title: Left ventricular deformation recovery from cine MRI using an incompressible model.
abstract: This paper presents a method for 3-D deformation recovery of the left ventricular (LV) wall from anatomical cine magnetic resonance imaging (MRI). The method is based on a deformable model that is incompressible, a desired property since the myocardium has been shown to be nearly incompressible. The LV wall needs to be segmented in an initial frame after which the method automatically determines the deformation everywhere in the LV wall throughout the cardiac cycle. Two studies were conducted to validate the method. In the first study, the deformation recovered from a 3-D anatomical cine MRI of a healthy volunteer was compared against the manual segmentation of the LV wall and against the corresponding 3-D tagged cine MRI. The average volume agreement between the model and the manual segmentation had a false positive rate of 3%, false negative rate of 3%, and true positive rate of 93%. The average distance between the model and manually determined intersections of perpendicular tag planes was 1.6 mm (1.1 pixel). Another set of 3-D anatomical and tagged MRI scans was taken of the same volunteer four months later. The method was applied to the second set and the recovered deformation was very similar to the one obtained from the first set. In the second study, the method was applied to 3-D anatomical cine MRI scans of three patients with ventricular dyssynchrony and three age-matched healthy volunteers. The LV wall deformations recovered for the three normals agreed well and the recovered strains were similar to those reported by other researchers for normal subjects. Strains and displacements of the three patients were clearly smaller than those of the three normals indicating reduced cardiac function. The deformation recovered for the three normals and the three patients was validated against manual segmentation and corresponding tag cine MRI scans and the agreement was similar to that of the first validation study.
authors: Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
authors: Arnaud
authors: A
authors: Bistoquet
authors: John
authors: J
authors: Oshinski
authors: Oskar
authors: O
authors: Skrinjar
mesh_terms: D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D004548:Elasticity; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013314:Stress, Mechanical; D013382:Subtraction Technique; D018487:Ventricular Dysfunction, Left / Q000175:diagnosis* / Q000503:physiopathology*