Deep Learning Model for Classifying Metastatic Epidural Spinal Cord Compression on MRI.

ABSTRACT:

Background

Metastatic epidural spinal cord compression (MESCC) is a devastating complication of advanced cancer. A deep learning (DL) model for automated MESCC classification on MRI could aid earlier diagnosis and referral.

Purpose

To develop a DL model for automated classification of MESCC on MRI.

Materials and methods

Patients with known MESCC diagnosed on MRI between September 2007 and September 2017 were eligible. MRI studies with instrumentation, suboptimal image quality, and non-thoracic regions were excluded. Axial T2-weighted images were utilized. The internal dataset split was 82% and 18% for training/validation and test sets, respectively. External testing was also performed. Internal training/validation data were labeled using the Bilsky MESCC classificatio

SUBMITTER: Hallinan JTPD 

PROVIDER: S-EPMC9114468 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature