(Sunday, 7/12/2020) [Eastern Time (GMT-4)]
Room: AAPM ePoster Library
Purpose: To analyze the setup errors and residual errors of different spinal cord segmental parts in esophageal cancer patients under radiation treatment, and to explore the necessity of adjusting spinal cord extension margin according to the segmental area.
Methods: 60 cases of esophageal cancer were selected and were divided into neck, chest and abdomen groups, 20 cases each, according to the radiotherapy site. Mesh mask or vacuum bag were used for fixation. IMRT technology was used to treat these patients. CTVision (Siemens CT-On-Rail system) was used to obtain 20 consecutive pre-treatment CT images for each case. Images were exported to MIM software for processing and positioning parameter extraction. The range of delineation for the spinal cord in pre-treatment CT should be consistent with that in the planning CT. Dice coefficient, Hausdorff distance maximum value and centroid coordinate values outlining the spinal cord were processed and extracted. The calculation formula of the contour expansion margin value is M = 1.3 ? +0.5 s, where ? and s are total group systematic error and total group random error.
Results: With residual centroid method, calculated from ? and s, the margins on X, Y, Z direction of spinal cord in neck, chest, abdominal areas, for non-IGRT positioning are 3.86, 5.37, 6.36 mm, 3.45, 3.83, 4.51 mm; 4.05, 4.83, 7.0 6mm , and for IGRT positioning are 2.85, 2.19, 2.83 mm; 2.32, 2.20, 2.16 mm; 2.86;2.21, 2.83 mm, respectively. The margins have a similar variation trend with residual Hausdorff distance method.
Conclusion: From the residue error study, the IGRT setup errors are different in each segment of the spinal cord, and the non-IGRT setup errors vary even more in different segment of the spinal cord. Therefore different spinal cord extension margins should be used during treatment planning for added safety concerns and optimization convenience.
Keywords
Segmentation, Patient Positioning, Image Guidance
Taxonomy
IM/TH- image Segmentation: General (Most aspects)
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