The objective of this study was to investigate the correlation between local myocardial function estimates from CT and myocardial strain from tagged MRI in the same heart. Accurate detection of regional myocardial dysfunction can be an important finding in the diagnosis of functionally significant coronary artery disease. Tagged MRI is currently a reference standard for noninvasive regional myocardial function analysis; however, it has practical drawbacks. We have developed a CT imaging protocol and automated image analysis algorithm for estimating regional cardiac function from a few heartbeats. This method tracks the motion of the left ventricular (LV) endocardial surface to produce local function maps: we call the method Stretch Quantification of Endocardial Engraved Zones (SQUEEZ). Myocardial infarction was created by ligation of the left anterior descending coronary artery for 2 h followed by reperfusion in canine models. Tagged and cine MRI scans were performed during the reperfusion phase and first-pass contrast enhanced CT scans were acquired. The average delay between the CT and MRI scans was cc) was calculated from the tagged MRI data. The agreement between peak systolic Ecc and SQUEEZ was investigated in 162 segments in the 9 hearts. Linear regression and Bland–Altman analysis was used to assess the correlation between the two metrics of local LV function. The results show good agreement between SQUEEZ and Ecc: (r = 0.71, slope = 0.78, p <0.001). Furthermore, Bland–Altman showed a small bias of −0.02 with 95 % confidence interval of 0.1, and standard deviation of 0.05 representing ~6.5 % of the dynamic range of LV function. The good agreement between the estimates of local myocardial function obtained from CT SQUEEZ and tagged MRI provides encouragement to investigate the use of SQUEEZ for measuring regional cardiac function at a low clinical dose in humans.
- CT SQUEEZ
- Myocardial function
- Tagged MRI
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Cardiology and Cardiovascular Medicine