BACKGROUND: Quantitative assessment of regional myocardial function has important diagnostic implications in cardiac disease. Recent advances in CT imaging technology have allowed fine anatomic structures, such as endocardial trabeculae, to be resolved and potentially used as fiducial markers for tracking local wall deformations. We developed a method to detect and track such features on the endocardium to extract a metric that reflects local myocardial contraction. METHODS AND RESULTS: First-pass CT images and contrast-enhanced cardiovascular magnetic resonance images were acquired in 8 infarcted and 3 healthy pigs. We tracked the left ventricle wall motion by segmenting the blood from myocardium and calculating trajectories of the endocardial features seen on the blood cast. The relative motions of these surface features were used to represent the local contraction of the endocardial surface with a metric we call stretch quantifier of endocardial engraved zones (SQUEEZ). The average SQUEEZ value and the rate of change in SQUEEZ were calculated for both infarcted and healthy myocardial regions. SQUEEZ showed a significant difference between infarct and remote regions (P<0.0001). No significant difference was observed between normal myocardium (noninfarcted hearts) and remote regions (P=0.8). CONCLUSIONS: We present a new quantitative method for measuring regional cardiac function from high-resolution volumetric CT images, which can be acquired during angiography and myocardial perfusion scans. Quantified measures of regional cardiac mechanics in normal and abnormally contracting regions in infarcted hearts were shown to correspond well with noninfarcted and infarcted regions as detected by delayed enhancement cardiovascular magnetic resonance images.
BACKGROUND: Quantitative assessment of regional myocardial function has important diagnostic implications in cardiac disease. Recent advances in CT imaging technology have allowed fine anatomic structures, such as endocardial trabeculae, to be resolved and potentially used as fiducial markers for tracking local wall deformations. We developed a method to detect and track such features on the endocardium to extract a metric that reflects local myocardial contraction. METHODS AND RESULTS: First-pass CT images and contrast-enhanced cardiovascular magnetic resonance images were acquired in 8 infarcted and 3 healthy pigs. We tracked the left ventricle wall motion by segmenting the blood from myocardium and calculating trajectories of the endocardial features seen on the blood cast. The relative motions of these surface features were used to represent the local contraction of the endocardial surface with a metric we call stretch quantifier of endocardial engraved zones (SQUEEZ). The average SQUEEZ value and the rate of change in SQUEEZ were calculated for both infarcted and healthy myocardial regions. SQUEEZ showed a significant difference between infarct and remote regions (P<0.0001). No significant difference was observed between normal myocardium (noninfarcted hearts) and remote regions (P=0.8). CONCLUSIONS: We present a new quantitative method for measuring regional cardiac function from high-resolution volumetric CT images, which can be acquired during angiography and myocardial perfusion scans. Quantified measures of regional cardiac mechanics in normal and abnormally contracting regions in infarcted hearts were shown to correspond well with noninfarcted and infarcted regions as detected by delayed enhancement cardiovascular magnetic resonance images.
Authors: Davis M Vigneault; Amir Pourmorteza; Marvin L Thomas; David A Bluemke; J Alison Noble Journal: Med Image Anal Date: 2018-03-29 Impact factor: 8.545
Authors: Michael W Tee; Samuel Won; Fabio S Raman; Colin Yi; Davis M Vigneault; Cynthia Davies-Venn; Songtao Liu; Albert C Lardo; João A C Lima; J Alison Noble; Craig A Emter; David A Bluemke Journal: Radiology Date: 2015-04-08 Impact factor: 11.105
Authors: Ashish Manohar; Lorenzo Rossini; Gabrielle Colvert; Davis M Vigneault; Francisco Contijoch; Marcus Y Chen; Juan C Del Alamo; Elliot R McVeigh Journal: J Med Imaging (Bellingham) Date: 2019-11-08
Authors: Amir Pourmorteza; Noemie Keller; Richard Chen; Albert Lardo; Henry Halperin; Marcus Y Chen; Elliot McVeigh Journal: Int J Cardiovasc Imaging Date: 2018-03-13 Impact factor: 2.357
Authors: Lik Chuan Lee; Liang Ge; Zhihong Zhang; Matthew Pease; Serjan D Nikolic; Rakesh Mishra; Mark B Ratcliffe; Julius M Guccione Journal: Med Biol Eng Comput Date: 2014-05-03 Impact factor: 2.602