Computer evaluation of left ventricular wall motion by means of shape-based tracking and symbolic description.
Relevant cardiac pathologies manifest themselves as abnormal movements of left ventricular (LV) myocardial wall. An objective quantification is usually accomplished by computer analysis of temporal sequences of LV contours, as obtained by angiography or echography. However the choice of the reference system for measuring motion is still open to discussion. Simple geometric models cannot deal with the non-uniform myocardial fibre structure, which gives rise to non-rigid movements, asynchronous even in normal subjects. Therefore, a new method, Curvature-Motion (CM), was developed for improving motion assessment. Since LV contour shape and position change smoothly throughout the cardiac cycle, the points of curvature extremes are tracked frame-to-frame and selected by exploiting physiologically-based assumptions; then, the points lying among these landmarks are mapped onto sequential contours, according to local displacements and curvature changes. In this way point-trajectories are allowed to be curvilinear and different in systole and diastole. CM gave no significant differences in estimating the known motion of computer-generated contours (R=0.88), unlike other methods commonly adopted (R<0.80). Moreover, for the evaluation of regional wall motion of a preclassified set of angiographic contours, CM showed a greater specificity (88%) and accuracy (90%) with respect to the centre-line method (respectively 83% and 87%). Finally, a fuzzy logic inference system is proposed for translating significant motion patterns from the quantitative form, as provided by the analysis method, into the linguistic terms used by cardiologists in their clinical examinations. This makes the interpretation of quantitative analysis easier and allows medical users to interact with the system for searching particular properties in a single clinical report as well as in a large database.
Baroni
M
M
Department of Electronic Engineering, University of Florence, Italy. baroni@diefi.die.unifi.it
D000465:Algorithms; D002932:Cineangiography / Q000379:methods; D003198:Computer Simulation; D003287:Contrast Media; D003323:Coronary Aneurysm / Q000000981:diagnostic imaging; D003327:Coronary Disease / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation* / Q000379:methods*; D015635:Radionuclide Ventriculography; D013997:Time Factors; D018487:Ventricular Dysfunction, Left / Q000000981:diagnostic imaging; D016276:Ventricular Function
D003287:Contrast Media