Aim: We aimed to evaluate the dosimetric influence of Acuros XB (AXB) dose-to-medium (D_m) and dose-to-water (D_w) reporting mode on carcinoma cervix using intensity-modulated radiation therapy (IMRT) and RapidArc (RA) technique. Materials and Methods: A cohort of thirty patients cared for carcinoma cervix was retrospectively selected for the study. Plans were computed using analytical anisotropic algorithm (AAA), AXB-D_m, and AXB-D_w algorithms for dosimetric comparison. A paired t-test and Pitman–Morgan dispersion test were executed to appraise the difference in mean values and the inter-patient variability of the differences. Results: The dose–volume parameters were higher for AXB-D_w in contrast to AAA for IMRT and RA plans, excluding D_98%, minimum dose to planning target volume (PTV) and rectum mean dose (RA). There was no systematic trend observed in dose–volume parameters for PTV and organs at risk (OARs) between AXB-D_m and AXB-D_w for IMRT and RA plans. The dose–volume parameters for target were higher for AXB-D_m in comparison to AAA in IMRT and RA plans, except D_98% and minimum dose to PTV. Analysis envisaged less inter-patient variability while switching from AAA to AXB-D_m in comparison to those switching from AAA to AXB-D_w. Conclusions: The present study reveals the important difference between AAA, AXB-D_m, and AXB-D_w computations for cervix carcinoma using IMRT and RA techniques. The inter-patient variability and systematic difference in dose–volume parameters computed using AAA, AXB-D_m, and AXB-D_w algorithms present the possible impact on the dose prescription to PTV and their relative constraints to OARs for IMRT and RA techniques. This may help in the decision-making in clinic while switching from AAA to AXB (D_m or D_w) algorithm for cervix carcinoma using IMRT and RA techniques.

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Purpose: In the field of medical diagnosis, deep learning-based computer-aided detection of diseases will reduce the burden of physicians in the diagnosis of diseases especially in the case of lung cancer nodule classification. Materials and Methods: A hybridized model which integrates deep features from Residual Neural Network using transfer learning and handcrafted features from the histogram of oriented gradients feature descriptor is proposed to classify the lung nodules as benign or malignant. The intrinsic convolutional neural network (CNN) features have been incorporated and they can resolve the drawbacks of handcrafted features that do not completely reflect the specific characteristics of a nodule. In the meantime, they also reduce the need for a large-scale annotated dataset for CNNs. For classifying malignant nodules and benign nodules, radial basis function support vector machine is used. The proposed hybridized model is evaluated on the LIDC-IDRI dataset. Results: It has achieved an accuracy of 97.53%, sensitivity of 98.62%, specificity of 96.88%, precision of 95.04%, F₁ score of 0.9679, false-positive rate of 3.117%, and false-negative rate of 1.38% and has been compared with other state of the art techniques. Conclusions: The performance of the proposed hybridized feature-based classification technique is better than the deep features-based classification technique in lung nodule classification.

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Context: Interplay effects have become the significant problem in lung cancer radiotherapy. Since these effects yield dose variation within the target and surrounding tissues. Aim: The aim of this study is to investigate the effect of the dosimetric parameters of interplay effects in 6 MV flattening filter-free (FFF) photon beams for lung cancer. Settings and Design: This study performed planning, measurement, and data analysis sections for examining different breathing amplitudes and phases, doses, dose rates, field sizes, and fractionations. Subjects and Methods: Standard and clinical plans were created on the eclipse treatment planning system. The static and dynamic measurements were performed using a robotic platform and two-dimensional (2D) diode array. The gamma passing rates were defined as the percent of dose variation caused by the interplay effects. Statistical Analysis Used: Unpaired t-test. Results: The outcomes showed three trends between gamma passing rates (γ) and dosimetric parameters. First, a decreasing trend was breathing amplitudes. The lowest γ of maximum amplitudes (2 cm) in both one dimensional and 2D were <25%. Second, an increasing trend was field sizes. The lowest γ of minimum field size (4 cm × 4 cm²) was <55%. Third, constant outcomes were breathing phases, doses, dose rates, and a number of fractions. The γ values of these factors were 53.1%, 55.1%, 34.7%, and 36.7%, respectively. Conclusions: Lung tumor motion-induced interplay effects in 6 MV FFF photon beams are more pronounced for higher breathing amplitudes and smaller field sizes.

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Aim: The embryo/fetus may be accidentally exposed to ionizing radiation. The aim of this study is to calculate embryo/fetus doses in pregnant women who underwent F-18 fludeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) scan. Materials and Methods: Between June 2015 and June 2021, 15 pregnant women underwent F-18 FDG PET/CT applied to the Genetic Research Center (GETAM). The OLINDA/EXM package program was used for internal radiation dosimetry according to the Medical Internal Radiation Dose scheme. FetDose V4 computer software was used to compute the embryo/fetus absorbed dose from CT scan. Results: The amount of the injected F-18 FDG activity to patients varied between 333 and 555 MBq. The mean embryo/fetal dose from F-18 FDG was 7.2 ± 2.8 mGy. In addition, the CT component dose to the embryo/fetus dose ranged from 8.5 to 16 mGy with a mean of 12.14 ± 2.05. Conclusions: The embryo/fetus dose from F-18 FDG PET/CT was <15 mGy, however, questioning the women's childbearing prior to scintigraphy is the first-line strategy to avoid accidental radiation exposure and stochastic risks.

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Purpose: Calculation of photon attenuation is necessary for the selection of shielding materials for an irradiation facility. Methods and Materials: In this work, a Monte Carlo simulation was utilized to assess the effectiveness of clay-polyethylene mixture and clay as the radiation shielding materials for high-energy gamma sources (Ir-192). Ordinary concrete was also studied as the benchmark. Results: The calculated linear attenuation values for ordinary concrete are within 0.44% of the standard XCOM value for 380 keV photon. In the case of a multienergy Ir-192 gamma source, the calculated linear attenuation coefficient (μ) for ordinary concrete is 15.5% and 7.25% higher than clay and fabricated clay-polyethylene, respectively. Meanwhile, the μ value for fabricated clay-polyethylene is 8.3% higher than that of clay. Conclusion: In conclusion, a 10 cm thickness of clay and clay-polyethylene mixture is sufficient to attenuate 87% and 89% of photons from Ir-192 source. The calculated linear attenuation coefficients for the three shielding materials are also consistently higher, about 7.5%, than that of the XCOM value for 380 keV photon.

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Purpose: This study aimed to evaluate the shielding integrity of a typical radiotherapy facility using the Monte Carlo (MC) method. Materials and Methods: EGSnrc MC code was used to design a radiotherapy bunker with appropriate materials and thicknesses. A concrete density of 2.36 g/cm³ was used as a shielding material for primary and secondary barriers. The lead slab was used in the entrance door. The complex geometries of the bunker were modeled by using the egs++ application code embedded in the software. Phase-space generated from a linac machine built with BEAMnrc codes was used as a source of 18 MV X-ray beam set at 100 cm source–surface distance with a field size of 40 cm × 40 cm. Energy deposited in each geometrical region was evaluated and analyzed. Results: Energy deposited at the entrance door, supervised and controlled areas were found to be approximately 0%. No significant difference in the energy deposition on the geometries was observed when the gantry angles were set at either 90° or 270° (P = 1). Conclusion: The findings in this study revealed that the EGSnrc MC code can be used as a veritable tool in the design and evaluation of structural shielding efficiency in a radiotherapy facility.

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Purpose: To fully exploit the benefits of magnetic resonance imaging (MRI) for radiotherapy, it is desirable to develop segmentation methods to delineate patients' MRI images fast and accurately. The purpose of this work is to develop a semi-automatic method to segment organs and tumor within the brain on standard T1- and T2-weighted MRI images. Methods and Materials: Twelve brain cancer patients were retrospectively included in this study, and a simple rigid registration was used to align all the images to the same spatial coordinates. Regions of interest were created for organs and tumor segmentations. The K-nearest neighbor (KNN) classification algorithm was used to characterize the knowledge of previous segmentations using 15 image features (T1 and T2 image intensity, 4 Gabor filtered images, 6 image gradients, and 3 Cartesian coordinates), and the trained models were used to predict organ and tumor contours. Dice similarity coefficient (DSC), normalized surface dice, sensitivity, specificity, and Hausdorff distance were used to evaluate the performance of segmentations. Results: Our semi-automatic segmentations matched with the ground truths closely. The mean DSC value was between 0.49 (optical chiasm) and 0.89 (right eye) for organ segmentations and was 0.87 for tumor segmentation. Overall performance of our method is comparable or superior to the previous work, and the accuracy of our semi-automatic segmentation is generally better for large volume objects. Conclusion: The proposed KNN method can accurately segment organs and tumor using standard brain MRI images, provides fast and accurate image processing and planning tools, and paves the way for clinical implementation of MRI-guided radiotherapy and adaptive radiotherapy.

