Assessment of cardiac motion effects on the fiber architecture of the human heart in vivo

Intravoxel Incoherent Motion Magnetic Resonance Imaging with Integrated Slice-specific Shimming for old myocardial infarction: A Pilot Study

Currently, little is known regarding the value of quantitative parameters derived from the intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) with integrated slice-specific shimming (iShim) sequence in detecting old myocardial infarction and myocardial fibrosis. This study was to investigate the value of IVIM-MRI with iShim sequence in diagnosing old myocardial infarction and fibrosis. Thirty-five patients with both old myocardial infarction and myocardial fibrosis and 12 healthy volunteers were prospectively enrolled to undergo cardiac diffusion-weighted imaging (DWI) using seven b-values (0, 20, 60, 80, 120, 200 and 600 s/mm²). The iShim sequence was used for IVIM data acquisition, and the diffusion parameters, D, D* and f values for IVIM, and conventional apparent diffusion coefficient (ADC) were evaluated on the anterior, posterior and lateral walls of the ventricular septum using the short axis of the heart. Significant differences were found in the D, D* and f values between healthy subjects and patients with old myocardial infarction and myocardial fibrosis (P = 0.000), with the median value of the D and f significantly smaller in the myocardial infarction and fibrosis than in the normal control but the median value of D* significantly greater in the myocardial infarction and fibrosis than in the normal control. In the receiver operating curve analysis, the areas under the curve were 0.939, 0.988 and 0.959 for the D, D* and f values, respectively. The sensitivities and specificities were 84.6% and 94.4% for D, 88.9% and 84.6% for D* and 100% and 93.1% for the f values, respectively. In conclusion, the IVIM-derived parameters (D, D* and f) obtained using the iShim DWI technique showed high capacity in diagnosing old myocardial infarction and myocardial fibrosis by providing diffusion and perfusion information, which may have great importance in future clinical practice.

Accelerating cardiac diffusion tensor imaging combining local low-rank and 3D TV constraint

OBJECTIVE

Diffusion tensor magnetic resonance imaging (DT-MRI, or DTI) is a promising technique for invasively probing biological tissue structures. However, DTI is known to suffer from much longer acquisition time with respect to conventional MRI and the problem is worsened when dealing with in vivo acquisitions. Therefore, faster DTI for both ex vivo and in vivo scans is highly desired.

MATERIALS AND METHODS

This paper proposes a new compressed sensing (CS) reconstruction method that employs local low-rank (LLR) model and three-dimensional (3D) total variation (TV) constraint to reconstruct cardiac diffusion-weighted (DW) images from highly undersampled k-space data. The LLR model takes the set of DW images corresponding to different diffusion gradient directions as a 3D image volume and decomposes the latter into overlapping 3D blocks. Then, the 3D blocks are stacked as two-dimensional (2D) matrix. Finally, low-rank property is applied to each block matrix and the 3D TV constraint to the 3D image volume. The underlying constrained optimization problem is finally solved using the first-order fast method. The proposed method is evaluated on real ex vivo cardiac DTI data as a prerequisite to in vivo cardiac DTI applications.

RESULTS

The results on real human ex vivo cardiac DTI images demonstrate that the proposed method exhibits lower reconstruction errors for DTI indices, including fractional anisotropy (FA), mean diffusivities (MD), transverse angle (TA), and helix angle (HA), compared to existing CS-based DTI image reconstruction techniques.

CONCLUSION

The proposed method provides better reconstruction quality and more accurate DTI indices in comparison with the state-of-the-art CS-based DW image reconstruction methods.

Will the real ventricular architecture please stand up?

Ventricular twisting, essential for cardiac function, is attributed to the contraction of myocardial helical fibers. The exact relationship between ventricular anatomy and function remains to be determined, but one commonly used explanatory model is the helical ventricular myocardial band (HVMB) model of Torrent‐Guasp. This model has been successful in explaining many aspects of ventricular function, (Torrent‐Guasp et al. Eur. J. Cardiothorac. Surg., 25, 376, 2004; Buckberg et al. Eur. J. Cardiothorac. Surg., 47, 587, 2015; Buckberg et al. Eur. J. Cardiothorac. Surg. 47, 778, 2015) but the model ignores important aspects of ventricular anatomy and should probably be replaced. The purpose of this review is to compare the HVMB model with a different model (nested layers). A complication when interpreting experimental observations that relate anatomy to function is that, in the myocardium, shortening does not always imply activation and lengthening does not always imply inactivation.

