Dose-volume Histograms Research Articles

Effectiveness of intraoral stentsin reducing oral adverse events during radiotherapy for maxillary or nasal cavity malignant tumors.

Many patients experience oral adverse events during head and neck cancer radiotherapy (RT). The methods of management of such events are under debate. One such technique is the intraoral stent (IOS) technique, which removes normal tissue from the irradiation field. This retrospective study examined the factors associated with the occurrence of oral mucositis (OM) and dysgeusia and the efficacy of IOSs in preventing them. Twenty-nine patients who underwent RT in the maxilla or nasal cavity between 2016 and 2022 were included. They were investigated for background characteristics, treatment factors (IOS and dose-volume histogram), and oral adverse events (OM and dysgeusia). Significant risk factors for the incidence of grade ≥ 2 (Common Terminology Criteria for Adverse Events v5.0) OM were the non-use of IOSs (p = 0.004) and diabetes (p = 0.025). A significant risk factor for the incidence of grade ≥ 1 dysgeusia was concomitant chemotherapy (p = 0.019). The radiation dose to the tongue was significantly lower in the IOS group than in the non-IOS group. Our findings suggest that the use of an IOS during RT reduces the severity of OM by reducing irradiation to the tongue. Therefore, the use of an IOS is recommended during RT performed in the maxilla or nasal cavity.

Technical note: Errors introduced when using Dose Voxel Kernels for estimating absorbed dose from radiopharmaceutical therapies involving alpha emitters.

In radiopharmaceutical therapies (RPT) involving beta emitters, absorbed dose (Dabs) calculations often employ the use of dose voxel kernels (DVK). Such methods are faster and easier to implement than Monte Carlo (MC) simulations. Using DVK methods implies a non-stochastic distribution of particles. This is a valid assumption for betas where thousands to tens of thousands of particles traversing the cell nucleus are required to achieve cell kill. However, alpha particles have linear energy transfers (LET) that are ∼500 times higher than LETs of betas. This results in a significant probability of killing a cell from even a single traversal through its nucleus. Consequently, the activity used for therapy involving alphas is very low, and the use of DVKs for estimating Dabs will generate results that may be erroneous. This work aims at illustrating how use of DVKs affect the resulting Dabs in small tumors when irradiated with clinically relevant amounts of beta- and alpha-emitters. The results are compared with those from using a Monte Carlo method where the energy deposition from individual tracks is simulated. To illustrate the issues associated with DVK for alpha radiopharmaceutical therapies at the microscale, a tumor cluster model was used to compare beta (177Lu) and alphas (211At, 225Ac, and 227Th) irradiations. We used 103 beta particles and 20 alpha particles per cell, which is within the range of the required number of particle traversals through its nucleus to sterilize a cell. Results from using both methods were presented with Dabs histograms, dose volume histograms, and Dabs error maps. For beta-emitter (177Lu) irradiating the modeled tumor cluster, resulting Dabs was similar for both DVK and MC methods. For all alpha emitters, the use of DVK led to an overestimation of Dabs when compared to results generated using a MC approach. Our results demonstrate that the use of DVK methods for alpha emitters can lead to an overestimation in the calculated Dabs. The use of DVKs for therapies involving alpha emitters may therefore not be appropriate when only referring to the mean Dabs metric.

Development of patient and catheter specific error thresholds for high dose rate prostate brachytherapy.

In-vivo source tracking has been an active topic of research in the field of high-dose rate brachytherapy in recent years to verify accuracy in treatment delivery. Although detection systems for source tracking are being developed, the allowable threshold of treatment error is still unknown and is likely patient-specific due to anatomy and planning variation. The purpose of this study was to determine patient and catheter-specific shift error thresholds for in-vivo source tracking during high-dose-rate prostate brachytherapy (HDRPBT). A module was developed in the previously described graphical processor unit multi-criteria optimization (gMCO) algorithm. The module generates systematic catheter shift errors retrospectively into HDRPBT treatment plans, performed on 50 patients. The catheter shift model iterates through the number of catheters shifted in the plan (from 1 to all catheters), the direction of shift (superior, inferior, medial, lateral, cranial, and caudal), and the magnitude of catheter shift (1-6mm). For each combination of these parameters, 200 error plans were generated, randomly selecting the catheters in the plan to shift. After shifts were applied, dose volume histogram (DVH) parameters were re-calculated. Catheter shift thresholds were then derived based on plans where DVH parameters were clinically unacceptable (prostate V100<95%, urethra D0.1cc>118%, and rectum Dmax>80%). Catheter thresholds were also Pearson correlated to catheter robustness values. Patient-specific thresholds varied between 1 to 6mm for all organs, in all shift directions. Overall, patient-specific thresholds typically decrease with an increasing number of catheters shifted. Anterior and inferior directions were less sensitive than other directions. Pearson's correlation test showed a strong correlation between catheter robustness and catheter thresholds for the rectum and urethra, with correlation values of -0.81 and -0.74, respectively (p<0.01), but no correlation was found for the prostate. It was possible to determine thresholds for each patient, with thresholds showing dependence on shift direction, and number of catheters shifted. Not every catheter combination is explorable, however, this study shows the feasibility to determine patient-specific thresholds for clinical application. The correlation of patient-specific thresholds with the equivalent robustness value indicated the need for robustness consideration during plan optimization and treatment planning.

