Organ Doses Research Articles

Artificial intelligence in diagnostic radiology for dose management : Advances and perspectives using the example of computed tomography

Imaging procedures employing ionizing radiation require compliance with European directives and national regulations in order to protect patients. Each exposure must be indicated, individually adapted, and documented. Unacceptable dose exceedances must be detected and reported. These tasks are time-consuming and require meticulous diligence. Computed tomography (CT) is the most important contributor to medical radiation exposure. Optimizing the patient's dose is therefore mandatory. Use of modern technology and reconstruction algorithms already reduces exposure. Checking the indication, planning, and performing the examination are further important process steps with regard to radiation protection. Patient exposure is usually monitored by dose management systems (DMS). In special cases, arisk assessment is required by calculating the organ doses. Artificial intelligence (AI)-assisted techniques are increasingly used in various steps of the process: they support examination planning, improve patient positioning, and enable automated scan length adjustments. They also provide real-time estimates of individual organ doses. The integration of AI into medical imaging is proving successful in terms of dose optimization in various areas of the radiological workflow, from reconstruction to examination planning and performing exams. However, the use of AI in conjunction with DMS has not yet been considered on alarge scale. AI processes offer promising tools to support dose management. However, their implementation in the clinical setting requires further research, extensive validation, and continuous monitoring.

Rapid patient-specific organ dose estimation in computed tomography scans via integration of radiomics features and neural networks.

Computed tomography (CT) offers detailed cross-sectional images of internal anatomy for disease detection but carries a risk of solid cancer or blood malignancies due to exposure to X-ray radiation. This study aimed to develop a new method to quickly predict patient-specific organ doses from CT examinations by training neural networks (NNs) based on radiomics features. CT Digital Imaging and Communications in Medicine (DICOM) image data were exported to DeepViewer, a clinical autosegmentation software, to segment the regions of interest (ROIs) for patient organs. Radiomics feature extraction was performed based on the selected CT data and ROIs. Reference organ doses were computed using Monte Carlo (MC) simulations. Patient-specific organ doses were predicted by training a NN model based on radiomics features and reference doses. For the dose prediction performance, the relative root mean squared error (RRMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) were evaluated on the test sets. The robustness of the NN model was evaluated via the random rearrangement of patient samples in the training and test sets. The maximal difference between the reference and predicted doses was less than 1 mGy for all investigated organs. The range of MAPE was 1.68% to 5.2% for head organs, 11.42% to 15.2% for chest organs, and 5.0% to 8.0% for abdominal organs; the maximal R2 values were 0.93, 0.86, and 0.89 for the head, chest, and abdominal organs, respectively. The radiomics feature-based NN model can achieve accurate prediction of patient-specific organ doses at a high speed of less than 1 second using a single central processing unit, which supports its use as a user-friendly online clinical application.

Effects of minimum monitor unit per dynamic control point on intensity‐modulated radiotherapy planning for nasopharyngeal carcinoma: A retrospective study

The present study aimed to improve the dose distribution of radiotherapy planning for nasopharyngeal carcinoma (NPC) by comparing the effects of various minimum monitor units (MUs) per dynamic control point (MMCP) values on the quality and execution efficiency of dynamic intensity-modulated radiotherapy (IMRT) planning. Thirty-four clinically implemented dynamic IMRT plans for patients with NPC were retrospectively selected. In total, 170 plans were obtained by modifying only the MMCP values (set as 1, 3, 5, 7, and 9) in the treatment planning system's (TPS) optimization parameters. These plans were divided into 5 groups. Analyzing the effects of MMCP on the target and organ dose at risk (OAR), also the execution efficiency of the treatment plan in each group and using a quality score system, we conducted an objective quantitative study of the dose distribution and execution efficiency. The target dose evaluation indicators (target coverage (TC), homogeneity index (HI), and conformity index (CI)) of all IMRT plans showed a trend of variation with an increase in MMCP values, and the difference was statistically significant when MMCP values were 5, 7, 9, and 1 (p < 0.05). With an increase in MMCP, the dose to OAR slightly increased, but the difference was not statistically significant (p > 0.05). With an increase in MMCP, the average number of MUs per segment significantly increased (p < 0.01). The groups based on MMCP values of 1, 3, 5, 7, and 9 received quality score system of 1.188, 1.180, 1.171, 0.987, and 1.184, respectively, with the MMCP7 group achieving the lowest score, indicating that this plan had the highest overall quality. The MMCP value for dynamic IMRT planning in the Monaco TPS for patients with NPC should be set to 7 to achieve fewer segments, the best execution efficiency without significantly deteriorating the target and OAR dose.

Computational assessment dose distribution of the antero-posterior and postero-anterior in Boron Neutron Capture Therapy for colorectal cancer

Abstract Colorectal is part of the gastrointestinal system that anatomically and physiologically, is excretory and extends throughout the abdominal region. In BNCT (Boron Neutron Capture Therapy) treatment for colorectal cancer, special projections are needed to ensure the dose is distributed effectively in cancer cells. Computational evaluation was carried out using PHITS 3.30 version, to determine the number of doses for organs at risk in the Antero-Posterior (AP) projection compared to the Postero-Anterior (PA) projection in this case, if the cancer cells are located in different parts, there are rectum and colon (transverse). BNCT treatment planning was designed using a female abdomen phantom voxel with the patient position Left Lateral Decubitus. Based on the simulation and evaluation results, it’s confirmed that isoeffective dose and irradiation time examined in the rectum is significantly reduced in the postero-anterior position so that postero-anterior and antero-posterior calculation results are 0.74 Gy and 20.61 Gy. However, if the cancer cells are in the transverse colon, antero-posterior projection is more effective for cases of colon cancer in the transverse colon of 0.71 Gy, and the postero-anterior projection with a dose of 29.15 Gy.

Dose conversion in retrospective dosimetry: Results and implications from an inter-laboratory comparison featuring a realistic exposure scenario

Dose conversion coefficients attempt to harmonize the material-, location-, and exposure-dependent results from retrospective dosemeters. The issues and uncertainties arising from dose conversion are explored within the framework of an interlaboratory comparison exercise in which mobile phones were positioned around anthropomorphic phantoms and exposed to non-uniform photon fields, with the glass and resistors they contain employed as fortuitous dosemeters. The difficulties of adopting pre-calculated tables of generic conversion coefficients are evaluated first, and then compared against those arising through the use of bespoke data derived by Monte Carlo modelling, and also against not converting the doses measured by the phones. It is seen that the different subjective choices that users might make when selecting ‘optimal’ generic data can lead to a significant source of uncertainty (up to around 70 %), though may be improved (to around 30 %) by appropriate quality controls. Use of generic coefficients typically led to over-estimates of the organ doses: an average discrepancy of ca. a factor of 2 was found, but this is still better than the factor of around 3 observed when no conversion coefficients were applied. Use of bespoke conversion factors led to the best estimates of organ doses, although they still over-estimated by approximately 1.5 on average, and an uncertainty of around 20 % was associated with generating their values. Overall, applying bespoke conversion data improves but does not guarantee correct dose categorization of individuals, with the inconsistences in the measured results found generally to be the limiting factor in obtaining accurate dose assessments.

Clinical Application of Equivalent Uniform Dose in Intensity-Modulated Rotational Radiotherapy Based on Eclipse TPS

To investigate the application of equivalent uniform dose (EUD) in intensity-modulated rotational radiotherapy and to explore optimization methods for improving the quality of modulated treatment plans. The impact of the parameter a in the EUD formula on the characteristics of the EUD curve was analyzed using Python. Thirty cases of head and neck tumors, thoracic tumors, and pelvic tumors were randomly selected for treatment planning. Dose optimization for the target area and organs at risk were performed using a physics-based optimization approach or an optimization approach that combines physical constraints with the EUD function. The dose distribution and compliance with constraints of the two groups of plans were compared, while also observing the effect of different values of a on the planning outcomes. The impact of the value of a on the changes in EUD curve characteristics was consistent with its impact on the results of EUD plan optimization. When -15≤ a≤-5, the dose distribution in the target area was more uniform; when 1≤ a≤7, the effect on the uniform dose and low-dose regions in organs at risk was more noticeable; when 10≤ a≤30, the effect of constraining the high-dose regions in organs at risk was more pronounced, with the EUD for the target area and organs at risk exhibiting different expressions under different a values. The study also found that the target dose distribution and the protection of organs at risk in the EUD optimization group were better than those in the physical optimization group only. The a-value has a significant impact on the, the dose distribution in the target area and the organ at risk, providing a reference for the setting of a-value while using EUD to optimize the intensity modulation plan. The using of EUD optimization method can not only achieve excellent dose distribution in the target area, but also significantly reduce the normal tissue dose and the probability of complications, which has certain clinical application value.

Simultaneous integrated boost-intensity modulated radiation therapy (SIBIMRT) planning for pelvic tumours: dose coverage to target volume and normal tissue sparing.

To evaluate the better radiotherapy plan for pelvic tumours that may achieve a high target coverage dose and low normal tissue tolerance dose using simultaneous integrated boost-intensity-modulated radiation therapy technique. The analytical, cross-sectional, descriptive study was conducted from October 2020 to March 2021 at Al- Amal National Hospital for Cancer Treatment, Baghdad, Iraq, and comprised male pelvic cancer patients aged 50-80 years. Computed tomography scans were randomly selected. For each patient, 4 treatment plans (phases Ι and Π) were generated using the simultaneous integrated boost-intensity-modulated radiation therapy technique while keeping all parameters constant except the number of beams, which were 5, 7, 9 and 11. The optimal and safe dose was defined as the one to cover 95% planning target volume. Homogeneity and conformity indices were used to assess the uniformity of dose distribution in the target volume, and various treatment plans in the same patient were compared. Data was analysed using SPSS 24. There were 15 males with mean age 67.12±2.84 years. There was a significant variance in the target volume dose and organ at risk in the 4 different plans generated using the simultaneous integrated boost-intensitymodulated radiation therapy technique (p<0.05). The 9-beam treatment plan was the best for coverage of tumours and protection of healthy organs assessed through homogeneity and conformity indices (p<0.05). The 9-beam treatment plan showed significant tumour coverage, homogeneity and conformity values, and sparing dose for organs at risk.

Assessment of occupational radiation exposure during a specific endoscopic retrograde cholangiopancreatography procedure.

The aim of this study was to evaluate the occupational radiation exposure of staff during endoscopic retrograde cholangiopancreatography (ERCP), with a focus on individuals closest to the radiation source, and to identify potential increases in exposure to hands and eye lenses. Patient radiation exposure during ERCP was also assessed. Staff organ doses were monitored using a Philips Allura Xper FD 20 fluoroscopy system, during 24 ERCP procedures for a period of 7months. Staff doses were measured using thermoluminescence dosemeters and electronic personal dosemeters, and patient effective doses were simulated and calculated. Physicians' annual organ doses ranged from 0.2 to 1.6mSv for shoulders, 0.1 to 0.4mSv for eye lenses, and 0.3 to 1.6mSv for fingers. The annual organ dose of the nursing staff ranged from 0.08 to 2.4mSv for shoulders, 0.02 to 2.3mSv for eye lenses, and 1.2 to 5.3mSv for fingers. The effective dose to patients ranged from 0.009 to 0.46mSv. Staff doses were within safe limits, but patient doses were high, emphasizing the need for improved radiation protection.

Cross‐Institutional Prediction System for Estimating Patient‐Specific Organ Dose from Chest CT Scans without Segmenting Internal Organs

This study aims to establish and validate a cross‐institutional prediction system for estimating patient‐specific organ doses from chest CT scans. By collaborating across multiple institutions, the study seeks to develop models that allow rapid online estimation of organ doses, eliminating the need for complex organ segmentation. Researchers delineate skin outlines from chest CT images obtained from two different institutions. Radiomics features are extracted from the chest CT data and skin contours. Organ doses are computed using Monte Carlo simulations as reference organ doses. Single‐ and cross‐institutional support vector regression (SVR) models are trained with radiomics features to predict organ doses from chest CT scans. Model performance is assessed using metrics like maean absolute percentage error (MAPE) and R‐squared (R2). For chest organs (lungs, heart, spinal cord, trachea, and esophagus), single‐institutional SVR models achieve MAPE values ranging from 4.72% to 15.31% and R2 values from 0.73 to 0.93. Cross‐institutional models have MAPE values in the range of 2.16–7.49% and R2 values from 0.84 to 0.99. SVR models trained with radiomics features from skin outlines can reliably estimate organ doses from chest CT scans. The proposed method is applicable across different institutions, and cross‐institutional models enhance predictive accuracy, generality, and robustness.

