Machine learning-based analysis of [¹⁸F]DCFPyL PET radiomics for risk stratification in primary prostate cancer.

ABSTRACT:

Purpose

Quantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [¹⁸F]DCFPyL PET metrics to predict metastatic disease or high-risk pathological tumor features.

Methods

In a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [¹⁸F]DCFPyL PET-CT. Primary tumors were delineated using 50-70% peak isocontour thresholds on images with and without partial-volume correction (PVC). Four hundred and eighty standardized radiomic featur

SUBMITTER: Cysouw MCF 

PROVIDER: S-EPMC7835295 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature