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COCORIVO is an interventional study evaluating the impact of body composition on dosimetry of 177Lu-PSMA radioligand therapy in patients with metastatic castration-resistant prostate cancer (mCRPC). Body composition (muscle, lean, visceral fat, subcutaneous fat and total fat masses) will be automatically quantified from whole-body CT images acquired at 72-96h after 177Lu-PSMA injection using the Anthropometer3DNet software. Dosimetry will be evaluated for tumors and organs at risk (salivary glands, bone marrow, kidneys). The study also evaluates the impact of body composition on SUV quantification, the feasibility of single-timepoint dosimetry, and the evolution of body composition during treatment.
Full description
Prostate-specific membrane antigen (PSMA) is highly expressed in metastatic castration-resistant prostate cancer. 177Lu-PSMA-617 is a radioligand therapy delivering beta-particle radiation to PSMA-expressing cells. The VISION trial demonstrated significant improvement in progression-free and overall survival compared to standard of care.
Hypotheses: patients with higher fat mass may have better treatment response due to higher tumor dose; discordance between BMI-based and CT-based body composition measurements; SUV quantification in PET/CT and SPECT/CT depends on patient morphology; dosimetry of organs at risk depends on morphology; body composition changes during treatment; PSA kinetics are modified by dosimetry.
Study design: patients scheduled for 177Lu-PSMA treatment (4 or 6 cycles, 7400 MBq IV every 6 weeks) are enrolled. After cycle 1, SPECT/CT is performed at 72-96H (all patients) and additionally at 4-24H and 168-196H (40 patients for multipoint dosimetry). Body composition is extracted from the non-injected CT component of SPECT/CT using Anthropometer3DNet. Nutritional assessment (MNA questionnaire, blood tests including albumin, transthyretin, CRP, PSA) is performed at baseline (C1) and end of treatment (C4 or C6).
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100 participants in 1 patient group
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Pierre Decazes, MD, PhD; Doriane Richard, PhD
Data sourced from clinicaltrials.gov
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