AbstractObjective To investigate the time efficiency and accuracy of atlas-based auto-segmentation (ABAS) software with different atlas template numbers and layers of computed tomography(CT) scans in delineation of the target tissues of cervical cancer patients receiving radiotherapy. Methods The CT images from 20, 40, 60, 80, 100, and 120 patients with cervical cancer were separately selected as atlas templates for MIM auto-segmentation software, and the CT-based tumor volumes of another 20 patients with cervical cancer were manually contoured by physicians. The quality of contours obtained automatically from the software and manual contouring was compared by one-way analysis of variance (ANOVA), randomized block ANOVA, and least significant difference t test. The impact of atlas template numbers and layers of CT scans on the accuracy and time efficiency of MIM software was analyzed based on the time spent in delineation, dice similarity coefficient, and overlap index. Results Taking manual contouring as the reference, no significant differences were observed in the accuracy and time efficiency of auto-contouring when atlas template numbers ranged from 20 to 120(all P>0.05). The ABAS auto-contouring significantly shortened the time for target contours when the layers of CT scans were less than 65(all P>0.05), but reduced the accuracy of rectal contours (P=0.000), while CT scans with 67 layers achieved the highest accuracy of rectal contours (P=0.037). Conclusions The ABAS software shows an advantage in delineation of the target tissues of cervical cancer patients receiving radiotherapy, and 20 templates are suggested to construct this atlas. The CT scans with 65 layers are recommended for patients when target tissues include the bladder, femur, and spinal cord, and CT scans with 67 layers are recommended for patients when target tissues include the rectum.
Corresponding Authors:
Li Yi,Email:flinglee@sina.com
Cite this article:
Sun Yuchen,Zhang Xiaozhi,Li Yi. Clinical feasibility of atlas-based auto-segmentation software in radiotherapy for cervical cancer[J]. Chinese Journal of Radiation Oncology, 2017, 26(10): 1167-1172.
Sun Yuchen,Zhang Xiaozhi,Li Yi. Clinical feasibility of atlas-based auto-segmentation software in radiotherapy for cervical cancer[J]. Chinese Journal of Radiation Oncology, 2017, 26(10): 1167-1172.
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