Purpose: To apply cross-correlation delay (XCD) analysis to myocardial phase contrast magnetic resonance (PCMR) tissue velocity data and to compare XCD to three established "time-to-peak" dyssynchrony parameters. Materials and Methods: Myocardial tissue velocity was acquired using PCMR in 10 healthy volunteers (negative controls) and 10 heart failure patients who met criteria for cardiac resynchronization therapy (positive controls). All dyssynchrony parameters were computed from PCMR velocity curves. Sensitivity, specificity, and receiver operator curve (ROC) analysis for separating positive and negative controls were computed for each dyssynchrony parameter. Results: XCD had higher sensitivity (90%) and specificity (100%) for discriminating between normal and patient groups than any of the time-to-peak dyssynchrony parameters. ROC analysis showed that XCD was the best parameter for separating the positive and negative control groups. Conclusion:XCD is superior to time-to-peak dyssynchrony parameters for discriminating between subjects with and without dyssynchrony and may aid in the selection of patients for cardiac resynchronization therapy.
Purpose To develop a robust method to assess regional mechanical dyssynchrony from cine short-axis MR images. Cardiac resynchronization therapy (CRT) is an effective treatment for patients with heart failure and evidence of left-ventricular (LV) dyssynchrony. Patient response to CRT is greatest when the LV pacing lead is placed in the most dyssynchronous segment. Existing techniques for assessing regional dyssynchrony require difficult acquisition and/or postprocessing. Our goal was to develop a widely applicable and robust method to assess regional mechanical dyssynchrony. Materials and Methods Using the endocardial boundary, radial displacement curves (RDCs) were generated throughout the LV. Cross-correlation was used to determine the delay time between each RDC and a patient-specific reference. Delay times were projected onto the American Heart Association 17-segment model creating a regional dyssynchrony map. Our method was tested in 10 normal individuals and 10 patients enrolled for CRT (QRS > 120 ms, NYHA III-IV, EF < 35%). Results Delay times over the LV were 23.9 ± 33.8 ms and 93.1 ± 99.9 ms (P < 0.001) in normal subjects and patients, respectively. Interobserver reproducibility for segment averages was 6.8 ± 39.3 ms and there was 70% agreement in identifying the latest contracting segment. Conclusion We have developed a method that can reliably calculate regional delay times from cine steady-state free-precession (SSFP) images. Maps of regional dyssynchrony could be used to identify the latest-contracting segment to assist in CRT lead implantation.
Background: The development of clinically applicable fluid-structure interaction (FSI) models of the left heart is inherently challenging when using in vivo cardiovascular magnetic resonance (CMR) data for validation, due to the lack of a well-controlled system where detailed measurements of the ventricular wall motion and flow field are available a priori. The purpose of this study was to (a) develop a clinically relevant, CMR-compatible left heart physical model; and (b) compare the left ventricular (LV) volume reconstructions and hemodynamic data obtained using CMR to laboratory-based experimental modalities. Methods: The LV was constructed from optically clear flexible silicone rubber. The geometry was based off a healthy patient's LV geometry during peak systole. The LV phantom was attached to a left heart simulator consisting of an aorta, atrium, and systemic resistance and compliance elements. Experiments were conducted for heart rate of 70 bpm. Wall motion measurements were obtained using high speed stereo-photogrammetry (SP) and cine-CMR, while flow field measurements were obtained using digital particle image velocimetry (DPIV) and phase-contrast magnetic resonance (PC-CMR). Results: The model reproduced physiologically accurate hemodynamics (aortic pressure = 120/80 mmHg; cardiac output = 3.5 L/min). DPIV and PC-CMR results of the center plane flow within the ventricle matched, both qualitatively and quantitatively, with flow from the atrium into the LV having a velocity of about 1.15 m/s for both modalities. The normalized LV volume through the cardiac cycle computed from CMR data matched closely to that from SP. The mean difference between CMR and SP was 5.5 ± 3.7 %. Conclusions: The model presented here can thus be used for the purposes of: (a) acquiring CMR data for validation of FSI simulations, (b) determining accuracy of cine-CMR reconstruction methods, and (c) conducting investigations of the effects of altering anatomical variables on LV function under normal and disease conditions.