PURPOSE: Adaptive planning to accommodate anatomic changes during treatment requires repeat segmentation. This study uses dosimetric endpoints to assess automatically deformed contours. METHODS AND MATERIALS: Sixteen patients with head-and-neck cancer had adaptive plans because of anatomic change during radiotherapy. Contours from the initial planning computed tomography (CT) were deformed to the mid-treatment CT using an intensity-based free-form registration algorithm then compared with the manually drawn contours for the same CT using the Dice similarity coefficient and an overlap index. The automatic contours were used to create new adaptive plans. The original and automatic adaptive plans were compared based on dosimetric outcomes of the manual contours and on plan conformality. RESULTS: Volumes from the manual and automatic segmentation were similar; only the gross tumor volume (GTV) was significantly different. Automatic plans achieved lower mean coverage for the GTV: V95: 98.6 +/- 1.9% vs. 89.9 +/- 10.1% (p = 0.004) and clinical target volume: V95: 98.4 +/- 0.8% vs. 89.8 +/- 6.2% (p < 0.001) and a higher mean maximum dose to 1 cm(3) of the spinal cord 39.9 +/- 3.7 Gy vs. 42.8 +/- 5.4 Gy (p = 0.034), but no difference for the remaining structures. CONCLUSIONS: Automatic segmentation is not robust enough to substitute for physician-drawn volumes, particularly for the GTV. However, it generates normal structure contours of sufficient accuracy when assessed by dosimetric end points. (c) 2010 Elsevier Inc. All rights reserved.
PURPOSE: Adaptive planning to accommodate anatomic changes during treatment requires repeat segmentation. This study uses dosimetric endpoints to assess automatically deformed contours. METHODS AND MATERIALS: Sixteen patients with head-and-neck cancer had adaptive plans because of anatomic change during radiotherapy. Contours from the initial planning computed tomography (CT) were deformed to the mid-treatment CT using an intensity-based free-form registration algorithm then compared with the manually drawn contours for the same CT using the Dice similarity coefficient and an overlap index. The automatic contours were used to create new adaptive plans. The original and automatic adaptive plans were compared based on dosimetric outcomes of the manual contours and on plan conformality. RESULTS: Volumes from the manual and automatic segmentation were similar; only the gross tumor volume (GTV) was significantly different. Automatic plans achieved lower mean coverage for the GTV: V95: 98.6 +/- 1.9% vs. 89.9 +/- 10.1% (p = 0.004) and clinical target volume: V95: 98.4 +/- 0.8% vs. 89.8 +/- 6.2% (p < 0.001) and a higher mean maximum dose to 1 cm(3) of the spinal cord 39.9 +/- 3.7 Gy vs. 42.8 +/- 5.4 Gy (p = 0.034), but no difference for the remaining structures. CONCLUSIONS: Automatic segmentation is not robust enough to substitute for physician-drawn volumes, particularly for the GTV. However, it generates normal structure contours of sufficient accuracy when assessed by dosimetric end points. (c) 2010 Elsevier Inc. All rights reserved.
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Authors: Kuo Men; Huaizhi Geng; Chingyun Cheng; Haoyu Zhong; Mi Huang; Yong Fan; John P Plastaras; Alexander Lin; Ying Xiao Journal: Med Phys Date: 2018-12-07 Impact factor: 4.071
Authors: Xingyu Wu; Jayaram K Udupa; Yubing Tong; Dewey Odhner; Gargi V Pednekar; Charles B Simone; David McLaughlin; Chavanon Apinorasethkul; Ontida Apinorasethkul; John Lukens; Dimitris Mihailidis; Geraldine Shammo; Paul James; Akhil Tiwari; Lisa Wojtowicz; Joseph Camaratta; Drew A Torigian Journal: Med Image Anal Date: 2019-01-29 Impact factor: 8.545
Authors: M A Deeley; A Chen; R D Datteri; J Noble; A Cmelak; E Donnelly; A Malcolm; L Moretti; J Jaboin; K Niermann; Eddy S Yang; David S Yu; B M Dawant Journal: Phys Med Biol Date: 2013-05-17 Impact factor: 3.609