A study on whether deep learning models based on CT images for bone density classification and prediction can be used for opportunistic osteoporosis screening.

ABSTRACT: This study utilized deep learning to classify osteoporosis and predict bone density using opportunistic CT scans and independently tested the models on data from different hospitals and equipment. Results showed high accuracy and strong correlation with QCT results, showing promise for expanding osteoporosis screening and reducing unnecessary radiation and costs.

Purpose

To explore the feasibility of using deep learning to establish a model for osteoporosis classification and bone density value prediction based on opportunistic CT scans and to verify its generalization and diagnostic ability using an independent test set.

Methods

A total of 1219 cases of opportunistic CT scans were included in this study, with QCT results as the reference standard. The training set: test set:

SUBMITTER: Peng T 

PROVIDER: S-EPMC10786975 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature