An automated 4D approach for left ventricular assessment in clinical cine MR images

Abstract

Cine Magnetic Resonance (MR) imaging has become the method-of-choice for the examination of the dynamic behaviour of the heart. An assessment of the left ventricle can reveal regions of myocardial dysfunction and their severeness. The scope of this work is a complete analysis of the left ventricular dynamics for the usage in a clinical environment. For that purpose, endocardial and epicardial borders are automatically extracted in 3D cine data in a first step. This is followed by a segmentation of the endocardium and the myocardium into 17 segments following the recommendations of the American Heart Association and the computation of common global volumetric values (stroke volume, ejection fraction etc.) and parameters that describe the left ventricular dynamics (wall motion, wall thickening). A retrospective analysis of cardiac cine MR image data from 20 patients (healthy ones, patients with abnormal wall motion, and patients who suffered an infarction) has been done. That image data has been acquired in the clinical routine at two different hospitals. The here presented automated approach led to a successful segmentation and assessment of the left ventricle for all data sets. The pathological cases could be identified easily due to their characteristic change of the motion pattern. The main advantage of our approach is the reproducibility of the assessment results and the gain in time for the cardiologist who has to analyse the huge amount of cine data.