Automated Detection and Segmentation of Bone Metastases on Spine MRI Using U-Net: A Multicenter Study.

ABSTRACT:

Objective

To develop and evaluate a deep learning model for automated segmentation and detection of bone metastasis on spinal MRI.

Materials and methods

We included whole spine MRI scans of adult patients with bone metastasis: 662 MRI series from 302 patients (63.5 ± 11.5 years; male:female, 151:151) from three study centers obtained between January 2015 and August 2021 for training and internal testing (random split into 536 and 126 series, respectively) and 49 MRI series from 20 patients (65.9 ± 11.5 years; male:female, 11:9) from another center obtained between January 2018 and August 2020 for external testing. Three sagittal MRI sequences, including non-contrast T1-weighted image (T1), contrast-enhanced T1-weighted Dixon fat-only image (FO), and contrast-enhanced fat-sup

SUBMITTER: Kim DH 

PROVIDER: S-EPMC10973735 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature