Total body irradiation is an important part of the conditioning regimens frequently used to prepare patients for allogeneic hematopoietic stem cell transplantation (SCT). Volumetric-modulated arc therapy enabled total body irradiation (VMAT-TBI), an alternative to conventional TBI (cTBI), is a novel radiotherapy treatment technique that has been implemented and investigated in our institution. The purpose of this study is to (1) report our six-year clinical experience in terms of treatment planning strategy and delivery time and (2) evaluate the clinical outcomes and toxicities in our cohort of patients treated with VMAT-TBI. This is a retrospective single center study. Forty-four patients at our institution received VMAT-TBI and chemotherapy conditioning followed by allogeneic SCT between 2014 and 2020. Thirty-two patients (73%) received standard-dose TBI (12-13.2 Gy in 6-8 fractions twice daily), whereas 12 (27%) received low-dose TBI (2-4 Gy in one fraction). Treatment planning, delivery, and treatment outcome data including overall survival (OS), relapse-free survival (RFS), and toxicities were analyzed. The developed VMAT-TBI planning strategy consistently generated plans satisfying our dose constraints, with planning target volume coverage >90%, mean lung dose ∼50% to 75% of prescription dose, and minimal hotspots in critical organs. Most of the treatment deliveries were <100 minutes (range 33-147, mean 72). The median follow-up was 26 months. At the last follow-up, 34 of 44 (77%) of patients were alive, with 1- and 2-year OS of 90% and 79% and RFS of 88% and 71%, respectively. The most common grade 3+ toxicities observed were mucositis (31 patients [71%]) and nephrotoxicity (6 patients [13%]), both of which were deemed multifactorial in cause. Four patients (9%) in standard-dose cohort developed grade 3+ pneumonitis, with 3 cases in the setting of documented respiratory infection and only 1 (2%) deemed likely related to radiation alone. VMAT-TBI provides a safe alternative to cTBI. The dose modulation capability of VMAT-TBI may lead to new treatment strategies, such as simultaneous boost and further critical organ sparing, for better malignant cell eradication, immune suppression, and lower toxicities.

Purpose:: The focus of this work was the demonstration and validation of VirtuaLinac with clinical photon beams and to investigate the implementation of low‐Z targets in a TrueBeam linear accelerator (Linac) using Monte Carlo modeling.Methods:: VirtuaLinac, a cloud based web application utilizing Geant4 Monte Carlo code, was used to model the Linac treatment head components. Particles were propagated through the lower portion of the treatment head using BEAMnrc. Dose distributions and spectral distributions were calculated using DOSXYZnrc and BEAMdp, respectively. For validation, 6 MV flattened and flattening filter free (FFF) photon beams were generated and compared to measurement for square fields, 10 and 40 cm wide and at d_max for diagonal profiles. Two low‐Z targets were investigated: a 2.35 MeV carbon target and the proposed 2.50 MeV commercial imaging target for the TrueBeam platform. A 2.35 MeV carbon target was also simulated in a 2100EX Clinac using BEAMnrc. Contrast simulations were made by scoring the dose in the phosphor layer of an IDU20 aSi detector after propagating through a 4 or 20 cm thick phantom composed of water and ICRP bone.Results:: Measured and modeled depth dose curves for 6 MV flattened and FFF beams agree within 1% for 98.3% of points at depths greater than 0.85 cm. Ninety three percent or greater of points analyzed for the diagonal profiles had a gamma value less than one for the criteria of 1.5 mm and 1.5%. The two low‐Z target photon spectra produced in TrueBeam are harder than that from the carbon target in the Clinac. Percent dose at depth 10 cm is greater by 3.6% and 8.9%; the fraction of photons in the diagnostic energy range (25–150 keV) is lower by 10% and 28%; and contrasts are lower by factors of 1.1 and 1.4 (4 cm thick phantom) and 1.03 and 1.4 (20 cm thick phantom), for the TrueBeam 2.35 MV/carbon and commercial imaging beams, respectively.Conclusions:: VirtuaLinac is a promising new tool for Monte Carlo modeling of novel target designs. A significant spectral difference is observed between the low‐Z target beam on the Clinac platform and the proposed imaging beam line on TrueBeam, with the former providing greater diagnostic energy content.

Purpose: Varian Ethos utilizes novel intelligent‐optimization‐engine (IOE) designed to automate the planning. However, this introduced a black box approach to plan optimization and challenge for planners to improve plan quality. This study aims to evaluate machine‐learning‐guided initial reference plan generation approaches for head & neck (H&N) adaptive radiotherapy (ART).Methods: Twenty previously treated patients treated on C‐arm/Ring‐mounted were retroactively re‐planned in the Ethos planning system using a fixed 18‐beam intensity‐modulated radiotherapy (IMRT) template. Clinical goals for IOE input were generated using (1) in‐house deep‐learning 3D‐dose predictor (AI‐Guided) (2) commercial knowledge‐based planning (KBP) model with universal RTOG‐based population criteria (KBP‐RTOG) and (3) an RTOG‐based constraint template only (RTOG) for in‐depth analysis of IOE sensitivity. Similar training data was utilized for both models. Plans were optimized until their respective criteria were achieved or DVH‐estimation band was satisfied. Plans were normalized such that the highest PTV dose level received 95% coverage. Target coverage, high‐impact organs‐at‐risk (OAR) and plan deliverability was assessed in comparison to clinical (benchmark) plans. Statistical significance was evaluated using a paired two‐tailed student t‐test.Results: AI‐guided plans were superior to both KBP‐RTOG and RTOG‐only plans with respect to clinical benchmark cases. Overall, OAR doses were comparable or improved with AI‐guided plans versus benchmark, while they increased with KBP‐RTOG and RTOG plans. However, all plans generally satisfied the RTOG criteria. Heterogeneity Index (HI) was on average <1.07 for all plans. Average modulation factor was 12.2 ± 1.9 (p = n.s), 13.1 ± 1.4 (p = <0.001), 11.5 ± 1.3 (p = n.s.) and 12.2 ± 1.9 for KBP‐RTOG, AI‐Guided, RTOG and benchmark plans, respectively.Conclusion: AI‐guided plans were the highest quality. Both KBP‐enabled and RTOG‐only plans are feasible approaches as clinics adopt ART workflows. Similar to constrained optimization, the IOE is sensitive to clinical input goals and we recommend comparable input to an institution's planning directive dosimetric criteria.