Prediction of Lesion-Based Treatment Response after Two Cycles of Lu-177 Prostate Specific Membrane Antigen Treatment in Metastatic Castration-Resistant Prostate Cancer Using Machine Learning.

Journal: Urologia internationalis

PMID: 39348812

Abstract

INTRODUCTION: Lutetium-177 (Lu-177) prostate-specific membrane antigen (PSMA) therapy is a radionuclide treatment that prolongs overall survival in metastatic castration-resistant prostate cancer (MCRPC). We aimed to predict lesion-based treatment response after Lu-177 PSMA treatment using machine learning with texture analysis data obtained from pretreatment Gallium-68 (Ga-68) PSMA positron emission tomography/computed tomography (PET/CT).

Authors

Ogün Bülbül

Department of Nuclear Medicine, Recep Tayyip Erdogan University, Faculty of Medicine, Training and Research Hospital, Rize, Turkey.
Demet Nak

Department of Nuclear Medicine, Recep Tayyip Erdogan University, Faculty of Medicine, Training and Research Hospital, Rize, Turkey.
Sibel Göksel

Department of Nuclear Medicine, Adnan Menderes University, Faculty of Medicine, Aydin, Turkey.

Keywords

Aged Aged, 80 and over Antigens, Surface Gallium Radioisotopes Glutamate Carboxypeptidase II Humans Lutetium Machine Learning Male Middle Aged Neoplasm Metastasis Positron Emission Tomography Computed Tomography Prostatic Neoplasms, Castration-Resistant Radioisotopes Radiopharmaceuticals Retrospective Studies Treatment Outcome

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View on PubMed Access via DOI PubMed (39348812)

Prediction of Lesion-Based Treatment Response after Two Cycles of Lu-177 Prostate Specific Membrane Antigen Treatment in Metastatic Castration-Resistant Prostate Cancer Using Machine Learning.

Abstract

Authors

Keywords

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