Liao Chien-Yi, Maniscalco Austen Matthew, Zhao Hengrui, Bai Ti, Choi Byongsu, Moon Dominic, Yang Daniel, Wang Jing, Zhong Xinran, Nguyen Dan, Godley Andrew, Jiang Steve B, Sher David, Lin Mu-Han
Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA; Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Radiother Oncol. 2025 Apr;205:110707. doi: 10.1016/j.radonc.2025.110707. Epub 2025 Jan 7.
Daily online adaptive radiotherapy (DART) increases treatment accuracy by crafting daily customized plans that adjust to the patient's daily setup and anatomy. The routine application of DART is limited by its resource-intensive processes. This study proposes a novel DART strategy for head and neck squamous cell carcinoma (HNSCC), automizing the process by propagating physician-edited treatment contours for each fraction.
This study retrospectively analyzed 24 HNSCC patients treated with DART, encompassing 810 fractions. Both weekly and daily offline editing of the contours were emulated, propagating them to subsequent fractions using rigid and deformable image registration (DIR), respectively. Contour margins (CM) of 1, 2, and 3 mm were applied to create an adaptive gross tumor volume (aGTV) /adaptive clinical target volume (aCTV). Geometric coverage of the aGTV/aCTV relative to the ground-truth GTV/CTV were assessed. Additionally, adaptive dose distributions were predicted based on the aGTV/aCTV, and the dosimetric coverage of these predictions on the ground-truth GTV/CTV was evaluated. The recommended CM was identified by comparing the geometric and dosimetric accuracy across different combinations of CM, registration methods, and contour update frequencies.
Rigid registration failed to accurately propagate most targets, even with a 3 mm CM. With DIR and a 2 mm CM, weekly or daily contour propagation achieved ≥ 98 % geometric coverage for gross tumor/nodal targets and ≥ 94 % for small suspicious nodes. DIR with weekly and daily contours achieved target dose coverage: V95% ≥ 99 % and V100% ≥ 95 % to the aGTV.
This study shows that DIR can effectively propagate periodically edited treatment contours for HNSCC patients, provided the correct CM is used. By adjusting contours weekly offline and using DIR at the console, the need for daily physician attendance can be eliminated.
每日在线自适应放疗（DART）通过制定每日定制计划来提高治疗精度，该计划可根据患者每日的摆位和解剖结构进行调整。DART的常规应用受到其资源密集型流程的限制。本研究提出了一种针对头颈部鳞状细胞癌（HNSCC）的新型DART策略，通过传播医生编辑的各分次治疗轮廓来实现流程自动化。
本研究回顾性分析了24例接受DART治疗的HNSCC患者，共810个分次。模拟了每周和每日的轮廓离线编辑，并分别使用刚性和可变形图像配准（DIR）将其传播至后续分次。应用1、2和3毫米的轮廓边界（CM）来创建自适应大体肿瘤体积（aGTV）/自适应临床靶体积（aCTV）。评估了aGTV/aCTV相对于真实GTV/CTV的几何覆盖情况。此外，基于aGTV/aCTV预测了自适应剂量分布，并评估了这些预测在真实GTV/CTV上的剂量覆盖情况。通过比较不同CM、配准方法和轮廓更新频率组合的几何和剂量学准确性，确定了推荐的CM。
即使采用3毫米的CM，刚性配准也无法准确传播大多数靶区。使用DIR和2毫米的CM时，每周或每日的轮廓传播对大体肿瘤/淋巴结靶区的几何覆盖≥98%，对小的可疑淋巴结的几何覆盖≥94%。每周和每日轮廓的DIR实现了靶区剂量覆盖：aGTV的V95%≥99%且V100%≥95%。
本研究表明，只要使用正确的CM，DIR可以有效地传播HNSCC患者定期编辑的治疗轮廓。通过每周离线调整轮廓并在控制台使用DIR，可以消除每日医生到场的需求。