Single-shot turbo spin echo acquisition for in vivo cardiac diffusion MRI

Diffusion MRI offers the ability to noninvasively characterize the microstructure of myocardium tissue and detect disease related pathology in cardiovascular examination. This study investigates the feasibility of in vivo cardiac diffusion MRI under free-breathing condition. A high-speed imaging technique, correlation imaging, is used to enable single-shot turbo spin echo for free-breathing cardiac data acquisition. The obtained in vivo cardiac diffusion-weighted images illustrate robust image quality and minor geometry distortions. The resultant diffusion scalar maps show reliable quantitative values consistent with those previously published in the literature. It is demonstrated that this technique has the potential for in vivo free-breathing cardiac diffusion MRI.

Consistent Spatial-Temporal Longitudinal Atlas Construction for Developing Infant Brains

Brain atlases are an essential component in understanding the dynamic cerebral development, especially for the early postnatal period. However, longitudinal atlases are rare for infants, and the existing ones are generally limited by their fuzzy appearance. Moreover, since longitudinal atlas construction is typically performed independently over time, the constructed atlases often fail to preserve temporal consistency. This problem is further aggravated for infant images since they typically have low spatial resolution and insufficient tissue contrast. In this paper, we propose a novel framework for consistent spatial-temporal construction of longitudinal atlases for developing infant brain MR images. Specifically, for preserving structural details, the atlas construction is performed in spatial-temporal wavelet domain simultaneously. This is achieved by a patch-based combination of results from each frequency subband. Compared with the existing infant longitudinal atlases, our experimental results indicate that our approach is able to produce longitudinal atlases with richer structural details and also better longitudinal consistency, thus leading to higher performance when used for spatial normalization of a group of infant brain images.

Image-Based Investigation of Human in Vivo Myofibre Strain

Cardiac myofibre deformation is an important determinant of the mechanical function of the heart. Quantification of myofibre strain relies on 3D measurements of ventricular wall motion interpreted with respect to the tissue microstructure. In this study, we estimated in vivo myofibre strain using 3D structural and functional atlases of the human heart. A finite element modelling framework was developed to incorporate myofibre orientations of the left ventricle (LV) extracted from 7 explanted normal human hearts imaged ex vivo with diffusion tensor magnetic resonance imaging (DTMRI) and kinematic measurements from 7 normal volunteers imaged in vivo with tagged MRI. Myofibre strain was extracted from the DTMRI and 3D strain from the tagged MRI. We investigated: i) the spatio-temporal variation of myofibre strain throughout the cardiac cycle; ii) the sensitivity of myofibre strain estimates to the variation in myofibre angle between individuals; and iii) the sensitivity of myofibre strain estimates to variations in wall motion between individuals. Our analysis results indicate that end systolic (ES) myofibre strain is approximately homogeneous throughout the entire LV, irrespective of the inter-individual variation in myofibre orientation. Additionally, inter-subject variability in myofibre orientations has greater effect on the variabilities in myofibre strain estimates than the ventricular wall motions. This study provided the first quantitative evidence of homogeneity of ES myofibre strain using minimally-invasive medical images of the human heart and demonstrated that image-based modelling framework can provide detailed insight to the mechanical behaviour of the myofibres, which may be used as a biomarker for cardiac diseases that affect cardiac mechanics.

