[¹⁷⁷Lu]Lu-PSMA RLT represents an effective option for advanced mCRPC. SPECT/CT allows the assessment of biodistribution and lesion-level tracer accumulation. We aimed to determine whether semiquantitative RLT SPECT/CT parameters could predict response on a lesion level.
We retrospectively considered consecutive mCRPC patients who, between February 2022 and January 2026, received minimum two [¹⁷⁷Lu]Lu-PSMA-617 cycles at Messina and Genova Universities, with SPECT/CT at the 1st RLT, including whole PSMA-positive disease. Each [¹⁷⁷Lu]Lu-PSMA-617-positive lesion was semiautomatically segmented using MIM through a 40% threshold to extract SUVmax, SUVmean, Total Lesion Volume (TLV), and Total Lesion Activity (TLA=SUVmean×TLV). Each lesion's semiquantitative parameter was correlated with the single-lesion response at the last RLT cycle, classified as progressive or non-progressive (complete/partial response, stable disease) according to cut-offs from qualitative RECIP 1.0 and quantitative PPP criteria. ROC curves were used to determine the best cutoffs.
We included 23 mCRPC patients for a total of 290 lesions: 249 osteomedullary, 34 lymph nodal, and 7 visceral. At the last cycle, 60 out of 290 lesions progressed, while 230 out of 290 remained stable/responded to RLT. 1st cycle [¹⁷⁷Lu]Lu-PSMA-617 SPECT/CT semiquantitative parameters were significantly higher in non-PD than in PD lesions (p < 0.001 for TLA, SUVmax, SUVmean; p = 0.008 for TLV). On ROC analysis, TLA reached an AUC of 0.854 (best cut-off = 61.7), SUVmax 0.843 (best cut-off = 11.8), SUVmean 0.838 (best cut-off = 6), and TLV 0.612 (best cut-off = 7.05mL), respectively.
Our preliminary findings suggest that 1st cycle [¹⁷⁷Lu]Lu-PSMA-617 SPECT/CT semiquantitative parameters, especially when reflecting PSMA-expression, may serve as promising early predictors of the single-lesion response to RLT.
European journal of nuclear medicine and molecular imaging. 2026 May 20 [Epub ahead of print]
Riccardo Laudicella, Greta Celesti, Matteo Bauckneht, Agatino Micali, Federica Midili, Antonio Bucca, Victorian M Ferro, Michela Piergentili, Giorgia Ricciardello, Anna Brogna, Benedetta Pagano, Sergio Baldari, Irene A Burger, Fabio Minutoli
Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy. ., Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy., IRCCS Azienda Ospedaliera Metropolitana, Genova, Italy., Health Physics Unit, Messina University Hospital G. Martino, Messina, Italy., Health Physics School of Specialization, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy., Department of Nuclear Medicine, Faculty of Medicine, Kantonsspital Baden, affiliated Hospital for Research and Teaching, University of Zurich, Baden, Switzerland.