Swin Unetr-Based Prediction of [68Ga]Ga-Fapi-46 Pet/Ct Dose Rate Maps in Cancer Patients: Quantitative Comparison With [18F]Fdg Pet/Ct Publisher Pubmed



Izadi Yazdi S ; Babapour Mofrad F ; Yazdani E ; Karamzade Ziarati N ; Arabi H ; Sadeghi M
Source: BMC Medical Imaging Published:2026

Abstract

Background: Fibroblast activation protein (FAP) is a promising theranostic target due to its high stroma expression in numerous malignancies. This study presents the first DL-based framework for predicting dose rate maps (DRMs) from [68Ga]Ga-FAPI-46 PET/CT, following a quantitative and dosimetric comparison with [18F]FDG PET/CT. The approach supports personalized pre-therapeutic planning in radiopharmaceutical therapies (RPTs). Methods: PET/CT scans with [68Ga]Ga-FAPI-46 and [18F]FDG from 22 cancer patients were retrospectively analyzed. DRMs were generated using the dose voxel kernel (DVK) method using the GATE toolkit. Absorbed doses (ADs) obtained from DVK-based DRMs for tumors and organs at risk (OARs) were compared with those derived from full Monte Carlo (MC), and local energy deposition (LED), based DRMs, and organ-level estimates calculated using OLINDA/EXM v1.1. Tracer uptake of [68Ga]Ga-FAPI-46 and [18F]FDG was compared using SUVmax, SUVmean, and tumor-to-background ratio (TBR). A shifted windows UNEt TRansformers (Swin UNETR) model was trained to predict DRMs and benchmarked against ResNet-32 using R², RMSE, and gamma index. Results: [68Ga]Ga-FAPI-46 PET/CT demonstrated higher TBRs and lower OARs uptake and ADs compared to [18F]FDG, indicating its promise in enhancing lesion detectability. The Swin UNETR model achieved an RMSE of 0.0598 Gy2/s, R2 of 0.960, and a gamma pass rate of 98.71%, outperforming ResNet-32. Conclusion: Compared to [18F]FDG, [68Ga]Ga-FAPI-46 PET offers higher image contrast, better lesion detectability, and improved dosimetric profiles, supporting personalized RPT planning. While Swin UNETR enables fast and accurate DRM prediction from [68Ga]Ga-FAPI-46, broader validation in larger, multicenter cohorts is needed to ensure reproducibility and clinical impact. © The Author(s) 2026.