Liu Han, Sintay Benjamin, Wiant David
Department of Radiation Oncology, Cone Health Cancer Center, Greensboro, North Carolina, USA.
J Appl Clin Med Phys. 2025 Jul;26(7):e70150. doi: 10.1002/acm2.70150.
Head-and-neck (HN) contouring presents significant challenges due to the complex anatomy of the region and the proximity of organs-at-risk (OARs) to the target. Manual contouring is time-consuming, labor-intensive, and prone to inter- and intra-observer variability. Additionally, contours delineated prior to treatment may not accurately reflect the patient's anatomy over the extended treatment course. This study explores the feasibility of using auto-generated OAR contours in HN planning.
A retrospective study was conducted on 20 patients, each with a planning CT and 35 CBCT images. OARs were manually delineated and automatically generated using atlas-based segmentation algorithms on planning CTs. Treatment plans were created via a novel two-step optimization process, incorporating a knowledge-based planning solution for both auto-generated (aOAR-plan) and manual OARs (mOAR-plan). The accuracy of auto-generated contours was quantified using the overlap index (OI) and dose similarity coefficient (DSC). Planning dose comparisons were performed between aOAR- and mOAR-plans. Additionally, planning doses were transferred from CT to CBCTs based on clinical shifts, and contour-based deformable registration was employed to calculate cumulative doses. Cumulative dose evaluations were performed for serial organs and parallel organs that can be fully imaged within the CBCT field.
For OARs located farther from the target, even though atlas-based segmentation could not accurately reproduce patient anatomy, excellent agreement in planning doses was observed between the aOAR- and mOAR-plans. The average OI/DSC between manual and auto-generated contours were 85.0% ± 5.4%/87.4% ± 2.6% for the larynx, 76.0% ± 9.3%/77.0% ± 5.8% for the pharynx, 89.9% ± 4.0%/87.8% ± 2.5% for the oral cavity, 81.5% ± 10.5%/78.2% ± 5.9% and 83.2% ± 10.6%/77.8% ± 7.5% for the left and right parotid, respectively. The cumulative dose differences for OARs between aOAR- and mOAR-plans were within 2 Gy for 90% of patients studied.
Automated-contouring tools offer improvement in contour consistency, provide acceptable doses compared with manually drawn contours in HN radiotherapy.
由于头颈部（HN）区域解剖结构复杂且危及器官（OARs）靠近靶区，HN轮廓勾画面临重大挑战。手动轮廓勾画耗时、费力，且容易出现观察者间和观察者内的差异。此外，治疗前勾画的轮廓可能无法在整个延长的治疗过程中准确反映患者的解剖结构。本研究探讨在HN放疗计划中使用自动生成的OAR轮廓的可行性。
对20例患者进行回顾性研究，每位患者有1张计划CT图像和35张CBCT图像。在计划CT图像上，通过基于图谱的分割算法手动勾画并自动生成OARs。通过一种新颖的两步优化过程创建治疗计划，该过程为自动生成的（aOAR计划）和手动勾画的OARs（mOAR计划）都纳入了基于知识的计划解决方案。使用重叠指数（OI）和剂量相似系数（DSC）对自动生成轮廓的准确性进行量化。在aOAR计划和mOAR计划之间进行计划剂量比较。此外，根据临床移位将计划剂量从CT转移到CBCT，并采用基于轮廓的可变形配准来计算累积剂量。对CBCT视野内可完全成像的串行器官和并行器官进行累积剂量评估。
对于距离靶区较远的OARs，尽管基于图谱的分割不能准确再现患者解剖结构，但在aOAR计划和mOAR计划之间观察到计划剂量有良好的一致性。手动和自动生成轮廓之间的平均OI/DSC，喉部为85.0%±5.4%/87.4%±2.6%，咽部为76.0%±9.3%/77.0%±5.8%，口腔为89.9%±4.0%/87.8%±2.5%，左侧腮腺为81.5%±10.5%/78.2%±5.9%，右侧腮腺为83.2%±10.6%/77.8%±7.5%。在所研究的90%的患者中，aOAR计划和mOAR计划之间OARs的累积剂量差异在2 Gy以内。
在HN放疗中，自动轮廓勾画工具可提高轮廓的一致性，与手动勾画的轮廓相比能提供可接受的剂量。
