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Skeletal muscle radiodensity as an automated survival predictor in men with metastatic castration-resistant prostate cancer undergoing PSMA-targeted radioligand therapy

Year: 2026
Type: article
Study design: Observational Study
Abstract: PURPOSE: Skeletal muscle radiodensity (SMD) is an emerging imaging-derived marker of muscle quality. Its prognostic relevance in patients with metastatic castration-resistant prostate cancer (mCRPC) undergoing [¹⁷⁷Lu]Lu-PSMA-617 radioligand therapy has not yet been systematically evaluated. This study aims to investigate the prognostic value of SMD derived from routine pretherapeutic PET/CT imaging in a large real-world mCRPC cohort treated with [¹⁷⁷Lu]Lu-PSMA-617. METHODS: In this single-center study, the largest to date cohort comprising 410 mCRPC patients was analyzed. SMD was quantified automatically from the L3-level CT component of pretherapeutic [⁶⁸Ga]Ga-PSMA-PET/CT using an AI-based segmentation tool. An optimal SMD cut-off (19.26 HU) was determined for survival stratification. Associations with overall survival (OS) were assessed using multivariable Cox regression (univariable and multivariable, adjusted for baseline PSA) and Kaplan-Meier analysis. RESULTS: Lower SMD was associated with reduced OS (HR 1.87, P<.001). Median OS were significantly shorter in the SMD-low group compared to the SMD-high group (7.6 months vs. 12.2 months; P<.001). This prognostic stratification was seen in both, patients with or without PSA50 or PSA90 response, respectively. SMD correlated with age, albumin, and PSA, but not with BMI. CONCLUSION: SMD assessed from routine pretherapeutic PET/CT is a non-invasive prognostic biomarker in patients undergoing PSMA-targeted radioligand therapy. Integration of host-derived imaging biomarkers such as SMD with tumor-specific parameters may improve risk stratification, prehabilitation and support future individualized treatment strategies in advanced prostate cancer.
Language: English
Field: Medicine
Open Access status: hybrid
Estimated APC paid: $3,490
OpenAlex ID: W7170095992
FWCI:
Cites: 36
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