ArticleJournal of applied clinical medical physics2026
Image-based evaluation of a commercial AI synthetic CT generator for brain and prostate MR-only radiotherapy.
Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundSynthetic CTs (sCT) were developed to provide electron density information for MR-only treatment planning. Some AI-based sCT generators have received FDA-clearance and better capture tissue heterogeneity through voxel-wise mappings to improve image guidance and dose calculation. PURPOSE: To quantitatively characterize the image quality and geometric surrogate agreement of an FDA 510(k) cleared AI-based synthetic CT generator (TheraPanacea) for brain and prostate MR-only radiotherapy, using per-structure volumetric analysis, Hounsfield unit (HU) assessment, and multi-metric geometric evaluation.
methodsPaired CT/MR datasets from 20 brain and 20 prostate patients were retrospectively analyzed. sCTs were generated from T1w (brain) and T2w (pelvis) MR images acquired on the same day with identical immobilization. Auto-contours from TheraPanacea and MIM Contour ProtégéAI were compared against MIM Contour ProtégéAI contours on the reference CT. Bone was segmented via a fixed-threshold method. Evaluation metrics included contour volumes, cross-contour HU comparisons, centroid offsets, overlap and surface-based similarity metrics, and manual bony landmark measurements.
resultsSoft-tissue mean HU differences were <50 HU across both cohorts. Central ROIs showed <20 HU deviations, apart from heterogeneous bone and air-filled regions. Bony structures exhibited HU range compression in the sCT, where HU differences between the sCT and the reference CT differed by a maximum of 347 ± 14 HU in the femoral heads and 455 ± 50 HU in the sacrum. Global histograms confirmed HU range compression. Centroids shifted < 2 mm for all contours (brain A-P predominant, pelvis non-systematic). Boundary metrics showed MDA < 5 mm, and bony landmarks differed < 1 mm between the reference CT and the sCT. Small structures in the brain had inconsistent auto-segmentation, displaying different volumes and low Dice/JI scores. Dental implants in the sCT produced localized MR-like susceptibility artifacts. Within manual contoured implant ROIs, the mean HU values were underestimated by ∼9,000 HU relative to CT.
conclusionTheraPanacea sCT demonstrated acceptable soft-tissue HU (± 50 HU) and geometric surrogate agreement (< 2-5 mm) relative to CT, with larger errors in cortical bone, air interfaces, and implants. Site-specific QA must verify bone HU compression, peripheral geometric agreement via landmark measures, and manually review small/high-contrast contours (optic nerves, cochleae, rectum). Institutional image and dosimetric validation, particularly with implanted devices, remains essential prior to clinical deployment.
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