Objective We sought to assess the relationship of left ventricular (LV) trabeculae and papillary muscles (TPM) with clinical characteristics in a community-based, free living adult cohort and to determine the effect of TPM on quantitative measures of LV volume, mass and ejection fraction (EF). Background Hypertrabeculation has been associated with adverse cardiovascular events, but the distribution and clinical correlates of the volume and mass of the TPM in a normal left ventricle have not been well characterized. Methods Short-axis cine cardiovascular magnetic resonance (CMR) images, obtained using a steady-state free precession sequence, from 1494 members of the Framingham Offspring cohort were analyzed using software that automatically segments TPM. Absolute TPM volume, TPM as a fraction of end-diastolic volume (TPM/EDV), and TPM mass as a fraction of LV mass (TPMm/LVM) were determined on all Offspring and in a referent group of Offspring free of clinical cardiovascular disease and hypertension. Results In the referent group (aged 61±9 years, with 262 men and 423 women) TPM was 23±3 % of LV EDV in both sexes (p=0.9). TPM/EDV decreased with age (p<0.02) but was not associated with body mass index (BMI). TPMm/LVM was inversely correlated with age (p<0.0001), BMI (p<0.018) and systolic blood pressure (p<0.0001). Among all 1494 participants (699 men) LV volumes decreased 23%, LV mass increased 28% and EF increased by 7.5 EF units (p<0.0001) when TPM were considered myocardial mass rather than part of the LV blood pool. Conclusions Global CMR LV parameters are significantly affected by whether TPM are considered as part of the LV blood pool or as part of LV mass. Our cross-sectional data from a healthy referent group of adults free of clinical cardiovascular disease demonstrate that TPM/EDV decreases with increasing age in both sexes, but is not related to hypertension or obesity.

We have developed a method for automatic contour propagation in cine cardiac magnetic resonance images. The method consists of a new active contour model that tries to maintain a constant contour environment by matching gray values in profiles perpendicular to the contour. Consequently, the contours should maintain a constant position with respect to neighboring anatomical structures, such that the resulting contours reflect the preferences of the user. This is particularly important in cine cardiac magnetic resonance images because local image features do not describe the desired contours near the papillary muscle. The accuracy of the propagation result is influenced by several parameters. Because the optimal setting of these parameters is application dependent, we describe how to use full factorial experiments to optimize the parameter setting. We have applied our method to cine cardiac magnetic resonance image sequences from the long axis two-chamber view, the long axis four-chamber view, and the short axis view. We performed our optimization procedure for each contour in each view. Next, we performed an extensive clinical validation of our method on 69 short axis data sets and 38 long axis data sets. In the optimal parameter setting, our propagation method proved to be fast, robust, and accurate. The resulting cardiac contours are positioned within the interobserver ranges of manual segmentation. Consequently, the resulting contours can be used to accurately determine physiological parameters such as stroke volume and ejection fraction.

The purpose of this study is to enable high spatial resolution voxel-wise quantitative analysis of myocardial perfusion in dynamic contrast-enhanced cardiovascular MR, in particular by finding the most favorable quantification algorithm in this context. Four deconvolution algorithms--Fermi function modeling, deconvolution using B-spline basis, deconvolution using exponential basis, and autoregressive moving average modeling--were tested to calculate voxel-wise perfusion estimates. The algorithms were developed on synthetic data and validated against a true gold-standard using a hardware perfusion phantom. The accuracy of each method was assessed for different levels of spatial averaging and perfusion rate. Finally, voxel-wise analysis was used to generate high resolution perfusion maps on real data acquired from five patients with suspected coronary artery disease and two healthy volunteers. On both synthetic and perfusion phantom data, the B-spline method had the highest error in estimation of myocardial blood flow. The autoregressive moving average modeling and exponential methods gave accurate estimates of myocardial blood flow. The Fermi model was the most robust method to noise. Both simulations and maps in the patients and hardware phantom showed that voxel-wise quantification of myocardium perfusion is feasible and can be used to detect abnormal regions.

We propose a novel automatic method to segment the myocardium on late-enhancement cardiac MR (LE CMR) images with a multi-step approach. First, in each slice of the LE CMR volume, a geometrical template is deformed so that its borders fit the myocardial contours. The second step consists in introducing a shape prior of the left ventricle. To do so, we use the cine MR sequence that is acquired along with the LE CMR volume. As the myocardial contours can be more easily automatically obtained on this data, they are used to build a 3D mesh representing the left ventricle geometry and the underlying myocardium thickness. This mesh is registered towards the contours obtained with the geometrical template, then locally adjusted to guarantee that scars are included inside the final segmentation. The quantitative evaluation on 27 volumes (272 slices) shows robust and accurate results.

The aim of this article is to describe a novel hardware perfusion phantom that simulates myocardial first-pass perfusion allowing comparisons between different MR techniques and validation of the results against a true gold standard. MR perfusion images were acquired at different myocardial perfusion rates and variable doses of gadolinium and cardiac output. The system proved to be sensitive to controlled variations of myocardial perfusion rate, contrast agent dose, and cardiac output. It produced distinct signal intensity curves for perfusion rates ranging from 1 to 10 mL/mL/min. Quantification of myocardial blood flow by signal deconvolution techniques provided accurate measurements of perfusion. The phantom also proved to be very reproducible between different sessions and different operators. This novel hardware perfusion phantom system allows reliable, reproducible, and efficient simulation of myocardial first-pass MR perfusion. Direct comparison between the results of image-based quantification and reference values of flow and myocardial perfusion will allow development and validation of accurate quantification methods. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.