Automated quantification of PET/CT skeletal tumor burden in prostate cancer using artificial intelligence: The PET index.

ABSTRACT:

Purpose

Consistent assessment of bone metastases is crucial for patient management and clinical trials in prostate cancer (PCa). We aimed to develop a fully automated convolutional neural network (CNN)-based model for calculating PET/CT skeletal tumor burden in patients with PCa.

Methods

A total of 168 patients from three centers were divided into training, validation, and test groups. Manual annotations of skeletal lesions in [¹⁸F]fluoride PET/CT scans were used to train a CNN. The AI model was evaluated in 26 patients and compared to segmentations by physicians and to a SUV 15 threshold. PET index representing the percentage of skeletal volume taken up by lesions was estimated.

Results

There was no case in which all readers agreed on prevalence of lesions

SUBMITTER: Lindgren Belal S 

PROVIDER: S-EPMC10027829 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature