Methodology for integrating MCNP6 Monte Carlo simulation into PLUNC for prostate brachytherapy planning

In this study, we evaluate dosimetric advantages of using patient‐specific aperture system with intensity‐modulated proton therapy (IMPT) for head and neck tumors at the shallow depth. We used four types of patient‐specific aperture system (PSAS) to irradiate shallow regions less than 4 g/cm2 with a sharp lateral penumbra. Ten head and neck IMPT plans with or without aperture were optimized separately with the same 95% prescription dose and same dose constraint for organs at risk (OARs). The plans were compared using dose volume histograms (DVHs), dose distributions, and some dose indexes such as volume receiving 50% of the prescribed dose (V50), mean or maximum dose (Dmean and Dmax) to the OARs. All examples verified in this study had decreased V50 and OAR doses. Average, maximum, and minimum relative reductions of V50 were 15.4%, 38.9%, and 1.0%, respectively. Dmax and Dmean of OARs were decreased by 0.3% to 25.7% and by 1.0% to 46.3%, respectively. The plans with the aperture over more than half of the field showed decreased V50 or OAR dose by more than 10%. The dosimetric advantage of patient‐specific apertures with IMPT was clarified in many cases. The PSAS has some dosimetric advantages for clinical use, and in some cases, it enables to fulfill dose constraints.

Ion therapy guideline (Version 2020)

An Assessment of Organ-at-Risk Dose and Interfraction Variability Using 4 Different Applicators for Intracavitary Gynecologic HDR Brachytherapy

ProposeProton therapy of esophageal cancer is beneficial to spare normal tissue in clinical practice. However, intra-fractional and inter-fractional variance of tumor motion during treatment may compromise target coverage. The purpose of this study was to investigate the interplay effect due to intra-fractional motion and the effect of the robust optimization parameters for inter-fractional motion in the intensity modulation proton therapy (IMPT).Materials and methodsThis study retrospectively analyzed 42 patients with esophageal cancer treated at Shandong Cancer Hospital. The patients were divided into two groups. Twenty-one patients had a 4DCT image with 10 respiratory phases reconstructed (Gintra). In addition, twenty-one patients underwent a second 3D CT scan following the initial one (Ginter). The RayStation11B treatment planning system was used to create the IMPT plans for these two groups of patients. All patients were planned with a prescribed dose of 50.4 Gy (RBE) in 28 fractions for clinical target volume (CTV). 4D dynamic dose (4DDD) was then calculated to assess the interplay effect by considering respiratory motion and dynamic beam delivery for Gintra. Seven IMPT plans with different robust optimization parameters were designed for the 21 Ginter patient. The setup uncertainties were set to ± 0–6 mm for Ginter. Plan quality and dose-volume histogram (DVH) parameters for the target and organs at risk (OARs) were then analyzed.ResultsFor Gintra, 4DDD was slightly perturbated compared to the nominal plan dose. The mean value of CTV D98% of nominal dose and 4DDD were 49.9 and 49.1 Gy (RBE), respectively, and the CTV D95% were 50.4 and 49.9 Gy (RBE), respectively. For Ginter, the DVH parameters of the target area and the OARs showed a linear relationship with the corresponding robust optimization parameters in IMPT. When the robust optimization parameters were set with a larger value, the dose coverage of the target was improved. However, the dose of OARs increased at the same time. The D98% of the target for the seven plans (setup6, setup5, setup4, setup3, setup2, setup1, setup0 plan) were 49.42 ± 0.75, 48.95 ± 1.21, 48.54 ± 1.48, 47.55 ± 2.31, 47.07 ± 2.71, 44.58 ± 4.20 and 44.02 ± 4.44 Gy(RBE), respectively. The Dmean of heart were 12.18 ± 3.05, 11.28 ± 2.86, 10.90 ± 2.77, 9.76 ± 2.39, 9.73 ± 2.39, 8.33 ± 2.22 and 8.22 ± 2.20 Gy (RBE), respectively.ConclusionIn this study, the differences in dose distributions between the 4DDD and nominal plans for Gintra can be attributed to the interplay effects. While target coverage remained stable, variations in OAR doses should be evaluated for Gintra. For Ginter, smaller setup uncertainty parameters may not fully mitigate inter-fractional tumor motion, leading to greater variation in target dose and potential inadequate coverage. The linear relationship between setup uncertainty and D98% suggested that improved setup uncertainties can enhance target coverage, while higher setup uncertainties tend to increase OARs doses, particularly to the heart and lungs.

