Assessing Heterogeneity Effects on Points A, B, and Organs at Risk Doses in High-dose-Rate Brachytherapy for Cervical Cancer - A Comparison of 192Ir and 60Co Sources Using Monte Carlo N-Particle 5.

Purpose: The present article deals with investigating the effects of tissue heterogeneity consideration on the dose distribution of 192Ir and 60Co sources in high-dose-rate brachytherapy (HDR-BT). Materials and Methods: A Monte Carlo N-Particle 5 (MCNP5) code was developed for the simulation of the dose distribution in homogeneous and heterogeneous phantoms for cervical cancer patients. The phantoms represented water-equivalent and human body-equivalent tissues. Treatment data for a patient undergoing HDR-BT with a 192Ir source were used as a reference for validation, and for 60Co, AAPM Task Group 43 methodology was also applied. The dose values were calculated for both source types in the phantoms. Results: The results showed a good agreement between the calculated dose in the homogeneous phantom and the real patient's treatment data, with a relative difference of less than 5% for both sources. However, when comparing the absorbed doses at critical points such as Point A right, Point A left, Point B right, Point B left, bladder International Commission on Radiation Units and Measurement (ICRU) point, and recto-vaginal ICRU point, the study revealed significant percentage differences (approximately 5.85% to 12.02%) between the homogeneous and heterogeneous setups for both 192Ir and 60Co sources. The analysis of dose-volume histograms (DVH) indicated that organs at risk, notably the rectum and bladder, still received doses within recommended limits. Conclusions: The study concludes that 60Co and 192Ir sources can be effectively used in HDR-BT, provided that careful consideration is given to tissue heterogeneity effects during treatment planning to ensure optimal therapeutic outcomes.

Enhanced radio-photodynamic therapy potential of advanced gold-based nanoclusters for breast cancer treatment.

The purpose of current study was to assess the impact of ALA-coated gold nanoclusters (Au NPs) on the combined therapeutic effects of radiotherapy (RT) and photodynamic therapy (PDT) on healthy MCF-10A and MCF-7 breast cancer cells. The Au NPs were covered with ALA using PEG polymer, resulting in the synthesis of Au@ALA NPs. The successful synthesis of the final NPs was confirmed through FTIR, XRD, TEM, and UV-Vis tests. MCF-10A and MCF-7 cell lines were treated with different concentrations of Au@ALA NPs and exposed to irradiation of 2 and 4 Gy (using MV X-ray) and 630 nm laser light irradiation. Cytotoxicity was assessed using a multifaceted approach involving the MTT assay, real-time PCR, and colony forming assay. The findings revealed that the damage inflicted by Au@ALA NPs on cancerous tissue was significantly greater than that on normal tissue. The cytotoxic effects of all experimental groups exhibited a direct correlation with increasing concentrations and radiation doses. The combination of Au@ALA NPs with RT doses of 2 and 4 Gy resulted in a reduction in cell viability by a factor of 1.58 (P = 0.001) and 1.73 (P = 0.004), respectively. Furthermore, the simultaneous intervention of NPs with PDT and RT at doses of 2 and 4 Gy led to a decrease in cell viability by a factor of 2.10 (P = 0.001) and 3.08 (P = 0.001) in turn. Furthermore, the real-time PCR and colonogenic assay results demonstrated that the combined treatment significantly increased phosphorylation of ATM and expression of TP53, indicating an adequate synergistic effect on breast cancer cells. The concurrent application of Au@ALA NPs in RT and PDT successfully enhanced the radiosensitization of breast cancer cells to megavoltage RT and PDT.

Deep learning in ovarian cancer diagnosis: a comprehensive review of various imaging modalities.

Ovarian cancer poses a major worldwide health issue, marked by high death rates and a deficiency in reliable diagnostic methods. The precise and prompt detection of ovarian cancer holds great importance in advancing patient outcomes and determining suitable treatment plans. Medical imaging techniques are vital in diagnosing ovarian cancer, but achieving accurate diagnoses remains challenging. Deep learning (DL), particularly convolutional neural networks (CNNs), has emerged as a promising solution to improve the accuracy of ovarian cancer detection. This systematic review explores the role of DL in improving the diagnostic accuracy for ovarian cancer. The methodology involved the establishment of research questions, inclusion and exclusion criteria, and a comprehensive search strategy across relevant databases. The selected studies focused on DL techniques applied to ovarian cancer diagnosis using medical imaging modalities, as well as tumour differentiation and radiomics. Data extraction, analysis, and synthesis were performed to summarize the characteristics and findings of the selected studies. The review emphasizes the potential of DL in enhancing the diagnosis of ovarian cancer by accelerating the diagnostic process and offering more precise and efficient solutions. DL models have demonstrated their effectiveness in categorizing ovarian tissues and achieving comparable diagnostic performance to that of experienced radiologists. The integration of DL into ovarian cancer diagnosis holds the promise of improving patient outcomes, refining treatment approaches, and supporting well-informed decision-making. Nevertheless, additional research and validation are necessary to ensure the dependability and applicability of DL models in everyday clinical settings.

Quantitative and Visual Analysis of Data Augmentation and Hyperparameter Optimization in Deep Learning-Based Segmentation of Low-Grade Glioma Tumors Using Grad-CAM.

This study executes a quantitative and visual investigation on the effectiveness of data augmentation and hyperparameter optimization on the accuracy of deep learning-based segmentation of LGG tumors. The study employed the MobileNetV2 and ResNet backbones with atrous convolution in DeepLabV3+ structure. The Grad-CAM tool was also used to interpret the effect of augmentation and network optimization on segmentation performance. A wide investigation was performed to optimize the network hyperparameters. In addition, the study examined 35 different models to evaluate different data augmentation techniques. The results of the study indicated that incorporating data augmentation techniques and optimization can improve the performance of segmenting brain LGG tumors up to 10%. Our extensive investigation of the data augmentation techniques indicated that enlargement of data from 90° and 225° rotated data,up to down and left to right flipping are the most effective techniques. MobilenetV2 as the backbone,"Focal Loss" as the loss function and "Adam" as the optimizer showed the superior results. The optimal model (DLG-Net) achieved an overall accuracy of 96.1% with a loss value of 0.006. Specifically, the segmentation performance for Whole Tumor (WT), Tumor Core (TC), and Enhanced Tumor (ET) reached a Dice Similarity Coefficient (DSC) of 89.4%, 70.1%, and 49.9%, respectively. Simultaneous visual and quantitative assessment of data augmentation and network optimization can lead to an optimal model with a reasonable performance in segmenting the LGG tumors.

Monte Carlo Dosimetric Study of Percutaneous Vertebroplasty and Brachytherapy for the Treatment of Spinal Metastases.

Background: Percutaneous vertebroplasty employs bone cement for injecting into the fractured vertebral body (VB) caused by spinal metastases. Radioactive bone cement and also brachytherapy seeds have been utilized to suppress the tumor growth in the VB. Objective: This study aims to investigate the dose distributions of low-energy brachytherapy seeds, and to compare them to those of radioactive bone cement, by Monte Carlo simulation. Material and Methods: In this simulation study, nine CT scan images were imported in Geant4. For the simulation of brachytherapy, I-125, Cs-131, or Pd-103 seeds were positioned in the VB, and for the simulation of vertebroplasty, the VB was filled by a radioactive cement loaded by P-32, Ho-166, Y-90, or Sm-153 radioisotopes. The dose-volume histograms of the VB, and the spinal cord (SC) were obtained after segmentation, considering that the reference dose is the minimum dose covered 95% of the VB. Results: The SC sparing was improved by using beta-emitting cement because of their steep gradient dose distribution. I-125 seeds and Y-90 radioisotope showed better VB coverage for brachytherapy and vertebroplasty techniques, respectively. Pd-103 seeds and P-32 radioisotope showed better SC sparing for brachytherapy and vertebroplasty, respectively. The minimum mean doses that covered 100% of the VB were 62.0%, 56.5%, and 45.0% for I-125, Cs-131, and Pd-103 seeds, and 28.3%, 28.6%, 32.9%, and 17.7%, for P-32, Ho-166, Y-90, and Sm-153 sources, respectively. Conclusion: I-125 and Cs-131 seeds may be useful for large tumors filling the entire VB, and also for the extended tumors invading multiple vertebrae. Beta-emitting bone cement is recommended for tumors located near the SC.

