Machine Learning Models Combining [68Ga]Ga-PSMA-11 PET Radiomics and Clinical Features to Predict Overall Survival for Metastatic Castration-resistant Prostate Cancer Treated with [177Lu]Lu-PSMA Radioligand Therapy.

Lucas Edouard¹, Léa Papillon², Loïc Ferrer², Yann Godbert³, Marie Meyer³, Vincent Prega-Renaud³, Céline Subreville⁴, Nadège Anizan⁵, Nicolas Benziane-Ouaritini⁶, Olivier Gallinato², Mathilde Cabart⁶, Diego Teyssonneau⁶, Guilhem Roubaud⁶, Thierry Colin², Paul Schwartz³

¹Nuclear Medicine Department, Institut Bergonié, Bordeaux, France. Electronic address: lucas@edouard.eu.

²Sophia Genetics, Pessac, France.

³Nuclear Medicine Department, Institut Bergonié, Bordeaux, France.

⁴Department of Pharmacy, Institut Bergonié, Bordeaux, France.

⁵Department of Physics, Institut Bergonié, Bordeaux, France.

⁶Department of Medical Oncology, Institut Bergonié, Bordeaux, France.

PubMed DOI

Abstract

PURPOSE: Metastatic castration-resistant prostate cancer (mCRPC) remains incurable despite recent therapeutic advances. [177Lu]Lu-PSMA RLT (lutetium-177 labelled prostate-specific membrane antigen radioligand therapy) provides meaningful clinical benefit in selected patients. However, ∼30% of the patients do not respond to [177Lu]Lu-PSMA RLT. Although several baseline prognostic factors are well k…

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