Determining whether input features are consistently strongly correlated with organ-at-risk (OAR) dose across different diseases can improve the accuracy of dose-volume histogram (DVH) prediction in knowledge-based treatment planning. In this study, we utilized patient geometric and dosimetric data to establish correlations with OAR doses and investigated the differences between distance-to-dose and dosimetric-to-dose relationships. Ninety nasopharyngeal cancer radiotherapy plans, 66 esophageal cancer radiotherapy plans and 52 rectal cancer radiotherapy plans were selected as study objects. Geometric feature was quantified by the distance-to-target histogram (DTH), and dosimetric feature was quantified by the conformal-plan-dose-volume histogram (CPDVH). The distance-to-dose correlation and dosimetric feature-to-dose correlation were calculated. DTH-DVH and CPDVH-DVH correlations were calculated for fractional OAR volumes of 30%, 50% and 60%. The correlations were calculated using the Pearson product-moment correlation coefficient (R). Compared to the distance-to-dose correlation, dosimetric feature achieved a stronger correlation (R) with OAR doses for 10 out of 13 OARs, including those to the brainstem (− 0.83, 0.93) and lung (− 0.60, 0.92). Compared to the DTH-DVH correlation, the CPDVH dose-volume achieved a stronger correlation (R) with the DVH dose-volume for 10 out of 13 OARs, including the brainstem (mean, − 0.67 vs. 0.80) and lung (mean, − 0.64 vs. 0.76). Compared to the CPDVH-DVH correlation, the DTH distance-volume showed a stronger correlation with the DVH dose-volume at the parotid (mean, − 0.88 vs. 0.60) and bladder (mean, − 0.56 vs. 0.46). The results indicated that the dosimetric feature showed a stronger correlation with most OAR doses than the distance-to-dose correlation, which is helpful for accurate DVH prediction. Patient geometry influences dosimetric feature-to-dose correlation when many OARs voxels are located inside the C-shaped target region or when the OARs significantly overlap with the target, and using only dosimetric feature for the DVH prediction of these OARs is not appropriate.

Standardized patient-specific pretreatment dosimetry planning is mandatory in the modern era of nuclear molecular radiotherapy, which may eventually lead to improvements in the final therapeutic outcome. Only a comprehensive definition of a dosage therapeutic window encompassing the range of absorbed doses, that is, helpful without being detrimental can lead to therapy individualization and improved outcomes. As a result, setting absorbed dose safety limits for organs at risk (OARs) requires knowledge of the absorbed dose-effect relationship. Data sets of consistent and reliable inter-center dosimetry findings are required to characterize this relationship. We developed and standardized a new pretreatment planning model consisting of a predictive dosimetry procedure for OARs in patients with neuroendocrine tumors (NETs) treated with 177 Lu-DOTATATE (Lutathera). In the retrospective study described herein, we used machine learning (ML) regression algorithms to predict absorbed doses in OARs by exploiting a combination of radiomic and dosiomic features extracted from patients' imaging data. Pretreatment and posttreatment data for 20 patients with NETs treated with 177 Lu-DOTATATE were collected from two clinical centers. A total of 3412 radiomic and dosiomic features were extracted from the patients' computed tomography (CT) scans and dose maps, respectively. All dose maps were generated using Monte Carlo simulations. An ML regression model was designed based on ML algorithms for predicting the absorbed dose in every OAR (liver, left kidney, right kidney, and spleen) before and after the therapy and between each therapy session, thus predicting any possible radiotoxic effects. We evaluated nine ML regression algorithms. Our predictive model achieved a mean absolute dose error (MAE, in Gy) of 0.61 for the liver, 1.58 for the spleen, 1.30 for the left kidney, and 1.35 for the right kidney between pretherapy 68 Ga-DOTATOC positron emission tomography (PET)/CT and posttherapy 177 Lu-DOTATATE single photon emission (SPECT)/CT scans. Τhe best predictive performance observed was based on the gradient boost for the liver, the left kidney and the right kidney, and on the extra tree regressor for the spleen. Evaluation of the model's performance according to its ability to predict the absorbed dose in each OAR in every possible combination of pretherapy 68 Ga-DOTATOC PET/CT and any posttherapy 177 Lu-DOTATATE treatment cycle SPECT/CT scans as well as any 177 Lu-DOTATATE SPECT/CT treatment cycle and the consequent 177 Lu-DOTATATE SPECT/CT treatment cycle revealed mean absorbed dose differences ranges from -0.55 to 0.68Gy. Incorporating radiodosiomics features from the 68 Ga-DOTATOC PET/CT and first 177 Lu-DOTATATE SPECT/CT treatment cycle scans further improved the precision and minimized the standard deviation of the predictions in nine out of 12 instances. An average improvement of 57.34% was observed (range: 17.53%-96.12%). However, it's important to note that in three instances (i.e., Ga,C.1→C3 in spleen and left kidney, and Ga,C.1→C2 in right kidney) we did not observe an improvement (absolute differences of 0.17, 0.08, and 0.05Gy, respectively). Wavelet-based features proved to have high correlated predictive value, whereas non-linear-based ML regression algorithms proved to be more capable than the linear-based of producing precise prediction in our case. The combination of radiomics and dosiomics has potential utility for personalized molecular radiotherapy (PMR) response evaluation and OAR dose prediction. These radiodosiomic features can potentially provide information on any possible disease recurrence and may be highly useful in clinical decision-making, especially regarding dose escalation issues.

Objective. To create two non-coplanar, stereotactic ablative radiotherapy (SABR) lung patient treatment plans compliant with the radiation therapy oncology group (RTOG) 0813 dosimetric criteria using a simple, isocentric, therapy with kilovoltage arcs (SITKA) system designed to provide low cost external radiotherapy treatments for low- and middle-income countries (LMICs). Approach. A treatment machine design has been proposed featuring a 320 kVp x-ray tube mounted on a gantry. A deep learning cone-beam CT (CBCT) to synthetic CT (sCT) method was employed to remove the additional cost of planning CTs. A novel inverse treatment planning approach using GPU backprojection was used to create a highly non-coplanar treatment plan with circular beam shapes generated by an iris collimator. Treatments were planned and simulated using the TOPAS Monte Carlo (MC) code for two lung patients. Dose distributions were compared to 6 MV volumetric modulated arc therapy (VMAT) planned in Eclipse on the same cases for a Truebeam linac as well as obeying the RTOG 0813 protocols for lung SABR treatments with a prescribed dose of 50 Gy. Main results. The low-cost SITKA treatments were compliant with all RTOG 0813 dosimetric criteria. SITKA treatments showed, on average, a 6.7 and 4.9 Gy reduction of the maximum dose in soft tissue organs at risk (OARs) as compared to VMAT, for the two patients respectively. This was accompanied by a small increase in the mean dose of 0.17 and 0.30 Gy in soft tissue OARs. Significance. The proposed SITKA system offers a maximally low-cost, effective alternative to conventional radiotherapy systems for lung cancer patients, particularly in low-income countries. The system’s non-coplanar, isocentric approach, coupled with the deep learning CBCT to sCT and GPU backprojection-based inverse treatment planning, offers lower maximum doses in OARs and comparable conformity to VMAT plans at a fraction of the cost of conventional radiotherapy.

