First Report On Physician Assessment and Clinical Acceptability of Custom-Retrained Artificial Intelligence Models for Clinical Target Volume and Organs-at-Risk Auto-Delineation for Postprostatectomy Patients.

PURPOSE: To assess the clinical acceptability of a commercial deep-learning-based auto-segmentation (DLAS) prostate model that was retrained using institutional data for delineation of the clinical target volume (CTV) and organs-at-risk (OARs) for postprostatectomy patients, accounting for clinical and imaging protocol variations. METHODS AND MATERIALS: CTV and OARs of 109 prostate-bed patients were used to evaluate the performance of the vendor-trained model and custom retrained DLAS models using different training quantities. Two new models for OAR structures were retrained (n = 30, 60 data sets), while separate models were trained for a new CTV structure (n = 30, 60, 90 data sets), with the remaining data sets used for testing (n = 49, 19). The dice similarity coefficient (DSC), Hausdorff distance, and mean surface distance were evaluated. Six radiation oncologists performed a qualitative evaluation scoring both preference and clinical utility for blinded structure sets. Physician consensus data sets identified from the qualitative evaluation were used toward a separate CTV model. RESULTS: Both the 30- and 60-case retrained OAR models had median DSC values between 0.91 to 0.97, improving significantly over the vendor-trained model for all OARs except the penile bulb. The brand new 60-case CTV model had a median DSC of 0.70 improving significantly over the 30-case model. DLAS (60-case model) and manual contours were blinded and evaluated by physicians with contours deemed acceptable or precise for 87% and 94% of cases for DLAS and manual delineations, respectively. DLAS-generated CTVs were scored precise or acceptable in 54% of cases, compared with the manual delineation value of 73%. The 30-case physician consensus CTV model did not show a significant difference compared with the randomly selected models. CONCLUSIONS: Custom retraining using institutional data leads to performance improvement in the clinical utility and accuracy of DLAS for postprostatectomy patients. A small number of data sets are sufficient for building an institutional site-specific DLAS OAR model, as well as for training new structures. Data indicates the workload for identifying training data sets could be shared among groups for the male pelvic region, making it accessible to clinics of all sizes.

Virtual particle Monte Carlo: A new concept to avoid simulating secondary particles in proton therapy dose calculation.

BACKGROUND: In proton therapy dose calculation, Monte Carlo (MC) simulations are superior in accuracy but more time consuming, compared to analytical calculations. Graphic processing units (GPUs) are effective in accelerating MC simulations but may suffer thread divergence and racing condition in GPU threads that degrades the computing performance due to the generation of secondary particles during nuclear reactions. PURPOSE: A novel concept of virtual particle (VP) MC (VPMC) is proposed to avoid simulating secondary particles in GPU-accelerated proton MC dose calculation and take full advantage of the computing power of GPU. METHODS: Neutrons and gamma rays were ignored as escaping from the human body; doses of electrons, heavy ions, and nuclear fragments were locally deposited; the tracks of deuterons were converted into tracks of protons. These particles, together with primary and secondary protons, are considered to be the realistic particles. Histories of primary and secondary protons were replaced by histories of multiple VPs. Each VP corresponded to one proton (either primary or secondary). A continuous-slowing-down-approximation model, an ionization model, and a large angle scattering event model corresponding to nuclear interactions were developed for VPs by generating probability distribution functions (PDFs) based on simulation results of realistic particles using MCsquare. For efficient calculations, these PDFs were stored in the Compute Unified Device Architecture textures. VPMC was benchmarked with TOPAS and MCsquare in phantoms and with MCsquare in 13 representative patient geometries. Comparisons between the VPMC calculated dose and dose measured in water during patient-specific quality assurance (PSQA) of the selected 13 patients were also carried out. Gamma analysis was used to compare the doses derived from different methods and calculation efficiencies were also compared. RESULTS: Integrated depth dose and lateral dose profiles in both homogeneous and inhomogeneous phantoms all matched well among VPMC, TOPAS, and MCsquare calculations. The 3D-3D gamma passing rates with a criterion of 2%/2 mm and a threshold of 10% was 98.49% between MCsquare and TOPAS and 98.31% between VPMC and TOPAS in homogeneous phantoms, and 99.18% between MCsquare and TOPAS and 98.49% between VPMC and TOPAS in inhomogeneous phantoms, respectively. In patient geometries, the 3D-3D gamma passing rates with 2%/2 mm/10% between dose distributions from VPMC and MCsquare were 98.56 ± 1.09% in patient geometries. The 2D-3D gamma analysis with 3%/2 mm/10% between the VPMC calculated dose distributions and the 2D measured planar dose distributions during PSQA was 98.91 ± 0.88%. VPMC calculation was highly efficient and took 2.84 ± 2.44 s to finish for the selected 13 patients running on four NVIDIA Ampere GPUs in patient geometries. CONCLUSION: VPMC was found to achieve high accuracy and efficiency in proton therapy dose calculation.

GPU-accelerated Monte Carlo-based online adaptive proton therapy: A feasibility study.

PURPOSE: To develop an online graphic processing unit (GPU)-accelerated Monte Carlo-based adaptive radiation therapy (ART) workflow for pencil beam scanning (PBS) proton therapy to address interfraction anatomical changes in patients treated with PBS. METHODS AND MATERIALS: A four-step workflow was developed using our in-house developed GPU-accelerated Monte Carlo-based treatment planning system to implement online Monte Carlo-based ART for PBS. The first step conducts diffeomorphic demon-based deformable image registration (DIR) to propagate contours on the initial planning CT (pCT) to the verification CT (vCT) to form a new structure set. The second step performs forward dose calculation of the initial plan on the vCT with the propagated contours after manual approval (possible modifications involved). The third step triggers a reoptimization of the plan depending on whether the verification dose meets the clinical requirements or not. A robust evaluation will be done for both the verification plan in the second step and the reopotimized plan in the third step. The fourth step involves a two-stage (before and after delivery) patient-specific quality assurance (PSQA) of the reoptimized plan. The before-delivery PSQA is to compare the plan dose to the dose calculated using an independent fast open-source Monte Carlo code, MCsquare. The after-delivery PSQA is to compare the plan dose to the dose recalculated using the log file (spot MU, spot position, and spot energy) collected during the delivery. Jaccard index (JI), dice similarity coefficients (DSCs), and Hausdorff distance (HD) were used to assess the quality of the propagated contours in the first step. A commercial plan evaluation software, ClearCheck™, was integrated into the workflow to carry out efficient plan evaluation. 3D Gamma analysis was used during the fourth step to ensure the accuracy of the plan dose from reoptimization. Three patients with three different disease sites were chosen to evaluate the feasibility of the online ART workflow for PBS. RESULTS: For all three patients, the propagated contours were found to have good volume conformance [JI (lowest-highest: 0.833-0.983) and DSC (0.909-0.992)] but suboptimal boundary coincidence [HD (2.37-20.76 mm)] for organs-at-risk. The verification dose evaluated by ClearCheck™ showed significant degradation of the target coverage due to the interfractional anatomical changes. Reoptimization on the vCT resulted in great improvement of the plan quality to a clinically acceptable level. 3D Gamma analyses of PSQA confirmed the accuracy of the plan dose before delivery (mean Gamma index = 98.74% with a threshold of 2%/2 mm/10%), and after delivery based on the log files (mean Gamma index = 99.05% with a threshold of 2%/2 mm/10%). The average time cost for the complete execution of the workflow was around 858 s, excluding the time for manual intervention. CONCLUSION: The proposed online ART workflow for PBS was demonstrated to be efficient and effective by generating a reoptimized plan that significantly improved the plan quality.

Practice Recommendations for Lung Cancer Radiotherapy During the COVID-19 Pandemic: An ESTRO-ASTRO Consensus Statement.

