연세의대 / 김나리, 장지석,김용배, 김진성*
Abstract
Background: Since intensity-modulated radiation therapy (IMRT) has become popular for the treatment of gynecologic cancers, the contouring process has become more critical. This study evaluated the feasibility of atlas-based auto-segmentation (ABAS) for contouring in patients with endometrial and cervical cancers.
Methods: A total of 75 sets of planning CT images from 75 patients were collected. Contours for the pelvic nodal clinical target volume (CTV), femur, and bladder were carefully generated by two skilled radiation oncologists. Of 75 patients, 60 were randomly registered in three different atlas libraries for ABAS in groups of 20, 40, or 60. ABAS was conducted in 15 patients, followed by manual correction (ABASc). The time required to generate all contours was recorded, and the accuracy of segmentation was assessed using Dice's coefficient (DC) and the Hausdorff distance (HD) and compared to those of manually delineated contours.
Results: For ABAS-CTV, the best results were achieved with groups of 60 patients (DC, 0.79; HD, 19.7 mm) and the worst results with groups of 20 patients (DC, 0.75; p = 0.012; HD, 21.3 mm; p = 0.002). ABASc-CTV performed better than ABAS-CTV in terms of both HD and DC (ABASc [n = 60]; DC, 0.84; HD, 15.6 mm; all p < 0.017). ABAS required an average of 45.1 s, whereas ABASc required 191.1 s; both methods required less time than the manual methods (p < 0.001). Both ABAS-Femur and simultaneous ABAS-Bilateral-femurs showed satisfactory performance, regardless of the atlas library used (DC > 0.9 and HD ≤10.0 mm), with significant time reduction compared to that needed for manual delineation (p < 0.001). However, ABAS-Bladder did not prove to be feasible, with inferior results regardless of library size (DC < 0.6 and HD > 40 mm). Furthermore, ABASc-Bladder required a longer processing time than manual contouring to achieve the same accuracy.
Conclusions: ABAS could help physicians to delineate the CTV and organs-at-risk (e.g., femurs) in IMRT planning considering its consistency, efficacy, and accuracy.
Affiliations
Nalee Kim 1 2 , Jee Suk Chang 1 , Yong Bae Kim 1 , Jin Sung Kim 3
1 Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
2 Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
3 Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea. JINSUNG@yuhs.ac.
편집위원
Auto Segmentation 여전히 핫 이슈이며 임상에서의 필요성으로 인하여 많은 관심을 불러일으킵니다.
2020-07-02 14:44:32