Clinical feasibility of atlas‐based auto‐segmentation for organ‐at‐risk contouring in head‐and‐neck radiotherapy
Han Liu, Benjamin Sintay, David Wiant

TL;DR
This study shows that automated contouring tools can produce consistent and accurate organ contours for head-and-neck radiotherapy, resulting in acceptable treatment plans.
Contribution
The study demonstrates the clinical feasibility of atlas-based auto-segmentation for head-and-neck radiotherapy planning.
Findings
Auto-generated OAR contours showed excellent agreement with manual contours in planning doses for organs farther from the target.
Cumulative dose differences between auto-generated and manual OAR plans were within 2 Gy for 90% of patients.
Atlas-based segmentation achieved average overlap indices and dose similarity coefficients above 76% for most OARs.
Abstract
Head‐and‐neck (HN) contouring presents significant challenges due to the complex anatomy of the region and the proximity of organs‐at‐risk (OARs) to the target. Manual contouring is time‐consuming, labor‐intensive, and prone to inter‐ and intra‐observer variability. Additionally, contours delineated prior to treatment may not accurately reflect the patient's anatomy over the extended treatment course. This study explores the feasibility of using auto‐generated OAR contours in HN planning. A retrospective study was conducted on 20 patients, each with a planning CT and 35 CBCT images. OARs were manually delineated and automatically generated using atlas‐based segmentation algorithms on planning CTs. Treatment plans were created via a novel two‐step optimization process, incorporating a knowledge‐based planning solution for both auto‐generated (aOAR‐plan) and manual OARs (mOAR‐plan). The…
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Taxonomy
TopicsAdvanced Radiotherapy Techniques · Head and Neck Cancer Studies · Lung Cancer Diagnosis and Treatment
