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Prognostic Value of AI-Assisted Lesion Tracking on End-of-Treatment PSMA PET in mCRPC Patients Treated with
Vishnu Murthy1, Koichiro Kimura1, Lela Theus1
1Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, Ahmanson Translational Theranostics Division, Los Angeles, California.
Abstract:
This study aimed to explore the prognostic value of the artificial intelligence-assisted lesion tracking applied to prostate-specific membrane antigen (PSMA) PET in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with PSMA radiopharmaceutical therapy. Methods: TRAQinform IQ was applied to baseline and end-of-treatment 68Ga-PSMA-11 PET scans from 20 patients with mCRPC treated with 177Lu-PSMA-617. Lesion response parameters and the TRAQinform Profile score-designed for early treatment response assessment-were generated. Survival analyses were performed. Results: A higher percentage of "new" lesions was associated with a shorter overall survival (OS) (hazard ratio, 1.03; P = 0.002), whereas a higher percentage of "disappeared" lesions was linked to improved OS (hazard ratio, 0.98; P = 0.028). Patients with a TRAQinform Profile score of 2.7 or greater had a shorter OS than those with a score of less than 2.7 (10.9 mo vs. 44.3 mo; P = 0.027). Conclusion: Artificial intelligence-assisted lesion-tracking analysis of PSMA PET is prognostic for OS in patients with mCRPC undergoing PSMA radiopharmaceutical therapy.
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