In brachytherapy for cervix cancer, doses to organs at risk (OARs) are traditionally calculated using the ICRU-38 point doses to rectum and bladder. Three-dimensional image-guided brachytherapy allows assessment of OAR dose with dose volume histograms (DVHs). The purpose of this study was to analyse the correlation between DVHs and ICRU point doses. Using the PLATO™ planning system, the bladder, rectum and sigmoid were retrospectively contoured on 62 CT datasets for 20 patients treated with definitive radiotherapy. The median external beam radiotherapy dose was 45 Gy. Brachytherapy was delivered using a CT-MRI compatible tandem and ovoids to a median dose of 24 Gy in three fractions. DVHs were calculated, and the minimum dose to 2 cc of tissue receiving the highest dose (D(2cc) ) was recorded and compared with the ICRU point doses (D(ICRU) ). The mean rectal D(ICRU) was 4.01 Gy compared with D(2cc) of 4.28 Gy. The mean bladder D(ICRU) was 6.74 Gy compared with D(2cc) of 8.65 Gy. The mean sigmoid D(2cc) was 4.58 Gy. The mean dose ratios (D(2cc) /D(ICRU) ) were 1.08 for rectum and 1.39 for bladder. D(ICRU) correlated with D(2cc) for rectum (r = 0.76, P = 0.001) and for bladder (r = 0.78, P = 0.01). OAR doses assessed by DVH criteria were higher than ICRU point doses. The significant correlation between D(2cc) and D(ICRU) has allowed us to set DVH dose constraints for CT-based brachytherapy and thus begin the transition from two-dimensional to three-dimensional image-guided brachytherapy planning.

Weak correlation between gamma passing rates and dose differences in target volumes and organs at risk (OARs) has been reported in several studies. Evaluation on the differences between planned dose-volume histogram (DVH) and reconstructed DVH from measurement was adopted and incorporated into patient-specific quality assurance (PSQA). However, it is difficult to develop a methodology allowing the evaluation of errors on DVHs accurately and quickly. To develop a DVH-based pretreatment PSQA for volumetric modulated arc therapy (VMAT) with combined deep learning (DL) and machine learning models to overcome the limitation of conventional gamma index (GI) and improve the efficiency of DVH-based PSQA. A DL model with a three-dimensional squeeze-and-excitation residual blocks incorporated into a modified U-net was developed to predict the measured PSQA DVHs of 208 head-and-neck (H&N) cancer patients underwent VMAT between 2018 and 2021 from two hospitals, in which 162 cases was randomly selected for training, 18 for validation, and 28 for testing. After evaluating the differences between treatment planning system (TPS) and PSQA DVHs predicted by DL model with multiple metrics, a pass or fail (PoF) classification model was developed using XGBoost algorithm. Evaluation of domain experts on dose errors between TPS and reconstructed PSQA DVHs was taken as ground truth for PoF classification model training. The prediction model was able to achieve a good agreement between predicted, measured, and TPS doses. Quantitative evaluation demonstrated no significant difference between predicted PSQA dose and measured dose for target and OARs, except for Dmean of PTV6900 (p=0.001), D50 of PTV6000 (p=0.014), D2 of PTV5400 (p=0.009), D50 of left parotid (p=0.015), and Dmax of left inner ear (p=0.007). The XGBoost model achieved an area under curves, accuracy, sensitivity, and specificity of 0.89 versus 0.88, 0.89 versus 0.86, 0. 71 versus 0.71, and 0.95 versus 0.91 with measured and predicted PSQA doses, respectively. The agreement between domain experts and the classification model was 86% for 28 test cases. The successful prediction of PSQA doses and classification of PoF for H&N VMAT PSQA indicating that this DVH-based PSQA method is promising to overcome the limitations of GI and to improve the efficiency and accuracy of VMAT delivery.

The purpose of this study is to investigate whether quality assurance (QA) for cone-beam computed tomography (CBCT) image rotation is necessary in order to ensure the accuracy of CBCT based image-guided radiation therapy (IGRT) and adaptive radiotherapy (ART). Misregistration of angular coordinates during CBCT acquisition may lead to a rotated reconstructed image. If target localization is performed based on this image, an under- or over-dosage of the target volume (TV) and organs at risk (OARs) may occur. Therefore, patient CT image sets were rotated by 1° up to 3° and the treatment plans were recalculated to quantify changes in dose–volume histograms. A computer code in C++ was written to model the TV displacement and overlap area of an ellipse shape at the target and dose prescription levels corresponding to the image rotation. We investigated clinical scenarios in IGRT and ART in order to study the implications of image rotation on dose distributions for: (1) lateral TV and isocenter (SBRT), (2) central TV and isocenter (IMRT), (3) lateral TV and isocenter (IMRT). Mathematical analysis showed the dose coverage of TV depends on its shape, size, location, and orientation relative to the isocenter. Evaluation of three first scenario for θ = 1° showed variations in TV D95 in the context of IGRT and ART when compared to the original plan were within 2.7 ± 2.6% and 7.7 ± 6.9% respectively while variations in the second and third scenarios were less significant (<0.5%) for the angular range evaluated. However a larger degree of variation was found in terms of minimum and maximum doses for target and OARs. The rotation of CBCT image data sets may have significant dosimetric consequences in IGRT and ART. The TV's location relative to isocenter and shape determine the extent of alterations in dose indicators. Our findings suggest that a CBCT QA criterion of 1° would be a reasonable action level to ensure accurate dose delivery.

