Related Experiment Video
Updated: Jun 17, 2026

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
Published on: November 23, 2019
Cross-anatomical evaluation of a deep-learning auto-contouring system: qualitative, geometric, and dosimetric
Sara Endo1, Masaki Nakamura2, Takeshi Fujisawa2
1Radiation Safety and Quality Assurance Division, National Cancer Center Hospital East, Chiba, Japan.
Background:
Accurate and consistent delineation of target and normal structures is essential for safe and effective radiotherapy. Compared with manual or atlas-based methods, deep learning-based auto-contouring has demonstrated improved efficiency and reduced interobserver variability. However, its performance can vary across anatomical regions and clinical contexts, and comprehensive multi-site validation remains limited. Existing studies have tended to assess only geometric similarity or a single region, providing insufficient insight into real-world usability and dosimetric influence. A systematic evaluation that integrates physician-based quality assessment, quantitative geometric metrics, and plan-level dosimetry across diverse anatomical sites is needed to support broader clinical implementation of deep learning-based auto-contouring for differentiation between target and normal structures.
Purpose:
To perform the first practice-oriented, cross-anatomical evaluation of the SYNAPSE Radiotherapy system (v1.5) and to assess its qualitative usability, geometric agreement (Dice similarity coefficient [DSC], mean distance to agreement [MDA], and maximum Hausdorff distance [HD]), and plan-level dosimetric impact across six anatomical sites.
Methods:
We retrospectively analyzed data for 120 patients across six sites, namely, the head, head and neck, thorax, abdomen, male pelvis, and female pelvis. Thirty organs at risk were auto-segmented using the SYNAPSE Radiotherapy platform, and three board-certified radiation oncologists graded the clinical usability of the platform on a 4-point scale. Geometric agreement was quantified using the DSC, MDA, and maximum HD. Plan-level dosimetric comparisons were performed for representative targets. Institutional review board approval was obtained (number 2017-440).
Results:
Overall, 76.1% of auto-contours were qualitatively judged to be clinically usable (score ≥3). Geometric thresholds were achieved for most structures (DSC > 0.8 in 54.8%, MDA < 2.5 mm in 71.5%, and maximum HD < 12.5 mm in 50%), with only 8/29 being major outliers. Auto-contours tended to be larger than manual contours in 72% of cases. Dosimetrically, 88.1% of organs showed dose-volume differences within ±5%, and dose constraint achievement rates were comparable between auto-contours and manual contours (93.9% vs. 95.%). Median doses to planning target volumes (e.g., prostate and iliac nodes) were also consistent, indicating minimal clinical impact.
Conclusions:
The SYNAPSE Radiotherapy system showed high overall clinical usability with organ-dependent variability. Our findings expand the platform-specific evidence for the SYNAPSE Radiotherapy system by linking geometry to dosimetric impact and supporting clinical deployment with an organ-specific quality assurance policy, while highlighting contexts in which targeted expert review remains necessary for safe clinical translation.
