biostudies-literatureUnknown131(2)Kendrick JDepartment of Health, Government of Western Australia<h4>Objectives</h4>The primary aim of this study was to quantify the subject-level test-retest repeatability of artificial intelligence (AI)-derived PSMA PET imaging biomarkers using a previously developed model. The secondary aim was to assess the performance of this segmentation model, which was trained on [⁶⁸ Ga]Ga-PSMA-11 PET scans, on [¹⁸F]F-PSMA-1007 PET scans.<h4>Methods</h4>This was a post-hoc analysis of a prospective, single-center, test-retest trial. Seventeen patients with metastatic prostate cancer (mPCa) were randomised into groups, either receiving the same tracer ([⁶⁸ Ga]Ga-PSMA-11 or [¹⁸F]F-PSMA-1007) for both scans (intra-tracer group, n = 9) or a different tracer (inter-tracer group, n = 8). Scans were delineated using a fully La Radiologia medica320-331https://www.ebi.ac.uk/biostudies/studies/S-EPMC12932408biostudies-literatureDeep learning-based PSMA PET segmentation repeatability: A post-hoc analysis of a single-center, prospective, test-retest trial.PMC12932408Ebert MAHassan GMBarry NOng JSLJeraj RKendrick JFrancis RJfalseDeep learning-based PSMA PET segmentation repeatability: A post-hoc analysis of a single-center, prospective, test-retest trial.<h4>Objectives</h4>The primary aim of this study was to quantify the subject-level test-retest repeatability of artificial intelligence (AI)-derived PSMA PET imaging biomarkers using a previously developed model. The secondary aim was to assess the performance of this segmentation model, which was trained on [⁶⁸ Ga]Ga-PSMA-11 PET scans, on [¹⁸F]F-PSMA-1007 PET scans.<h4>Methods</h4>This was a post-hoc analysis of a prospective, single-center, test-retest trial. Seventeen patients with metastatic prostate cancer (mPCa) were randomised into groups, either receiving the same tracer ([⁶⁸ Ga]Ga-PSMA-11 or [¹⁸F]F-PSMA-1007) for both scans (intra-tracer group, n = 9) or a different tracer (inter-tracer group, n = 8). Scans were delineated using a fully 2026-01-01T00:00:00Z2026 Feb2026-07-16T21:32:44.165Z2026-07-10T03:16:28.009ZS-EPMC129324084116603210.1007/s11547-025-02137-1