Evidence map›Paper›PMID 39705148›Full record

ArticleJournal of applied clinical medical physics2025

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.

Abby Yashayaeva, R Lee MacDonald, Amanda Cherpak

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Article in Journal of applied clinical medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Abby YashayaevaDepartment of Physics and Atmospheric Sciences, Dalhousie University, Halifax, Canada.
R Lee MacDonaldDepartment of Physics and Atmospheric Sciences, Dalhousie University, Halifax, Canada.
Amanda CherpakDepartment of Physics and Atmospheric Sciences, Dalhousie University, Halifax, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn 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.

methodsA 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.

resultsThe Ethos v1 body contour did not adapt adequately for the weight-loss image set [mean absolute volume deviation from baseline (MAD) = 205 cm

conclusionContours 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.

Indexed as

Cone-Beam Computed TomographyHead and Neck NeoplasmsImage Processing, Computer-AssistedPhantoms, ImagingRadiotherapy Planning, Computer-AssistedSoftwareTomography, X-Ray ComputedWeight LossAlgorithmsHumansOrgans at RiskPrinting, Three-DimensionalRadiotherapy DosageRadiotherapy, Intensity-Modulatedadaptive radiotherapyautomated contouringimage‐guided radiotherapy

Identifiers

PMID39705148
PMCPMC11969106

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