Real-time morphological and dosimetric adaptation in nasopharyngeal carcinoma radiotherapy: insights from autosegmented fractional fan-beam CT

鼻咽癌放射治疗中实时形态学和剂量学自适应:来自自动分割扇形束CT的启示

阅读:1

Abstract

BACKGROUND: To quantify morphological and dosimetric variations in nasopharyngeal carcinoma (NPC) radiotherapy via autosegmented fan-beam computed tomography (FBCT) and to inform decision-making regarding appropriate objectives and optimal timing for adaptive radiotherapy (ART). METHODS: This retrospective study analyzed 23 NPC patients (681 FBCT scans) treated at Sun Yat-sen Cancer Center from August 2022 to May 2024. The inclusion criterion was as follows: ≥1 weekly FBCT via a CT-linac with ≤ 2 fractions between scans. Four deep learning-based autosegmentation models were developed to assess weekly volume, Dice similarity coefficient (DSC), and dose variations in organs at risk (OARs) and target volumes. RESULTS: A systematic review of autosegmentation on FBCT scans demonstrated satisfactory accuracy overall, and missegmentation was manually modified. Linear decreases in volume and/or DSC were observed in the parotid glands, submandibular glands, thyroid, spinal cord, and target volumes (R² > 0.7). The linear dose variation included coverage of the low risk planning target volume (-3.01%), the mean dose to the parotid glands (+ 2.45 Gy) and thyroid (+ 1.18 Gy), the D1% of the brainstem (+ 0.56 Gy), and the maximum dose to the spinal cord (+ 1.12 Gy). The greatest reduction in target volume coverage was noted in PGTVns, reaching 7.15%. The most significant dose changes occurred during weeks 3-6. CONCLUSIONS: During NPC radiotherapy, the progressive dose deviations may not be corrected through repositioning alone, necessitating ART intervention. As dose variations in OARs rarely exceed 3 Gy and target coverage fluctuations remain within 10%, ART does not need to be performed frequently, and weeks 3-6 represent the most appropriate window.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。