Purpose: The Ethos (Varian Medical Systems) radiotherapy device combines semi-automated anatomy detection and plan generation for cone beam computer tomography (CBCT)-based daily online adaptive radiotherapy (oART). However, CBCT offers less soft tissue contrast than magnetic resonance imaging (MRI). This work aims to present the clinical workflow of CBCT-based oART with shuttle-based offline MR guidance. Methods: From February to November 2023, 31 patients underwent radiotherapy on the Ethos (Varian, Palo Alto, CA, USA) system with machine learning (ML)-supported daily oART. Moreover, patients received weekly MRI in treatment position, which was utilized for daily plan adaptation, via a shuttle-based system. Initial and adapted treatment plans were generated using the Ethos treatment planning system. Patient clinical data, fractional session times (MRI + shuttle transport + positioning, adaptation, QA, RT delivery) and plan selection were assessed for all fractions in all patients. Results: In total, 737 oART fractions were applied and 118 MRIs for offline MR guidance were acquired. Primary sites of tumors were prostate (n= 16), lung (n= 7), cervix (n= 5), bladder (n= 1) and endometrium (n= 2). The treatment was completed in all patients. The median MRI acquisition time including shuttle transport and positioning to initiation of the Ethos adaptive session was 53.6 min (IQR 46.5–63.4). The median total treatment time without MRI was 30.7 min (IQR 24.7–39.2). Separately, median adaptation, plan QA and RT times were 24.3 min (IQR 18.6–32.2), 0.4 min (IQR 0.3–1,0) and 5.3 min (IQR 4.5–6.7), respectively. The adapted plan was chosen over the scheduled plan in 97.7% of cases. Conclusion: This study describes the first workflow to date of a CBCT-based oART combined with a shuttle-based offline approach for MR guidance. The oART duration times reported resemble the range shown by previous publications for first clinical experiences with the Ethos system.
目的：Ethos（瓦里安医疗系统）放射治疗设备结合了半自动解剖结构检测与计划生成功能，用于基于锥形束计算机断层扫描（CBCT）的每日在线自适应放射治疗（oART）。然而，CBCT的软组织对比度低于磁共振成像（MRI）。本研究旨在介绍基于CBCT的oART结合穿梭式离线MRI引导的临床工作流程。方法：2023年2月至11月期间，31例患者在Ethos（美国加州帕洛阿尔托瓦里安公司）系统上接受了机器学习（ML）支持的每日oART放射治疗。此外，患者每周在治疗体位接受MRI检查，通过穿梭式系统将其用于每日计划调整。初始和调整后的治疗计划均使用Ethos治疗计划系统生成。对所有患者的所有分次治疗，评估了患者临床数据、分次治疗时间（MRI+穿梭转运+摆位、自适应调整、质量保证、放射治疗实施）以及计划选择情况。结果：总共实施了737次oART分次治疗，并获取了118次用于离线MRI引导的MRI图像。肿瘤原发部位包括前列腺（n=16）、肺（n=7）、宫颈（n=5）、膀胱（n=1）和子宫内膜（n=2）。所有患者均完成治疗。从MRI采集（包括穿梭转运和摆位）到Ethos自适应治疗环节开始的中位时间为53.6分钟（四分位距46.5–63.4）。不含MRI的中位总治疗时间为30.7分钟（四分位距24.7–39.2）。其中，自适应调整、计划质量保证和放射治疗实施的中位时间分别为24.3分钟（四分位距18.6–32.2）、0.4分钟（四分位距0.3–1.0）和5.3分钟（四分位距4.5–6.7）。在97.7%的治疗分次中选择了自适应调整计划而非原定计划。结论：本研究首次描述了基于CBCT的oART结合穿梭式离线MRI引导的工作流程。报告的oART持续时间与既往文献中Ethos系统初步临床经验所示范围相近。
肿瘤(癌症)患者之家