Abstract 12470: Computational Evaluation of Myocardial Performance from Four-Dimensional Images
Introduction: In four-dimensional cardiac images, myocardial motion and deformation at every local point can be tracked by combination of model-based shape analysis and finite element method. With a statistical strategy, some early cues of cardiovascular disease can be found by comparing individual cases with a huge number of sample records.
Hypothesis: Now imaging equipment such as helical CT and multi-phase SPECT can capture a time series of cardiac images in three-dimension.
Methods: The image set is processed by computer for automatic modeling of myocardial motion everywhere on the heart. The motion characteristics and mechanics, including moving velocity, periodical excursion, maximum force, stress and strain, are quantitatively obtained. In this way, the statistical information is extracted from a number of subjects in the database. The normal distribution is formed for a specific cluster. For an individual, the dynamical parameters are extracted to evaluate the corresponding behavior of myocardium areas. Abnormality can be recognized according to the 68-95-99.7 rule in statistics. Performance is regarded to be normal if the tissue motion is located within 1 standard deviation (σ) of the mean among the statistical population. If between 1σ and 2σ, it may contain early cues of cardiac diseases and should further check the area size and shape. The subject is often related with obvious disease if between 2σ and 3σ and with severe disease if beyond 3σ. The corresponding areas are marked as “O”, “+”, “++”, and “+++”.
Results: A statistical model is constructed from 200 subjects from three hospitals of one city. Their images were scanned during the last 10 years. Nine subjects were in the follow-up study and three of them were found with early cues by the proposed method. Two of the three were with cardiomyopathy and ischaemic heart disease after five and six years, respectively.
Conclusions: A novel method is carried out with regional tracking of myocardial motion and statistical analysis. It provides a powerful means in assessment of myocardial working conditions. Performance is evaluated to find early cues of cardiovascular diseases from parametric derivation, which is very meaningful for disease diagnosis, control, and prevention.
- © 2012 by American Heart Association, Inc.