Prior information guided auto-segmentation of clinical target volume of tumor bed in postoperative breast cancer radiotherapy.

ABSTRACT:

Background

Accurate delineation of clinical target volume of tumor bed (CTV-TB) is important but it is also challenging due to surgical effects and soft tissue contrast. Recently a few auto-segmentation methods were developed to improve the process. However, those methods had comparatively low segmentation accuracy. In this study the prior information was introduced to aid auto-segmentation of CTV-TB based on a deep-learning model.

Methods

To aid the delineation of CTV-TB, the tumor contour on preoperative CT was transformed onto postoperative CT via deformable image registration. Both original and transformed tumor contours were used for prior information in training an auto-segmentation model. Then, the CTV-TB contour on postoperative CT was predicted by the model. 110 pai

SUBMITTER: Xie X 

PROVIDER: S-EPMC10577969 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature