Assessment of myocardial injury after reperfused infarction by T1ρ cardiovascular magnetic resonance.

BACKGROUND: The evolution of T1ρ and of other endogenous contrast methods (T2, T1) in the first month after reperfused myocardial infarction (MI) is uncertain. We conducted a study of reperfused MI in pigs to serially monitor T1ρ, T2 and T1 relaxation, scar size and transmurality at 1 and 4 weeks post-MI. METHODS: Ten Yorkshire swine underwent 90 min of occlusion of the circumflex artery and reperfusion. T1ρ, T2 and native T1 maps and late gadolinium enhanced (LGE) cardiovascular magnetic resonance (CMR) data were collected at 1 week (n = 10) and 4 weeks (n = 5). Semi-automatic FWHM (full width half maximum) thresholding was used to assess scar size and transmurality and compared to histology. Relaxation times and contrast-to-noise ratio were compared in healthy and remote myocardium at 1 and 4 weeks. Linear regression and Bland-Altman was performed to compare infarct size and transmurality. RESULTS: Relaxation time differences between infarcted and remote myocardial tissue were ∆T1 (infarct-remote) = 421.3 ± 108.8 (1 week) and 480.0 ± 33.2 ms (4 week), ∆T1ρ = 68.1 ± 11.6 and 74.3 ± 14.2, and ∆T2 = 51.0 ± 10.1 and 59.2 ± 11.4 ms. Contrast-to-noise ratio was CNRT1 = 7.0 ± 3.5 (1 week) and 6.9 ± 2.4 (4 week), CNRT1ρ = 12.0 ± 6.2 and 12.3 ± 3.2, and CNRT2 = 8.0 ± 3.6 and 10.3 ± 5.8. Infarct size was not significantly different for T1ρ, T1 and T2 compared to LGE (p = 0.14) and significantly decreased from 1 to 4 weeks (p < 0.01). Individual infarct size changes were ∆T1ρ = -3.8%, ∆T1 = -3.5% and ∆LGE = -2.8% from 1 - 4 weeks, but there was no observed change in infarct size for T2 or histologically. CONCLUSIONS: T1ρ was highly correlated with alterations left ventricle (LV) pathology at 1 and 4 weeks post-MI and therefore it may be a useful method endogenous contrast imaging of infarction.

Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.

Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.