{"title":"Body contour adaptation for weight-loss and bolus for head and neck radiotherapy on Ethos version 2.0 and HyperSight: Synthetic CT versus direct calculation.","authors":"Abby Yashayaeva, R Lee MacDonald, Amanda Cherpak","doi":"10.1002/acm2.14587","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>In radiotherapy, body contour inaccuracies may compromise the delineation of adjacent structures and affect calculated dose. Here, we evaluate the un-editable body contours auto-generated by Ethos versions 1.0 (v1) and 2.0 (v2) treatment planning softwares for two simulated cases: weight-loss and bolus application, particularly important for head and neck radiotherapy patients.</p><p><strong>Methods: </strong>A 3D-printed target structure was secured to the neck of an anthropomorphic phantom and sequentially covered with silicone boluses of uniform thickness, providing cases for bolus application (0.5 and 1 cm) and weight-loss (2.0, 1.5, 1.0, 0.5, and 0 cm). HyperSight CBCT images of the phantom were acquired to simulate the online adaptation process. Baseline body contours were manually produced and compared to those auto-generated in Ethos v1 (synthetic CTs) and Ethos v2 (synthetic CTs and direct calculation on HyperSight CBCTs). Additionally, the target volume D95% dose metric for weight-loss adapted plans generated by the Ethos v2 were analyzed as a function of surface layer thickness.</p><p><strong>Results: </strong>The Ethos v1 body contour did not adapt adequately for the weight-loss image set [mean absolute volume deviation from baseline (MAD) = 205 cm<sup>3</sup>]. The weight-loss synthetic CT and HyperSight CBCT volumes in Ethos v2 were comparable to manually generated contours (MAD = 34 and 46 cm<sup>3</sup> <sub>,</sub> respectively); however, the bolus Hypersight CBCT body contour intersected the outer edge of the phantom (MAD = 157 cm<sup>3</sup>). The D95% deviation from the planned dose decreased by up to 10% when using the Ethos v2 adapted plan for the weight-loss scenario.</p><p><strong>Conclusion: </strong>Contours in Ethos v1 rely on reference contours and deformable registration algorithms, whereas Ethos v2 does not. Hence, Ethos v2 is preferred for cases involving weight change. A tight-fitted air gap-free bolus is critical for achieving accurate body contours for Ethos v2 Hypersight CBCTs.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14587"},"PeriodicalIF":2.0000,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Clinical Medical Physics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/acm2.14587","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Body contour adaptation for weight-loss and bolus for head and neck radiotherapy on Ethos version 2.0 and HyperSight: Synthetic CT versus direct calculation.
Purpose: In radiotherapy, body contour inaccuracies may compromise the delineation of adjacent structures and affect calculated dose. Here, we evaluate the un-editable body contours auto-generated by Ethos versions 1.0 (v1) and 2.0 (v2) treatment planning softwares for two simulated cases: weight-loss and bolus application, particularly important for head and neck radiotherapy patients.
Methods: A 3D-printed target structure was secured to the neck of an anthropomorphic phantom and sequentially covered with silicone boluses of uniform thickness, providing cases for bolus application (0.5 and 1 cm) and weight-loss (2.0, 1.5, 1.0, 0.5, and 0 cm). HyperSight CBCT images of the phantom were acquired to simulate the online adaptation process. Baseline body contours were manually produced and compared to those auto-generated in Ethos v1 (synthetic CTs) and Ethos v2 (synthetic CTs and direct calculation on HyperSight CBCTs). Additionally, the target volume D95% dose metric for weight-loss adapted plans generated by the Ethos v2 were analyzed as a function of surface layer thickness.
Results: The Ethos v1 body contour did not adapt adequately for the weight-loss image set [mean absolute volume deviation from baseline (MAD) = 205 cm3]. The weight-loss synthetic CT and HyperSight CBCT volumes in Ethos v2 were comparable to manually generated contours (MAD = 34 and 46 cm3, respectively); however, the bolus Hypersight CBCT body contour intersected the outer edge of the phantom (MAD = 157 cm3). The D95% deviation from the planned dose decreased by up to 10% when using the Ethos v2 adapted plan for the weight-loss scenario.
Conclusion: Contours in Ethos v1 rely on reference contours and deformable registration algorithms, whereas Ethos v2 does not. Hence, Ethos v2 is preferred for cases involving weight change. A tight-fitted air gap-free bolus is critical for achieving accurate body contours for Ethos v2 Hypersight CBCTs.
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