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Radiofrequency (RF) field (B1) mapping by combining the double-angle method (DAM) and T1 correction was investigated. The signal intensities S1 and S2 acquired by flip angle (FA) α and double FA 2α at short repetition time (TR) were converted to a signal intensity at TR=∞ by T1 correction. Then, these were used for DAM calculation. The T1 values are measured from two different images acquired with different TRs based on the saturation recovery (SR) method preliminarily. The effects of imaging parameters for T1 estimation and measured FA were investigated using CuSO₄-doped water phantoms. A two-dimensional gradient echo type echo planar imaging pulse sequence was used. T1 values obtained by the 2-SR method were underestimated compared to the multipoint inversion recovery method. FA error was less than 5% when the appropriate imaging parameters were used. The acquisition time could be shortened to under 25 s by the use of T1-corrected DAM.

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Background: The photon dose calculation model anisotropic analytical algorithm (AAA) available with eclipse integrated treatment planning system (TPS) (Varian) supports telecobalt dose calculation from Version 13.6 onward. Formerly, pencil beam convolution (PBC) was used for modeling telecobalt machines. Eclipse TPS no longer supports PBC dose calculation algorithm in v13.6 and above. The AAA dose calculation model is a three-dimensional PBC/superposition algorithm. Its configuration is based on Monte-Carlo-determined basic physical parameters that are tailored to measured clinical beam data. Aim: The study investigated the feasibility of clinical implementation of AAA in Eclipse TPS for Bhabhatron II. Materials and Methods: The indigenous telecobalt machine, Bhabhatron II, was configured as a generic machine because an inbuilt machine model for the same was not available in Varian Eclipse TPS algorithm library. In such a scenario, it was necessary to evaluate and validate dosimetric parameters of the TPS because improper tailoring would cause errors in dose calculations. Beam data measurements of the machine were carried out which were used for configuration of the algorithm. Result: After successful configuration, a variety of plans created in TPS were executed on the machine and subsequently evaluated. Conclusion: From this study, we concluded that AAA-based dose calculation in TPS is very well suited for accurate dose calculations for telecobalt machine and can be implemented for clinical use.

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Purpose: To evaluate the image quality of semi-anatomical chest radiographs acquired using low radiation doses from seven different flat-panel detector (FPD) systems. Materials and Methods: Radiographs of a semi-anatomical chest phantom were acquired at 70 and 110 kVp using 7 different FPDs from 5 vendors. Radiation doses were measured using a dose-area-product (DAP) meter. To standardize measurements across all FPDs, DAP value of 51.05 μGym² obtained at 70 kVp and 9.43 μGym² at 110 kVp was used as reference in this study. Radiation doses were reduced by manually adjusting mAs for both tube potentials in all FPD systems to achieve acceptable image quality. Contrast-to-noise ratio, signal-to-noise ratio and figure of merit (FOM) in lung, heart, and diaphragm for all images were analyzed. Results: In comparison with set standard protocol, radiation dose reduction of 20%, 21%, 21.6%, 59.5%, 60.7%, 62.2%, and 67.6% with optimal image quality was observed in Prognosys Prorad, GE Definium 8000, Siemens Fusion, Fujifilm FGX, Fujifilm FGXR, Philips Digital Diagnost and Siemens Aristos at 70 kVp. At 110 kVp, dose reduction of 15.7% and 34.8% was possible only for Philips Digital Diagnost and Siemens Aristos. FOM was high at 110 kVp even when radiation doses were reduced by a factor 2 when compared to 70 kVp in all digital radiography systems. Conclusion: This study demonstrates the feasibility of using a semi-anatomical chest phantom in the optimization of radiation dose and image quality. The FOM was a good indicator in assessing image quality between different detectors.

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Context: Automated detection of COVID-19 in real time can greatly help clinicians to handle increasing number of cases for preliminary screening. Deep CNN models trained with sufficiently large datasets may become best candidates to meet the purpose. Aims: This study aims for automated detection and classification of COVID-19 and viral pneumonia diseases by applying deep CNN model using chest X-ray images. The proposed model performs multiclass classification to meet the purpose. Settings and Design: The proposed model is built on top of VGG16 architecture with pretrained ImageNet weights. The model was fine-tuned using additional custom layers to deliver better performance specific to the target. Subjects and Methods: A total of 15,153 samples are used in this work. These samples include chest X-ray images of COVID-19, viral pneumonia, and normal cases. The entire dataset was split into train and test sets, with a ratio of 80:20 before training the model. To enhance important image features, image preprocessing and augmentation were applied before feeding the image batches to the model. Statistical Analysis Used: Performance of the model is evaluated through accuracy, precision, recall, and F1 score performance metrics. The results produced by the model are also compared with other recent leading studies. Results: The proposed model has achieved a classification accuracy of 98% with 98% precision, 96% recall, and 97% F1 score on the test dataset for multiclass classification. The area under receiver operating characteristic curve score was 0.99 for all three cases of multiclass classification. Conclusions: The proposed classification model may be highly useful for the preliminary diagnosis of COVID-19 and viral pneumonia cases, especially during heavy workloads and large quantities.

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Background: The experimental determination of relative output factors presents the greatest challenge, especially for small fields with different detectors. The aim of this study is to evaluate the influence of jaw positions on small-field output factors for the fields defined by micro-multileaf collimator and circular cones with different detectors. Materials and Methods: The stereotactic output factors were measured on Primus linear accelerator with BrainLab micro-multileaf collimator (mMLC) and circular cones as add-on tertiary collimators. Square field sizes ranging from 0.6 cm × 0.6 cm to 9.8 cm × 9.8 cm and circular fields of diameter ranging from 1.0 cm to 4.0 cm were defined by mMLC and circular cones, respectively. The influence of jaw position on output factor was assessed for different geometric configurations with three different detectors. Results: The values obtained with PinPoint ion chamber were consistent with microDiamond detector for fields greater than 24 mm × 24 mm, but an underestimation of 23.9% was noticed in 6 mm x 6 mm field size. For the mMLC defined field size of 6 mm × 6 mm, when the X-Y jaw was moved from 8 mm × 8 mm to 80 mm × 80 mm, an increase in the output by a factor of 1.7 was observed with both microDiamond and stereotactic radiosurgery diode, whereas an increase in output by a factor of 1.9 was noticed with PinPoint ion chamber. Conclusion: Output factors obtained with different detectors show high differences in the smallest field size for all collimating systems. This study confirms that the position of X and Y jaw above the tertiary collimator significantly influences the small-field output factor.

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To provide accurate and fast 3-D dose verification for hypofractionated stereotactic radiotherapy (SRT/SBRT) of small and multi targets calculated with a Varian Eclipse treatment planning system (TPS) delivered on a Varian accelerator. Ten brain and lung hypofractionated SRT/SBRT linac-based and CyberKnife plans were generated by the Eclipse system for delivery on the accelerator with the Millenium-120 leaf multileaf collimator (MLC) and Multiplan for the CyberKnife machine. These clinical SRT/SBRT plans required accurate quality assurance measurements to obtain absolute point dose and 3-D dose distributions due to the low number of fractions and high fraction doses. For small-field and multi-target plans, the EGS4/MCSIM code was used to calculate the dose distribution. A 0.125 cc ion chamber, a 0.016 cc pin-point chamber and Kodak EDR2 film were used for the measurements and the results were compared with Monte Carlo (MC) calculations. The dosimetry for small-field and multi-target treatment plans is challenging due to the comparable range of secondary electrons and the field sizes defined by SRT/SBRT MLC segments. Our MC simulations can accurately reproduce the linac dose distributions (within 1%/1 mm) three dimensionally. For the clinical SRT/SBRT plans investigated in this work, the MC doses agreed within 3% with ion chamber measurements and within 2%/2 mm with film measurements. The doses calculated by the Eclipse AAA algorithm and Multiplan differed by no more than 5% from MC calculations for small (4–40 cc) Planning Target Volumes (PTVs). MC dose calculation provides accurate and fast 3-D dose verification for hypofractionated SRT for small and multi-target treatment plans generated by a Varian Eclipse TPS on a Varian accelerator and Multiplan treatment planning on the CyberKnife System.

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Aim: The aim of this article is to assess Tamil Nadu adult diagnostic reference levels (DRLs) by collecting radiation dose data from the four different dental modalities. Materials and Methods: The study was carried out using routine adult exposure settings in 131 intraoral, 75 panoramic, 35 cephalometric, and 10 dental cone beam computed tomography (CBCT) X-ray devices. DRLs were assessed for intraoral and extraoral (panoramic, cephalometric, and CBCT) examinations in terms of incident air kerma (K_{a, i}) and kerma area product (P_KA), respectively. Air kerma measurements, for all dental units, were made using calibrated RTI black Piranha 557 dosimeter (RTI Electronics AB, Sweden). The dosimeter was kept at the exit cone of the X-ray tube and on the detector side of the X-ray unit for intraoral and extraoral air kerma measurements, respectively. The obtained air kerma in extraoral modalities is multiplied with the beam area to evaluate P_KA. Results: The third quartile values calculated from the median for adult intraoral (mandibular molar), panoramic, cephalometric, and CBCT were 1.5 mGy, 116 mGycm², 40 mGycm², and 532 mGycm², respectively. The proposed DRL in the present study was comparable to those reported in Germany, Greece, the UK, Japan, and Korea. Conclusion: This study revealed the need for dose management and radiation dose optimization, in various dental facilities in the state. It was also found that dental facilities employed with the digital type of detector are not always related to lower exposure.

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The effective atomic number and electron density of some Fricke gel dosimeters were calculated for photon interaction in the energy range from 10 keV to 1000 MeV using Auto-Z_eff, direct and power law methods. The results are presented relative to those of water to allow direct comparison. It is found, that the effective atomic numbers and effective electron densities calculated with the Auto-Z_eff and direct methods, demonstrates a good agreement in the energy interval extending from 0.1 MeV to 10 MeV. For effective atomic number relative to water, Ferrous Agarose Xylenol gel showed better water equivalence with difference up to 0.3%, while FX-PVA-GTA and Ferrous Xylenol Gelatin gels showed differences up to 2.26% and 2.25%, respectively.

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Purpose: The purpose of he study was to reduce setup errors during intensity-modulated radiation therapy (IMRT) with an original knee fixation device (KFD) and evaluate the clinical target volume (CTV) coverage. Methods: Participants were classified into two groups: knee flexion (KF) group (n = 16), wherein participants' knees were fixed in a flexed position using the proposed KFD during planning computed tomography, and knee extension group (KE; n = 15), wherein no KFD was used. We investigated the residual rotational errors and inter-fractional setup errors with or without KFD. Furthermore, inter-fractional margins were calculated using logistic regression analysis, and CTV coverage was evaluated. Results: The residual rotational errors in the yaw and roll directions (P < 0.02) and the inter-fractional error in the anterior-posterior (A-P) direction (P < 0.02) improved significantly in the KF group compared with the KE group. Repeatability was improved for the pitch direction. The inter-fractional margins were 6.68 mm and 4.87 mm in the A-P and superior-inferior (S-I) directions, respectively, in the KF group, representing reductions (mm) of 20.8% and 12.6% compared with the KE group, respectively. The odds ratios for CTV coverage in the KF group compared to the KE group were 2.76 (P < 0.001) and 1.74 (P < 0.05) in the A-P and S-I directions, respectively. Conclusions: The IMRT fixation method using an original KFD improved the residual rotational error in the three directions and the inter-fractional error in the A-P direction, reduced the interfractional margins in the A-P, and S-I directions and improved CTV coverage. Our original KFD may be a useful fixation method during prostate IMRT.

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