (CQI), and monitor unit (MU). Differences among automatic NTO, manual NTO, and without NTO were evaluated using the Wilcoxon signed-rank test.</p> <p><italic>Results:</italic> Comparisons obtained without and with manual NTO were: CI of 0.77 vs. 0.96 (p = 0.002), GI of 4.52 vs. 4.69 (p = 0.233), mGI of 4.93 vs. 3.95 (p = 0.001), HI of 1.10 vs. 1.10 (p = 0.330), and MU/cGy of 3.44 vs. 3.42 (p = 0.460). Planning without NTO produced a poor conformity index. Comparisons of automatic and manual NTOs were: CI of 0.92 vs. 0.96 (p = 0.035), GI of 5.25 vs. 4.69 (p = 0.253), mGI of 4.46 vs. 3.95 (p = 0.001), HI of 1.09 vs. 1.10 (p = 0.004), MU/cGy of 3.31 vs. 3.42 (p = 0.041).</p> <p><italic>Conclusions:</italic> Based on these results, manual NTO with a priority of 100 and dose fall-off 0.5 mm<sup>-1</sup> was optimal, as indicated by the high dose reduction in normal tissue.</p> </abstract>ARTICLE2022-06-21T00:00:00.000+00:00Local diagnostic reference levels and effective doses: single institution levels for interventional cardiology procedures for adult patients<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> The current regulations in Poland in the field of interventional radiology only include diagnostic reference levels (DRL) for five procedures, containing only two for cardiological (hemodynamic) procedures, and only for adults. Given the insufficient number of DRLs, the need to introduce local levels based on the intervention procedures performed was identified. The purpose of this research was the evaluation of radiation doses (DRL, effective dose) received by patients in cardiological interventional procedures.</p> <p><italic>Material and methods:</italic> The DRL level was defined as the 75th percentile of the distribution of dosimetric parameters KAP and K<sub>air,ref</sub> for each type of cardiological procedure. Data include three different X-ray units and 27 interventional cardiologists, derived from February 2019 to June 2019 and from August 2021 to December 2021. In order to estimate the effective dose, the appropriate conversion factors for cardiological procedures were used. The total number of analyzed procedures was 3818.</p> <p><italic>Results:</italic> The proposed local DRL levels were found to be mostly lower than data found in literature and in the current Polish national requirements (60%-70% lower for coronary angiography (CA) and percutaneous coronary angioplasty (PCI) procedures). Median equivalent doses for cardiological procedures were estimated at 2.66 mSv, 6.11 mSv and 7.22 mSv for CA, PCI and combined PCI with CA procedure, respectively.</p> <p><italic>Conclusions:</italic> The proposed local/institutional DRLs seem to be suitable for use and could be utilized by other centers for comparison purposes.</p> </abstract>ARTICLE2022-05-28T00:00:00.000+00:00Evaluation of SRS MapCHECK with StereoPHAN phantom as a new pre-treatment system verification for SBRT plans<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> The aim of this study was to evaluate the new 2-Dimensional diode array SRS MapCHECK (SunNuclear, Melbourne, USA) with dedicated phantom StereoPHAN (SunNuclear, Melbourne, USA) for the pre-treatment verification of the stereotactic body radiotherapy (SBRT).</p> <p><italic>Material and methods:</italic> For the system, the short and mid-long stability, dose linearity with MU, angular dependence, and field size dependence (ratio of relative output factor) were measured. The results of verification for 15 pre-treatment cancer patients (5 brains, 5 lungs, and 5 livers) performed with SRS MapCHECK and EBT3 Gafchromic films were compared. All the SBRT plans were optimized with the Eclipse (v. 15.6, Varian, Palo Alto, USA) treatment planning system (TPS) using the Acuros XB (Varian, Palo Alto, USA) dose calculation algorithm and were delivered to the Varian EDGE® (Varian, Palo Alto, USA) accelerator equipped with a high-definition multileaf collimator. The 6MV flattening-filter-free beam (FFF) was used.</p> <p><italic>Results:</italic> Short and mid-long stability of SRS MapCHECK was very good (0.1%-0.2%), dose linearity with MU and dependence of the response of the detector on field size results were also acceptable (for dose linearity R<sup>2</sup> = 1 and 6% difference between microDiamond and SRS MapCHECK response for the smallest field of 1 × 1 cm<sup>2</sup>). The angular dependence was very good except for the angles close to 90° and 270°. For pre-treatment plan verification, the gamma method was used with the criteria of 3% dose difference and 3 mm distance to agreement (3%/3 mm), and 2%/2 mm, 1%/1 mm, 3%/1 mm, and 2%/1 mm. The highest passing rate for all criteria was observed on the SRS MapCHECK system.</p> <p><italic>Conclusions:</italic> It is concluded that SRS MapCHECK with StereoPHAN has sufficient potential for pre-treatment verification of the SBRT plans, so that verification of stereotactic plans can be significantly accelerated.</p> </abstract>ARTICLE2022-05-28T00:00:00.000+00:00Implementation of the Sievert integral for the calculation of dose distribution around the BEBIG Co-60 high dose rate brachytherapy source<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> In radiotherapy, a computerized treatment planning system (TPS) is used for performing treatment planning to estimate the dose distribution within a patient. To simplify the dose calculation, mathematical algorithms are employed. TG43 formalism is widely used for brachytherapy. Before the implementation of a particular dose calculation algorithm in clinical practice, it is imperative to acknowledge the limitations and uncertainties associated with the algorithm. Regarding this, outputs of the algorithm are compared to measurements or dose calculation approaches using simple source placement geometries. The manual dose calculation method has to be robust, straightforward, and devoid of complexities to reduce the likelihood of committing errors in the dose calculation process. A lot of manual dose calculation approaches have been proposed for Brachytherapy sources, but one needs to ascertain their reliability.</p> <p><italic>Material and methods:</italic> Considering this, the output of an HDRplus treatment planning system dedicated to brachytherapy treatment planning and using the TG43 formalism to calculate the dose distribution around a BEBIG Co-60 source was validated with Sievert integral dose calculation approach. Simple source placement geometries were created with the TPS using the universal applicator, LLA1200-20, selected from the applicator library, and doses at various equidistant points from the applicator calculated with the TPS and the Sievert integral. Various steps to enhance the efficacy of the Sievert integral approach have been outlined.</p> <p><italic>Results:</italic> The doses compared favourably well with deviations ranging from 0.03 – 10.51% (mean of 3.13%), and 0.03 – 5.63% (mean of 2.55%) for angles along the perpendicular bisector of the source, ranging from 0° &lt; θ &lt; 70° and 0° &lt; θ &lt; 48°, respectively.</p> <p><italic>Conclusions:</italic> The Sievert integral breaks down at angles: θ ≥ 60°, and therefore, neglecting large angles, the Sievert integral would be an efficient, effective, and valid tool for quality control of the HDRplus TPS for the Co-60 source.</p> </abstract>ARTICLE2022-05-28T00:00:00.000+00:00Influence of PEG-coated Bismuth Oxide Nanoparticles on ROS Generation by Electron Beam Radiotherapy<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> Nanoparticles (NPs) have been proven to enhance radiotherapy doses as radiosensitizers. The introduction of coating materials such as polyethylene glycol (PEG) to NPs could impact the NPs’ biocompatibility and their effectiveness as radiosensitizers. Optimization of surface coating is a crucial element to ensure the successful application of NPs as a radiosensitizer in radiotherapy. This study aims to investigate the influence of bismuth oxide NPs (BiONPs) coated with PEG on reactive oxygen species (ROS) generation on HeLa cervical cancer cell line.</p> <p><italic>Material and methods:</italic> Different PEG concentrations (0.05, 0.10, 0.15 and 0.20 mM) were used in the synthesis of the NPs. The treated cells were irradiated with 6 and 12 MeV electron beams with a delivered dose of 3 Gy. The reactive oxygen species (ROS) generation was measured immediately after and 3 hours after irradiation.</p> <p><italic>Results:</italic> The intracellular ROS generation was found to be slightly influenced by electron beam energy and independent of the PEG concentrations. Linear increments of ROS percentages over the 3 hours of incubation time were observed.</p> <p><italic>Conclusions:</italic> Finally, the PEG coating might not substantially affect the ROS generated and thus emphasizing the functionalized BiONPs application as the radiosensitizer for electron beam therapy.</p> </abstract>ARTICLE2022-05-06T00:00:00.000+00:00Evaluation and risk factors of volume and dose differences of selected structures in patients with head and neck cancer treated on Helical TomoTherapy by using Deformable Image Registration tool<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> The aim of this study was the evaluation of volume and dose differences in selected structures in patients with head and neck cancer during treatment on Helical TomoTherapy (HT) using a commercially available deformable image registration (DIR) tool. We attempted to identify anatomical and clinical predictive factors for significant volume changes probability.</p> <p><italic>Material and methods:</italic> According to our institutional protocol, we retrospectively evaluated the group of 20 H&amp;N cancer patients treated with HT who received Adaptive Radiotherapy (ART) due to soft tissue alterations spotted on daily MVCT. We compared volumes on initial computed tomography (iCT) and replanning computed tomography (rCT) for clinical target volumes (CTV) – CTV1 (the primary tumor) and CTV2 (metastatic lymph nodes), parotid glands (PG) and body contour (B-body). To estimate the planned and delivered dose discrepancy, the dose from the original plan was registered and deformed to create a simulation of dose distribution on rCT (DIR-rCT).</p> <p><italic>Results:</italic> The decision to replan was made at the 4th week of RT (N = 6; 30%). The average volume reduction in parotid right PG[R] and left PG[L] was 4.37 cc (18.9%) (p &lt; 0.001) and 3.77 cc (16.8%) (p = 0.004), respectively. In N = 13/20 cases, the delivered dose was greater than the planned dose for PG[R] of mean 3 Gy (p &lt; 0.001), and in N = 6/20 patients for PG[L] the mean of 3.6 Gy (p = 0.031). Multivariate regression analysis showed a very strong predictor explaining 88% (R<sup>2</sup> = 0.88) and 83% (R<sup>2</sup> = 0.83) of the variance based on the mean dose of iPG[R] and iPG[L] (p &lt; 0.001), respectively. No statistically significant correlation between volume changes and risk factors was found.</p> <p><italic>Conclusions:</italic> Dosimetric changes to the target demonstrated the validity of replanning. A DIR tool can be successfully used for dose deformation and ART qualification, significantly reducing the workload of radiotherapy centers. In addition, the mean dose for PG was a significant predictor that may indicate the need for a replan.</p> </abstract>ARTICLE2022-05-06T00:00:00.000+00:00Effective atomic number and photon buildup factor of bismuth doped tissue for photon and particles beam interaction<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> The doping of high Z nanoparticles into the tumor tissue increases the therapeutic efficiency of radiotherapy called nanoparticle enhanced radiotherapy (NERT). In the present study, we are identifying the effective types of radiation and effective doping concentration of bismuth radiosensitizer for NERT application by analyzing effective atomic number (Zeff) and photon buildup factor (PBF) of bismuth (Bi) doped soft tissue for the photon, electron, proton, alpha particle, and carbon ion interactions.</p> <p><italic>Material and methods:</italic> The direct method was used for the calculation of Zeff for photon and electron beams (10 keV-30 MeV). The phy-X/ZeXTRa software was utilized for the particle beams such as proton, alpha particle, and carbon ions (1-15 MeV). Bismuth doping concentrations of 5, 10, 15, 20, 25 and 30 mg/g were considered. The PBF was calculated over 15 keV-15 MeV energies using phy-X/PSD software.</p> <p><italic>Results:</italic> The low energy photon (&lt;100 keV) interaction with a higher concentration of Bi dopped tissue gives the higher values of Zeff. The Zeff increased with the doping concentration of bismuth for all types of radiation. The Zeff was dependent on the type of radiation, the energy of radiation, and the concentration of Bi doping. The particle beams such as electron, proton, alpha particle, and carbon ion interaction gives the less values of Zeff has compared to photon beam interaction. On the other hand, the photon buildup factor values were decreased while increasing the Bi doping concentration.</p> <p><italic>Conclusions:</italic> According to Zeff and PBF, the low energy photon and higher concentration of radiosensitizer are the most effective for nanoparticle enhanced radiotherapy application. Based on the calculated values of Zeff, the particle beams such as electron, proton, alpha particle, and carbon ions were less effective for NERT application. The presented values of Zeff and PBF are useful for the radiation dosimetry in NERT.</p> </abstract>ARTICLE2022-03-29T00:00:00.000+00:00Neutron conversion coefficients of ambient dose equivalent and personal dose equivalent<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> This work aims to calculate the ambient and personal dose equivalent conversion coefficients.</p> <p><italic>Material and methods:</italic> The conversion coefficients have been calculated using MC simulation. Additionally, this paper proposes a new method that depends on an analytical approach.</p> <p><italic>Results:</italic> The obtained results in good agreement between MC and an analytical approach were observed. The obtained results were compared to those published in ICRU 57 report.</p> <p><italic>Conclusions:</italic> We deduced that the analytical approach is as effective and suitable as the MC simulation to calculate the operational quantity conversion coefficients.</p> </abstract>ARTICLE2022-03-29T00:00:00.000+00:00Comparison of organs at risk doses between deep inspiration breath-hold and free-breathing techniques during radiotherapy of left-sided breast cancer: A Meta-Analysis<abstract> <title style='display:none'>Abstract</title> <p>After radiotherapy (RT) of left-sided breast cancer patients, organs at risk (OARs) such as heart, left anterior descending (LAD) coronary artery, and left lung could be affected by radiation dose in the long term. The objective of this study was to perform a comprehensive meta-analysis and determine OARs dose reduction during left-sided breast cancer treatment using different RT modalities combined with deep inspiration breath-hold (DIBH) relative to free-breathing (FB). PubMed, Scopus, EMBASE, ProQuest, Google Scholar, and Cochrane Library electronic databases were used to search for studies until June 6, 2021. Nineteen eligible studies were selected and analyzed using the RevMan 5.3 statistical software package. The pooled weighted mean difference (MD) with their 95% confidence intervals for each of the three OAR mean doses were determined using a random-effects meta-analysis model to assess the dose reductions. From a total of 189 studies, 1 prospective study, 15 retrospective studies, and 3 randomized control trials (RCTs) with an overall of 634 patients were included. Reduction of doses to the heart (weighted MD = -1.79 Gy; 95% CI (-2.28, -1.30); P = 0.00001), LAD (weighted MD = -8.34 Gy; 95% CI (-11.06, -5.61); P = 0.00001), and left-lung (weighted MD = -0.90 Gy; 95% CI (-1.19, -0.61); P = 0.00001) were observed using DIBH combinations relative to FB combination. This study emphasizes that during the treatment of left-sided breast/chest wall (CW) ± supraclavicular (SCV) ± infraclavicular (ICV) ± internal mammary chain (IMC) lymph nodes (LN) ± axillary (Ax)/ cancer patients, different RT modalities combined with DIBH techniques are better options to reduce dose to OARs compared to FB, which benefits to minimize the long-term complications.</p> </abstract>ARTICLE2022-03-29T00:00:00.000+00:00Risk Factors Associated with In-Hospital Mortality in Iranian Patients with COVID-19: Application of Machine Learning<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> Predicting the mortality risk of COVID-19 patients based on patient’s physiological conditions and demographic characteristics can help optimize resource consumption along with the provision of effective medical services for patients. In the current study, we aimed to develop several machine learning models to forecast the mortality risk in COVID-19 patients, evaluate their performance, and select the model with the highest predictive power.</p> <p><italic>Material and methods:</italic> We conducted a retrospective analysis of the records belonging to COVID-19 patients admitted to one of the main hospitals of Qazvin located in the northwest of Iran over 12 months period. We selected 29 variables for developing machine learning models incorporating demographic factors, physical symptoms, comorbidities, and laboratory test results. The outcome variable was mortality as a binary variable. Logistic regression analysis was conducted to identify risk factors of in-hospital death.</p> <p><italic>Results:</italic> In prediction of mortality, Ensemble demonstrated the maximum values of accuracy (0.8071, 95%CI: 0.7787, 0.8356), F1-score (0.8121 95%CI: 0.7900, 0.8341), and AUROC (0.8079, 95%CI: 0.7800, 0.8358). Including fourteen top-scored features identified by maximum relevance minimum redundancy algorithm into the subset of predictors of ensemble classifier such as BUN level, shortness of breath, seizure, disease history, fever, gender, body pain, WBC, diarrhea, sore throat, blood oxygen level, muscular pain, lack of taste and history of drug (medication) use are sufficient for this classifier to reach to its best predictive power for prediction of mortality risk of COVID-19 patients.</p> <p><italic>Conclusions:</italic> Study findings revealed that old age, lower oxygen saturation level, underlying medical conditions, shortness of breath, seizure, fever, sore throat, and body pain, besides serum BUN, WBC, and CRP levels, were significantly associated with increased mortality risk of COVID-19 patients. Machine learning algorithms can help healthcare systems by predicting and reduction of the mortality risk of COVID-19 patients.</p> </abstract>ARTICLE2022-03-29T00:00:00.000+00:00Dosimetric verification of multi-tumor target cases treated with SRS HyperArc technique using EBT3 radiochromic films<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> Dosimetric verification of Intensity Modulation Radiotherapy treatment plans is usually carried out before the start of treatment. It is of special importance in the case of highly modulated plans, such as plans for patients in whom many tumors are irradiated simultaneously. In this work, we present the results of the verification of multi-target plans performed with the stereotactic HyperArc technique.</p> <p><italic>Material and methods:</italic> The results of dosimetric verification of 35 patient plans in the head are presented. The results are analyzed in terms of the number of tumors, and the distance of the tumor from the isocenter. Measurements were carried out with the film method. The gamma methodology was used (3%/2mm).</p> <p><italic>Results:</italic> The results showed a very good agreement between measurements and calculations.</p> <p><italic>Conclusions:</italic> No dependence of the verification result on the number of targets and the distance between the center of tumor and isocenter was found.</p> </abstract>ARTICLE2022-03-29T00:00:00.000+00:00Effects of Bismuth Oxide Nanoparticles, Cisplatin and Baicalein-rich Fraction on ROS Generation in Proton Beam irradiated Human Colon Carcinoma Cells<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> Proton beam radiotherapy is an advanced cancer treatment technique, which would reduce the effects of radiation on the surrounding healthy cells. The usage of radiosensitizers in this technique might further elevate the radiation dose towards the cancer cells.</p> <p><italic>Material and methods:</italic> The present study investigated the production of intracellular reactive oxygen species (ROS) due to the presence of individual radiosensitizers, such as bismuth oxide nanoparticles (BiONPs), cisplatin (Cis) or baicalein-rich fraction (BRF) from <italic>Oroxylum indicum</italic> plant, as well as their combinations, such as BiONPs-Cis (BC), BiONPs-BRF (BB), or BiONPs-Cis-BRF (BCB), on HCT-116 colon cancer cells under proton beam radiotherapy.</p> <p><italic>Results:</italic> It was found that the ROS in the presence of Cis at 3 Gy of radiation dose was the highest, followed by BC, BiONPs, BB, BRF, and BCB treatments. The properties of bismuth as a radical scavenger, as well as the BRF as a natural compound, might contribute to the lower intracellular ROS induction. The ROS in the presence of Cis and BC combination were also time-dependent and radiation dose-dependent.</p> <p><italic>Conclusions:</italic> As the prospective alternatives to the Cis, the BC combination and individual BiONPs showed the capacities to be developed as radiosensitizers for proton beam therapy.</p> </abstract>ARTICLE2022-03-29T00:00:00.000+00:00Empirical method for modeling the percent depth dose curves of electron beam in radiation therapy<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> This study presents an empirical method to model the electron beam percent depth dose curve (PDD) using the primary and tail functions in radiation therapy. The modeling parameters N and n can be used to derive the depth relative stopping power of the electron energy in radiation therapy.</p> <p><italic>Methods and Materials:</italic> The electrons PDD curves were modeled with the primary-tail function in this study. The primary function included exponential function and main parameters of N, µ while the tail function was composed by a sigmoid function with the main parameter of n. The PDD for five electron energies were modeled by the primary and tail function by adjusting the parameters of N, µ and n. The R<sub>50</sub> and R<sub>p</sub> can be derived from the modeled straight line of 80% to 20% region of PDD. The same electron energy with different cone sizes was also modeled with the primary-tail function. The stopping power for different electron energies at different depths can also be derived from the parameters of N, µ and n. Percent ionization depth curve can then be derived from the percent depth dose by dividing its depth relevant stopping power for comparing with the original water phantom measurement.</p> <p><italic>Results:</italic> The main parameters N, n increase, but µ decreases in primary-tail function when electron energy increased. The relationship of parameters n, N and LN(-µ) with electron energy are n = 31.667 E<sub>0</sub> - 88, N = 0.9975 E<sub>0</sub> - 2.8535, LN(-µ) = -0.1355 E<sub>0</sub> - 6.0986, respectively. Stopping power of different electron energy can be derived from n and N with the equation: stopping power = (−0.042 ln N<sub><italic>E</italic><sub>0</sub></sub> + 1.072)e<sup>(−n−<sub>E0</sub>·5·10<sup>−5</sup>+0.0381·d)</sup>, where d is the depth in water. Percent depth dose was derived from the percent reading curve by multiplying the stopping power relevant to the depth in water at certain electron energy.</p> <p><italic>Conclusion:</italic> The PDD of electrons at different energies and field sizes can be modeled with an empirical model to deal with the stopping power calculation. The primary-tail equation provides a uncomplicated solution than a pencil beam or other numerical algorism for investigators to research the behavior of electron beam in radiation therapy.</p> </abstract>ARTICLE2021-12-23T00:00:00.000+00:00Using of Laplacian Re-decomposition image fusion algorithm for glioma grading with SWI, ADC, and FLAIR images<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> Based on the tumor’s growth potential and aggressiveness, glioma is most often classified into low or high-grade groups. Traditionally, tissue sampling is used to determine the glioma grade. The aim of this study is to evaluate the efficiency of the Laplacian Re-decomposition (LRD) medical image fusion algorithm for glioma grading by advanced magnetic resonance imaging (MRI) images and introduce the best image combination for glioma grading.</p> <p><italic>Material and methods:</italic> Sixty-one patients (17 low-grade and 44 high-grade) underwent Susceptibility-weighted image (SWI), apparent diffusion coefficient (ADC) map, and Fluid attenuated inversion recovery (FLAIR) MRI imaging. To fuse different MRI image, LRD medical image fusion algorithm was used. To evaluate the effectiveness of LRD in the classification of glioma grade, we compared the parameters of the receiver operating characteristic curve (ROC).</p> <p><italic>Results:</italic> The average Relative Signal Contrast (RSC) of SWI and ADC maps in high-grade glioma are significantly lower than RSCs in low-grade glioma. No significant difference was detected between low and high-grade glioma on FLAIR images. In our study, the area under the curve (AUC) for low and high-grade glioma differentiation on SWI and ADC maps were calculated at 0.871 and 0.833, respectively.