3D printing of realistic body phantoms: Comparison of measured and simulated organ doses on the example of a CT scan on a pregnant woman

AbstractBackgroundMedical examinations or treatment of pregnant women using ionizing radiation are sometimes unavoidable. In such cases, the risk of harm to the embryo and fetus after exposure to ionizing radiation must be carefully estimated. However, no commercially available anthropomorphic body phantoms of pregnant women are available for dose measurements. A promising possibility for the production of body phantoms for patient groups that are not adequately represented by the phantoms of reference persons is 3D printing. However, this approach is still in the evaluation phase.PurposeTo print the abdomen of a woman in the late stage of pregnancy and compare the dose distribution measured using thermoluminescence dosimeters (TLDs) in the printed phantom for two different computed tomography (CT) protocols with the corresponding results of Monte Carlo simulations on voxel models of the pregnant woman.Materials and methodsThe physical phantom was produced through multi‐material extrusion printing using different print materials identified in previous studies to simulate homogeneous soft tissues and the mean compositions of maternal and fetal bones. The 3D printed abdomen was combined with a conventionally produced anthropomorphic female phantom to obtain a whole‐body phantom of a pregnant woman. Dose values resulting from two different CT scans acquired at tube voltages of 80 and 120 kV were measured using TLDs positioned in the physical phantom and cross‐validated with the results of Monte Carlo simulations performed for two different voxel models. The first was a voxelized model of the produced phantom itself and the second a realistic digital model of a pregnant woman. Representative CT values of the materials used in the printed phantom were determined from the acquired CT images.ResultsThe CT values of maternal and fetal tissue structures in the phantom are comparable to CT values of real human tissues. The difference between most organ doses measured in the 3D printed phantom and simulated in the voxel models was below 20% and equivalent within the measurement uncertainties. Only the dose to the fetal head was up to 50% higher and not equivalent for the realistic model and the 80 kV‐protocol. As expected, the agreement was better for the voxelized than for the realistic model. For both models a slight energy dependence was observed, with larger deviations for the 80‐kV protocol especially for organs located in the pelvic region.ConclusionIndividualized physical body phantoms, such as that of a pregnant woman, can be produced using 3D printing. The good agreement between measured and simulated doses to the fetus cross‐validates both dosimetric methods. Therefore, this study demonstrates the suitability of 3D printing phantoms for patients not adequately represented by commercially available body phantoms of reference persons.

Prior-image-based low-dose CT reconstruction for adaptive radiation therapy.

The study aims to reduce the imaging radiation dose in Adaptive Radiotherapy (ART) while maintaining high-quality CT images, critical for effective treatment planning and monitoring. We developed the Prior-aware Learned Primal-Dual Network (pLPD-UNet), which uses prior CT images to enhance reconstructions from low-dose scans. The network was separately trained on thorax and abdomen datasets to accommodate the unique imaging requirements of each anatomical region. The pLPD-UNet demonstrated improved reconstruction accuracy and robustness in handling sparse data compared to traditional methods. It effectively maintained image quality essential for precise organ delineation and dose calculation, while achieving a significant reduction in radiation exposure. This method offers a significant advancement in the practice of ART by integrating prior imaging data, potentially setting a new standard for balancing radiation safety with the need for high-resolution imaging in cancer treatment planning.

2128: Individual organ dose calculations from CT imaging of Hodgkin lymphoma patients treated with protons

2128: Individual organ dose calculations from CT imaging of Hodgkin lymphoma patients treated with protons

Innovative nano-shielding for minimizing stray radiation dose in external radiation therapy: A promising approach to enhance patient safety

This study investigates the effectiveness of novel nanocomposite shielding materials in reducing out-of-field radiation doses during radiation therapy, employing Geant4 Monte Carlo (MC) simulations alongside an anthropomorphic female phantom. The research focuses on two radiation modalities: 6 MV beams with and without flattening filters. Utilizing the Geant4 MC code, detailed simulations of a Varian Clinac 2100C/D linear accelerator and an ICRP-145 mesh-type human phantom were conducted to estimate the doses to out-of-field organs from unintended secondary radiation. This involved simulating a comprehensive linac model, including all relevant beam-line components, and assessing the shielding effects of three different nanocomposites doped with metal nanoparticles at various thicknesses. The nanocomposites, comprising Polytetrafluoroethylene (PTFE), with PtO2, IrO2, and Bi2O3 nanoparticles, were evaluated for their potential to reduce patient organ doses from stray photon doses. The results showed that these materials could significantly lower radiation exposure to non-target tissues.

2406: A novel MR-guided treatment planning tool reduces accumulated critical organ dose in prostate cancer

2406: A novel MR-guided treatment planning tool reduces accumulated critical organ dose in prostate cancer

The determination of coefficients for size specific effective dose for adult and pediatric patients undergoing routine computed tomography examinations.

