Atherosclerotic Plaque Burden on Abdominal CT: Automated Assessment With Deep Learning on Noncontrast and Contrast-enhanced Scans.

ABSTRACT:

Background

Abdominal aortic atherosclerotic plaque burden may have clinical significance but manual measurement is time-consuming and impractical.

Purpose

To perform external validation on an automated atherosclerotic plaque detector for noncontrast and postcontrast abdominal CT.

Materials and methods

The training data consisted of 114 noncontrast CT scans and 23 postcontrast CT urography scans. The testing data set consisted of 922 CT colonography (CTC) scans, and 1207 paired noncontrast and postcontrast CT scans from renal donors from a second institution. Reference standard data included manual plaque segmentations in the 137 training scans and manual plaque burden measurements in the 922 CTC scans. The total Agatston score and group (0-3) was determined using full

SUBMITTER: Summers RM 

PROVIDER: S-EPMC7969468 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature