Abstract: Several embodiments of a method and apparatus for detecting interventricular dyssynchrony are provided. In one embodiment, the apparatus includes an image segment processor and an image classifier. The image segment processor may segment left and right ventricles in source images of a subject's heart to form left and right ventricle segments in segmented images. Each source image may include cross sections of the right and left ventricles in common spatial relation along the short axis plane and in common temporal relation in reference to a cardiac cycle. The source images and corresponding segmented images may be temporally-spaced in relation to the cardiac cycle. The image classifier may determine first and second cross-sectional areas associated with the left and right ventricle segments for each segmented image, compare the first and second cross-sectional areas, and classify the subject's heart in an interventricular dyssynchronous class or a non-dyssynchronous class.

Abstract: The present invention provides a method for diagnosis end-stage cardiomyopathy includes measuring expression of claudin-5 levels in a patient suspected of suffering from end-stage cardiomyopathy as well as a method for treating end-stage cardiomyopathy includes administering an effective amount of a composition effectively upregulates the claudin-5 or inhibits degradation of claudin-5

Abstract: Several embodiments of a method and apparatus for detecting interventricular dyssynchrony are provided. In one embodiment, the apparatus includes an image segment processor and an image classifier. The image segment processor may segment left and right ventricles in source images of a subject's heart to form left and right ventricle segments in segmented images. Each source image may include cross sections of the right and left ventricles in common spatial relation along the short axis plane and in common temporal relation in reference to a cardiac cycle. The source images and corresponding segmented images may be temporally-spaced in relation to the cardiac cycle. The image classifier may determine first and second cross-sectional areas associated with the left and right ventricle segments for each segmented image, compare the first and second cross-sectional areas, and classify the subject's heart in an interventricular dyssynchronous class or a non-dyssynchronous class.