AI predicts responses in patients with prostate cancer

An AI model based on F-18 DCFPyL PSMA-PET/CT images shows promise for predicting treatment response in patients with metastatic castration-resistant prostate cancer (mCRPC), according to a study presented November 30 at RSNA in Chicago. The deep-learning model was trained on PET/CT imaging from 128 patients and identified a high-risk subgroup who may benefit from focused care or alternative therapies, said Andrew Voter, MD, of Johns Hopkins Medicine in Baltimore, MD.“Despite widespread adoption of prostate-specific membrane antigen [PSMA] PET/CT imaging for prostate cancer, prognostication of patient outcomes remains challenging,” he noted.To that end, Voter and colleagues tested the feasibility of a multimodal fusion 3D convolutional neural network (CNN) to identify patients at risk for progression based on baseline PSMA-PET/CT imaging.The training set included baseline PSMA-PET/CT scans using F-18 DCFPyL radiotracer (Pylarify, Lantheus Medical Imaging) and follow-up scans over three years from 148 patients (age, 71.7 ± 8.4 years; average PSA levels, 19.4) with mCRPC. In these, a total of 1,781 radiotracer-avid foci were labeled as suspicious for malignancy. Lesions were classified as either progressive or nonprogressive based on increased radiotracer avidity or a greater than 2 mm increase in size.Next, the researchers validated the model using an independent test set of PET/CT images comprising 320 lesions from 34 patients (age, 72.2 ± 7.1 years; average PSA levels 1...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Subspecialties Molecular Imaging Genitourinary Radiology Source Type: news