Evaluation of left ventricular torsion by cardiovascular magnetic resonance

Recently there has been considerable interest in LV torsion and its relationship with symptomatic and pre-symptomatic disease processes. Torsion gives useful additional information about myocardial tissue performance in both systolic and diastolic function. CMR assessment of LV torsion is simply and efficiently performed. However, there is currently a wide variation in the reporting of torsional motion and the procedures used for its calculation. For example, torsion has been presented as twist (degrees), twist per length (degrees/mm), shear angle (degrees), and shear strain (dimensionless). This paper reviews current clinical applications and shows how torsion can give insights into LV mechanics and the influence of LV geometry and myocyte fiber architecture on cardiac function. Finally, it provides recommendations for CMR measurement protocols, attempts to stimulate standardization of torsion calculation, and suggests areas of useful future research

Feasibility of single breath-hold left ventricular function with 3 Tesla TSENSE acquisition and 3D modeling analysis

<p>Abstract</p> <p>Background</p> <p>A single breath-hold evaluation of ventricular function would allow assessment in cases where scan time or patient tolerance is limited. Spatiotemporal acceleration techniques such as TSENSE decrease cardiovascular MR acquisition time, but standard slice summation analysis requires enough short axis slices to cover the left ventricle (LV). By reducing the number of short axis slices, incorporating long axis slices, and applying a 3D model based analysis, it may be possible to obtain accurate LV mass and volumes. We evaluated LV volume, mass and ejection fraction at 3.0T using a 3D modeling analysis in 9 patients with a history of myocardial infarction and one healthy volunteer. Acquisition consisted of a standard short axis SSFP stack and a 15 heart-beat single breath-hold six slice multi-planar (4 short and 2 long axis) TSENSE SSFP protocol with an acceleration factor of <it>R </it>= 4.</p> <p>Results</p> <p>Differences (standard minus accelerated protocol mean ± s.d.) and coefficients of variation (s.d. of differences as a percentage of the average estimate) were 7.5 ± 9.6 mL and 6% for end-diastolic volume (p = 0.035), 0.4 ± 5.1 mL and 7% for end-systolic volume (p = NS), 7.1 ± 8.1 mL and 9% for stroke volume (p = 0.022), 2.2 ± 2.8% and 5% for ejection fraction (p = 0.035), and -7.1 ± 6.2 g and 4% for LV mass (p = 0.005), respectively. Intra- and inter-observer errors were similar for both protocols (p = NS for all measures).</p> <p>Conclusion</p> <p>These results suggest that clinically useful estimates of LV function can be obtained in a TSENSE accelerated single breath-hold reduced slice acquisition at 3T using 3D modeling analysis techniques.</p

Aortic valve stenotic area calculation from phase contrast cardiovascular magnetic resonance: the importance of short echo time

<p>Abstract</p> <p>Background</p> <p>Cardiovascular magnetic resonance (CMR) can potentially quantify aortic valve area (AVA) in aortic stenosis (AS) using a single-slice phase contrast (PC) acquisition at valve level: AVA = aortic flow/aortic velocity-time integral (VTI). However, CMR has been shown to underestimate aortic flow in turbulent high velocity jets, due to intra-voxel dephasing. This study investigated the effect of decreasing intra-voxel dephasing by reducing the echo time (TE) on AVA estimates in patients with AS.</p> <p>Method</p> <p>15 patients with moderate or severe AS, were studied with three different TEs (2.8 ms/2.0 ms/1.5 ms), in the main pulmonary artery (MPA), left ventricular outflow tract (LVOT) and 0 cm/1 cm/2.5 cm above the aortic valve (AoV). PC estimates of stroke volume (SV) were compared with CMR left ventricular SV measurements and PC peak velocity, VTI and AVA were compared with Doppler echocardiography. CMR estimates of AVA obtained by direct planimetry from cine acquisitions were also compared with the echoAVA.</p> <p>Results</p> <p>With a TE of 2.8 ms, the mean PC SV was similar to the ventricular SV at the MPA, LVOT and AoV_{0 cm}(by Bland-Altman analysis bias ± 1.96 SD, 1.3 ± 20.2 mL/-6.8 ± 21.9 mL/6.5 ± 50.7 mL respectively), but was significantly lower at AoV₁and AoV_2.5(-29.3 ± 31.2 mL/-21.1 ± 35.7 mL). PC peak velocity and VTI underestimated Doppler echo estimates by approximately 10% with only moderate agreement. Shortening the TE from 2.8 to 1.5 msec improved the agreement between ventricular SV and PC SV at AoV_{0 cm}(6.5 ± 50.7 mL vs 1.5 ± 37.9 mL respectively) but did not satisfactorily improve the PC SV estimate at AoV_{1 cm}and AoV_{2.5 cm}. Agreement of CMR AVA with echoAVA was improved at TE 1.5 ms (0.00 ± 0.39 cm²) versus TE 2.8 (0.11 ± 0.81 cm²). The CMR method which agreed best with echoAVA was direct planimetry (-0.03 cm²± 0.24 cm²).</p> <p>Conclusion</p> <p>Agreement of CMR AVA at the aortic valve level with echo AVA improves with a reduced TE of 1.5 ms. However, flow measurements in the aorta (AoV 1 and 2.5) are underestimated and 95% limits of agreement remain large. Further improvements or novel, more robust techniques are needed in the CMR PC technique in the assessment of AS severity in patients with moderate to severe aortic stenosis.</p

Orthogonal Decomposition of Left Ventricular Remodeling in Myocardial Infarction

BACKGROUND: Left ventricular size and shape are important for quantifying cardiac remodeling in response to cardiovascular disease. Geometric remodeling indices have been shown to have prognostic value in predicting adverse events in the clinical literature, but these often describe interrelated shape changes. We developed a novel method for deriving orthogonal remodeling components directly from any (moderately independent) set of clinical remodeling indices. RESULTS: Six clinical remodeling indices (end-diastolic volume index, sphericity, relative wall thickness, ejection fraction, apical conicity, and longitudinal shortening) were evaluated using cardiac magnetic resonance images of 300 patients with myocardial infarction, and 1991 asymptomatic subjects, obtained from the Cardiac Atlas Project. Partial least squares (PLS) regression of left ventricular shape models resulted in remodeling components that were optimally associated with each remodeling index. A Gram-Schmidt orthogonalization process, by which remodeling components were successively removed from the shape space in the order of shape variance explained, resulted in a set of orthonormal remodeling components. Remodeling scores could then be calculated that quantify the amount of each remodeling component present in each case. A one-factor PLS regression led to more decoupling between scores from the different remodeling components across the entire cohort, and zero correlation between clinical indices and subsequent scores. CONCLUSIONS: The PLS orthogonal remodeling components had similar power to describe differences between myocardial infarction patients and asymptomatic subjects as principal component analysis, but were better associated with well-understood clinical indices of cardiac remodeling. The data and analyses are available from www.cardiacatlas.org

The Cardiac Atlas Project--An Imaging Database for Computational Modeling and Statistical Atlases of the Heart

MOTIVATION: Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups. RESULTS: Three main open-source software components were developed: (i) a database with web-interface; (ii) a modeling client for 3D + time visualization and parametric description of shape and motion; and (iii) open data formats for semantic characterization of models and annotations. The database was implemented using a three-tier architecture utilizing MySQL, JBoss and Dcm4chee, in compliance with the DICOM standard to provide compatibility with existing clinical networks and devices. Parts of Dcm4chee were extended to access image specific attributes as search parameters. To date, approximately 3000 de-identified cardiac imaging examinations are available in the database. All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (http://www.mozilla.org/MPL/MPL-1.1.txt)