The OCDA-Net: a 3D convolutional neural network-based system for classification and staging of ovarian cancer patients using [18F]FDG PET/CT examinations.

OBJECTIVE: To create the 3D convolutional neural network (CNN)-based system that can use whole-body [18F]FDG PET for recurrence/post-therapy surveillance in ovarian cancer (OC). METHODS: In this study, 1224 image sets from OC patients who underwent whole-body [18F]FDG PET/CT at Kowsar Hospital between April 2019 and May 2022 were investigated. For recurrence/post-therapy surveillance, diagnostic classification as cancerous, and non-cancerous and staging as stage III, and stage IV were determined by pathological diagnosis and specialists' interpretation. New deep neural network algorithms, the OCDAc-Net, and the OCDAs-Net were developed for diagnostic classification and staging of OC patients using [18F]FDG PET/CT images. Examinations were divided into independent training (75%), validation (10%), and testing (15%) subsets. RESULTS: This study included 37 women (mean age 56.3 years; age range 36-83 years). Data augmentation techniques were applied to the images in two phases. There were 1224 image sets for diagnostic classification and staging. For the test set, 170 image sets were considered for diagnostic classification and staging. The OCDAc-Net areas under the receiver operating characteristic curve (AUCs) and overall accuracy for diagnostic classification were 0.990 and 0.92, respectively. The OCDAs-Net achieved areas under the receiver operating characteristic curve (AUCs) of 0.995 and overall accuracy of 0.94 for staging. CONCLUSIONS: The proposed 3D CNN-based models provide potential tools for recurrence/post-therapy surveillance in OC. The OCDAc-Net and the OCDAs-Net model provide a new prognostic analysis method that can utilize PET images without pathological findings for diagnostic classification and staging.

Automatic segmentation of glioblastoma multiform brain tumor in MRI images: Using Deeplabv3+ with pre-trained Resnet18 weights.

PURPOSE: To assess the effectiveness of deep learning algorithms in automated segmentation of magnetic resonance brain images for determining the enhanced tumor, the peri-tumoral edema, the necrotic/ non-enhancing tumor, and Normal tissue volumes. METHODS AND MATERIALS: A new deep neural network algorithm, Deep-Net, was developed for semantic segmentation of the glioblastoma tumors in MR images, using the Deeplabv3+ architecture, and the pre-trained Resnet18 initial weights. The MR image Dataset used for training the network was taken from the BraTS 2020 training set, with the ground truth labels for different tumor subregions manually drawn by a group of expert neuroradiologists. In this work, two multi-modal MRI scans, i.e., T1ce and FLAIR of 293 patients with high-grade glioma (HGG), were used for deep network training (Deep-Net). The performance of the network was assessed for different hyper-parameters, to obtain the optimum set of parameters. The similarity scores were used for the evaluation of the optimized network. RESULTS: According to the results of this study, epoch #37 is the optimum epoch giving the best global accuracy (97.53%), and loss function (0.14). The Deep-Net sensitivity in the delineation of the enhanced tumor is more than 90%. CONCLUSIONS: The results indicate that the Deep-Net was able to segment GBM tumors with high accuracy.

DESIGN AND FABRICATION OF A PEDIATRIC THYROID PHANTOM FOR USE IN RADIO-IODINE UPTAKE MEASUREMENT, IMAGE QUALITY CONTROL AND DOSIMETRY.

Estimating internal contamination from 131I for children in nuclear accidents is a crucial subject in the radiation protection field. Throughout this paper, an urgent and simple method was proposed for measuring 131I inside the pediatric thyroid gland by constructing a neck and thyroid phantom. For this purpose, CT scan images of healthy child's thyroids were obtained, and the sizes of different parts were determined by a 3D slicer image processing software. Girls with the body surface area between 0.95 and 1.05 were involved in this study. The fabricated phantom is composed of 5 cylindrical slabs of 2-cm thickness, and several small holes were constructed for TLD dosemeters near the thyroid gland and all other parts of the neck. The phantom was constructed utilizing a 3D printer with acrylonitrile butadiene styrene plastic. The thyroid phantom was filled with radioiodine-131, and calibration curves were plotted for contamination estimation. A nodular thyroid phantom was also constructed. The nodular phantom or the resolution phantom has 4 removable parts containing cylindrical holes with diameters of 3, 6, 9 and 12 mm. These holes on the thyroid glands can be filled with different activities of radionuclides to serve as hot and cold spots for quality control of nuclear medicine images. The results show that the designed phantom is applicable in different fields such as nuclear image quality and resolution tests, dosimetry and iodine thyroid uptake estimation in nuclear medicine departments, and nuclear emergency monitoring.

The effect of tandem-ovoid titanium applicator on points A, B, bladder, and rectum doses in gynecological brachytherapy using 192Ir.

PURPOSE: The dosimetry procedure by simple superposition accounts only for the self-shielding of the source and does not take into account the attenuation of photons by the applicators. The purpose of this investigation is an estimation of the effects of the tandem and ovoid applicator on dose distribution inside the phantom by MCNP5 Monte Carlo simulations. MATERIAL AND METHODS: In this study, the superposition method is used for obtaining the dose distribution in the phantom without using the applicator for a typical gynecological brachytherapy (superposition-1). Then, the sources are simulated inside the tandem and ovoid applicator to identify the effect of applicator attenuation (superposition-2), and the dose at points A, B, bladder, and rectum were compared with the results of superposition. The exact dwell positions, times of the source, and positions of the dosimetry points were determined in images of a patient and treatment data of an adult woman patient from a cancer center. The MCNP5 Monte Carlo (MC) code was used for simulation of the phantoms, applicators, and the sources. RESULTS: The results of this study showed no significant differences between the results of superposition method and the MC simulations for different dosimetry points. The difference in all important dosimetry points was found to be less than 5%. CONCLUSIONS: According to the results, applicator attenuation has no significant effect on the calculated points dose, the superposition method, adding the dose of each source obtained by the MC simulation, can estimate the dose to points A, B, bladder, and rectum with good accuracy.

Comparison of TG-43 dosimetric parameters of brachytherapy sources obtained by three different versions of MCNP codes.

Monte Carlo simulations are widely used for calculation of the dosimetric parameters of brachytherapy sources. MCNP4C2, MCNP5, MCNPX, EGS4, EGSnrc, PTRAN, and GEANT4 are among the most commonly used codes in this field. Each of these codes utilizes a cross-sectional library for the purpose of simulating different elements and materials with complex chemical compositions. The accuracies of the final outcomes of these simulations are very sensitive to the accuracies of the cross-sectional libraries. Several investigators have shown that inaccuracies of some of the cross section files have led to errors in 125I and 103Pd parameters. The purpose of this study is to compare the dosimetric parameters of sample brachytherapy sources, calculated with three different versions of the MCNP code - MCNP4C, MCNP5, and MCNPX. In these simulations for each source type, the source and phantom geometries, as well as the number of the photons, were kept identical, thus eliminating the possible uncertainties. The results of these investigations indicate that for low-energy sources such as 125I and 103Pd there are discrepancies in gL(r) values. Discrepancies up to 21.7% and 28% are observed between MCNP4C and other codes at a distance of 6 cm for 103Pd and 10 cm for 125I from the source, respectively. However, for higher energy sources, the discrepancies in gL(r) values are less than 1.1% for 192Ir and less than 1.2% for 137Cs between the three codes.

Evaluation of BEBIG HDR (60)Co system for non-invasive image-guided breast brachytherapy.

PURPOSE: HDR (60)Co system has recently been developed and utilized for brachytherapy in many countries outside of the U.S. as an alternative to (192)Ir. In addition, the AccuBoost(®) technique has been demonstrated to be a successful non-invasive image-guided breast brachytherapy treatment option. The goal of this project is to evaluate the possibility of utilizing the BEBIG HDR (60)Co system for AccuBoost treatment. These evaluations are performed with Monte Carlo (MC) simulation technique. MATERIAL AND METHODS: In this project, the MC calculated dose distributions from HDR (60)Co for various breast sizes have been compared with the simulated data using an HDR (192)Ir source. These calculations were performed using the MCNP5 code. The initial calculations were made with the same applicator dimensions as the ones used with the HDR (192)Ir system (referred here after as standard applicator). The activity of the (60)Co source was selected such that the dose at the center of the breast would be the same as the values from the (192)Ir source. Then, the applicator wall-thickness for the HDR (60)Co system was increased to diminish skin dose to levels received when using the HDR (192)Ir system. With this geometry, dose values to the chest wall and the skin were evaluated. Finally, the impact of a conical attenuator with the modified applicator for the HDR (60)Co system was analyzed. RESULTS: These investigations demonstrated that loading the (60)Co sources inside the thick-walled applicators created similar dose distributions to those of the (192)Ir source in the standard applicators. However, dose to the chest wall and breast skin with (60)Co source was reduced using the thick-walled applicators relative to the standard applicators. The applicators with conical attenuator reduced the skin dose for both source types. CONCLUSIONS: The AccuBoost treatment can be performed with the (60)Co source and thick-wall applicators instead of (192)Ir with standard applicators.

Dosimetry of gamma chamber blood irradiator using PAGAT gel dosimeter and Monte Carlo simulations.

Currently, the use of blood irradiation for inactivating pathogenic microbes in infected blood products and preventing graft-versus-host disease (GVHD) in immune suppressed patients is greater than ever before. In these systems, dose distribution and uniformity are two important concepts that should be checked. In this study, dosimetry of the gamma chamber blood irradiator model Gammacell 3000 Elan was performed by several dosimeter methods including thermoluminescence dosimeters (TLD), PAGAT gel dosimetry, and Monte Carlo simulations using MCNP4C code. The gel dosimeter was put inside a glass phantom and the TL dosimeters were placed on its surface, and the phantom was then irradiated for 5 min and 27 sec. The dose values at each point inside the vials were obtained from the magnetic resonance imaging of the phantom. For Monte Carlo simulations, all components of the irradiator were simulated and the dose values in a fine cubical lattice were calculated using tally F6. This study shows that PAGAT gel dosimetry results are in close agreement with the results of TL dosimetry, Monte Carlo simulations, and the results given by the vendor, and the percentage difference between the different methods is less than 4% at different points inside the phantom. According to the results obtained in this study, PAGAT gel dosimetry is a reliable method for dosimetry of the blood irradiator. The major advantage of this kind of dosimetry is that it is capable of 3D dose calculation.

Perturbation of TG-43 parameters of the brachytherapy sources under insufficient scattering materials.

In the recommendations of Task Group #43 from American Association of Physicists in Medicine (AAPM TG43), methods of brachytherapy source dosimetry are recommended, under full scattering conditions. However, in actual brachytherapy procedures, sources may not be surrounded by full scattering tissue in all directions. Clinical examples include high-dose-rate (HDR) brachytherapy of the breast or low-dose-rate (LDR) brachytherapy of ocular melanoma using eye plaque treatment with 125I and 103Pd. In this work, the impact of the missing tissue on the TG-43-recommended dosimetric parameters of different brachytherapy sources was investigated. The impact of missing tissue on the TG-43-recommended dosimetric parameters of 137Cs, 192Ir, and 103Pd brachytherapy sources was investigated using the MCNP5 Monte Carlo code. These evaluations were performed by placing the sources at different locations inside a 30 × 30 × 30 cm3 cubical water phantom and comparing the results with the values of the source located at the center of the phantom, which is in a full scattering condition. The differences between the thickness of the overlying tissues for different source positions and the thickness of the overlying tissue in full scattering condition is referred to as missing tissue. The results of these investigations indicate that values of the radial dose function and 2D anisotropy function vary as a function of the thickness of missing tissue, only in the direction of the missing tissue. These changes for radial dose function were up to 5%, 11%, and 8% for 137Cs, 192Ir, and 103Pd, respectively. No significant changes are observed for the values of the dose rate constants. In this project, we have demonstrated that the TG-43 dosimetric parameters may only change in the directions of the missing tissue. These results are more practical than the published data by different investigators in which a symmetric effect of the missing tissue on the dosimetric parameters of brachytherapy source are being considered, regardless of the implant geometry in real clinical cases.

Developing a Treatment Planning Software Based on TG-43U1 Formalism for Cs-137 LDR Brachytherapy.

BACKGROUND: The old Treatment Planning Systems (TPSs) used for intracavitary brachytherapy with Cs-137 Selectron source utilize traditional dose calculation methods, considering each source as a point source. Using such methods introduces significant errors in dose estimation. As of 1995, TG-43 is used as the main dose calculation formalism in treatment TPSs. OBJECTIVES: The purpose of this study is to design and establish a treatment planning software for Cs-137 Solectron brachytherapy source, based on TG-43U1 formalism by applying the effects of the applicator and dummy spacers. MATERIALS AND METHODS: Two softwares used for treatment planning of Cs-137 sources in Iran (STPS and PLATO), are based on old formalisms. The purpose of this work is to establish and develop a TPS for Selectron source based on TG-43 formalism. In this planning system, the dosimetry parameters of each pellet in different places inside applicators were obtained by MCNP4c code. Then the dose distribution around every combination of active and inactive pellets was obtained by summing the doses. The accuracy of this algorithm was checked by comparing its results for special combination of active and inactive pellets with MC simulations. Finally, the uncertainty of old dose calculation formalism was investigated by comparing the results of STPS and PLATO softwares with those obtained by the new algorithm. RESULTS: For a typical arrangement of 10 active pellets in the applicator, the percentage difference between doses obtained by the new algorithm at 1cm distance from the tip of the applicator and those obtained by old formalisms is about 30%, while the difference between the results of MCNP and the new algorithm is less than 5%. CONCLUSIONS: According to the results, the old dosimetry formalisms, overestimate the dose especially towards the applicator's tip. While the TG-43U1 based software perform the calculations more accurately.

Radiation dose to neonates undergoing X-ray imaging in special care baby units in Iran.

Radiographic imaging has a significant role in the timely diagnosis of the diseases of neonates in intensive care units. The estimation of the dose received by the infants undergoing radiographic examination is of great importance, due to greater more radiosensitivity and longer life expectancy of the neonates and premature babies. In this study, the values of entrance skin dose (ESD), dose area products (DAPs), energy imparted (EI), whole-body dose, effective dose and risk of childhood cancer were estimated using three methods including direct method [using thermoluminescence dosimetry (TLD) chips], indirect method (using tube output) and Monte Carlo (MC) method (using MCNP4C code). In the first step, the ESD of the neonates was directly measured using TLD-100 chips. Fifty neonates, mostly premature, with different weights and gestational ages in five hospitals mostly suffering from respiratory distress syndrome and pneumonia were involved in this study. In the second step, the values of ESD to neonates were indirectly obtained from the tube output in different imaging techniques. The imaging room, incubator, neonates and other components were then simulated in order to obtain the ESD values using the MCNP4C code. Finally, the values of ESD assessed by the three methods were used for calculation of DAP, EI, whole-body dose, effective dose and risk of childhood cancer. The results indicate that the mean ESD per radiograph estimated by the direct, indirect and MC methods are 56.6±4.1, 50.1±3.1 and 54.5±3.3 µGy, respectively. The mean risk of childhood cancer estimated in this study varied between 4.21×10(-7) and 2.72×10(-6).

Impact of the vaginal applicator and dummy pellets on the dosimetry parameters of Cs-137 brachytherapy source.

In this study, dose rate distribution around a spherical 137Cs pellet source, from a low-dose-rate (LDR) Selectron remote afterloading system used in gynecological brachytherapy, has been determined using experimental and Monte Carlo simulation techniques. Monte Carlo simulations were performed using MCNP4C code, for a single pellet source in water medium and Plexiglas, and measurements were performed in Plexiglas phantom material using LiF TLD chips. Absolute dose rate distribution and the dosimetric parameters, such as dose rate constant, radial dose functions, and anisotropy functions, were obtained for a single pellet source. In order to investigate the effect of the applicator and surrounding pellets on dosimetric parameters of the source, the simulations were repeated for six different arrangements with a single active source and five non-active pellets inside central metallic tubing of a vaginal cylindrical applicator. In commercial treatment planning systems (TPS), the attenuation effects of the applicator and inactive spacers on total dose are neglected. The results indicate that this effect could lead to overestimation of the calculated F(r,θ), by up to 7% along the longitudinal axis of the applicator, especially beyond the applicator tip. According to the results obtained in this study, in a real situation in treatment of patients using cylindrical vaginal applicator and using several active pellets, there will be a large discrepancy between the result of superposition and Monte Carlo simulations.