PURPOSE: To apply high-temporal-resolution tissue phase mapping (TPM) to derive a detailed representation of normal regional myocardial motion in a large cohort of 58 normal subjects (three age groups) and one patient with dilated cardiomyopathy. MATERIALS AND METHODS: Analysis included transformation of the acquired myocardial velocities into radial, circumferential, and long-axis motion components representing left ventricular (LV) function with a spatiotemporal resolution of 1.3 x 2.6 x 8 mm(3) and 13.8 msec, respectively. To compare multidirectional regional myocardial velocities between groups of subjects, a multisegment and multislice visualization model was employed. Regional myocardial motion was mapped onto the visualization model to display the current status of myocardial motion from base to apex as in-plane velocity vector fields in conjunction with color-coded long-axis plane motion. Moreover, correlation analysis was used to investigate regional differences in myocardial dynamics. RESULTS: Age-related changes in LV myocardial velocities resulted in significant differences of peak and time-to-peak velocities in the radial and long-axis directions. Correlation analysis revealed clearly visible regional differences in the temporal evolution of long-axis and circumferential velocities, particularly between the youngest and oldest age groups. Comparison of pathological LV motion with age-matched volunteers indicated marked regional alterations in myocardial velocities and dynamics. CONCLUSION: High-temporal-resolution TPM in combination with a schematic visualization model and correlation analysis permits the identification of local changes in myocardial velocities associated with different age groups and a common LV pathology.
PURPOSE: To apply high-temporal-resolution tissue phase mapping (TPM) to derive a detailed representation of normal regional myocardial motion in a large cohort of 58 normal subjects (three age groups) and one patient with dilated cardiomyopathy. MATERIALS AND METHODS: Analysis included transformation of the acquired myocardial velocities into radial, circumferential, and long-axis motion components representing left ventricular (LV) function with a spatiotemporal resolution of 1.3 x 2.6 x 8 mm(3) and 13.8 msec, respectively. To compare multidirectional regional myocardial velocities between groups of subjects, a multisegment and multislice visualization model was employed. Regional myocardial motion was mapped onto the visualization model to display the current status of myocardial motion from base to apex as in-plane velocity vector fields in conjunction with color-coded long-axis plane motion. Moreover, correlation analysis was used to investigate regional differences in myocardial dynamics. RESULTS: Age-related changes in LV myocardial velocities resulted in significant differences of peak and time-to-peak velocities in the radial and long-axis directions. Correlation analysis revealed clearly visible regional differences in the temporal evolution of long-axis and circumferential velocities, particularly between the youngest and oldest age groups. Comparison of pathological LV motion with age-matched volunteers indicated marked regional alterations in myocardial velocities and dynamics. CONCLUSION: High-temporal-resolution TPM in combination with a schematic visualization model and correlation analysis permits the identification of local changes in myocardial velocities associated with different age groups and a common LV pathology.
Authors: Alexander Ruh; Roberto Sarnari; Haben Berhane; Kenny Sidoryk; Kai Lin; Ryan Dolan; Arleen Li; Michael J Rose; Joshua D Robinson; James C Carr; Cynthia K Rigsby; Michael Markl Journal: Int J Cardiovasc Imaging Date: 2019-02-04 Impact factor: 2.357
Authors: Yuchi Han; Dana C Peters; Kraig V Kissinger; Beth Goddu; Susan B Yeon; Warren J Manning; Reza Nezafat Journal: Am J Cardiol Date: 2010-07-15 Impact factor: 2.778
Authors: Jeremy Collins; Cort Sommerville; Patrick Magrath; Bruce Spottiswoode; Benjamin H Freed; Keith H Benzuly; Robert Gordon; Himabindu Vidula; Dan C Lee; Clyde Yancy; James Carr; Michael Markl Journal: Circ Cardiovasc Imaging Date: 2014-12-31 Impact factor: 7.792