Comparison of Doses to Parotid, Temporomandibular Joint, and Pharyngeal Constrictor Muscles Using Different Techniques in Radiotherapy for Oropharyngeal Cancer.

The purpose of this research was to compare two treatment techniques for oropharyngeal cancers: conventional linac-based static intensity-modulated radiotherapy (sIMRT) and helical tomotherapy (HT). The study examined several parameters, including target coverage, organs at risk, integral dose, and beam on time. Additionally, the study evaluated the doses to the parotid, temporomandibular joint, and pharyngeal constrictor muscles, which are important for swallowing. The present study retrospectively analyzed the data of 13 patients with oropharyngeal cancer who underwent radiotherapy between 2019 and 2021. The treatment plans for each patient were regenerated using both sIMRT and HT treatment planning systems with the sequential boost method. The techniques were evaluated and compared based on dose-volume histogram, homogeneity index, and conformity index parameters. The target coverage and organs at risk were statistically compared for two techniques. Additionally, the doses received by the healthy tissue volume were obtained for integral dose evaluation. The beam on time for each technique was assessed. When considering planning target volume evaluation, there was no difference in Dmeans between the two techniques and sIMRT demonstrated higher D2% values compared to the HT. The HT technique had better results for all organs at risk, such as the parotid, temporomandibular joint, and pharyngeal constrictor muscle. As for integral dose, it has been shown that the sIMRT technique provides better protection compared to HT. In addition, the beam on time was also longer with the HT technique. Both techniques may provide optimal target coverage for patients with oropharyngeal cancer. HT conferred notable advantages, especially with regard to critical structures implicated in swallowing, such as the parotid, temporomandibular joint, and pharyngeal constrictor muscle, in comparison to sIMRT.

A physically constrained Monte Carlo-Neural Network coupling algorithm for BNCT dose calculation.

In boron neutron capture therapy (BNCT)-a form of binary radiotherapy-the primary challenge in treatment planning systems for dose calculations arises from the time-consuming nature of the Monte Carlo (MC) method. Recent progress, including the use of neural networks (NN), has been made to accelerate BNCT dose calculations. However, this approach may result in significant dose errors in both the tumor and the skin, with the latter being a critical organ in BNCT. Furthermore, owing to the lack of physical processes in purely NN-based approaches, their reliability for clinical dose calculations in BNCT is questionable. In this study, a physically constrained MC-NN (PCMC-NN) coupling algorithm is proposed to achieve fast and accurate computation of the BNCT three-dimensional (3D) therapeutic dose distribution. This approach synergizes the high precision of the MC method with the speed of the NN and utilizes physical conservation laws to constrain the coupling process. It addresses the time-consuming issue of the traditional MC method while reducing dose errors. Clinical data were collected from 113 glioblastoma patients. For each patient, the 3D dose distributions for both the coarse and detailed dose grids were calculated using the MC code PHITS. Among these patients, the data from 14 patients were allocated to the test set, 9 to the validation set, and the remaining to the training set. A neural network, 3D-Unet, was built based on the coarse grid dose and patient CT information to enable fast and accurate computation of the 3D detailed grid dose distribution of BNCT. Statistical evaluations, including relative deviation, dose deviation, mean absolute error (MAE), and mean absolute percentage error (MAPE) were conducted. Our findings suggested that the PCMC-NN algorithm substantially outperformed the traditional NN and interpolation methods. Furthermore, the proposed algorithm significantly reduced errors, particularly in the skin and GTV, and improved computational accuracy (hereinafter referred to simply as 'accuracy') with a MAPE range of 1.6%-4.0% and a maximum MAE of 0.3Gy (IsoE) for different organs. The dose-volume histograms generated by the PCMC-NN aligned well with those obtained from the MC method, further validating its accuracy. The PCMC-NN algorithm enhanced the speed and accuracy of BNCT dose calculations by combining the MC method with the NN algorithm. This indicates the significant potential of the proposed algorithm for clinical applications in optimizing treatment planning.

Predicting radiation pneumonitis in lung cancer: a EUD-based machine learning approach for volumetric modulated arc therapy patients.

This study aims to develop an optimal machine learning model that uses lung equivalent uniform dose (lung EUD to predict radiation pneumonitis (RP) occurrence in lung cancer patients treated with volumetric modulated arc therapy (VMAT). We analyzed a cohort of 77 patients diagnosed with locally advanced squamous cell lung cancer (LASCLC) receiving concurrent chemoradiotherapy with VMAT. Patients were categorized based on the onset of grade II or higher radiation pneumonitis (RP 2+). Dose volume histogram data, extracted from the treatment planning system, were used to compute the lung EUD values for both groups using a specialized numerical analysis code. We identified the parameter α, representing the most significant relative difference in lung EUD between the two groups. The predictive potential of variables for RP2+, including physical dose metrics, lung EUD, normal tissue complication probability (NTCP) from the Lyman-Kutcher-Burman (LKB) model, and lung EUD-calibrated NTCP for affected and whole lung, underwent both univariate and multivariate analyses. Relevant variables were then employed as inputs for machine learning models: multiple logistic regression (MLR), support vector machine (SVM), decision tree (DT), and K-nearest neighbor (KNN). Each model's performance was gauged using the area under the curve (AUC), determining the best-performing model. The optimal α-value for lung EUD was 0.3, maximizing the relative lung EUD difference between the RP 2+ and non-RP 2+ groups. A strong correlation coefficient of 0.929 (P< 0.01) was observed between lung EUD (α = 0.3) and physical dose metrics. When examining predictive capabilities, lung EUD-based NTCP for the affected lung (AUC: 0.862) and whole lung (AUC: 0.815) surpassed LKB-based NTCP for the respective lungs. The decision tree (DT) model using lung EUD-based predictors emerged as the superior model, achieving an AUC of 0.98 in both training and validation datasets. The likelihood of developing RP 2+ has shown a significant correlation with the advancements in RT technology. From traditional 3-D conformal RT, lung cancer treatment methodologies have transitioned to sophisticated techniques like static IMRT. Accurately deriving such a dose-effect relationship through NTCP modeling of RP incidence is statistically challenging due to the increased number of degrees-of-freedom. To the best of our knowledge, many studies have not clarified the rationale behind setting the α-value to 0.99 or 1, despite the closely aligned calculated lung EUD and lung mean dose MLD. Perfect independence among variables is rarely achievable in real-world scenarios. Four prominent machine learning algorithms were used to devise our prediction models. The inclusion of lung EUD-based factors substantially enhanced their predictive performance for RP 2+. Our results advocate for the decision tree model with lung EUD-based predictors as the optimal prediction tool for VMAT-treated lung cancer patients. Which could replace conventional dosimetric parameters, potentially simplifying complex neural network structures in prediction models.

Evaluation of robustness of optimization methods in breast intensity-modulated radiation therapy using TomoTherapy.

Intensity-modulated radiation therapy (IMRT) has become a popular choice for breast cancer treatment. We aimed to evaluate and compare the robustness of each optimization method used for breast IMRT using TomoTherapy. A retrospective analysis was performed on 10 patients with left breast cancer. For each optimization method (clipping, virtual bolus, and skin flash), a corresponding 50Gy/25 fr plan was created in the helical and direct TomoTherapy modes. The dose-volume histogram parameters were compared after shifting the patients anteriorly and posteriorly. In the helical mode, when the patient was not shifted, the median D1cc (minimum dose delivered to 1cc of the organ volume) of the breast skin for the clipping and virtual bolus plans was 52.2 (interquartile range: 51.9-52.6) and 50.4 (50.1-50.8) Gy, respectively. After an anterior shift, D1cc of the breast skin for the clipping and virtual bolus plans was 56.0 (55.6-56.8) and 50.9 (50.5-51.3) Gy, respectively. When the direct mode was used without shifting the patient, D1cc of the breast skin for the clipping, virtual bolus, and skin flash plans was 52.6 (51.9-53.1), 53.4 (52.6-53.9), and 52.3 (51.7-53.0) Gy, respectively. After shifting anteriorly, D1cc of the breast skin for the clipping, virtual bolus, and skin flash plans was 55.6 (54.1-56.4), 52.4 (52.0-53.0), and 53.6 (52.6-54.6) Gy, respectively. The clipping method is not sufficient for breast IMRT. The virtual bolus and skin flash methods were more robust optimization methods according to our analyses.

Cone-beam computed tomography-guided online adaptive radiotherapy for pharyngeal cancer with whole neck irradiation: dose-volume histogram analysis between adapted and scheduled plans.

The present study aimed to evaluate whether an adapted plan with Ethos™ could be used for pharyngeal cancer. Ten patients with pharyngeal cancer who underwent chemoradiotherapy with available daily cone-beam computed tomography (CBCT) data were included. Simulated treatments were generated on the Ethos™ treatment emulator using CBCTs every four to five fractions for two plans: adapted and scheduled. The simulated treatments were divided into three groups: early (first-second week), middle (third-fourth week), and late (fifth-seventh week) periods. Dose-volume histogram parameters were compared for each period between the adapted and scheduled plans in terms of the planning target volume (PTV) (D98%, D95%, D50% and D2%), spinal cord (Dmax and D1cc), brainstem (Dmax) and ipsilateral and contralateral parotid glands (Dmedian and Dmean). The PTV D98%, D95% and D2% of the adapted plan were significantly higher than those of the scheduled plans in all periods, except for D98% in the late period. The adapted plan significantly reduced the spinal cord Dmax and D1cc compared with the scheduled plan in all periods. Ipsilateral and contralateral parotid glands Dmean of the adapted plan were lower than those of scheduled plan in the late period. In conclusion, the present study revealed that the adapted plans could maintain PTV coverage while reducing the doses to organs at risk in each period compared with scheduled plans.

Evaluation of gross target volumes in CECT vs MRI in head and neck cancer and its implication on concordance indices and dose-volume parameters of IMRT treatment plan

ABSTRACT Background: Although radiotherapy treatment planning (RTP) for head and neck cancers (HNCs) is based on contrast enhanced computed tomography (CECT), soft tissue contrasts are better evident on magnetic resonance imaging (MRI). We therefore evaluated dose-volume histogram (DVH) parameters along with concordance index (ConI), conformity index (CI), and homogeneity index (HI) of planning target volume (PTV) of GTV delineated on CECT vs MRI in HNCs enrolled for intensity modulated radiotherapy (IMRT). Methodology: Forty consecutive HNCs were enrolled in this study. All underwent CECT and MRI simulations with immobilization devices. GTVp and GTVn were delineated independently on CECT and MRI images. Corresponding MRI volumes were then copied to CECT. IMRT plans were generated on the CECT incorporating PTV margins. DVH parameters of PTVpn for both CECT and MRI were compared. In addition, mean (±SD) percentage difference of GTVp, GTVn, GTVpn, ConI, CI, and HI were evaluated using paired t-test. Results: The GTVp (P = 0.005), GTVn (P = 0.009), and GTVpn (P &lt; 0.001) delineated on MRI were found to be significantly larger than GTV delineated on CECT. In eight patients, GTV outlined on CECT were larger than MRI. Significant mean differences in CECT vs MRI of CI (P &lt; 0.001), HI (P &lt; 0.001), ConI (P &lt; 0.001), and DVH parameters (D2, D95, D98, V95, and V100 all P &lt; 0.001; D50: P = 0.009) were noted. Conclusion: The GTVs and corresponding PTVs were significantly larger on MRI compared to CECT. This resulted in significant differences in DVH parameters, CI, ConI, and HI. This could be improved by co-registered MRI-CECT volumes during routine IMRT treatment planning for HNCs.

RapidBrachyTG43: A Geant4-based TG-43 parameter and dose calculation module for brachytherapy dosimetry.

