Effects of algorithm and matching number on the auto-segmentation of organs-at-risk in patients with cervical cancer(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2019年第11期
- Page:
- 1243-1248
- Research Field:
- 医学放射物理
- Publishing date:
Info
- Title:
- Effects of algorithm and matching number on the auto-segmentation of organs-at-risk in patients with cervical cancer
- Author(s):
- WANG Jinyuan1; XU Shouping1; 2; YANG Wei1; ZHANG Huijuan1; QU Baolin1; 2; ZHENG Qingzeng3
- 1. Department of Radiotherapy, Chinese PLA General Hospital, Beijing 100853, China; 2. Beihang Advanced Innovation Center for Big Date-based Precision Medicine, Beijing 100083, China; 3. Department of Radiotherapy, Beijing Geriatric Hospital, Beijing 100095, China
- Keywords:
- cervical cancer; organs-at-risk; radiotherapy; auto-segmentation
- PACS:
- R730.55；R811.1
- DOI:
- DOI:10.3969/j.issn.1005-202X.2019.11.001
- Abstract:
- To evaluate the effects of segmentation algorithms and matching numbers on the Atlas-based auto-segmentation of organs-at-risk (OAR) in patients with cervical cancer. Methods The Atlas database of cervical cancer which contains 60 cases was established with MIM-Maestro software. Another 10 patients with cervical cancer were randomly selected out of the Atlas database. The manual segmentations of OAR, namely bladder, rectum and bilateral femoral head, by an experienced radiation oncologist, were defined as the reference volume (Vref). Subsequently, the OAR were automatically segmented by majority vote algorithm versus STAPLE algorithm, with the matching number of 1, 3, 5, 7 and 9. The segmentation results were assessed using time for segmentation (T), Dice similarity coefficient (DSC), sensitivity index (SI), deviation of centroid (DC), Jaccard coefficient (JAC) and Hausdorff distance (HD). The results were also analyzed with one-way analysis of variance and paired sample t test. Results The time for segmentation was independent of the algorithm and increased linearly with the increasing of matching number. The results obtained by majority vote algorithm and STAPLE algorithm showed that there were statistical differences in the SI of bladder and the DSC, HD, JAC of left femoral head between the matching number of 1 and 3, 5, 7, 9. For STAPLE algorithm, the SI of bladder and bilateral femoral head showed statistical differences between the matching number of 1, 3 and 5, 7, 9. Moreover, significant difference was only found in the SI of bilateral femoral head between two algorithms. Conclusion The effect of segmentation algorithms on the Atlas-based OAR auto-segmentation is trivial. The time for segmentation was positively correlated with matching number. With the comprehensive consideration of segmentation results, the matching number of 3 is recommended for clinical application.
Last Update: 2019-11-28