O10. Optimism or Greed: Methods of dose escalation in IGABT through total dose constraint optimization

Purpose: Intracavitary brachytherapy (IBT) is the standard boost treatment for patients with locally advanced cervical cancer. Volumetric modulated arc therapy (VMAT) boost serves as an alternative to IBT boost, but it has inferior target tumour coverage and organ at risk (OAR) sparing. In this study, a pear-shaped dose distribution was generated in the applicator-guided (AG)-VMAT boost on the existing IBT boost patient by an intercomparison with the existing VMAT boost practice. Method: The treatment plan of eight patients treated with the VMAT boost and ten patients treated with the IBT boost was analysed. Then, the IBT boost CT images were exported from the OnCentra Brachytherapy treatment planning system (TPS) to Eclipse TPS to plan AG-VMAT boost to reproduce the pear-shaped dose distribution. Result: AG-VMAT boost successfully reproduced the pear-shaped outline using the 100% isodose line from the IBT boost. The IBT boost treatment planning had the best dosimetry coverage for tumours by D90 23·33 Gy and CI 1·00. The D2cc of the bladder, rectum and femoral heads in the VMAT boost were in significantly higher doses than IBT and AG-VMAT boosts (p ≤ 0·05). The cumulative EQD2 for the D90 in the IBT boost only fell within the tolerance limit. Meanwhile, the D2cc of all the OAR doses in these three techniques was within the dose constraint set by the American Brachytherapy Society (ABS). Conclusion: 24 Gy/3 fractions AG-VMAT boost successfully reproduced the pear-shaped dose distribution for D90 of the target, with D2cc of the OAR remaining within the ABS limit.

A treatment planning system (TPS) produces volumetric modulated arc therapy (VMAT) plans by applying an optimization process to an objective function, followed by an accurate calculation of the final, deliverable dose. However, during the optimization step, a rapid dose calculation algorithm is required, which reduces its accuracy and its representation of the objective function space. Monte Carlo (MC) routines, considered the gold standard in accuracy, are currently too slow for practical comprehensive VMAT optimization. Therefore, we propose a novel approach called enhanced optimization (EO), which employs the TPS VMAT plan as a starting point, and applies small perturbations to nudge the solution closer to a true objective minimum. The perturbations consist of beamlet dose matrices, calculated using MC routines on a distributed-computing framework. DICOM files for clinical VMAT plans files are exported from the TPS and used to generate input files for the EGSnrc MC toolkit. Beamlet doses are calculated using the MC routines, each corresponding to a single multileaf collimator leaf from a single control point traveling 0.5cm in or out of the field. A typical VMAT plan requires 5000 to 10000 beamlets, which may be calculated overnight. This results in a ternary-valued objective function, which may use the same clinical objectives as the original VMAT plan. A simple greedy search algorithm is applied to minimize this function and determine the optimal set of ternary variables. The resulting modified control point parameters are imported into the TPS to calculate the final, deliverable dose, and to compare the EO plan with the original. EO was evaluated retrospectively on seven VMAT plans (two adult brain, one pediatric brain, two head and neck, and two prostate). Additionally, the use of stricter objectives was investigated for two of the cases: the left cochlea planning organ at risk (OAR) volume objective for the pediatric brain case, and the rectum objective for a prostate case. EO produced improved objective scores (by 6% to 60%) and dose-volume histograms (DVH) for the brain plans and the head and neck plans. For each of these plans, the target dose minimum and homogeneity were preserved, while one or more of the OAR DVH's was reduced. Although EO also reduced the objective scores for the prostate plans (by 46% and 79%), their absolute score and DVH improvements were not substantial. The stricter objective on the pediatric brain case resulted in lower dose to the OAR without compromising the target dose. However, the rectum dose in the prostate case could not be improved without reducing dose homogeneity to the planning target volume, suggesting that VMAT prostate cases may already be highly optimized by the TPS. We have developed a novel approach to improving the dose distribution of VMAT plans, which relies on MC calculations to provide small modifications to the control points. This method may be particularly useful for complex treatments in which a certain OAR is of concern and it is difficult for the treatment planner to obtain an acceptable solution with the TPS. Further development will reduce the beamlet computation time and result in more sophisticated EO treatment planning methods.

PurposeNeutron therapy is a high linear energy transfer modality that is useful for the treatment of radioresistant head and neck (H&N) cancers. It has been limited to 3-dimensioanal conformal-based fast-neutron therapy (3DCNT), but recent technical advances have enabled the clinical implementation of intensity-modulated neutron therapy (IMNT). This study evaluated the comparative dosimetry of IMNT and 3DCNT plans for the treatment of H&N cancers.Materials and MethodsSeven H&N IMNT plans were retrospectively created for patients previously treated with 3DCNT at the University of Washington (Seattle). A custom RayStation model with neutron-specific scattering kernels was used for inverse planning. Organ-at-risk (OAR) objectives from the original 3DCNT plan were initially used and were then systematically reduced to investigate the feasibility of improving a therapeutic ratio, defined as the ratio of the mean tumor to OAR dose. The IMNT and 3DCNT plan quality was evaluated using the therapeutic ratio, isodose contours, and dose volume histograms.ResultsWhen compared with the 3DCNT plans, IMNT reduces the OAR dose for the equivalent tumor coverage. Moreover, IMNT is most advantageous for OARs in close spatial proximity to the target. For the 7 patients with H&N cancers examined, the therapeutic ratio for IMNT increased by an average of 56% when compared with the 3DCNT. The maximum OAR dose was reduced by an average of 20.5% and 20.7% for the spinal cord and temporal lobe, respectively. The mean dose to the larynx decreased by an average of 80%.ConclusionThe IMNT significantly decreases the OAR doses compared with 3DCNT and provides comparable tumor coverage. Improvements in the therapeutic ratio with IMNT are especially significant for dose-limiting OARs near tumor targets. Moreover, IMNT provides superior sparing of healthy tissues and creates significant new opportunities to improve the care of patients with H&N cancers treated with neutron therapy.

IntroductionPatients with virally mediated head and neck cancer (VMHNC) often present with advanced nodal disease that is highly radioresponsive as demonstrated by tumour and nodal regression during treatment. The resultant changes may impact on the planned dose distribution and so adversely affect the therapeutic ratio. The aim of this study was to evaluate the dosimetric effect of treatment-induced anatomical changes in VMHNC patients who had undergone a replan.MethodsThirteen patients with virally mediated oropharyngeal or nasopharyngeal cancer who presented for definitive radiotherapy between 2005 and 2010 and who had a replan generated were investigated. The dosimetric effect of anatomical changes was quantified by comparing dose–volume histograms (DVH) of primary and nodal gross target volumes and organs at risk (OAR), including spinal cord and parotid glands, from the original plan and a comparison plan.ResultsEleven three-dimensional conformal radiation therapy (3DCRT) and two intensity modulated radiation therapy (IMRT) plans were evaluated. Dose to the spinal cord and brainstem increased by 4.1% and 2.6%, respectively. Mean dose to the parotid glands also increased by 3.5%. In contrast, the dose received by 98% of the primary and nodal gross tumour volumes decreased by 0.15% and 0.3%, respectively, when comparing the initial treatment plan to the comparison plan.ConclusionIn this study, treatment-induced anatomical changes had the greatest impact on OAR dose with negligible effect on the dose to nodal gross tumour volumes. In the era of IMRT, accounting for treatment-induced anatomical changes is important as focus is placed on minimizing the acute and long-term side effects of treatment.