The effects of noise in cardiac diffusion tensor imaging and the benefits of averaging complex data

There is growing interest in cardiac diffusion tensor imaging (cDTI), but, unlike other diffusion MRI applications, there has been little investigation of the effects of noise on the parameters typically derived. One method of mitigating noise floor effects when there are multiple image averages, as in cDTI, is to average the complex rather than the magnitude data, but the phase contains contributions from bulk motion, which must be removed first. The effects of noise on the mean diffusivity (MD), fractional anisotropy (FA), helical angle (HA) and absolute secondary eigenvector angle (E2A) were simulated with various diffusion weightings (b values). The effect of averaging complex versus magnitude images was investigated. In vivo cDTI was performed in 10 healthy subjects with b = 500, 1000, 1500 and 2000 s/mm(2). A technique for removing the motion-induced component of the image phase present in vivo was implemented by subtracting a low-resolution copy of the phase from the original images before averaging the complex images. MD, FA, E2A and the transmural gradient in HA were compared for un-averaged, magnitude- and complex-averaged reconstructions. Simulations demonstrated an over-estimation of FA and MD at low b values and an under-estimation at high b values. The transition is relatively signal-to-noise ratio (SNR) independent and occurs at a higher b value for FA (b = 1000-1250 s/mm(2)) than MD (b ≈ 250 s/mm(2)). E2A is under-estimated at low and high b values with a transition at b ≈ 1000 s/mm(2), whereas the bias in HA is comparatively small. The under-estimation of FA and MD at high b values is caused by noise floor effects, which can be mitigated by averaging the complex data. Understanding the parameters of interest and the effects of noise informs the selection of the optimal b values. When complex data are available, they should be used to maximise the benefit from the acquisition of multiple averages. The combination of complex data is also a valuable step towards segmented acquisitions.

Quantitative representation and description of intravoxel fiber complexity in HARDI

Diffusion tensor imaging and high angular resolution diffusion imaging are often used to analyze the fiber complexity of tissues. In these imaging techniques, the most commonly calculated metric is anisotropy, such as fractional anisotropy (FA), generalized anisotropy (GA), and generalized fractional anisotropy (GFA). The basic idea underlying these metrics is to compute the deviation from free or spherical diffusion. However, in many cases, the question is not really to know whether it concerns spherical diffusion. Instead, the main concern is to describe and quantify fiber complexity such as fiber crossing in a voxel. In this context, it would be more direct and effective to compute the deviation from a single fiber bundle instead of a sphere. We propose a new metric, called PEAM (PEAnut Metric), which is based on computing the deviation of orientation diffusion functions (ODFs) from a single fiber bundle ODF represented by a peanut. As an example, the proposed PEAM metric is used to classify intravoxel fiber configurations. The results on simulated data, physical phantom data and real brain data consistently showed that the proposed PEAM provides greater accuracy than FA, GA and GFA and enables parallel and complex fibers to be better distinguished.

Spin echo versus stimulated echo diffusion tensor imaging of the in vivo human heart

Purpose

To compare signal‐to‐noise ratio (SNR) efficiency and diffusion tensor metrics of cardiac diffusion tensor mapping using acceleration‐compensated spin‐echo (SE) and stimulated echo acquisition mode (STEAM) imaging.

Methods

Diffusion weighted SE and STEAM sequences were implemented on a clinical 1.5 Tesla MR system. The SNR efficiency of SE and STEAM was measured (b = 50–450 s/mm²) in isotropic agar, anisotropic diffusion phantoms and the in vivo human heart. Diffusion tensor analysis was performed on mean diffusivity, fractional anisotropy, helix and transverse angles.

Results

In the isotropic phantom, the ratio of SNR efficiency for SE versus STEAM, SNR_t(SE/STEAM), was 2.84 ± 0.08 for all tested b‐values. In the anisotropic diffusion phantom the ratio decreased from 2.75 ± 0.05 to 2.20 ± 0.13 with increasing b‐value, similar to the in vivo decrease from 2.91 ± 0.43 to 2.30 ± 0.30. Diffusion tensor analysis revealed reduced deviation of helix angles from a linear transmural model and reduced transverse angle standard deviation for SE compared with STEAM. Mean diffusivity and fractional anisotropy were measured to be statistically different (P < 0.001) between SE and STEAM.

Conclusion

Cardiac DTI using motion‐compensated SE yields a 2.3–2.9× increase in SNR efficiency relative to STEAM and improved accuracy of tensor metrics. The SE method hence presents an attractive alternative to STEAM based approaches. Magn Reson Med 76:862–872, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Second-order motion-compensated spin echo diffusion tensor imaging of the human heart

PURPOSE

Myocardial microstructure has been challenging to probe in vivo. Spin echo-based diffusion-weighted sequences allow for single-shot acquisitions but are highly sensitive to cardiac motion. In this study, the use of second-order motion-compensated diffusion encoding was compared with first-order motion-compensated diffusion-weighted imaging during systolic contraction of the heart.

METHODS

First- and second-order motion-compensated diffusion encoding gradients were incorporated into a triggered single-shot spin echo sequence. The effect of contractile motion on the apparent diffusion coefficients and tensor orientations was investigated in vivo from basal to apical level of the heart.

RESULTS

Second-order motion compensation was found to increase the range of systolic trigger delays from 30%-55% to 15%-77% peak systole at the apex and from 25%-50% to 15%-79% peak systole at the base. Diffusion tensor analysis yielded more physiological transmural distributions when using second-order motion-compensated diffusion tensor imaging.

CONCLUSION

Higher-order motion-compensated diffusion encoding decreases the sensitivity to cardiac motion, thereby enabling cardiac DTI over a wider range of time points during systolic contraction of the heart.

Resolving intravoxel fiber architecture using nonconvex regularized blind compressed sensing

In diffusion magnetic resonance imaging, accurate and reliable estimation of intravoxel fiber architectures is a major prerequisite for tractography algorithms or any other derived statistical analysis. Several methods have been proposed that estimate intravoxel fiber architectures using low angular resolution acquisitions owing to their shorter acquisition time and relatively low b-values. But these methods are highly sensitive to noise. In this work, we propose a nonconvex regularized blind compressed sensing approach to estimate intravoxel fiber architectures in low angular resolution acquisitions. The method models diffusion-weighted (DW) signals as a sparse linear combination of unfixed reconstruction basis functions and introduces a nonconvex regularizer to enhance the noise immunity. We present a general solving framework to simultaneously estimate the sparse coefficients and the reconstruction basis. Experiments on synthetic, phantom, and real human brain DW images demonstrate the superiority of the proposed approach.

Free-breathing diffusion tensor imaging and tractography of the human heart in healthy volunteers using wavelet-based image fusion

Free-breathing cardiac diffusion tensor imaging (DTI) is a promising but challenging technique for the study of fiber structures of the human heart in vivo. This work proposes a clinically compatible and robust technique to provide three-dimensional (3-D) fiber architecture properties of the human heart. To this end, 10 short-axis slices were acquired across the entire heart using a multiple shifted trigger delay (TD) strategy under free breathing conditions. Interscan motion was first corrected automatically using a nonrigid registration method. Then, two post-processing schemes were optimized and compared: an algorithm based on principal component analysis (PCA) filtering and temporal maximum intensity projection (TMIP), and an algorithm that uses the wavelet-based image fusion (WIF) method. The two methods were applied to the registered diffusion-weighted (DW) images to cope with intrascan motion-induced signal loss. The tensor fields were finally calculated, from which fractional anisotropy (FA), mean diffusivity (MD), and 3-D fiber tracts were derived and compared. The results show that the comparison of the FA values (FA(PCATMIP) = 0.45 ±0.10, FA(WIF) = 0.42 ±0.05, P=0.06) showed no significant difference, while the MD values ( MD(PCATMIP)=0.83 ±0.12×10(-3) mm (2)/s, MD(WIF)=0.74±0.05×10(-3) mm (2)/s, P=0.028) were significantly different. Improved helix angle variations through the myocardium wall reflecting the rotation characteristic of cardiac fibers were observed with WIF. This study demonstrates that the combination of multiple shifted TD acquisitions and dedicated post-processing makes it feasible to retrieve in vivo cardiac tractographies from free-breathing DTI acquisitions. The substantial improvements were observed using the WIF method instead of the previously published PCATMIP technique.