</p> <p><italic>Conclusions:</italic> By fusing SWI and ADC map with LRD medical image fusion algorithm, we can increase AUC for low and high-grade glioma separation to 0.978. Our work has led us to conclude that, by fusing SWI and ADC map with LRD medical image fusion algorithm, we reach the highest diagnostic accuracy for low and high-grade glioma differentiation and we can use LRD medical fusion algorithm for glioma grading.</p> </abstract>ARTICLE2021-12-23T00:00:00.000+00:00A comprehensive Monte Carlo study to design a novel multi-nanoparticle loaded nanocomposites for augmentation of attenuation coefficient in the energy range of diagnostic X-rays<abstract> <title style='display:none'>Abstract</title> <p><italic>Introduction:</italic> The present study aimed to investigate the radiation protection properties of silicon-based composites doped with nano-sized Bi<sub>2</sub>O<sub>3</sub>, PbO, Sm<sub>2</sub>O<sub>3</sub>, Gd<sub>2</sub>O<sub>3</sub>, WO<sub>3,</sub> and IrO<sub>2</sub> particles. Radiation shielding properties of Sm<sub>2</sub>O<sub>3</sub> and IrO<sub>2</sub> nanoparticles were investigated for the first time in the current study.</p> <p><italic>Material and methods:</italic> The MCNPX (2.7.0) Monte Carlo code was utilized to calculate the linear attenuation coefficients of single and multi-nano structured composites over the X-ray energy range of 10–140 keV. Homogenous distribution of spherical nanoparticles with a diameter of 100 nm in a silicon rubber matrix was simulated. The narrow beam geometry was used to calculate the photon flux after attenuation by designed nanocomposites.</p> <p><italic>Results:</italic> Based on results obtained for single nanoparticle composites, three combinations of different nano-sized fillers Sm<sub>2</sub>O<sub>3</sub>+WO<sub>3</sub>+Bi<sub>2</sub>O<sub>3,</sub> Gd<sub>2</sub>O<sub>3</sub>+WO<sub>3</sub>+Bi<sub>2</sub>O<sub>3</sub>, and Sm<sub>2</sub>O<sub>3</sub>+WO<sub>3</sub>+PbO were selected, and their shielding properties were estimated. In the energy range of 20-60 keV Sm<sub>2</sub>O<sub>3</sub> and Gd<sub>2</sub>O<sub>3</sub> nanoparticles, in 70-100 keV energy range WO<sub>3</sub> and for photons energy higher than 90 keV, PbO and Bi<sub>2</sub>O<sub>3</sub> nanoparticles showed higher attenuation. Despite its higher density, IrO<sub>2</sub> had lower attenuation compared to other nanocomposites. The results showed that the nanocomposite containing Sm<sub>2</sub>O<sub>3,</sub> WO<sub>3</sub>, and Bi<sub>2</sub>O<sub>3</sub> nanoparticles provided better shielding among the studied samples.</p> <p><italic>Conclusions:</italic> All studied multi-nanoparticle nanocomposites provided optimum shielding properties and almost 8% higher attenuation relative to single nano-based composites over a wide range of photon energy used in diagnostic radiology. Application of these new composites is recommended in radiation protection. Further experimental studies are suggested to validate our findings.</p> </abstract>ARTICLE2021-12-23T00:00:00.000+00:00Pulmonary tuberculosis diagnosis, differentiation and disease management: A review of radiomics applications<abstract> <title style='display:none'>Abstract</title> <p>Pulmonary tuberculosis is a worldwide epidemic that can only be fought effectively with early and accurate diagnosis and proper disease management. The means of diagnosis and disease management should be easily accessible, cost effective and be readily available in the high tuberculosis burdened countries where it is most needed. Fortunately, the fast development of computer science in recent years has ensured that medical images can accurately be quantified. Radiomics is one such tool that can be used to quantify medical images. This review article focuses on the literature currently available on the application of radiomics explicitly for the purpose of diagnosis, differentiation from other pulmonary diseases and disease management of pulmonary tuberculosis. Despite using a formal search strategy, only five articles could be found on the application of radiomics to pulmonary tuberculosis. In all five articles reviewed, radiomic feature extraction was successfully used to quantify digital medical images for the purpose of comparing, or differentiating, pulmonary tuberculosis from other pulmonary diseases. This demonstrates that the use of radiomics for the purpose of tuberculosis disease management and diagnosis remains a valuable data mining opportunity not yet realised.</p> </abstract>ARTICLE2021-12-23T00:00:00.000+00:00en-us-1