Influence of longitudinal position on the evolution of steady-state signal in cardiac cine balanced steady-state free precession imaging

Background Emerging quantitative cardiac magnetic resonance imaging (CMRI) techniques use cine balanced steady-state free precession (bSSFP) to measure myocardial signal intensity and probe underlying physiological parameters. This correlation assumes that steady-state is maintained uniformly throughout the heart in space and time. Purpose To determine the effects of longitudinal cardiac motion and initial slice position on signal deviation in cine bSSFP imaging by comparing two-dimensional (2D) and three-dimensional (3D) acquisitions. Material and Methods Nine healthy volunteers completed cardiac MRI on a 1.5-T scanner. Short axis images were taken at six slice locations using both 2D and 3D cine bSSFP. 3D acquisitions spanned two slices above and below selected slice locations. Changes in myocardial signal intensity were measured across the cardiac cycle and compared to longitudinal shortening. Results For 2D cine bSSFP, 46% ± 9% of all frames and 84% ± 13% of end-diastolic frames remained within 10% of initial signal intensity. For 3D cine bSSFP the proportions increased to 87% ± 8% and 97% ± 5%. There was no correlation between longitudinal shortening and peak changes in myocardial signal. The initial slice position significantly impacted peak changes in signal intensity for 2D sequences ( P < 0.001). Conclusion The initial longitudinal slice location significantly impacts the magnitude of deviation from steady-state in 2D cine bSSFP that is only restored at the center of a 3D excitation volume. During diastole, a transient steady-state is established similar to that achieved with 3D cine bSSFP regardless of slice location.

Detecting Acute Myocardial Infarction by Diffusion-Weighted versus T2-Weighted Imaging and Myocardial Necrosis Markers

We used a porcine model of acute myocardial infarction to study the signal evolution of ischemic myocardium on diffusion-weighted magnetic resonance images (DWI). Eight Chinese miniature pigs underwent percutaneous left anterior descending or left circumflex coronary artery occlusion for 90 minutes followed by reperfusion, which induced acute myocardial infarction. We used DWI preprocedurally and hourly for 4 hours postprocedurally. We acquired turbo inversion recovery magnitude T2-weighted images (TIRM T2WI) and late gadolinium enhancement images from the DWI slices. We measured the serum myocardial necrosis markers myoglobin, creatine kinase-MB isoenzyme, and cardiac troponin I at the same time points as the magnetic resonance scanning. We used histochemical staining to confirm injury. All images were analyzed qualitatively. Contrast-to-noise ratio (the contrast between infarcted and healthy myocardium) and relative signal index were used in quantitative image analysis. We found that DWI identified myocardial signal abnormity early (&lt;4 hr) after acute myocardial infarction and identified the infarct-related high signal more often than did TIRM T2WI: 7 of 8 pigs (87.5%) versus 3 of 8 (37.5%) (P=0.046). Quantitative image analysis yielded a significant difference in contrast-to-noise ratio and relative signal index between infarcted and normal myocardium on DWI. However, within 4 hours after infarction, the serologic myocardial injury markers were not significantly positive. We conclude that DWI can be used to detect myocardial signal abnormalities early after acute myocardial infarction—identifying the infarction earlier than TIRM T2WI and widely used clinical serologic biomarkers.

A Comparison of Theory-Based and Experimentally Determined Myocardial Signal Intensity Correction Methods in First-Pass Perfusion Magnetic Resonance Imaging

Objectives.To evaluate the impact of correcting myocardial signal saturation on the accuracy of absolute myocardial blood flow (MBF) measurements.Materials and Methods.We performed 15 dual bolus first-pass perfusion studies in 7 dogs during global coronary vasodilation and variable degrees of coronary artery stenosis. We compared microsphere MBF to MBF calculated from uncorrected and corrected MRI signal. Four correction methods were tested, two theoretical methods (Th1 and Th2) and two empirical methods (Em1 and Em2).Results.The correlations with microsphere MBF (n=90segments) were: uncorrected (y=0.47x+1.1,r=0.70), Th1 (y=0.53x+1.0,r=0.71), Th2 (y=0.62x+0.86,r=0.73), Em1 (y=0.82x+0.86,r=0.77), and Em2 (y=0.72x+0.84,r=0.75). All corrected methods were not significantly different from microspheres, while uncorrected MBF values were significantly lower. For the top 50% of microsphere MBF values, flows were significantly underestimated by uncorrected SI (31%), Th1 (25%), and Th2 (19%), while Em1 (1%), and Em2 (9%) were similar to microsphere MBF.Conclusions.Myocardial signal saturation should be corrected prior to flow modeling to avoid underestimation of MBF by MR perfusion imaging.