Journal of applied clinical medical physics · 2026
Automatic target volume segmentation for offline adaptive head-and-neck radiotherapy.
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Moliner Gilles, Michaud Maxime, Guerin Antoine, Verstraet Rodolfe, Debrigode Charles, Lang Philippe, Greffier Joel
Аннотация
PURPOSE: To assess the clinical utility of Smartfuse (Therapanacea, France), a deformable image registration (DIR) algorithm for automatic propagation of target volumes in the context of offline adaptive head-and-neck radiotherapy.
MATERIALS AND METHODS: Ten patients underwent offline re-planning during head-and-neck radiotherapy. Target volumes (GTV and CTV) were manually delineated by radiation oncologists (ROs) on both the initial CT (CTi) and one re-planning CT (CTR). These manual contours were compared to those propagated by Smartfuse from CTi to CTR. The geometric agreement between DIR-propagated and RO-delineated contours was assessed using Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), and surface Dice similarity coefficient (sDSC) with 0 and 2 mm thresholds. Dosimetric evaluation was conducted by comparing dose distributions from generated plans using automatically propagated target volumes (PTVDIR) with reference plans based on RO-delineated targets (PTVRO). Coverage of RO-delineated targets (GTVRO + CTVRO and PTVRO) was assessed using D95%, D50%, Dmax, and V95% ≥ 95%. Spatial dose differences were analyzed using dose difference (DD) metrics at 5% and 2% thresholds.
RESULTS: Median DSC, HD95, sDSC0 mm and sDSC2 mm were 0.86, 4.0 mm, 0.29 and 0.73, respectively. For D95%, median relative differences between DIR and RO plans were -0.6% for GTVRO + CTVRO and -2.1% for PTVRO for D95%. All GTVRO + CTVRO reached V95% ≥ 95% with DIR plans, but only 61% of PTVRO did. Spatial DD analysis showed median pass rates of 99.2% (DD5%) and 74.5% (DD2%) for GTVRO + CTVRO, and 85.5% (DD5%) and 54.9% (DD2%) for PTVRO.
CONCLUSION: Smartfuse may facilitate efficient propagation of target volumes in this study. However, medical review of auto-propagated volumes remains essential, as dosimetric discrepancies may arise when relying solely on automatically generated PTV.
MATERIALS AND METHODS: Ten patients underwent offline re-planning during head-and-neck radiotherapy. Target volumes (GTV and CTV) were manually delineated by radiation oncologists (ROs) on both the initial CT (CTi) and one re-planning CT (CTR). These manual contours were compared to those propagated by Smartfuse from CTi to CTR. The geometric agreement between DIR-propagated and RO-delineated contours was assessed using Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), and surface Dice similarity coefficient (sDSC) with 0 and 2 mm thresholds. Dosimetric evaluation was conducted by comparing dose distributions from generated plans using automatically propagated target volumes (PTVDIR) with reference plans based on RO-delineated targets (PTVRO). Coverage of RO-delineated targets (GTVRO + CTVRO and PTVRO) was assessed using D95%, D50%, Dmax, and V95% ≥ 95%. Spatial dose differences were analyzed using dose difference (DD) metrics at 5% and 2% thresholds.
RESULTS: Median DSC, HD95, sDSC0 mm and sDSC2 mm were 0.86, 4.0 mm, 0.29 and 0.73, respectively. For D95%, median relative differences between DIR and RO plans were -0.6% for GTVRO + CTVRO and -2.1% for PTVRO for D95%. All GTVRO + CTVRO reached V95% ≥ 95% with DIR plans, but only 61% of PTVRO did. Spatial DD analysis showed median pass rates of 99.2% (DD5%) and 74.5% (DD2%) for GTVRO + CTVRO, and 85.5% (DD5%) and 54.9% (DD2%) for PTVRO.
CONCLUSION: Smartfuse may facilitate efficient propagation of target volumes in this study. However, medical review of auto-propagated volumes remains essential, as dosimetric discrepancies may arise when relying solely on automatically generated PTV.