BACKGROUND: The COVID-19 pandemic has caused radiotherapy resource pressures and led to increased risks for lung cancer patients and healthcare staff. An international group of experts in lung cancer radiotherapy established this practice recommendation pertaining to whether and how to adapt radiotherapy for lung cancer in the COVID-19 pandemic. METHODS: For this ESTRO & ASTRO endorsed project, 32 experts in lung cancer radiotherapy contributed to a modified Delphi consensus process. We assessed potential adaptations of radiotherapy in two pandemic scenarios. The first, an early pandemic scenario of risk mitigation, is characterized by an altered risk-benefit ratio of radiotherapy for lung cancer patients due to their increased susceptibility for severe COVID-19 infection, and minimization of patient travelling and exposure of radiotherapy staff. The second, a later pandemic scenario, is characterized by reduced radiotherapy resources requiring patient triage. Six common lung cancer cases were assessed for both scenarios: peripherally located stage I NSCLC, locally advanced NSCLC, postoperative radiotherapy after resection of pN2 NSCLC, thoracic radiotherapy and prophylactic cranial irradiation for limited stage SCLC and palliative thoracic radiotherapy for stage IV NSCLC. RESULTS: In a risk-mitigation pandemic scenario, efforts should be made not to compromise the prognosis of lung cancer patients by departing from guideline-recommended radiotherapy practice. In that same scenario, postponement or interruption of radiotherapy treatment of COVID-19 positive patients is generally recommended to avoid exposure of cancer patients and staff to an increased risk of COVID-19 infection. In a severe pandemic scenario characterized by reduced resources, if patients must be triaged, important factors for triage include potential for cure, relative benefit of radiation, life expectancy, and performance status. Case-specific consensus recommendations regarding multimodality treatment strategies and fractionation of radiotherapy are provided. CONCLUSION: This joint ESTRO-ASTRO practice recommendation established pragmatic and balanced consensus recommendations in common clinical scenarios of radiotherapy for lung cancer in order to address the challenges of the COVID-19 pandemic.

Hybrid 3D analytical linear energy transfer calculation algorithm based on precalculated data from Monte Carlo simulations.

PURPOSE: The dose-averaged linear energy transfer (LETd ) for intensity-modulated proton therapy (IMPT) calculated by one-dimensional (1D) analytical models deviates from more accurate but time-consuming Monte Carlo (MC) simulations. We developed a fast hybrid three-dimensional (3D) analytical LETd calculation that is more accurate than 1D analytical model. METHODS: We used the Geant4 MC code to generate 3D LETd distributions of monoenergetic proton beams in water for all energies and used a customized error function to fit the LETd lateral profiles at various depths to the MC simulation. The 3D LETd calculation kernel was a lookup table of these fitted coefficients, and LETd was determined directly from spot energies and voxel coordinates during analytical dose calculations. We validated our new method by comparing the calculated LETd distributions to MC results using 3D Gamma index analysis with 3%/2 mm criteria in 12 patient geometries. The significance of the improvement in Gamma index analysis passing rates over the 1D analytical model was determined using the Wilcoxon rank-sum test. RESULTS: The passing rate of 3D Gamma analysis comparing LETd distributions from the hybrid 3D method and the 1D method to MC simulations was significantly improved from 94.0% ± 2.5% to 98.0% ± 1.0% (P = 0.0003). The typical time to calculate dose and LETd simultaneously using an Intel Xeon E5-2680 2.50 GHz workstation was approximately 2.5 min. CONCLUSIONS: Our new method significantly improved the LETd calculation accuracy compared to the 1D method while maintaining significantly shorter calculation time even comparing with the GPU-based fast MC code.

Clinical Validation of a Ray-Casting Analytical Dose Engine for Spot Scanning Proton Delivery Systems.

PURPOSE: To describe and validate the dose calculation algorithm of an independent second-dose check software for spot scanning proton delivery systems with full width at half maximum between 5 and 14 mm and with a negligible spray component. METHODS: The analytical dose engine of our independent second-dose check software employs an altered pencil beam algorithm with 3 lateral Gaussian components. It was commissioned using Geant4 and validated by comparison to point dose measurements at several depths within spread-out Bragg peaks of varying ranges, modulations, and field sizes. Water equivalent distance was used to compensate for inhomogeneous geometry. Twelve patients representing different disease sites were selected for validation. Dose calculation results in water were compared to a fast Monte Carlo code and ionization chamber array measurements using dose planes and dose profiles as well as 2-dimensional-3-dimensional and 3-dimensional-3-dimensional γ-index analysis. Results in patient geometry were compared to Monte Carlo simulation using dose-volume histogram indices, 3-dimensional-3-dimensional γ-index analysis, and inpatient dose profiles. RESULTS: Dose engine model parameters were tuned to achieve 1.5% agreement with measured point doses. The in-water γ-index passing rates for the 12 patients using 3%/2 mm criteria were 99.5% ± 0.5% compared to Monte Carlo. The average inpatient γ-index analysis passing rate compared to Monte Carlo was 95.8% ± 2.9%. The average difference in mean dose to the clinical target volume between the dose engine and Monte Carlo was -0.4% ± 1.0%. For a typical plan, dose calculation time was 2 minutes on an inexpensive workstation. CONCLUSIONS: Following our commissioning process, the analytical dose engine was validated for all treatment sites except for the lung or for calculating dose-volume histogram indices involving point doses or critical structures immediately distal to target volumes. Monte Carlo simulations are recommended for these scenarios.

