Parameter distribution models for estimation of population based left ventricular deformation using sparse fiducial markers.
We present a method to estimate left ventricular (LV) motion based on three-dimensional (3-D) images that can be derived from any anatomical tomographic or 3-D modality, such as echocardiography, computed tomography, or magnetic resonance imaging. A finite element mesh of the LV was constructed to fit the geometry of the wall. The mesh was deformed by optimizing the nodal parameters to the motion of a sparse number of fiducial markers that were manually tracked in the images through the cardiac cycle. A parameter distribution model (PDM) of LV deformations was obtained from a database of MR tagging studies. This was used to filter the calculated deformation and incorporate a priori information on likely motions. The estimated deformation obtained from 13 normal untagged studies was compared with the deformation obtained from MR tagging. The end systolic (ES) circumferential and longitudinal strain values matched well with a mean difference of 0.1 +/- 3.2% and 0.3 +/- 3.0%, respectively. The calculated apex-base twist angle at ES had a mean difference of 1.0 +/- 2.3 degrees. We conclude that fiducial marker fitting in conjunction with a PDM provides accurate reconstruction of LV deformation in normal subjects.
Remme
Espen W
EW
Institute for Surgical Research, Rikshospitalet University Hospital, 0027 Oslo, Norway. espen.remme@medisin.uio.no
Augenstein
Kevin F
KF
Young
Alistair A
AA
Hunter
Peter J
PJ
D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D004548:Elasticity; D005240:Feasibility Studies; D005260:Female; D006352:Heart Ventricles / Q000033:anatomy & histology; 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; D008955:Models, Cardiovascular; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D016008:Statistical Distributions; D013318:Stroke Volume; D013382:Subtraction Technique; D016276:Ventricular Function; D016277:Ventricular Function, Left / Q000502:physiology*