The effective dose resulting from computed tomography (CT) scans provides an assessment of the risk associated with stochastic effects but does not account for the patient's size. Advances in Monte Carlo simulations offer the potential to obtain organ dose data from phantoms of varying stature, enabling derivation of a size-specific effective doses (SEDs) representing doses to individual patients. This study aimed to compute size-specific k-conversion factors for SED in routine CT examinations for adult and pediatric patients of different sizes. Radiation interactions were simulated for adult and pediatric phantom models of various sizes using National Cancer Institute CT version 3.0.20211123. Subsequent calculations of SED were performed, and coefficients for SED were derived, considering the variations in body sizes. The results revealed a strong correlation between effective diameter and weight, observed with size-specific k-conversion factors for adult and pediatric phantoms, respectively. While size-specific k-conversion factors for CT brain remained constant in adults, values for pediatric cases varied. When using the tube current modulation (TCM) system, size-specific k-conversion factors increased in larger phantoms and decreased in smaller ones. The extent of this increase or decrease correlated with the set TCM strength. This study provides coefficients for estimating SEDs in routine CT exams. Software utilizing look-up tables of coefficients can be used to provide dose information for CT scanners at local hospitals, offering guidance to practitioners on doses to individual patients and improving radiation risk awareness in clinical practice.

3D small-scale dosimetry and tumor control of 225Ac radiopharmaceuticals for prostate cancer

Radiopharmaceutical therapy using α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upalpha$$\\end{document}-emitting 225\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{225}$$\\end{document}Ac is an emerging treatment for patients with advanced metastatic cancers. Measurement of the spatial dose distribution in organs and tumors is needed to inform treatment dose prescription and reduce off-target toxicity, at not only organ but also sub-organ scales. Digital autoradiography with α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upalpha$$\\end{document}-sensitive detection devices can measure radioactivity distributions at 20–40 μm\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu {\\hbox {m}}$$\\end{document} resolution, but anatomical characterization is typically limited to 2D. We collected digital autoradiographs across whole tissues to generate 3D dose volumes and used them to evaluate the simultaneous tumor control and regional kidney dosimetry of a novel therapeutic radiopharmaceutical for prostate cancer, [225Ac]Ac-Macropa-PEG4-YS5, in mice. 22Rv1 xenograft-bearing mice treated with 18.5 kBq of [225Ac]Ac-Macropa-PEG4-YS5 were sacrificed at 24 h and 168 h post-injection for quantitative α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upalpha$$\\end{document}-particle digital autoradiography and hematoxylin and eosin staining. Gamma-ray spectroscopy of biodistribution data was used to determine temporal dynamics and 213\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{213}$$\\end{document}Bi redistribution. Tumor control probability and sub-kidney dosimetry were assessed. Heterogeneous 225\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{225}$$\\end{document}Ac spatial distribution was observed in both tumors and kidneys. Tumor control was maintained despite heterogeneity if cold spots coincided with necrotic regions. 225\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{225}$$\\end{document}Ac dose-rate was highest in the cortex and renal vasculature. Extrapolation of tumor control suggested that kidney absorbed dose could be reduced by 41% while maintaining 90% TCP. The 3D dosimetry methods described allow for whole tumor and organ dose measurements following 225\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{225}$$\\end{document}Ac radiopharmaceutical therapy, which correlate to tumor control and toxicity outcomes.

Two-fractionated stereotactic magnetic resonance-guided adaptive radiation therapy for patients with prostate cancer (SMART PRO trial): protocol for a confirmatory clinical trial

IntroductionIn an MRI-guided linear accelerator (MR-LINAC) system, the planned doses for organs at risk and for tumours are assessed by MR imaging and re-contouring at every treatment. This allows treatment...

Effects of organ dose modulation applied to a part of the scan range on radiation dose in computed tomography of the body