The AAPM TG-43U1 formalism remains the clinical standard for dosimetry of low- and high-energy -emitting brachytherapy sources. TG-43U1 and related reports provide consensus datasets of TG-43 parameters derived from various published measured data and Monte Carlo simulations. These data are used to perform standardized and fast dose calculations for brachytherapy treatmentplanning. Monte Carlo TG-43 dosimetry parameters are commonly derived to characterize novel brachytherapy sources. RapidBrachyTG43 is a module of RapidBrachyMCTPS, a Monte Carlo-based treatment planning system, designed to automate this process, requiring minimal user input to prepare Geant4-based Monte Carlo simulations for a source. RapidBrachyTG43 may also perform a TG-43 dose to water-in-water calculation for a plan, substantially accelerating the same calculation performed using RapidBrachyMCTPS's Monte Carlo dose calculationengine. TG-43 parameters , , , and were calculated using three commercial source models, one each of I, Ir, and Co, and were benchmarked to published data. TG-43 dose to water was calculated for a clinical breast brachytherapy plan and was compared to a Monte Carlo dose calculation with all patient tissues, air, and catheters set towater. TG-43 parameters for the three simulated sources agreed with benchmark datasets within tolerances specified by the High Energy Brachytherapy Dosimetry working group. A gamma index comparison between the TG-43 and Monte Carlo dose-to-water calculations with a dose difference and difference to agreement criterion of 1%/1 mm yielded a 98.9% pass rate, with all relevant dose volume histogram metrics for the plan agreeing within 1%. Performing a TG-43-based dose calculation provided an acceleration of dose-to-water calculation by a factor of165. Determination of TG-43 parameter data for novel brachytherapy sources may now be facilitated by RapidBrachyMCTPS. These parameter datasets and existing consensus or published datasets may also be used to determine the TG-43 dose for a plan inRapidBrachyMCTPS.

Potential dosimetric error in the adaptive workflow of a 1.5 T MR-Linac from patient movement relative to immobilisation systems.

In magnetic resonance- (MR-) based adaptive workflows for an MR-linac, the treatment plan is optimized and recalculated online using the daily MR images. The Unity MR-linac is supplied with a patient positioning device (ppd) using pelvic and abdomen thermoplastic masks attached to a board with high-density components. This study highlights the dosimetric effect of using this in such workflows when there are relative patient-ppd displacements, as these are not visualized on MR imaging and the treatment planning system assumes the patient is fixed relative to the ppd. The online adapted plans of two example rectum cancer patients treated at a Unity MR-linac were perturbed by introducing relative patient-ppd displacements, and the effect was evaluated on plan dosimetry. Forty-eight perturbed clinical adapted plans were recalculated, based on online MR-based synthetic computed tomography, and compared with the original plans, using dose-volume histogram parameters and gamma analysis. The target volume covered by the prescribed dose ( ) and by at least 107% of varied up to - 1.87% and + 3.67%, respectively for 0.5cm displacements, and to- 3.18% and + 4.96% for 2cm displacements; whilst 2%-2mm gamma analysis showed a median value of 92.9%. The use of a patient positioning system with high-density components in a Unity MR-based online adaptive treatment workflow can introduce unrecognized errors in plan dosimetry and it is recommended not to use such a device for such treatments, without modifying the device and the workflow, followed by careful clinical evaluation, or alternatively to use other immobilization methods.

Pharyngeal Constrictor Dose–Volume Histogram Metrics and Patient-Reported Dysphagia in Head and Neck Radiotherapy

AimsHead and neck radiotherapy long-term survival continues to improve and the management of long-term side-effects is moving to the forefront of patient care. Dysphagia is associated with dose to the pharyngeal constrictors and can be measured using patient-reported outcomes to evaluate its effect on quality of life. The aim of the present study was to relate pharyngeal constrictor dose–volume parameters with patient-reported outcomes to identify prognostic dose constraints. Materials and methodsA 64-patient training cohort and a 24-patient testing cohort of oropharynx and nasopharynx cancer patients treated with curative-intent chemoradiotherapy were retrospectively examined. These patients completed the MD Anderson Dysphagia Inventory outcome survey at 12 months post-radiotherapy to evaluate late dysphagia: a composite score lower than 60 indicated dysphagia. The pharyngeal constrictor muscles were subdivided into four substructures: superior, middle, inferior and cricopharyngeal. Dose–volume histogram (DVH) metrics for each of the structure combinations were extracted. A decision tree classifier was run for each DVH metric to identify dose constraints optimising the accuracy and sensitivity of the cohort. A 60% accuracy threshold and feature selection method were used to ensure statistically significant DVH metrics were identified. These dose constraints were then validated on the 24-patient testing cohort. ResultsExisting literature dose constraints only had two dose constraints performing above 60% accuracy and sensitivity when evaluated on our training cohort. We identified two well-performing dose constraints: the pharyngeal constrictor muscle D63% < 55 Gy and the superior–middle pharyngeal constrictor combination structure V31Gy < 100%. Both dose constraints resulted in ≥73% mean accuracy and ≥80% mean sensitivity on the training and testing patient cohorts. In addition, a pharyngeal constrictor muscle mean dose <57 Gy resulted in a mean accuracy ≥74% and mean sensitivity ≥60%. ConclusionMid-dose pharyngeal constrictor muscle and substructure combination dose constraints should be used in the treatment planning process to reduce late patient-reported dysphagia.

CNN-based multi-modal radiomics analysis of pseudo-CT utilization in MRI-only brain stereotactic radiotherapy: a feasibility study

BackgroundPseudo-computed tomography (pCT) quality is a crucial issue in magnetic resonance image (MRI)-only brain stereotactic radiotherapy (SRT), so this study systematically evaluated it from the multi-modal radiomics perspective.Methods34 cases (< 30 cm³) were retrospectively included (2021.9-2022.10). For each case, both CT and MRI scans were performed at simulation, and pCT was generated by a convolutional neural network (CNN) from planning MRI. Conformal arc or volumetric modulated arc technique was used to optimize the dose distribution. The SRT dose was compared between pCT and planning CT with dose volume histogram (DVH) metrics and gamma index. Wilcoxon test and Spearman analysis were used to identify key factors associated with dose deviations. Additionally, original image features were extracted for radiomic analysis. Tumor control probability (TCP) and normal tissue complication probability (NTCP) were employed for efficacy evaluation.ResultsThere was no significant difference between pCT and planning CT except for radiomics. The mean value of Hounsfield unit of the planning CT was slightly higher than that of pCT. The Gadolinium-based agents in planning MRI could increase DVH metrics deviation slightly. The median local gamma passing rates (1%/1 mm) between planning CTs and pCTs (non-contrast) was 92.6% (range 63.5–99.6%). Also, differences were observed in more than 85% of original radiomic features. The mean absolute deviation in TCP was 0.03%, and the NTCP difference was below 0.02%, except for the normal brain, which had a 0.16% difference. In addition, the number of SRT fractions and lesions, and lesion morphology could influence dose deviation.ConclusionsThis is the first multi-modal radiomics analysis of CNN-based pCT from planning MRI for SRT of small brain lesions, covering dosiomics and radiomics. The findings suggest the potential of pCT in SRT plan design and efficacy prediction, but caution needs to be taken for radiomic analysis.

Determination of Fractionation Scheme Based on Repair Effect Using Equivalent Uniform Dose (EUD) Model

Radiotherapy treatment planning is required to obtain an optimal balance between delivering a high dose to target volume and a low dose to organ at risks. In this planning, it is also necessary to determine the appropriate fractionation scheme for each patient. One of the commonly used methods to determine the fractionation scheme is calculating the Normal Tissue Complication Probability (NTCP) and Tumor Control Probability (TCP) parameters. In this study, the Equivalent Uniform Dose (EUD) model is used to calculate NTCP and TCP. This model is based on a non-uniform dose distribution that is sensitive to the biological factors of cells. The biological factor examined in this research is the repair effect, which is the ability of cells to repair themselves after being radiated. Thus, the objective of this research is to determine the fractionation scheme based on NTCP calculations using the EUD model while taking into account the repair effect. The data used in this study were obtained from 10 patients with glioblastoma brain cancer in the form of cumulative DVH (dose-volume histogram) and total time of radiation. Based on the NTCP calculations, the average risk of organ complication for each patient appears to be close to zero, with a range of values from 2 x 10-6% to 1 x 10-1%. These results indicate that the treatment planning conducted is proven to be safe and there are no complications for the patients. Furthermore, based on the NTCP and TCP calculations, the best fractionation scheme is hypofractionation, which remains safe while considering the dose limit for each normal organ surrounding the target.

Calculation of Organ Dose Distribution (in-field and Out-of-field) in Breast Cancer Radiotherapy on RANDO Phantom Using GEANT4 Application for Tomographic Emission (Gate) Monte Carlo Simulation.

Organ dose distribution calculation in radiotherapy and knowledge about its side effects in cancer etiology is the most concern for medical physicists. Calculation of organ dose distribution for breast cancer treatment plans with Monte Carlo (MC) simulation is the main goal of this study. Elekta Precise linear accelerator (LINAC) photon mode was simulated and verified using the GEANT4 application for tomographic emission. Eight different radiotherapy treatment plans on RANDO's phantom left breast were produced with the ISOgray treatment planning system (TPS). The simulated plans verified photon dose distribution in clinical tumor volume (CTV) with TPS dose volume histogram (DVH) and gamma index tools. To verify photon dose distribution in out-of-field organs, the point dose measurement results were compared with the same point doses in the MC simulation. Eventually, the DVHs for out-of-field organs that were extracted from the TPS and MC simulation were compared. Based on the implementation of gamma index tools with 2%/2 mm criteria, the simulated LINAC output demonstrated high agreement with the experimental measurements. Plan simulation for in-field and out-of-field organs had an acceptable agreement with TPS and experimental measurement, respectively. There was a difference between DVHs extracted from the TPS and MC simulation for out-of-field organs in low-dose parts. This difference is due to the inability of the TPS to calculate dose distribution in out-of-field organs. Based on the results, it was concluded that the treatment plans with the MC simulation have a high accuracy for the calculation of out-of-field dose distribution and could play a significant role in evaluating the important role of dose distribution for second primary cancer estimation.

Intensity-modulated vaginal brachytherapy applicator and single- and multi-channel applicators in vaginal cuff brachytherapy.

To compare the dosimetric performance of vaginal intensity-modulated brachytherapy (IM-BRT) applicator and single- (SC-BRT) and multi-channel brachytherapy (MC-BRT) applicators for vaginal cuff brachytherapy (VC-BRT). Fifteen patients with uterine-confined endometrium cancer who received adjuvant VC-BRT were included in this study. IM-BRT, SC-BRT, and MC-BRT treatment plans were created for two different clinical target volume (CTV) definitions: 1. Standard CTV, called CTVs; and 2. Virtually defined CTV, called CTVv, with asymmetrical tumor extension > 5 mm in thickness. Plan comparison was performed using dose-volume histogram (DVH) and treatment planning parameters. According to DVH analysis, D98 for CTVv and D2 for both CTVs and CTVv showed statistically significant differences between IM-BRT and SC-BRT plans, but there was no significant difference between IM-BRT and MC-BRT plans in terms of D98 and D2 for both CTVs and CTVv. Additionally, for CTVv plans, IM-BRT was found to be significantly superior to SC-BRT for the rectum (D2cc, V5Gy, and V7Gy), bladder (D2cc and V7Gy), and small bowel (D2cc, V5Gy, and V7Gy). On the other hand, DVH parameters of the sigmoid showed large difference between IM-BRT and SC-BRT plans, but it was not statistically significant. Similarly, the use of IM-BRT applicator demonstrated a noticeable dose reduction in all defined OARs when compared with MC-BRT applicator, but statistically significant for the rectum V7Gy (p = 0.03) only. While the IM-BRT applicator is still in pre-clinical phase, our investigation demonstrated the proof-of-concept in real patient treatment plans with promising dosimetric results compared with SC-BRT and MC-BRT plans in selected patient group.

Comparative analysis of two dose-volume histogram prediction tools for treatment planning in volumetric-modulated arc therapy: A multi-planner study

The increase in high-precision radiation therapy, particularly volumetric-modulated arc therapy (VMAT), has increased patient numbers and expanded treatment sites. However, a significant challenge in VMAT treatment planning is the inconsistent plan quality among different planners and facilities. This study explored the use of dose-volume histogram (DVH) prediction tools to address these disparities, specifically focusing on RapidPlan (Varian Medical Systems) and PlanIQ (Sun Nuclear). RapidPlan predicts achievable DVHs and automatically generates optimization objectives. While it has demonstrated organ-at-risk (OAR) dose reduction benefits, the quality of the plan used to build its model significantly affects its predictions. On the other hand, PlanIQ offers ease of use and does not require prior model-building. Five planners participated in this study, each creating two treatment plans: one referencing RapidPlan and the other using PlanIQ. The planners had the freedom to adjust parameters while referencing the DVH predictions. The plans were evaluated using “Plan Quality Metric” (PQM) scores to assess the planning target volume excluding the rectum and OARs. The results revealed that RapidPlan-referenced plans often outperformed PlanIQ-based plans, with less interplanner variability. PlanIQ played a pivotal role in the construction of the RapidPlan model. This study is the first to compare plans generated by multiple planners using both tools. This study provides insights into optimizing treatment planning by considering the characteristics of both RapidPlan and PlanIQ.

Delta4-based Dosimetric Error Detection in Volumetric-modulated Arc Therapy: Clinical Significance and Implications.

Volumetric-modulated arc therapy (VMAT) is an efficient method of administering intensity-modulated radiotherapy beams. The Delta4 device was employed to examine patient data. The utility of the Delta4 device in identifying errors for patient-specific quality assurance of VMAT plans was studied in this research. Intentional errors were purposely created in the collimator rotation, gantry rotation, multileaf collimator (MLC) position displacement, and increase in the number of monitor units (MU). The results show that when the characteristics of the treatment plans were changed, the gamma passing rate (GPR) decreased. The largest percentage of erroneous detection was seen in the increasing number of MU, with a GPR ranging from 41 to 92. Gamma analysis was used to compare the dose distributions of the original and intentional error designs using the 2%/2 mm criteria. The percentage of dose errors (DEs) in the dose-volume histogram (DVH) was also analyzed, and the statistical association was assessed using logistic regression. A modest association (Pearson's R-values: 0.12-0.67) was seen between the DE and GPR in all intentional plans. The findings indicated a moderate association between DVH and GPR. The data reveal that Delta4 is effective in detecting mistakes in treatment regimens for head-and-neck cancer as well as lung cancer. The study results also imply that Delta4 can detect errors in VMAT plans, depending on the details of the defects and the treatment plans employed.

Comparative Analysis of Dosimetry: IMRT versus 3DCRT in Left-Sided Breast Cancer Patients with Considering Some Organs in Out - of - Field Borders.

The local management approach for node-positive breast cancer has undergone substantial evolution. Consequently, there exists a pressing need to enhance our treatment strategies by placing greater emphasis on planning and dosimetric factors, given the availability of more conformal techniques and delineation criteria, achieving optimal goals of radiotherapy treatment. The primary aim of this article is to discuss how the extent of regional nodal coverage influences the choice between IMRT and 3D radiation therapy for patients. A total of 15 patients diagnosed with left breast cancer with disease involved lymph nodes were included in this study. Delivering the recommended dose required the use of a linear accelerator (LINAC) with photon beams energy of 6 mega voltage (6MV). Each patient had full breast radiation using two planning procedures: intensity-modulated radiotherapy (IMRT) and three-dimensional radiotherapy (3D conformal). Following the guidelines set forth by the Radiation Therapy Oncology Group (RTOG), the planned treatment coverage was carefully designed to fall between 95% and 107% of the recommended dose. Additionally, Dose Volume Histograms (DVHs) were generated the dose distribution within these anatomical contours. The DVH parameters were subjected to a comparative analysis, focusing on the doses absorbed by both Organs at Risk (OARs) and the Planning Target Volume (PTV). The findings suggest that low doses in IMRT plan might raise the risk of adverse oncological outcomes or potentially result in an increased incidence of subsequent malignancies. Consequently, the adoption of inverse IMRT remains limited, and the decision to opt for this therapy should be reserved for situations where it is genuinely necessary to uphold a satisfactory quality of life. Additionally, this approach helps in reducing the likelihood of developing thyroid problems and mitigates the risk of injuries to the supraclavicular area and the proximal head of the humerus bone.

Comparative Analysis of VMAT and IMRT Techniques: Evaluation of Dose Constraints and Bone Marrow Sparing in Cervical Cancer Patients Undergoing Chemoradiotherapy.

Carcinoma of the cervix is a globally significant cause of morbidity and mortality among women. Concurrent chemoradiotherapy, a standard approach for locally advanced cervical cancer, invariably involves pelvic irradiation. Although this strategy is effective, it inevitably affects the pelvic bone marrow, a crucial hematopoietic site, and leads to hematological toxicity The potential of IMRT to spare bone marrow in pelvic irradiation settings has been an area of significant interest, with the aim to mitigate the hematological toxicity associated with pelvic radiotherapy. Radiotherapy techniques have evolved in terms of conformity and normal tissue sparing. Our study intends to explore the use of BM sparing techniques among patients of carcinoma cervix. Twenty patients of carcinoma cervix FIGO Stage IIIB treated with concurrent chemoradiotherapy were selected for this study. The external contour of bones was delineated on planning CT as a surrogate for BM. We generated three plans on a single patient:1. without BM as the dose constraint, namely N-IMRT plan; 2. with BM constraint, namely BMS-IMRT plan; 3. VMAT plan in which BM constraint was given. The dose volume histogram (DVH) for planning target volume (PTV) and organs at risk (OAR) were analyzed. BM parameters: V10, V20, V30, V40, mean, maximum and minimum dose were compared. Results: PTV coverage was comparable in all techniques. VMAT plans resulted in superior BM sparing compared with N-IMRT plan (P-<0.001) and BMS-IMRT plan (P-<0.001, 0.021 and 0.001 respectively for V20, V30 and V40). VMAT plans had better CI compared with BMS-IMRT (P-0.002) and N-IMRT (P-0.001) plans. Our study adds to the growing evidence that VMAT might be the preferred technique for patients with carcinoma of the cervix undergoing concurrent chemoradiotherapy, as it provides comparable target coverage and better sparing of bone marrow compared to IMRT.