Direct histological validation of diffusion tensor MRI in formaldehyde-fixed myocardium.

Diffusion tensor MRI is emerging as a rapid, nondestructive method to map myocardial fiber organization. It accurately measures myofiber orientation in hearts bathed in or perfused with cardioplegic solution. This study shows it also accurately maps the fibrous architecture of formalin-fixed hearts. Fiber orientations obtained by MRI and histology at the same locations in an excised portion of rabbit ventricle differed on average by 3.7 degrees (SD = 6.4 degrees, N = 70), a closer correspondence than achieved with previous preparations. The longer acquisition times afforded by fixed-heart imaging provides better accuracy, and should enable high-resolution reconstruction of the entire ventricular architecture. Magn Reson Med 44:157-161, 2000.

Reconstruction of cardiac ventricular geometry and fiber orientation using magnetic resonance imaging.

An imaging method for the rapid reconstruction of fiber orientation throughout the cardiac ventricles is described. In this method, gradient-recalled acquisition in the steady-state (GRASS) imaging is used to measure ventricular geometry in formaldehyde-fixed hearts at high spatial resolution. Diffusion-tensor magnetic resonance imaging (DTMRI) is then used to estimate fiber orientation as the principle eigenvector of the diffusion tensor measured at each image voxel in these same hearts. DTMRI-based estimates of fiber orientation in formaldehyde-fixed tissue are shown to agree closely with those measured using histological techniques, and evidence is presented suggesting that diffusion tensor tertiary eigenvectors may specify the orientation of ventricular laminar sheets. Using a semiautomated software tool called HEARTWORKS, a set of smooth contours approximating the epicardial and endocardial boundaries in each GRASS short-axis section are estimated. These contours are then interconnected to form a volumetric model of the cardiac ventricles. DTMRI-based estimates of fiber orientation are interpolated into these volumetric models, yielding reconstructions of cardiac ventricular fiber orientation based on at least an order of magnitude more sampling points than can be obtained using manual reconstruction methods.

Electrophysiological modeling of cardiac ventricular function: from cell to organ.

Three topics of importance to modeling the integrative function of the heart are reviewed. The first is modeling of the ventricular myocyte. Emphasis is placed on excitation-contraction coupling and intracellular Ca2+ handling, and the interpretation of experimental data regarding interval-force relationships. Second, data on use of diffusion tensor magnetic resonance (DTMR) imaging for measuring the anatomical structure of the cardiac ventricles are presented. A method for the semi-automated reconstruction of the ventricles using a combination of gradient recalled acquisition in the steady state (GRASS) and DTMR images is described. Third, we describe how these anatomically and biophysically based models of the cardiac ventricles can be implemented on parallel computers.

Histological validation of myocardial microstructure obtained from diffusion tensor magnetic resonance imaging.

Diffusion tensor magnetic resonance imaging (MRI) is a possible new means of elucidating the anatomic structure of the myocardium. It enjoys several advantages over traditional histological approaches, including the ability to rapidly measure fiber organization in isolated, perfused, arrested hearts, thereby avoiding fixation and sectioning of artifacts. However, quantitative validation of this MRI method has been lacking. Here, fiber orientations estimated in the same locations in the same heart using both diffusion tensor MRI and histology are compared in a total of two perfused rabbit hearts. Fiber orientations were statistically similar for both methods and differed on average by 12 degrees at any single location. This is similar to the 10 degrees uncertainty in fiber orientation achieved with histology. In addition, imaging studies performed in a total of seven hearts support a level of organization beyond the myofiber, the recently described laminar organization of the ventricular myocardium.

The dynamic range of neonatal heart rate variability.

INTRODUCTION: Although it is generally appreciated that heart rate variability is low during severe illness, the extent, time course, and mathematical characteristics of heart rate variability during transitions between health and illness have not been systematically examined. The purpose of this study was to analyze heart rate variability in newborn infants during a rapid recovery from severe respiratory and circulatory failure. METHODS AND RESULTS: From prolonged ECG recordings, we evaluated heart rate variability in the time domain (mean, relative change, and coefficient of variation of RR intervals), in the frequency domain (using power spectra of the time series of RR intervals), and using a neural network. Qualitatively, RR interval plots showed little heart rate variability during severe illness but became "noisier" during recovery. Quantitatively, recovery was marked by twofold to threefold increases in time-domain parameters, by eightfold increases in frequency-domain parameters, and by more than 20-fold increases in a neural network measure. Time-domain and frequency-domain measures were correlated, but not strongly. Heart rate variability reached stable levels by 4 to 5 days. Heart rate did not change dramatically. CONCLUSION: Recovery from severe neonatal illness is accompanied by large and rapid increases in heart rate variability, but not by large changes in heart rate. This increase can be effectively assessed in the time domain, in the frequency domain, and by using a neural network.