Evaluation of the auto-segmentation based on self-registration and Atlas in adaptive radiotherapy for cervical cancer / 中华放射肿瘤学杂志

ABSTRACT

Objective To evaluate the accuracy and validate the feasibility of auto-segmentation based on self-registration and Atlas in adaptive radiotherapy for cervical cancer using MIM-Maestro software.Methods The CT scan images and delineation results of 60 cervical cancer patients were obtained to establish the Atlas template database.The planning CT (pCT) and replanning CT (rCT) images were randomly selected from 15 patients for the contouring of clinical target volume (CTV) and organs at risk (OAR) by an experienced radiation oncologist.The rCT images of 15 patients were auto-contoured using Atlas-based auto-segmentation (Atlas group),and mapping contours from the pCT to the rCT images was performed by rigid and deformable image registration (rigid group and deformable group).The time for the three methods of auto-segmentation was also recorded.The similarity of the auto-contours and reference contours was assessed using dice similarity coefficient (DSC),overlap index (OI),the average hausdorff distance (AHD) and the deviation of centroid (DC),and the results were statistically compared among three groups by using one-way analysis of variance.Results The mean time was 89.2 s,22.4 s and 42.6 s in the Atlas,rigid and deformable groups respectively.The DSC,OI and AHD for the CTV and rectum in the rigid and deformable groups significantly differed from those in the Atlas group (all P＜0.001).In the rigid and deformable groups,the OI for the intestine significantly differed from that in the Atlas group.The mean DSC for CTV was 0.89 in the rigid and deformable groups,and 0.76 in the Atlas group.The optimal delineation of the bladder,pelvis and femoral heads was obtained in the deformable group.Conclusions AIl three methods of auto-segmentation can automatically and rapidly contour the CTV and OARs.The performance in the deformable group is better than that in the rigid and Atlas groups.