Evaluation of the impact of strain correction on the orientation of cardiac diffusion tensors with in vivo and ex vivo porcine hearts

Purpose To evaluate the importance of strain-correcting stimulated echo acquisition mode echo-planar imaging cardiac diffusion tensor imaging. Methods Healthy pigs (n = 11) were successfully scanned with a 3D cine displacement-encoded imaging with stimulated echoes and a monopolar-stimulated echo-planar imaging diffusion tensor imaging sequence at 3 T during diastasis, peak systole, and strain sweet spots in a midventricular short-axis slice. The same diffusion tensor imaging sequence was repeated ex vivo after arresting the hearts in either a relaxed (KCl-induced) or contracted (BaCl2-induced) state. The displacement-encoded imaging with stimulated echoes data were used to strain-correct the in vivo cardiac diffusion tensor imaging in diastole and systole. The orientation of the primary (helix angles) and secondary (E2A) diffusion eigenvectors was compared with and without strain correction and to the strain-free ex vivo data. Results Strain correction reduces systolic E2A significantly when compared without strain correction and ex vivo (median absolute E2A = 34.3° versus E2A = 57.1° (P = 0.01), E2A = 60.5° (P = 0.006), respectively). The systolic distribution of E2A without strain correction is closer to the contracted ex vivo distribution than with strain correction, root mean square deviation of 0.027 versus 0.038. Conclusions The current strain-correction model amplifies the contribution of microscopic strain to diffusion resulting in an overcorrection of E2A. Results show that a new model that considers cellular rearrangement is required

Using a respiratory navigator significantly reduces variability when quantifying left ventricular torsion with cardiovascular magnetic resonance

BACKGROUND: Left ventricular (LV) torsion is an important indicator of cardiac function that is limited by high inter-test variability (50% of the mean value). We hypothesized that this high inter-test variability is partly due to inconsistent breath-hold positions during serial image acquisitions, which could be significantly improved by using a respiratory navigator for cardiovascular magnetic resonance (CMR) based quantification of LV torsion. METHODS: We assessed respiratory-related variability in measured LV torsion with two distinct experimental protocols. First, 17 volunteers were recruited for CMR with cine displacement encoding with stimulated echoes (DENSE) in which a respiratory navigator was used to measure and then enforce variability in end-expiratory position between all LV basal and apical acquisitions. From these data, we quantified the inter-test variability of torsion in the absence and presence of enforced end-expiratory position variability, which established an upper bound for the expected torsion variability. For the second experiment (in 20 new, healthy volunteers), 10 pairs of cine DENSE basal and apical images were each acquired from consecutive breath-holds and consecutive navigator-gated scans (with a single acceptance position). Inter-test variability of torsion was compared between the breath-hold and navigator-gated scans to quantify the variability due to natural breath-hold variation. To demonstrate the importance of these variability reductions, we quantified the reduction in sample size required to detect a clinically meaningful change in LV torsion with the use of a respiratory navigator. RESULTS: The mean torsion was 3.4 ± 0.2°/cm. From the first experiment, enforced variability in end-expiratory position translated to considerable variability in measured torsion (0.56 ± 0.34°/cm), whereas inter-test variability with consistent end-expiratory position was 57% lower (0.24 ± 0.16°/cm, p < 0.001). From the second experiment, natural respiratory variability from consecutive breath-holds translated to a variability in torsion of 0.24 ± 0.10°/cm, which was significantly higher than the variability from navigator-gated scans (0.18 ± 0.06°/cm, p = 0.02). By using a respiratory navigator with DENSE, theoretical sample sizes were reduced from 66 to 16 and 26 to 15 as calculated from the two experiments. CONCLUSIONS: A substantial portion (22-57%) of the inter-test variability of LV torsion can be reduced by using a respiratory navigator to ensure a consistent breath-hold position between image acquisitions

Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics

BACKGROUND: Cardiovascular magnetic resonance using displacement encoding with stimulated echoes (DENSE) is capable of assessing advanced measures of cardiac mechanics such as strain and torsion. A potential hurdle to widespread clinical adoption of DENSE is the time required to manually segment the myocardium during post-processing of the images. To overcome this hurdle, we proposed a radical approach in which only three contours per image slice are required for post-processing (instead of the typical 30–40 contours per image slice). We hypothesized that peak left ventricular circumferential, longitudinal and radial strains and torsion could be accurately quantified using this simplified analysis. METHODS AND RESULTS: We tested our hypothesis on a large multi-institutional dataset consisting of 541 DENSE image slices from 135 mice and 234 DENSE image slices from 62 humans. We compared measures of cardiac mechanics derived from the simplified post-processing to those derived from original post-processing utilizing the full set of 30–40 manually-defined contours per image slice. Accuracy was assessed with Bland-Altman limits of agreement and summarized with a modified coefficient of variation. The simplified technique showed high accuracy with all coefficients of variation less than 10% in humans and 6% in mice. The accuracy of the simplified technique was also superior to two previously published semi-automated analysis techniques for DENSE post-processing. CONCLUSIONS: Accurate measures of cardiac mechanics can be derived from DENSE cardiac magnetic resonance in both humans and mice using a simplified technique to reduce post-processing time by approximately 94%. These findings demonstrate that quantifying cardiac mechanics from DENSE data is simple enough to be integrated into the clinical workflow