Photon and Proton Radiation Therapy Utilization in a Population of More Than 100 Million Commercially Insured Patients.

PURPOSE: To characterize the changes in the use of radiation therapy (RT), specifically proton beam radiation therapy (PBRT), among adult and pediatric patients over a 11-year period in a very large population of insured patients. METHODS AND MATERIALS: We conducted a retrospective analysis of the OptumLabs Data Warehouse claims database of more than 100 million insured US enrollees. Descriptive analyses were undertaken to evaluate the characteristics of patients receiving RT from 2002 to 2012. RESULTS: There were 474,533 patients treated with RT from 2002 to 2012. The percentage of patients treated with 3-dimensional conformal radiation therapy, 2-dimensional RT/brachytherapy, intensity modulated radiation therapy (IMRT), stereotactic body radiation therapy (SBRT), and PBRT was 34.5%, 63.4%, 2.1%, 0.0%, and 0.1% and 40.4%, 36.0%, 21.9%, 1.1%, and 0.6% in 2002 and 2012, respectively. The greatest increase in utilization was of IMRT for prostate cancer, growing from 3.5% to 64.0%. For non-prostate cancer adults, IMRT use grew from 1.7% to 16.4%. For children, PBRT utilization increased from 0.3% to 9.7%. For prostate cancer patients, PBRT increased from 0.0% to 2.6%. For all patients, advanced technology (SBRT and PBRT) use was very low at <2%, versus 22% for IMRT. CONCLUSIONS: This is the largest and most geographically diverse description of RT utilization. Proton beam RT utilization remains very low and has had little impact on overall RT utilization compared with IMRT. The largest shift has occurred in IMRT for prostate cancer. Our findings indicate that overall utilization of proton therapy has been low and that its use has likely had little impact on national expenditures on cancer care in the current environment.

Consensus Statement on Proton Therapy in Early-Stage and Locally Advanced Non-Small Cell Lung Cancer.

Radiation dose escalation has been shown to improve local control and survival in patients with non-small cell lung cancer in some studies, but randomized data have not supported this premise, possibly owing to adverse effects. Because of the physical characteristics of the Bragg peak, proton therapy (PT) delivers minimal exit dose distal to the target volume, resulting in better sparing of normal tissues in comparison to photon-based radiation therapy. This is particularly important for lung cancer given the proximity of the lung, heart, esophagus, major airways, large blood vessels, and spinal cord. However, PT is associated with more uncertainty because of the finite range of the proton beam and motion for thoracic cancers. PT is more costly than traditional photon therapy but may reduce side effects and toxicity-related hospitalization, which has its own associated cost. The cost of PT is decreasing over time because of reduced prices for the building, machine, maintenance, and overhead, as well as newer, shorter treatment programs. PT is improving rapidly as more research is performed particularly with the implementation of 4-dimensional computed tomography-based motion management and intensity modulated PT. Given these controversies, there is much debate in the oncology community about which patients with lung cancer benefit significantly from PT. The Particle Therapy Co-operative Group (PTCOG) Thoracic Subcommittee task group intends to address the issues of PT indications, advantages and limitations, cost-effectiveness, technology improvement, clinical trials, and future research directions. This consensus report can be used to guide clinical practice and indications for PT, insurance approval, and clinical or translational research directions.

Value of Comorbidity Scales for Predicting Survival After Radiochemotherapy of Small Cell Lung Cancer.

