Machine learning for abdominal aortic calcification assessment from bone density machine-derived lateral spine images.

ABSTRACT:

Background

Lateral spine images for vertebral fracture assessment can be easily obtained on modern bone density machines. Abdominal aortic calcification (AAC) can be scored on these images by trained imaging specialists to assess cardiovascular disease risk. However, this process is laborious and requires careful training.

Methods

Training and testing of model performance of the convolutional neural network (CNN) algorithm for automated AAC-24 scoring utilised 5012 lateral spine images (2 manufacturers, 4 models of bone density machines), with trained imaging specialist AAC scores. Validation occurred in a registry-based cohort study of 8565 older men and women with images captured as part of routine clinical practice for fracture risk assessment. Cox proportional hazards mo

SUBMITTER: Sharif N 

PROVIDER: S-EPMC10435763 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature