Global left ventricular function in cardiac CT. Evaluation of an automated 3D region-growing segmentation algorithm

Eur Radiol. 2006 May;16(5):1117-23. doi: 10.1007/s00330-005-0079-z. Epub 2005 Dec 22.

Abstract

The purpose was to evaluate a new semi-automated 3D region-growing segmentation algorithm for functional analysis of the left ventricle in multislice CT (MSCT) of the heart. Twenty patients underwent contrast-enhanced MSCT of the heart (collimation 16 x 0.75 mm; 120 kV; 550 mAseff). Multiphase image reconstructions with 1-mm axial slices and 8-mm short-axis slices were performed. Left ventricular volume measurements (end-diastolic volume, end-systolic volume, ejection fraction and stroke volume) from manually drawn endocardial contours in the short axis slices were compared to semi-automated region-growing segmentation of the left ventricle from the 1-mm axial slices. The post-processing-time for both methods was recorded. Applying the new region-growing algorithm in 13/20 patients (65%), proper segmentation of the left ventricle was feasible. In these patients, the signal-to-noise ratio was higher than in the remaining patients (3.2+/-1.0 vs. 2.6+/-0.6). Volume measurements of both segmentation algorithms showed an excellent correlation (all P<or=0.0001); the limits of agreement for the ejection fraction were 2.3+/-8.3 ml. In the patients with proper segmentation the mean post-processing time using the region-growing algorithm was diminished by 44.2%. On the basis of a good contrast-enhanced data set, a left ventricular volume analysis using the new semi-automated region-growing segmentation algorithm is technically feasible, accurate and more time-effective.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Aged
  • Algorithms*
  • Cardiac Volume*
  • Coronary Artery Disease / diagnostic imaging
  • Coronary Artery Disease / physiopathology
  • Female
  • Heart Ventricles / diagnostic imaging
  • Heart Ventricles / physiopathology
  • Humans
  • Image Processing, Computer-Assisted*
  • Male
  • Middle Aged
  • Pattern Recognition, Automated*
  • Stroke Volume
  • Tomography, X-Ray Computed*
  • Ventricular Function, Left*