In vivo diffusion tensor MRI of the human heart: Reproducibility of breath‐hold and navigator‐based approaches

Nielles‐Vallespin, Sonia; Mekkaoui, Choukri; Gatehouse, Peter; Reese, Timothy G.; Keegan, Jennifer; Ferreira, Pedro F.; Collins, Steve; Speier, Peter; Feiweier, Thorsten; Silva, Ranil de; Jackowski, Marcel P.; Pennell, Dudley J.; Sosnovik, David E.; Firmin, David N.

doi:10.1002/mrm.24488

Cited by 156 publications

(263 citation statements)

References 64 publications

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“…In clinical diffusion imaging, non‐Gaussian models have the potential to help in assessing myocardial perfusion 19. However, gradient hardware in clinical scanners typically limit b‐values to 500 s/mm 2 46, 47, 48, reducing sensitivity to non‐Gaussian diffusion arising from finer tissue structures as demonstrated here. Stimulated echo approaches afford higher b‐values for a given maximum gradient amplitude due to long diffusion times.…”

Section: Discussionmentioning

confidence: 93%

Evaluation of non‐Gaussian diffusion in cardiac MRI

McClymont

Teh

Carruth

et al. 2016

Magnetic Resonance in Med

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PurposeThe diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non‐Gaussian modeling. The aim of this study was to investigate non‐Gaussian diffusion in healthy and hypertrophic hearts.MethodsThirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion‐weighted images were acquired at b‐values up to 10,000 s/mm2. Models of diffusion were fit to the data and ranked based on the Akaike information criterion.ResultsThe diffusion tensor was ranked best at b‐values up to 2000 s/mm2 but reflected the signal poorly in the high b‐value regime, in which the best model was a non‐Gaussian “beta distribution” model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet‐normal directions.ConclusionNon‐Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174–1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

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Section: Discussionmentioning

confidence: 93%

Evaluation of non‐Gaussian diffusion in cardiac MRI

McClymont

Teh

Carruth

et al. 2016

Magnetic Resonance in Med

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“…Despite the increasing number of attempts at in vivo DTMRI for assessing myofiber structure in the left ventricle, diffusion imaging of a beating heart remains extremely challenging, with many cofounding factors, such as bulk motion and myocardial strain, that can affect the measured signal. [47][48][49] The thin wall and the complex pattern of fibers in the atria present additional challenges to this task when compared with the ventricles. However, we can speculate that given a strong baseline knowledge of the fiber patterns in the human atrium, such as obtained in the present study, one could design a diffusion-weighted sequence to detect those patterns in selected regions of the atria in vivo.…”

Section: Pashakhanloo Et Almentioning

confidence: 99%

Myofiber Architecture of the Human Atria as Revealed by Submillimeter Diffusion Tensor Imaging

Pashakhanloo

Herzka

Ashikaga

et al. 2016

Circ: Arrhythmia and Electrophysiology

164

141

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Background-Accurate knowledge of the human atrial fibrous structure is paramount in understanding the mechanisms of atrial electric function in health and disease. Thus far, such knowledge has been acquired from destructive sectioning, and there is a paucity of data about atrial fiber architecture variability in the human population. Methods and Results-In this study, we have developed a customized 3-dimensional diffusion tensor magnetic resonance imaging sequence on a clinical scanner that makes it possible to image an entire intact human heart specimen ex vivo at submillimeter resolution. The data from 8 human atrial specimens obtained with this technique present complete maps of the fibrous organization of the human atria. The findings demonstrate that the main features of atrial anatomy are mostly preserved across subjects although the exact location and orientation of atrial bundles vary. Using the full tractography data, we were able to cluster, visualize, and characterize the distinct major bundles in the human atria. Furthermore, quantitative characterization of the fiber angles across the atrial wall revealed that the transmural fiber angle distribution is heterogeneous throughout different regions of the atria. Conclusions-The application of submillimeter diffusion tensor magnetic resonance imaging provides an unprecedented level of information on both human atrial structure, as well as its intersubject variability. The high resolution and fidelity of this data could enhance our understanding of structural contributions to atrial rhythm and pump disorders and lead to improvements in their targeted treatment. (Circ Arrhythm Electrophysiol. 2016;9:e004133.

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“…Without loss of generality, this subsection will just provide procedures of solving (8) which is a non-smooth convex optimization problem and can be solved by a variety of algorithms [34][35][36]. Here we adopt the alternating direction method of multipliers (ADMM) algorithm which is an efficient and fast algorithm well suited for solving large-scale optimization problems [37].…”

Section: Algorithmmentioning

confidence: 99%

“…CDTI, performed both ex vivo [4][5][6] and in vivo [7,8], reveals a helical fiber pattern along the ventricle wall with left-handed orientation in the subepicardial region and right-handed orientation in the subendocardial region for healthy heart [9]. Such pattern can be characterized by helix angle (HA) which represents the elevated angle out of the short-axis plane, indicating the local fiber orientation.…”

Section: Introductionmentioning

confidence: 99%

Accelerated Cardiac Diffusion Tensor Imaging Using Joint Low-Rank and Sparsity Constraints

Nguyen

Christodoulou

et al. 2018

IEEE Trans. Biomed. Eng.

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Abstract-Objective: The purpose of this manuscript is to accelerate cardiac diffusion tensor imaging (CDTI) by integrating low-rankness and compressed sensing. Methods: Diffusion-weighted images exhibit both transform sparsity and low-rankness. These properties can jointly be exploited to accelerate CDTI, especially when a phase map is applied to correct for the phase inconsistency across diffusion directions, thereby enhancing low-rankness. The proposed method is evaluated both ex vivo and in vivo, and is compared to methods using either a low-rank or sparsity constraint alone. Results: Compared to using a low-rank or sparsity constraint alone, the proposed method preserves more accurate helix angle features, the transmural continuum across the myocardium wall, and mean diffusivity at higher acceleration, while yielding significantly lower bias and higher intraclass correlation coefficient. Conclusion: Low-rankness and compressed sensing together facilitate acceleration for both ex vivo and in vivo CDTI, improving reconstruction accuracy compared to employing either constraint alone. Significance: Compared to previous methods for accelerating CDTI, the proposed method has the potential to reach higher acceleration while preserving myofiber architecture features which may allow more spatial coverage, higher spatial resolution and shorter temporal footprint in the future.Index Terms-Cardiac diffusion tensor imaging, phase correction, low-rank modeling, compressed sensing, helix angle, helix angle transmurality, mean diffusivity. I. INTRODUCTIONardiac diffusion tensor imaging (CDTI) is a powerful noninvasive tool capable of assessing the anatomic microstructure of the myocardium which is highly structured and organized into sheets of fibers making it suitable to be characterized by CDTI [1][2][3]. CDTI, performed both ex vivo [4][5][6] and in vivo [7,8], reveals a helical fiber pattern along the ventricle wall with left-handed orientation in the subepicardial region and right-handed orientation in the subendocardial region for healthy heart [9]. Such pattern can be characterized by helix angle (HA) which represents the elevated angle out of the short-axis plane, indicating the local fiber orientation. Myofibers around subendocardial regions, mid myocardium and subepicardial regions have HA> 0°, HA= 0° and HA< 0°, respectively [2]. In heart failure, the helical structure and orientation of the myocardial fibers are severely altered due to adverse remodeling [10,11].One of the major challenges for CDTI is the prolonged acquisition time, because of the multiple diffusion encoding measurements needed to robustly reconstruct the self-diffusion tensor [12]. In addition, multiple signal averages are required to maintain sufficient signal-to-noise ratio (SNR) due to signal loss caused by 2 decay and diffusion signal attenuation [13]. Though motion-induced signal loss can be effectively addressed by second-or higher-order motion compensation gradient waveforms [7,14], long acquisitions will likely incur more complex motio...

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In vivo diffusion tensor MRI of the human heart: Reproducibility of breath‐hold and navigator‐based approaches

Cited by 156 publications

References 64 publications

Evaluation of non‐Gaussian diffusion in cardiac MRI

Evaluation of non‐Gaussian diffusion in cardiac MRI

Myofiber Architecture of the Human Atria as Revealed by Submillimeter Diffusion Tensor Imaging

Accelerated Cardiac Diffusion Tensor Imaging Using Joint Low-Rank and Sparsity Constraints

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