Methods are presented to image the fiber architecture of the human myocardium in vitro and in vivo. NMR images are obtained of the diffusion anisotropy tensor, indicative of local myofiber orientation. Studies of cardiac necropsy specimens demonstrate classic features of ventricular myoarchitecture including the continuous endocardial to epicardial variation of fiber helix angles (angles to the ventricular circumferential direction) of approximately +1.3 to -1.3 radians. Cross-fiber anisotropy is also observed. In the beating heart, NMR diffusion data must be corrected for the effects of myocardial deformation during the cardiac cycle. This correction can be performed using an independent MRI method to map the strain-rate tensor field of the myocardium through time. Combining fiber orientation with local myocardial strain rate, local rates of myocardial fiber shortening may be computed.

Background and Purpose-Tissue signatures from acute MR imaging of the brain may be able to categorize physiological status and thereby assist clinical decision making. We designed and analyzed statistical algorithms to evaluate the risk of infarction for each voxel of tissue using acute human functional MRI. Methods-Diffusion-weighted MR images (DWI) and perfusion-weighted MR images (PWI) from acute stroke patients scanned within 12 hours of symptom onset were retrospectively studied and used to develop thresholding and generalized linear model (GLM) algorithms predicting tissue outcome as determined by follow-up MRI. The performances of the algorithms were evaluated for each patient by using receiver operating characteristic curves. Results-At their optimal operating points, thresholding algorithms combining DWI and PWI provided 66% sensitivity and 83% specificity, and GLM algorithms combining DWI and PWI predicted with 66% sensitivity and 84% specificity voxels that proceeded to infarct. Thresholding algorithms that combined DWI and PWI provided significant improvement to algorithms that utilized DWI alone (Pϭ0.02) but no significant improvement over algorithms utilizing PWI alone (Pϭ0.21). GLM algorithms that combined DWI and PWI showed significant improvement over algorithms that used only DWI (Pϭ0.02) or PWI (Pϭ0.04). The performances of thresholding and GLM algorithms were comparable (PϾ0.2). Conclusions-Algorithms that combine acute DWI and PWI can assess the risk of infarction with higher specificity and sensitivity than algorithms that use DWI or PWI individually. Methods for quantitatively assessing the risk of infarction on a voxel-by-voxel basis show promise as techniques for investigating the natural spatial evolution of ischemic damage in humans.

Muscle performance is markedly influenced by tissue perfusion. Techniques that allow quantification of microvascular flow are limited by the use of ionizing radiation. In this investigation, we apply an NMR model previously developed by Detre et al. to the measurement of human muscle perfusion during reactive hyperemia. We compare our results with conventional plethysmography adapted to NMR. Using echo-planar imaging, T1 and T2 were measured in 14 subjects during rest, ischemia, and reactive hyperemia. Mean leg muscle T1 in healthy volunteers is 850 ms at rest and 834 ms at reperfusion, leading to a calculated reactive hyperemia flow increase (T1 flow) of 103 +/- 40 ml/100 ml/min. T1 flows correlate well with NMR-plethysmography values. Changes in T2, which are sensitive to both deoxyhemoglobin content and vessel diameter variations, are also correlated with perfusion measurements. T1 changes allow quantification of regional perfusion in human muscle during reactive hyperemia.

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