The Charlson Comorbidity Index plus three comorbidity scales were evaluated for survival after radiochemotherapy of limited stage SCLC. For the Charlson Comorbidity Index, 2-4 points were compared to 5-8 points. For the Age-Comorbidity Score, 2-6 points were compared to 7-10 points. For the Medical Research Council (MRC) Breathlessness Scale, grades 0-2 were compared to grades 3-5. For the Simplified Comorbidity Score, 0-5 points were compared to 6-11 and 12-17 points. Charlson Comorbidity Index (p = 0.022) and MRC Breathlessness Scale (p < 0.001) showed significant associations with survival, the Age-Comorbidity Score a trend (p = 0.06). For the Simplified Comorbidity Score, no significant correlation was found (p = 0.54). Absolute differences in survival ≥20 % were observed for the MRC Breathlessness Scale at 1, 2, and 3 years, for the Charlson Comorbidity Index at 1 year, and for the Age-Comorbidity Score at 2 years. Thus, particularly the MRC Breathlessness Scale can contribute to personalization of the treatment of SCLC.

Scoring systems to estimate intracerebral control and survival rates of patients irradiated for brain metastases.

PURPOSE: To create and validate scoring systems for intracerebral control (IC) and overall survival (OS) of patients irradiated for brain metastases. METHODS AND MATERIALS: In this study, 1,797 patients were randomly assigned to the test (n = 1,198) or the validation group (n = 599). Two scoring systems were developed, one for IC and another for OS. The scores included prognostic factors found significant on multivariate analyses. Age, performance status, extracerebral metastases, interval tumor diagnosis to RT, and number of brain metastases were associated with OS. Tumor type, performance status, interval, and number of brain metastases were associated with IC. The score for each factor was determined by dividing the 6-month IC or OS rate (given in percent) by 10. The total score represented the sum of the scores for each factor. The score groups of the test group were compared with the corresponding score groups of the validation group. RESULTS: In the test group, 6-month IC rates were 17% for 14-18 points, 49% for 19-23 points, and 77% for 24-27 points (p < 0.0001). IC rates in the validation group were 19%, 52%, and 77%, respectively (p < 0.0001). In the test group, 6-month OS rates were 9% for 15-19 points, 41% for 20-25 points, and 78% for 26-30 points (p < 0.0001). OS rates in the validation group were 7%, 39%, and 79%, respectively (p < 0.0001). CONCLUSIONS: Patients irradiated for brain metastases can be given scores to estimate OS and IC. IC and OS rates of the validation group were similar to the test group demonstrating the validity and reproducibility of both scores.

Dose escalation beyond 30 grays in 10 fractions for patients with multiple brain metastases.

BACKGROUND: Whole-brain radiotherapy (WBRT) to 30 grays (Gy) in 10 fractions is the standard treatment in patients with multiple brain metastases in the majority of treatment centers worldwide. The current study investigated the potential benefit of dose escalation beyond 30 Gy. METHODS: Data regarding 416 patients who were treated with WBRT for multiple brain metastases were evaluated retrospectively. Survival and freedom from recurrent brain metastasis (local control) of 257 patients who were treated with 10 fractions of 3 Gy each for 2 weeks were compared with those of 159 patients treated with 45 Gy in 15 fractions for 3 weeks or 40 Gy in 20 fractions for 4 weeks. Eight additional potential prognostic factors were investigated including age, gender, Karnofsky performance score (KPS), tumor type, interval between tumor diagnosis and RT, number of metastases, extracranial metastases, and Recursive Partitioning Analysis (RPA) class. RESULTS: On multivariate analysis, improved survival was found to be associated with lower RPA class (P < .001), age <60 years (P = .026), KPS >or=70 (P < .001), and absence of extracranial metastases (P = .003). A trend was observed for number of metastases (2-3 vs >or=4; P = .07). Improved local control was associated with a KPS >or=70 (P < .001) and breast cancer (P < .001). A trend was observed for number of metastases (P = .059). The RT schedule did not appear to have any significant impact on survival (P = .86) or local control (P = .61). The subgroup analyses, performed for each of the 3 RPA classes, did not demonstrate a significantly better outcome with dose escalation. CONCLUSIONS: Dose escalation beyond 30 Gy in 10 fractions does not appear to improve survival or local control in patients with multiple brain metastases but does increase the treatment time and cost of therapy.