Swin UNETR-based prediction of [<sup>68</sup>Ga]Ga-FAPI-46 PET/CT dose rate maps in cancer patients: quantitative comparison with [<sup>18</sup>F]FDG PET/CT.
Authors
Affiliations (6)
Affiliations (6)
- Department of Medical Radiation Engineering, SR.C., Islamic Azad University, Tehran, Iran.
- Department of Medical Radiation Engineering, SR.C., Islamic Azad University, Tehran, Iran. [email protected].
- Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
- Research Center for Nuclear Medicine, Tehran University of Medical Sciences, Tehran, Iran.
- Division of Nuclear Medicine & Molecular Imaging, Geneva University Hospital, Geneva, CH-1211, Switzerland.
- Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran. [email protected].
Abstract
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 [<sup>68</sup>Ga]Ga-FAPI-46 PET/CT, following a quantitative and dosimetric comparison with [<sup>18</sup>F]FDG PET/CT. The approach supports personalized pre-therapeutic planning in radiopharmaceutical therapies (RPTs). PET/CT scans with [<sup>68</sup>Ga]Ga-FAPI-46 and [<sup>18</sup>F]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 [<sup>68</sup>Ga]Ga-FAPI-46 and [<sup>18</sup>F]FDG was compared using SUV<sub>max</sub>, SUV<sub>mean</sub>, 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. [<sup>68</sup>Ga]Ga-FAPI-46 PET/CT demonstrated higher TBRs and lower OARs uptake and ADs compared to [<sup>18</sup>F]FDG, indicating its promise in enhancing lesion detectability. The Swin UNETR model achieved an RMSE of 0.0598 Gy<sup>2</sup>/s, R<sup>2</sup> of 0.960, and a gamma pass rate of 98.71%, outperforming ResNet-32. Compared to [<sup>18</sup>F]FDG, [<sup>68</sup>Ga]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 [<sup>68</sup>Ga]Ga-FAPI-46, broader validation in larger, multicenter cohorts is needed to ensure reproducibility and clinical impact.