In computed tomography (CT), organ dose modulation (ODM) reduces radiation exposure from the anterior side to reduce radiation dose received by the radiosensitive organs located anteriorly. We investigated the effects of ODM applied to a part of the scan range on radiation dose in body CT. The thorax and thoraco-abdominopelvic region of an anthropomorphic whole-body phantom were imaged with and without ODM. ODM was applied to various regions, and the tube current modulation curves were compared. Additionally, the dose indices were compared with and without ODM in thoracic and thoraco-abdominopelvic CTs in 800 patients. ODM was applied to the thyroid in male patients and to the thyroid and breast in female patients. In phantom imaging of the thorax, the application of ODM below the scan range decreased the tube current, and that to the breast showed a further decrease. Decreased tube current was also observed in phantom imaging of the thoraco-abdominopelvic regions with ODM below the scan range, and the application of ODM to the whole scan range, thyroid, breast, and both thyroid and breast further reduced the tube current in the region to which ODM was applied. In patient imaging, the dose indices were significantly lower with ODM than without ODM, regardless of the scan range or sex. The absolute reduction in dose-length product was larger for thoraco-abdominopelvic CT (male, 43.2 mGy cm; female, 59.7 mGy cm) than for thoracic CT (male, 30.8 mGy cm; female, 37.6 mGy cm) in both sexes, indicating dose reduction in the abdominopelvic region to which ODM was not applied. In conclusion, The application of ODM in body CT reduces radiation dose not only in the region to which ODM is applied but also outside the region. In radiation dose management, it should be considered that even ODM applied to a limited region affects the dose indices.

A novel x-Ray and γ-Ray combination strategy for radiotherapy after breast-conserving surgery in patients with right breast cancer.

Radiotherapy is a primary therapeutic approach for breast cancer following breast-conserving surgery. The TaiChiB dual-modality radiotherapy system combining X-ray and focused γ-ray, offers a new approach to reduce the radiation dose of organs at risk (OARs) and has the potential to mitigate the adverse effects of radiotherapy. Currently, there are few studies on the dosimetric characteristics of the TaiChiB dual-modality system for actual treatment plans for specific diseases. The purpose of this work is to study the dosimetric advantages of dual-modal systems for right breast patients after breast-conserving surgery. Treatment plans for 20 patients with right breast cancer were generated for a linear accelerator (LINAC) based system and the TaiChiB dual-modality system, respectively. Volumetric modulated arc therapy plans with simultaneous integrated boost (VMAT-SIB) were made for the LINAC. Focused γ-ray was used to deliver the boost dose with the dual-modality system. The dosimetric parameters of the target and OARs were evaluated and compared between the treatment plans generated for the two systems. The TaiChiB dual-modality plans exhibit a higher conformal index (CI) and lower gradient index (GI) for the PGTV and PTV compared with the LINAC-based VMAT-SIB plans. Compared to VMAT-SIB plans, the PTV Dmax, PTV Dmean, PTV V110, PGTV Dmax, and PGTV Dmean of the TaiChiB dual-modality plans are significantly lower. Meanwhile, the dose to OARs, such as the Dmean of the heart, the V5 of liver, the Dmean of ipsilateral lung, the V30 of ipsilateral lung, the V20 of ipsilateral lung, the V5 of ipsilateral lung, the Dmean of contralateral lung, Dmax of contralateral breast and the Dmean of contralateral breast are significantly reduced. Our study demonstrates the dosimetric advantages of the novel TaiChiB dual-modality radiotherapy system for the treatment of right-sided breast cancer. Overall, for the TaiChiB dual-modality radiotherapy system, the radiation dose outside the target region decreases rapidly, thereby minimizing radiation exposure to neighboring organs and ensuring the conformity of the target area. Our research confirms the potential of the TaiChiB dual-modality system for future radiotherapy.

Fast prediction of personalized abdominal organ doses from CT examinations by radiomics feature-based machine learning models

The X-rays emitted during CT scans can increase solid cancer risks by damaging DNA, with the risk tied to patient-specific organ doses. This study aims to establish a new method to predict patient specific abdominal organ doses from CT examinations using minimized computational resources at a fast speed. The CT data of 247 abdominal patients were selected and exported to the auto-segmentation software named DeepViewer to generate abdominal regions of interest (ROIs). Radiomics feature were extracted based on the selected CT data and ROIs. Reference organ doses were obtained by GPU-based Monte Carlo simulations. The support vector regression (SVR) model was trained based on the radiomics features and reference organ doses to predict abdominal organ doses from CT examinations. The prediction performance of the SVR model was tested and verified by changing the abdominal patients of the train and test sets randomly. For the abdominal organs, the maximal difference between the reference and the predicted dose was less than 1 mGy. For the body and bowel, the organ doses were predicted with a percentage error of less than 5.2%, and the coefficient of determination (R2) reached up to 0.9. For the left kidney, right kidney, liver, and spinal cord, the mean absolute percentage error ranged from 5.1 to 8.9%, and the R2 values were more than 0.74. The SVR model could be trained to achieve accurate prediction of personalized abdominal organ doses in less than one second using a single CPU core.