Bieder Max, Böhm Markus, Duma Marciana-Nona, Wittig Andrea
Department of Radiotherapy and Radiation Oncology, Jena University Hospital, Friedrich-Schiller University Jena, Jena, Germany.
Institute for Medical Statistics, Computer Science and Data Science (IMSID), Jena University Hospital, Jena, Germany.
Front Oncol. 2025 Sep 2;15:1585338. doi: 10.3389/fonc.2025.1585338. eCollection 2025.
Current evidence on atlas-based auto-segmentation (ABS) in radiotherapy primarily addresses organs at risk, whereas its application for clinical target volume (CTV) delineation remains insufficiently explored. Additionally, the optimal number of datasets required for ABS atlases is debated. This study investigates ABS performance for automated CTV (aCTV) segmentation in anal cancer patients with F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET-CT)-positive lymph node (LN) metastases, using varying atlas sizes.
A retrospective analysis was conducted on 51 anal cancer patients who underwent F-FDG PET-CT-based treatment planning between 2009 and 2018. Patients with FDG-positive LN metastases were identified. Manual CTV (mCTV) delineation was performed in accordance with the UK National Guidance for IMRT in Anal Cancer. The resulting 51 mCTV datasets were integrated into a single ABS atlas, which was used to generate aCTVs for the 27 patients with FDG-positive LN metastases. For each of these 27 patients, five different atlas sizes (n = 10, 20, 30, 40, 50) were evaluated using a leave-one-out approach. Automated and manual CTVs were compared using the Dice Similarity Index (DSI), the percentage of FDG-positive LNs adequately covered, and volumes either erroneously included (mistakenly contoured volume, MCV) or omitted (not contoured volume, NCV) by the ABS process.
Of the 51 patients, 27 (52.9%) had FDG-positive LN metastases. The mean DSI for atlas sizes of n = 10, 20, 30, 40, and 50 were 0.73, 0.78, 0.79, 0.79, and 0.80, respectively. A DSI ≥ 0.7 was achieved in 24 patients (88.9%) across all atlas sizes. The increase in DSI between n = 10 and n = 40 was statistically significant (Bonferroni-adjusted p < 0.05). Mean relative NCV and MCV ranged from 21.8-23.9% and 17.7-19.5% of the respective mCTV volume, with decreasing trends as atlas size increased. Segmentation inaccuracies predominantly occurred in the upper mesorectal and lower ischiorectal regions.
In conclusion, ABS facilitates the delineation of CTVs in anal cancer patients and improves contouring efficiency. However, manual correction by radiation oncologists remains necessary.
目前关于放疗中基于图谱的自动分割(ABS)的证据主要涉及危及器官,而其在临床靶区(CTV)勾画中的应用仍未得到充分探索。此外,ABS图谱所需的最佳数据集数量也存在争议。本研究使用不同大小的图谱,调查了基于F-氟脱氧葡萄糖正电子发射断层扫描/计算机断层扫描(F-FDG PET-CT)的阳性淋巴结(LN)转移的肛管癌患者中自动CTV(aCTV)分割的ABS性能。
对2009年至2018年间接受基于F-FDG PET-CT治疗计划的51例肛管癌患者进行回顾性分析。确定FDG阳性LN转移患者。根据英国肛管癌调强放疗国家指南进行手动CTV(mCTV)勾画。将得到的51个mCTV数据集整合到一个单一的ABS图谱中,该图谱用于为27例FDG阳性LN转移患者生成aCTV。对于这27例患者中的每一例,使用留一法评估五种不同大小的图谱(n = 10、20、30、40、50)。使用骰子相似性指数(DSI)、充分覆盖的FDG阳性LN的百分比以及ABS过程错误包含(错误勾画体积,MCV)或遗漏(未勾画体积,NCV)的体积来比较自动和手动CTV。
51例患者中,27例(52.9%)有FDG阳性LN转移。n = 10、20、30、40和50的图谱的平均DSI分别为0.73、0.78、0.79、0.79和0.80。在所有图谱大小中,24例患者(88.9%)实现了DSI≥0.7。n = 10和n = 40之间DSI的增加具有统计学意义(Bonferroni校正p < 0.05)。平均相对NCV和MCV分别占各自mCTV体积的21.8 - 23.9%和17.7 - 19.5%,随着图谱大小增加呈下降趋势。分割不准确主要发生在直肠系膜上部和坐骨直肠下部区域。
总之,ABS有助于肛管癌患者CTV的勾画并提高轮廓绘制效率。然而,放疗肿瘤学家进行手动校正仍然是必要的。