A computational framework for the statistical analysis of cardiac diffusion tensors: application to a small database of canine hearts.
We propose a unified computational framework to build a statistical atlas of the cardiac fiber architecture from diffusion tensor magnetic resonance images (DT-MRIs). We apply this framework to a small database of nine ex vivo canine hearts. An average cardiac fiber architecture and a measure of its variability are computed using most recent advances in diffusion tensor statistics. This statistical analysis confirms the already established good stability of the fiber orientations and a higher variability of the laminar sheet orientations within a given species. The statistical comparison between the canine atlas and a standard human cardiac DT-MRI shows a better stability of the fiber orientations than their laminar sheet orientations between the two species. The proposed computational framework can be applied to larger databases of cardiac DT-MRIs from various species to better establish intraspecies and interspecies statistics on the anatomical structure of cardiac fibers. This information will be useful to guide the adjustment of average fiber models onto specific patients from in vivo anatomical imaging modalities.
INRIA, Asclepios Research Project, 06902 Sophia-Antipolis Cedex, France. jean-marc.peyrat@inria.fr
Jean-Marc
JM
Peyrat
Maxime
M
Sermesant
Xavier
X
Pennec
Hervé
H
Delingette
Chenyang
C
Xu
Elliot R
ER
McVeigh
Nicholas
N
Ayache
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D004285:Dogs; D006321:Heart / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008955:Models, Cardiovascular; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique