In vivo diffusion-tensor MRI of the human heart on a 3 tesla clinical scanner: An optimized second order (M2) motion compensated diffusion-preparation approach

Cardiac diffusion-weighted and tensor imaging: a Society for Cardiovascular Magnetic Resonance (SCMR) special interest group consensus statement

Thanks to recent developments in Cardiovascular magnetic resonance (CMR), cardiac diffusion-weighted magnetic resonance is fast emerging in a range of clinical applications. Cardiac diffusion-weighted imaging (cDWI) and diffusion tensor imaging (cDTI) now enable investigators and clinicians to assess and quantify the 3D microstructure of the heart. Free-contrast DWI is uniquely sensitized to the presence and displacement of water molecules within the myocardial tissue, including the intra-cellular, extra-cellular and intra-vascular spaces. CMR can determine changes in microstructure by quantifying: a) mean diffusivity (MD) -measuring the magnitude of diffusion; b) fractional anisotropy (FA) - specifying the directionality of diffusion; c) helix angle (HA) and transverse angle (TA) -indicating the orientation of the cardiomyocytes; d) E2A and E2A mobility - measuring the alignment and systolic-diastolic mobility of the sheetlets, respectively. This document provides recommendations for both clinical and research cDWI and cDTI, based on published evidence when available and expert consensus when not. It introduces the cardiac microstructure focusing on the cardiomyocytes and their role in cardiac physiology and pathophysiology. It highlights methods, observations and recommendations in terminology, acquisition schemes, post-processing pipelines, data analysis and interpretation of the different biomarkers. Despite the ongoing challenges discussed in the document and the need for ongoing technical improvements, it is clear that cDTI is indeed feasible, can be accurately and reproducibly performed and, most importantly, can provide unique insights into myocardial pathophysiology.

In vivo cardiac diffusion tensor imaging on an MR system featuring ultrahigh performance gradients with 200 mT/m maximum gradient strength

PURPOSE

Our aim is to assess the potential of an MR system with ultrahigh performance gradients (200 mT/m maximum gradient strength) to address two interrelated challenges in cardiac DTI: low SNR and sensitivity to bulk motion.

METHODS

Imaging was performed in 20 healthy volunteers, two patients, and one swine post-myocardial infarction. The impact of maximum gradient strength was assessed with spin echo cardiac DTI featuring second-order motion compensation and varying maximum system gradient strengths (40, 80, 200 mT/m). Motion compensation requirements at 200 mT/m were assessed with sequences featuring zeroth-, first-, and second-order motion compensation. SNR, mean diffusivity, fractional anisotropy, helix angle transmurality, and secondary eigenvector angle in the left ventricle were compared.

RESULTS

Increasing maximum system gradient strength from 40 and 80 mT/m to 200 mT/m increased SNR of b = 500 s/mm2 images by 150% and 40% due to reductions in TE. Observed improvements in DTI metrics included reduction in variance in mean diffusivity and helix angle transmurality across healthy volunteers, improved visualization of myocardial borders and delineation of suspected scar. Whereas second-order motion compensation acquisitions were robust to motion-induced signal dropout, zeroth- and first-order motion compensation acquisitions suffered from severe signal loss and localized signal voids, respectively.

CONCLUSION

Ultrahigh performance gradients (200 mT/m) enable high SNR DWIs of the heart and resultant improvements in diffusion tensor metrics. Despite reduced diffusion-encoding duration, second-order motion compensation is required to overcome sensitivity to cardiac motion.

The effects of field strength on stimulated echo and motion-compensated spin-echo diffusion tensor cardiovascular magnetic resonance sequences

BACKGROUND

In-vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) is an emerging technique for microstructural tissue characterization in the myocardium. Most studies are performed at 3T, where higher signal-to-noise ratio (SNR) should benefit this signal-starved method. However, a few studies have suggested that DT-CMR is possible at 1.5T, where echo planar imaging artifacts may be less severe and 1.5T hardware is more widely available.

METHODS

We recruited 20 healthy volunteers and performed mid-ventricular short-axis DT-CMR at 1.5T and 3T. Acquisitions were performed at peak systole and end-diastole using both stimulated echo acquisition mode (STEAM) and motion-compensated spin-echo (MCSE) sequences at matched spatial resolutions. DT-CMR parameters were averaged over the left ventricle and compared between 1.5T and 3T sequences using both datasets with and without the blow reference data included.

RESULTS

Eleven (1.5T) and 12 (3T) diastolic MCSE acquisitions were rejected as the helix angle (HA) demonstrated <50% normal appearance circumferentially or the acquisition was abandoned due to poor image quality; a maximum of one acquisition was rejected for other datasets. Subjective HA map quality was significantly better at 3T than 1.5T for STEAM (p < 0.05), but not for MCSE and other DT-CMR quality measures were consistent with improvements in STEAM at 3T over 1.5T. When blow data were excluded, no significant differences in mean diffusivity were observed between field strengths, but fractional anisotropy was significantly higher at 1.5T than 3T for STEAM systole (p < 0.05). Absolute second eigenvector orientation (E2A, sheetlet angle) was significantly higher at 1.5T than 3T for MCSE systole and STEAM diastole, but significantly lower for STEAM systole (all p < 0.05). Transmural HA distribution was less steep at 1.5T than 3T for STEAM diastole data (p < 0.05). SNR was higher at 3T than 1.5T for all acquisitions (p < 0.05).

CONCLUSION

While 3T provides benefits in terms of SNR, both STEAM and MCSE can be performed at 1.5T. However, MCSE is unreliable in diastole at both field strengths and STEAM benefits from the improved SNR at 3T over 1.5T. Future clinical research studies may be able to leverage the wider availability of 1.5T CMR hardware where MCSE acquisitions are desirable.

Cardiac DTI using short-axis PROPELLER: A feasibility study

PURPOSE

We aimed to develop a free-breathing (FB) cardiac DTI (cDTI) method based on short-axis PROPELLER (SAP) and M2 motion compensated spin-echo EPI (SAP-M2-EPI) to mitigate geometric distortion and eliminate aliasing in acquired diffusion-weighted (DW) images, particularly in patients with a higher body mass index (BMI).

THEORY AND METHODS

The study involved 10 healthy volunteers whose BMI values fell into specific categories: BMI <25 (4 volunteers), 25< BMI <28 (5 volunteers), and BMI >30 (1 volunteer). We compared DTI parameters, including fractional anisotropy (FA), mean diffusivity (MD), and helix angle transmurality (HAT), between SAP-M2-EPI and M2-ssEPI. To evaluate the performance of SAP-M2-EPI in reducing geometric distortions in the left ventricle (LV) compared to CINE and M2-ssEPI, we utilized the DICE similarity coefficient (DSC) and assessed misregistration area.

RESULTS

In all volunteers, SAP-M2-EPI yielded high-quality LV DWIs without aliasing, demonstrating significantly reduced geometric distortion (with an average DSC of 0.92 and average misregistration area of 90 mm2) and diminished signal loss due to bulk motion when compared to M2-ssEPI. DTI parameter maps exhibited consistent patterns across slices without motion related artifacts.

CONCLUSION

SAP-M2-EPI facilitates free-breathing cDTI of the entire LV, effectively eliminating aliasing and minimizing geometric distortion compared to M2-ssEPI. Furthermore, it preserves accurate quantification of myocardial microstructure.

Diffusion Tensor Phenomapping of the Healthy and Pressure-Overloaded Human Heart

Current techniques to image the microstructure of the heart with diffusion tensor MRI (DTI) are highly under-resolved. We present a technique to improve the spatial resolution of cardiac DTI by almost 10-fold and leverage this to measure local gradients in cardiomyocyte alignment or helix angle (HA). We further introduce a phenomapping approach based on voxel-wise hierarchical clustering of these gradients to identify distinct microstructural microenvironments in the heart. Initial development was performed in healthy volunteers (n=8). Thereader, subjects with severe but well-compensated aortic stenosis (AS, n=10) were compared to age-matched controls (CTL, n=10). Radial HA gradient was significantly reduced in AS (8.0±0.8°/mm vs. 10.2±1.8°/mm, p=0.001) but the other HA gradients did not change significantly. Four distinct microstructural clusters could be idenJfied in both the CTL and AS subjects and did not differ significantly in their properties or distribution. Despite marked hypertrophy, our data suggest that the myocardium in well-compensated AS can maintain its microstructural coherence. The described phenomapping approach can be used to characterize microstructural plasticity and perturbation in any organ system and disease.

Self-calibrated subspace reconstruction for multidimensional MR fingerprinting for simultaneous relaxation and diffusion quantification

PURPOSE

To propose a new reconstruction method for multidimensional MR fingerprinting (mdMRF) to address shading artifacts caused by physiological motion-induced measurement errors without navigating or gating.

METHODS

The proposed method comprises two procedures: self-calibration and subspace reconstruction. The first procedure (self-calibration) applies temporally local matrix completion to reconstruct low-resolution images from a subset of under-sampled data extracted from the k-space center. The second procedure (subspace reconstruction) utilizes temporally global subspace reconstruction with pre-estimated temporal subspace from low-resolution images to reconstruct aliasing-free, high-resolution, and time-resolved images. After reconstruction, a customized outlier detection algorithm was employed to automatically detect and remove images corrupted by measurement errors. Feasibility, robustness, and scan efficiency were evaluated through in vivo human brain imaging experiments.

RESULTS

The proposed method successfully reconstructed aliasing-free, high-resolution, and time-resolved images, where the measurement errors were accurately represented. The corrupted images were automatically and robustly detected and removed. Artifact-free T1, T2, and ADC maps were generated simultaneously. The proposed reconstruction method demonstrated robustness across different scanners, parameter settings, and subjects. A high scan efficiency of less than 20 s per slice has been achieved.

CONCLUSION

The proposed reconstruction method can effectively alleviate shading artifacts caused by physiological motion-induced measurement errors. It enables simultaneous and artifact-free quantification of T1, T2, and ADC using mdMRF scans without prospective gating, with robustness and high scan efficiency.

Facilitating diffusion tensor imaging of the brain during continuous gross head motion with first and second order motion compensating diffusion gradients

PURPOSE

To demonstrate the feasibility of motion compensating diffusion gradient schemes in the acquisition of quality diffusion tensor images (DTI) of the brain during continuous gross head motion.

METHODS

Five healthy subjects were scanned using a clinical 3 T MRI with and without continuous head motion. For one volunteer, DTI data was acquired using standard (M0) diffusion-weighted (DW) gradients, and first (M1) and second (M2) order gradient schemes that were previously developed for use in cardiac DTI. In four additional volunteers, DTI data was acquired with M0 and M2 gradients. DTI parameters were calculated and compared with established retrospective motion corrections.

RESULTS

In the absence of motion, DTI parameters calculated from M0, M1, and M2 data were consistent. In the presence of motion, up to 44% of DW images acquired with M0 gradients were corrupted by signal dropout, compared to 0% of the M2 images. In voxelwise comparisons, DTI parameters calculated using motion-M0 data were elevated compared to reference data. Retrospective corrections for extreme motion applied to motion-M0 data did not improve consistency with reference data in cases where motion corrupted >15% of DW images. In contrast, DTI parameters calculated with motion-M2 data were consistent with reference data.

CONCLUSION

This proof-of-principle study demonstrates that motion compensating diffusion gradients can mitigate artifacts because of continuous motion in DTI of the brain and offers promise for improved DTI accessibility. Further study will be necessary to determine the robustness of the approach in patient populations with high susceptibility to head motion.

High resolution single-shot myocardial imaging using bSSFP with wave encoding

BACKGROUND

Single-shot balanced steady-state free precession (bSSFP) sequence is widely used in cardiac imaging. However, the limited scan time in one heartbeat greatly hinders its spatial resolution compared to the segmented acquisition mode. Therefore, a highly accelerated single-shot bSSFP imaging technology is needed for clinical use.

PURPOSE

To develop and evaluate a wave-encoded bSSFP sequence with high acceleration rates for single-shot myocardial imaging.

METHODS

The proposed Wave-bSSFP method is implemented by adding a sinusoidal wave gradient in the phase encoding direction during the readout of bSSFP sequence. Uniform undersampling is used for acceleration. Its performance was first validated via phantom studies by comparison with conventional bSSFP. Then it was evaluated in volunteer studies via anatomical imaging, T2 -prepared bSSFP, and T1 mapping in in-vivo cardiac imaging. All methods were compared with accelerated conventional bSSFP reconstructed using iterative SENSE and compressed sensing (CS), to demonstrate the advantage of wave encoding in suppressing the noise amplification and artifacts induced by acceleration.

RESULTS

The proposed Wave-bSSFP method achieved a high acceleration factor of 4 for single-shot acquisitions. The proposed method showed lower average g-factors than bSSFP, and fewer blurring artifacts than CS reconstruction. The Wave-bSSFP with R = 4 achieved higher spatial and temporal resolutions compared with the conventional bSSFP with R = 2 in several applications such as T2 -prepared bSSFP and T1 mapping, and could be applied in systolic imaging.

CONCLUSION

Wave encoding can be used to highly accelerate 2D bSSFP imaging with single-shot acquisitions. Compared with the conventional bSSFP sequence, the proposed Wave-bSSFP method can effectively reduce the g-factor and aliasing artifacts in cardiac imaging.

Antagonism of contractile forces in left ventricular hypertrophy: a diagnostic challenge for better pathophysiological and clinical understanding

Cardiac function is characterised by haemodynamic parameters in the clinical scenario. Due to recent development in imaging techniques, the clinicians focus on the quantitative assessment of left ventricular size, shape and motion patterns mostly analysed by echocardiography and cardiac magnetic resonance. Because of the physiologically known antagonistic structure and function of the heart muscle, the effective performance of the heart remains hidden behind haemodynamic parameters. In fact, a smaller component of oblique transmural netting of cardiac muscle fibres simultaneously engenders contracting and dilating force vectors, while the predominant mass of the tangentially aligned fibres only acts in one direction. In case of hypertrophy, an increased influence of the dilating transmural fibre component might counteract systolic wall thickening, thereby counteract cardiac output. A further important aspect is the response to inotropic stimulation that is different for the tangentially aligned fibre component in comparison to the transmural component. Both aspects highlight the importance to integrate the analysis of intramural fibre architecture into the clinical cardiac diagnostics.

Slice-specific tracking for free-breathing diffusion tensor cardiac MRI

BACKGROUND

Diffusion tensor cardiac magnetic resonance (DT-CMR) imaging has great potential to characterize myocardial microarchitecture. However, its accuracy is limited by respiratory and cardiac motion and long scan times. Here, we develop and evaluate a slice-specific tracking method to improve the efficiency and accuracy of DT-CMR acquisition during free breathing.

METHODS

Coronal images were obtained along with signals from a diaphragmatic navigator. Respiratory and slice displacements were obtained from the navigator signals and coronal images, respectively, and these displacements were fitted with a linear model to obtain the slice-specific tracking factors. This method was evaluated in DT-CMR examinations of 17 healthy subjects, and the results were compared with those obtained using a fixed tracking factor of 0.6. DT-CMR with breath-holding was used for reference. Quantitative and qualitative evaluation methods were used to analyze the performance of the slice-specific tracking method and the consistency between the obtained diffusion parameters.

RESULTS

In the study, the slice-specific tracking factors showed an upward trend from the basal to the apical slice. Residual in-plane movements were lower in slice-specific tracking than in fixed-factor tracking (RMSE: 2.748 ± 1.171 versus 5.983 ± 2.623, P < 0.001). The diffusion parameters obtained using slice-specific tracking were not significantly different from those obtained from breath-holding acquisition (P > 0.05).

CONCLUSION

In free-breathing DT-CMR imaging, the slice-specific tracking method reduced misalignment of the acquired slices. The diffusion parameters obtained using this approach were consistent with those obtained with the breath-holding technique.

The comparison of diffusion tensor imaging in human hearts between 1.5 T and 3.0 T

BACKGROUND

The aim was to compare the diffusion tensor imaging (DTI) indices derived from human hearts between 1.5 T and 3.0 T scanners. Additionally, the reproducibility of DTI indices was assessed between 1.5 T and 3.0 T scanners.

METHODS

A total of 18 ex-vivo hearts were derived from patients who underwent heart transplantation. The DTI schemes were performed at 1.5 T and 3.0 T, respectively. Then, the same slices from each ex-vivo heart were selected for image analysis. The student's t-test or Wilcoxon-rank test was used to compare the statistical differences. The agreement of DTI indices was mainly reported as the interclass correlation coefficient (ICC).

RESULTS

No significant differences (all P > 0.05) were found in the DTI indices between 1.5 T and 3.0 T scanners. Interestingly, the ICC of all DTI indices was relatively lower with a low b-value. The reproducibility of the helix angle (HA) was relatively lower when compared to the other DTI indices.

CONCLUSION

The DTI indices of ex-vivo human hearts between 1.5 T and 3.0 T scanners had no significant differences. The consistency of DTI indices needed caution using a low b-value with different field strengths, and the relatively low reproducibility of HA should be considered.

MR Fingerprinting with b-Tensor Encoding for Simultaneous Quantification of Relaxation and Diffusion in a Single Scan

PURPOSE

Although both relaxation and diffusion imaging are sensitive to tissue microstructure, studies have reported limited sensitivity and robustness of using relaxation or conventional diffusion alone to characterize tissue microstructure. Recently, it has been shown that tensor-valued diffusion encoding and joint relaxation-diffusion quantification enable more reliable quantification of compartment-specific microstructural properties. However, scan times to acquire such data can be prohibitive. Here, we aim to simultaneously quantify relaxation and diffusion using MR fingerprinting (MRF) and b-tensor encoding in a clinically feasible time.

METHODS

We developed multidimensional MRF scans (mdMRF) with linear and spherical b-tensor encoding (LTE and STE) to simultaneously quantify T1, T2, and ADC maps from a single scan. The image quality, accuracy, and scan efficiency were compared between the mdMRF using LTE and STE. Moreover, we investigated the robustness of different sequence designs to signal errors and their impact on the maps.

RESULTS

T1 and T2 maps derived from the mdMRF scans have consistently high image quality, while ADC maps are sensitive to different sequence designs. Notably, the fast imaging steady state precession (FISP)-based mdMRF scan with peripheral pulse gating provides the best ADC maps that are free of image distortion and shading artifacts.

CONCLUSION

We demonstrated the feasibility of quantifying T1, T2, and ADC maps simultaneously from a single mdMRF scan in around 24 s/slice. The map quality and quantitative values are consistent with the reference scans.

A meshless fragile points method for rule-based definition of myocardial fiber orientation

BACKGROUND AND OBJECTIVE

Rule-based methods are commonly used to estimate the arrangement of myocardial fibers by solving the Laplace problem with appropriate Dirichlet boundary conditions. Existing algorithms are using the Finite Element Method (FEM) to solve the Laplace-Dirichlet problem. However, meshless methods are under development for cardiac electrophysiology simulation. The objective of this work is to propose a meshless rule based method for the determination of myocardial fiber arrangement without requiring a mesh discretization as it is required by FEM.

METHODS

The proposed method employs the Fragile Points Method (FPM) for the solution of the Laplace-Dirichlet problem. FPM uses simple discontinuous trial functions and single-point exact integration for linear trial functions that set it as a promising alternative to the Finite Element Method. We derive the FPM formulation of the Laplace-Dirichlet and we estimate ventricular and atrial fiber arrangements according to rules based on histology findings for four different geometries. The obtained fiber arrangements from FPM are compared with the ones obtained from FEM by calculating the angle between the fiber vector fields of the two methods for three different directions (i.e., longitudinal, sheet, transverse).

RESULTS

The fiber arrangements that were generated with FPM were in close agreement with the generated arrangements from FEM for all three directions. The mean angle difference between the FPM and FEM vector fields were lower than 0.030^∘ for the ventricular fiber arrangements and lower than 0.036^∘ for the atrial fiber arrangements.

DISCUSSION

The proposed meshless rule-based method was proven to generate myocardial fiber arrangements with very close agreement with FEM while alleviates the requirement for a mesh of the latter. This is of great value for cardiac electrophysiology solvers that are based on meshless methods since they require a well defined myocardial fiber arrangement to simulate accurately the propagation of electrical signals in the heart. Combining a meshless solution for both the determination of the fibers and the electrical signal propagation can allow for solution that do not require the definition of a mesh. To our knowledge, this work is the first one to propose a meshless rule-based method for myocardial fiber arrangement determination.

WA, Boyle J, Coll‐Font J, Dall'Armellina E, Ennis DB, Ferreira PF, Kalra P, Kolipaka A, Kozerke S, Lohr D, Mongeon F, Moulin K, Nguyen C, Nielles‐Vallespin S, Raterman B, Schreiber LM, Scott AD, Sosnovik DE, Stoeck CT, Tous C, Tunnicliffe EM, Weng AM, Croisille P, Viallon M, Schneider JE. Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study

Cardiac diffusion tensor imaging (DTI) is an emerging technique for the in vivo characterisation of myocardial microstructure, and there is a growing need for its validation and standardisation. We sought to establish the accuracy, precision, repeatability and reproducibility of state-of-the-art pulse sequences for cardiac DTI among 10 centres internationally. Phantoms comprising 0%-20% polyvinylpyrrolidone (PVP) were scanned with DTI using a product pulsed gradient spin echo (PGSE; N = 10 sites) sequence, and a custom motion-compensated spin echo (SE; N = 5) or stimulated echo acquisition mode (STEAM; N = 5) sequence suitable for cardiac DTI in vivo. A second identical scan was performed 1-9 days later, and the data were analysed centrally. The average mean diffusivities (MDs) in 0% PVP were (1.124, 1.130, 1.113) x 10^-3  mm² /s for PGSE, SE and STEAM, respectively, and accurate to within 1.5% of reference data from the literature. The coefficients of variation in MDs across sites were 2.6%, 3.1% and 2.1% for PGSE, SE and STEAM, respectively, and were similar to previous studies using only PGSE. Reproducibility in MD was excellent, with mean differences in PGSE, SE and STEAM of (0.3 ± 2.3, 0.24 ± 0.95, 0.52 ± 0.58) x 10^-5  mm² /s (mean ± 1.96 SD). We show that custom sequences for cardiac DTI provide accurate, precise, repeatable and reproducible measurements. Further work in anisotropic and/or deforming phantoms is warranted.

In Vivo Super-Resolution Cardiac Diffusion Tensor MRI: A Feasibility Study

A super-resolution (SR) technique is proposed for imaging myocardial fiber architecture with cardiac magnetic resonance. Images were acquired with a motion-compensated cardiac diffusion tensor imaging (cDTI) sequence. The heart left ventricle was covered with three stacks of thick slices, in short axis, horizontal and vertical long axes orientations, respectively. The three low-resolution stacks (2 × 2 × 8 mm³) were combined into an isotropic volume (2 × 2 × 2 mm³) by a super-resolution reconstruction. For in vivo measurements, each slice was acquired during a breath-hold period. Bulk motion was corrected by optimizing a similarity metric between intensity profiles from all intersecting slices in the dataset. The benefit of the proposed approach was evaluated using a numerical heart phantom, a physical helicoidal phantom with artificial fibers, and six healthy subjects. The SR technique showed improved results compared to the native scans, in terms of image quality and cDTI metrics. In particular, the myocardial helix angle (HA) was more accurately estimated in the physical phantom (HA = 41.5° ± 1.1°, with the ground truth being 42.0°). In vivo, it resulted in a sharper rate of change of HA across the myocardial wall (−0.993°/% ± 0.007°/% against −0.873°/% ± 0.010°/%).

Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods

Simulations of cardiac electrophysiology and mechanics have been reported to be sensitive to the microstructural anisotropy of the myocardium. Consequently, a personalized representation of cardiac microstructure is a crucial component of accurate, personalized cardiac biomechanical models. In-vivo cardiac Diffusion Tensor Imaging (cDTI) is a non-invasive magnetic resonance imaging technique capable of probing the heart's microstructure. Being a rather novel technique, issues such as low resolution, signal-to noise ratio, and spatial coverage are currently limiting factors. We outline four interpolation techniques with varying degrees of data fidelity, different amounts of smoothing strength, and varying representation error to bridge the gap between the sparse in-vivo data and the model, requiring a 3D representation of microstructure across the myocardium. We provide a workflow to incorporate in-vivo myofiber orientation into a left ventricular model and demonstrate that personalized modelling based on fiber orientations from in-vivo cDTI data is feasible. The interpolation error is correlated with a trend in personalized parameters and simulated physiological parameters, strains, and ventricular twist. This trend in simulation results is consistent across material parameter settings and therefore corresponds to a bias introduced by the interpolation method. This study suggests that using a tensor interpolation approach to personalize microstructure with in-vivo cDTI data, reduces the fiber uncertainty and thereby the bias in the simulation results.

Manifold-based respiratory phase estimation enables motion and distortion correction of free-breathing cardiac diffusion tensor MRI

PURPOSE

For in vivo cardiac DTI, breathing motion and B₀ field inhomogeneities produce misalignment and geometric distortion in diffusion-weighted (DW) images acquired with conventional single-shot EPI. We propose using a dimensionality reduction method to retrospectively estimate the respiratory phase of DW images and facilitate both distortion correction (DisCo) and motion compensation.

METHODS

Free-breathing electrocardiogram-triggered whole left-ventricular cardiac DTI using a second-order motion-compensated spin echo EPI sequence and alternating directionality of phase encoding blips was performed on 11 healthy volunteers. The respiratory phase of each DW image was estimated after projecting the DW images into a 2D space with Laplacian eigenmaps. DisCo and motion compensation were applied to the respiratory sorted DW images. The results were compared against conventional breath-held T₂ half-Fourier single shot turbo spin echo. Cardiac DTI parameters including fractional anisotropy, mean diffusivity, and helix angle transmurality were compared with and without DisCo.

RESULTS

The left-ventricular geometries after DisCo and motion compensation resulted in significantly improved alignment of DW images with T₂ reference. DisCo reduced the distance between the left-ventricular contours by 13.2% ± 19.2%, P < .05 (2.0 ± 0.4 for DisCo and 2.4 ± 0.5 mm for uncorrected). DisCo DTI parameter maps yielded no significant differences (mean diffusivity: 1.55 ± 0.13 × 10^-3 mm² /s and 1.53 ± 0.13 × 10^-3 mm² /s, P = .09; fractional anisotropy: 0.375 ± 0.041 and 0.379 ± 0.045, P = .11; helix angle transmurality: 1.00% ± 0.10°/% and 0.99% ± 0.12°/%, P = .44), although the orientation of individual tensors differed.

CONCLUSION

Retrospective respiratory phase estimation with LE-based DisCo and motion compensation in free-breathing cardiac DTI resulting in significantly reduced geometric distortion and improved alignment within and across slices.

Accelerated in Vivo Cardiac Diffusion-Tensor MRI Using Residual Deep Learning-based Denoising in Participants with Obesity

Purpose

To develop and assess a residual deep learning algorithm to accelerate in vivo cardiac diffusion-tensor MRI (DT-MRI) by reducing the number of averages while preserving image quality and DT-MRI parameters.

Materials and Methods

In this prospective study, a denoising convolutional neural network (DnCNN) for DT-MRI was developed; a total of 26 participants, including 20 without obesity (body mass index [BMI] < 30 kg/m²; mean age, 28 years ± 3 [standard deviation]; 11 women) and six with obesity (BMI ≥ 30 kg/m²; mean age, 48 years ± 11; five women), were recruited from June 19, 2019, to July 29, 2020. DT-MRI data were constructed at four averages (4Av), two averages (2Av), and one average (1Av) without and with the application of the DnCNN (4Av_DnCNN, 2Av_DnCNN, 1Av_DnCNN). All data were compared against the reference DT-MRI data constructed at eight averages (8Av). Image quality, characterized by using the signal-to-noise ratio (SNR) and structural similarity index (SSIM), and the DT-MRI parameters of mean diffusivity (MD), fractional anisotropy (FA), and helix angle transmurality (HAT) were quantified.

Results

No differences were found in image quality or DT-MRI parameters between the accelerated 4Av_DnCNN DT-MRI and the reference 8Av DT-MRI data for the SNR (29.1 ± 2.7 vs 30.5 ± 2.9), SSIM (0.97 ± 0.01), MD (1.3 µm²/msec ± 0.1 vs 1.31 µm²/msec ± 0.11), FA (0.32 ± 0.05 vs 0.30 ± 0.04), or HAT (1.10°/% ± 0.13 vs 1.11°/% ± 0.09). The relationship of a higher MD and lower FA and HAT in individuals with obesity compared with individuals without obesity in reference 8Av DT-MRI measurements was retained in 4Av_DnCNN and 2Av_DnCNN DT-MRI measurements but was not retained in 4Av or 2Av DT-MRI measurements.

Conclusion

Cardiac DT-MRI can be performed at an at least twofold-accelerated rate by using DnCNN to preserve image quality and DT-MRI parameter quantification.Keywords: Adults, Cardiac, Obesity, Technology Assessment, MR-Diffusion Tensor Imaging, Heart, Tissue CharacterizationSupplemental material is available for this article.© RSNA, 2021.

Free-breathing diffusion tensor MRI of the whole left ventricle using second-order motion compensation and multitasking respiratory motion correction

PURPOSE

We aimed to develop a novel free-breathing cardiac diffusion tensor MRI (DT-MRI) approach, M2-MT-MOCO, capable of whole left ventricular coverage that leverages second-order motion compensation (M2) diffusion encoding and multitasking (MT) framework to efficiently correct for respiratory motion (MOCO).

METHODS

Imaging was performed in 16 healthy volunteers and 3 heart failure patients with symptomatic dyspnea. The healthy volunteers were scanned to compare the accuracy of interleaved multislice coverage of the entire left ventricle with a single-slice acquisition and the accuracy of the free-breathing conventional MOCO and MT-MOCO approaches with reference breath-hold DT-MRI. Mean diffusivity (MD), fractional anisotropy (FA), helix angle transmurality (HAT), and intrascan repeatability were quantified and compared.

RESULTS

In all subjects, free-breathing M2-MT-MOCO DT-MRI yielded DWI of the entire left ventricle without bulk motion-induced signal loss. No significant differences were seen in the global values of MD, FA, and HAT in the multislice and single-slice acquisitions. Furthermore, global quantification of MD, FA, and HAT were also not significantly different between the MT-MOCO and breath-hold, whereas conventional MOCO yielded significant differences in MD, FA, and HAT with MT-MOCO and FA with breath-hold. In heart failure patients, M2-MT-MOCO DT-MRI was feasible yielding higher MD, lower FA, and lower HAT compared with healthy volunteers. Substantial agreement was found between repeated scans across all subjects for MT-MOCO.

CONCLUSION

M2-MT-MOCO enables free-breathing DT-MRI of the entire left ventricle in 10 min, while preserving quantification of myocardial microstructure compared to breath-held and single-slice acquisitions and is feasible in heart failure patients.

Magnetic Resonance-Based Characterization of Myocardial Architecture

Advances in technology have made it possible to image the microstructure of the heart with diffusion-weighted magnetic resonance. The technique provides unique insights into the cellular architecture of the myocardium and how this is perturbed in a range of disease contexts. In this review, the physical basis of diffusion MRI and the challenges of implementing it in the beating heart are discussed. Cutting edge acquisition and analysis techniques, as well as the results of initial clinical studies, are reported.

Motion-compensated b-tensor encoding for in vivo cardiac diffusion-weighted imaging

Motion is a major confound in diffusion-weighted imaging (DWI) in the body, and it is a common cause of image artefacts. The effects are particularly severe in cardiac applications, due to the nonrigid cyclical deformation of the myocardium. Spin echo-based DWI commonly employs gradient moment-nulling techniques to desensitise the acquisition to velocity and acceleration, ie, nulling gradient moments up to the 2nd order (M2-nulled). However, current M2-nulled DWI scans are limited to encode diffusion along a single direction at a time. We propose a method for designing b-tensors of arbitrary shapes, including planar, spherical, prolate and oblate tensors, while nulling gradient moments up to the 2nd order and beyond. The design strategy comprises initialising the diffusion encoding gradients in two encoding blocks about the refocusing pulse, followed by appropriate scaling and rotation, which further enables nulling undesired effects of concomitant gradients. Proof-of-concept assessment of in vivo mean diffusivity (MD) was performed using linear and spherical tensor encoding (LTE and STE, respectively) in the hearts of five healthy volunteers. The results of the M2-nulled STE showed that (a) the sequence was robust to cardiac motion, and (b) MD was higher than that acquired using standard M2-nulled LTE, where diffusion-weighting was applied in three orthogonal directions, which may be attributed to the presence of restricted diffusion and microscopic diffusion anisotropy. Provided adequate signal-to-noise ratio, STE could significantly shorten estimation of MD compared with the conventional LTE approach. Importantly, our theoretical analysis and the proposed gradient waveform design may be useful in microstructure imaging beyond diffusion tensor imaging where the effects of motion must be suppressed.

An organosynthetic dynamic heart model with enhanced biomimicry guided by cardiac diffusion tensor imaging

The complex motion of the beating heart is accomplished by the spatial arrangement of contracting cardiomyocytes with varying orientation across the transmural layers, which is difficult to imitate in organic or synthetic models. High-fidelity testing of intracardiac devices requires anthropomorphic, dynamic cardiac models that represent this complex motion while maintaining the intricate anatomical structures inside the heart. In this work, we introduce a biorobotic hybrid heart that preserves organic intracardiac structures and mimics cardiac motion by replicating the cardiac myofiber architecture of the left ventricle. The heart model is composed of organic endocardial tissue from a preserved explanted heart with intact intracardiac structures and an active synthetic myocardium that drives the motion of the heart. Inspired by the helical ventricular myocardial band theory, we used diffusion tensor magnetic resonance imaging and tractography of an unraveled organic myocardial band to guide the design of individual soft robotic actuators in a synthetic myocardial band. The active soft tissue mimic was adhered to the organic endocardial tissue in a helical fashion using a custom-designed adhesive to form a flexible, conformable, and watertight organosynthetic interface. The resulting biorobotic hybrid heart simulates the contractile motion of the native heart, compared with in vivo and in silico heart models. In summary, we demonstrate a unique approach fabricating a biomimetic heart model with faithful representation of cardiac motion and endocardial tissue anatomy. These innovations represent important advances toward the unmet need for a high-fidelity in vitro cardiac simulator for preclinical testing of intracardiac devices.

Three-dimensional simultaneous brain T1 , T2 , and ADC mapping with MR Multitasking

PURPOSE

To develop a simultaneous T₁ , T₂ , and ADC mapping method that provides co-registered, distortion-free images and enables multiparametric quantification of 3D brain coverage in a clinically feasible scan time with the MR Multitasking framework.

METHODS

The T₁ /T₂ /diffusion weighting was generated by a series of T₂ preparations and diffusion preparations. The underlying multidimensional image containing 3 spatial dimensions, 1 T₁ weighting dimension, 1 T₂ -preparation duration dimension, 1 b-value dimension, and 1 diffusion direction dimension was modeled as a 5-way low-rank tensor. A separate real-time low-rank model incorporating time-resolved phase correction was also used to compensate for both inter-shot and intra-shot phase inconsistency induced by physiological motion. The proposed method was validated on both phantom and 16 healthy subjects. The quantification of T₁ /T₂ /ADC was evaluated for each case. Three post-surgery brain tumor patients were scanned for demonstration of clinical feasibility.

RESULTS

Multitasking T₁ /T₂ /ADC maps were perfectly co-registered and free from image distortion. Phantom studies showed substantial quantitative agreement ( R 2 = 0.999 ) with reference protocols for T₁ /T₂ /ADC. In vivo studies showed nonsignificant T₁ (P = .248), T₂ (P = .97), ADC (P = .328) differences among the frontal, parietal, and occipital regions. Although Multitasking showed significant differences of T₁ (P = .03), T₂ (P < .001), and ADC (P = .001) biases against the references, the mean bias estimates were small (ΔT₁ % < 5%, ΔT₂ % < 7%, ΔADC% < 5%), with all intraclass correlation coefficients greater than 0.82 indicating "excellent" agreement. Patient studies showed that Multitasking T₁ /T₂ /ADC maps were consistent with the clinical qualitative images.

CONCLUSION

The Multitasking approach simultaneously quantifies T₁ /T₂ /ADC with substantial agreement with the references and is promising for clinical applications.

Diffusion tensor cardiovascular magnetic resonance in hypertrophic cardiomyopathy: a comparison of motion-compensated spin echo and stimulated echo techniques

Objectives

Diffusion tensor cardiovascular magnetic resonance (DT-CMR) interrogates myocardial microstructure. Two frequently used in vivo DT-CMR techniques are motion-compensated spin echo (M2-SE) and stimulated echo acquisition mode (STEAM). Whilst M2-SE is strain-insensitive and signal to noise ratio efficient, STEAM has a longer diffusion time and motion compensation is unnecessary. Here we compare STEAM and M2-SE DT-CMR in patients.

Materials and methods

Biphasic DT-CMR using STEAM and M2-SE, late gadolinium imaging and pre/post gadolinium T1-mapping were performed in a mid-ventricular short-axis slice, in ten hypertrophic cardiomyopathy (HCM) patients at 3 T.

Results

Adequate quality data were obtained from all STEAM, but only 7/10 (systole) and 4/10 (diastole) M2-SE acquisitions. Compared with STEAM, M2-SE yielded higher systolic mean diffusivity (MD) (p = 0.02) and lower fractional anisotropy (FA) (p = 0.02, systole). Compared with segments with neither hypertrophy nor late gadolinium, segments with both had lower systolic FA using M2-SE (p = 0.02) and trend toward higher MD (p = 0.1). The negative correlation between FA and extracellular volume fraction was stronger with STEAM than M2-SE (r² = 0.29, p < 0.001 STEAM vs. r² = 0.10, p = 0.003 M2-SE).

Discussion

In HCM, only STEAM reliably assesses biphasic myocardial microstructure. Higher MD and lower FA from M2-SE reflect the shorter diffusion times. Further work will relate DT-CMR parameters and microstructural changes in disease.

Electronic supplementary material

The online version of this article (10.1007/s10334-019-00799-3) contains supplementary material, which is available to authorized users.

Patient specific prospective respiratory motion correction for efficient, free-breathing cardiovascular MRI

PURPOSE

To develop a patient-specific respiratory motion correction technique with true 100% acquisition efficiency.

METHODS

A short training scan consisting of a series of single heartbeat images, each acquired with a preceding diaphragmatic navigator, was performed to fit a model relating the patient-specific 3D respiratory motion of the heart-to-diaphragm position. The resulting motion model was then used to update the imaging plane in real-time to correct for translational motion based on respiratory position provided by the navigator. The method was tested in a group of 11 volunteers with 5 separate free-breathing acquisitions: FB, no motion correction; FB-TF, free breathing with a linear tracking factor; Nav Gate, navigator gating; Nav Gate-TF, navigator gating with a tracking factor; and PROCO, prospective motion correction (proposed). Each acquisition lasted for 50 accepted heartbeats, where non-gated scans had a 100% acceptance rate, and gated scans accepted data only within a ±4 mm navigator window. Retrospective image registration was used to measure residual motion and determine the effectiveness of each method.

RESULTS

PROCO reduced the range/RMSE of residual motion to 4.08 ± 1.4/0.90 ± 0.3 mm, compared to 10.78 ± 6.9/2.97 ± 2.2 mm for FB, 5.32 ± 2.92/1.24 ± 0.8 mm for FB-TF, 4.08 ± 1.6/0.93 ± 0.4 mm for Nav Gate, and 2.90 ± 1.0/0.63 ± 0.2 mm for Nav Gate-TF. Nav Gate and Nav Gate-TF reduced scan efficiency to 48.84 ± 9.31% and 54.54 ± 10.12%, respectively.

CONCLUSION

PROCO successfully limited the residual motion in single-shot imaging to the level of traditional navigator gating while maintaining 100% acquisition efficiency.

Recent Advances in Cardiac Magnetic Resonance Imaging

Cardiac magnetic resonance (CMR) imaging provides accurate anatomic information and advanced soft contrast, making it the reference standard for assessing cardiac volumes and systolic function. In this review, we summarize the recent advances in CMR sequences. New technical development has widened the use of CMR imaging beyond the simple characterization of myocardial scars and assessment of contractility. These novel CMR sequences offer comprehensive assessments of coronary plaque characterization, myocardial fiber orientation, and even metabolic activity, and they can be readily applied in clinical settings. CMR imaging is able to provide new insights into understanding the pathophysiologic process of underlying cardiac disease, and it can help physicians choose the best treatment strategies. Although several limitations, including the high cost and time-consuming process, have limited the widespread clinical use of CMR imaging so far, recent advances in software and hardware technologies have made the future more promising.

High resolution in-vivo DT-CMR using an interleaved variable density spiral STEAM sequence

PURPOSE

Diffusion tensor cardiovascular magnetic resonance (DT-CMR) has a limited spatial resolution. The purpose of this study was to demonstrate high-resolution DT-CMR using a segmented variable density spiral sequence with correction for motion, off-resonance, and T2*-related blurring.

METHODS

A single-shot stimulated echo acquisition mode (STEAM) echo-planar-imaging (EPI) DT-CMR sequence at 2.8 × 2.8 × 8 mm³ and 1.8 × 1.8 × 8 mm³ was compared to a single-shot spiral at 2.8 × 2.8 × 8 mm³ and an interleaved spiral sequence at 1.8 × 1.8 × 8 mm³ resolution in 10 healthy volunteers at peak systole and diastasis. Motion-induced phase was corrected using the densely sampled central k-space data of the spirals. STEAM field maps and T2* measures were obtained using a pair of stimulated echoes each with a double spiral readout, the first used to correct the motion-induced phase of the second.

RESULTS

The high-resolution spiral sequence produced similar DT-CMR results and quality measures to the standard-resolution sequence in both cardiac phases. Residual differences in fractional anisotropy and helix angle gradient between the resolutions could be attributed to spatial resolution and/or signal-to-noise ratio. Data quality increased after both motion-induced phase correction and off-resonance correction, and sharpness increased after T2* correction. The high-resolution EPI sequence failed to provide sufficient data quality for DT-CMR reconstruction.

CONCLUSION

In this study, an in vivo DT-CMR acquisition at 1.8 × 1.8 mm² in-plane resolution was demonstrated using a segmented spiral STEAM sequence. Motion-induced phase and off-resonance corrections are essential for high-resolution spiral DT-CMR. Segmented variable density spiral STEAM was found to be the optimal method for acquiring high-resolution DT-CMR data.

A Spectral Fiedler Field-based Contrast Platform for Imaging of Nanoparticles in Colon Tumor

The temporal and spatial patterns of nanoparticle that ferry both imaging and therapeutic agent in solid tumors is significantly influenced by target tissue movement, low spatial resolution, and inability to accurately define regions of interest (ROI) at certain tissue depths. These combine to limit and define nanoparticle untreated regions in tumors. Utilizing graph and matrix theories, the objective of this project was to develop a novel spectral Fiedler field (SFF) based-computational technology for nanoparticle mapping in tumors. The novelty of SFF lies in the utilization of the changes in the tumor topology from baseline for contrast variation assessment. Data suggest that SFF can enhance the spatiotemporal contrast compared to conventional method by 2–3 folds in tumors. Additionally, the SFF contrast is readily translatable for assessment of tumor drug distribution. Thus, our SFF computational platform has the potential for integration into devices that allow contrast and drug delivery applications.

Diffusion Tensor Cardiac Magnetic Resonance Reveals Exosomes From Cardiosphere-Derived Cells Preserve Myocardial Fiber Architecture After Myocardial Infarction

The object of the study was to reveal the fiber microstructural response with diffusion tensor cardiac magnetic resonance after intramyocardial exosomes secreted by cardiosphere-derived cells (CDCEXO) in chronic porcine myocardial infarction. Porcine with myocardial infarction underwent intramyocardial delivery of human CDCEXO and placebo in a randomized placebo-controlled study. Four weeks after injection, viability improved in the CDCEXO group, whereas myocardial fiber architecture and cardiac function were preserved. In the placebo group, fiber architecture and cardiac function declined. Myocardial regeneration by CDCEXO is not tumor-like; instead, details of tissue architecture are faithfully preserved, which may foster physiological excitation and contraction.

An in-vivo comparison of stimulated-echo and motion compensated spin-echo sequences for 3 T diffusion tensor cardiovascular magnetic resonance at multiple cardiac phases

BACKGROUND

Stimulated-echo (STEAM) and, more recently, motion-compensated spin-echo (M2-SE) techniques have been used for in-vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) assessment of cardiac microstructure. The two techniques differ in the length scales of diffusion interrogated, their signal-to-noise ratio efficiency and sensitivity to both motion and strain. Previous comparisons of the techniques have used high performance gradients at 1.5 T in a single cardiac phase. However, recent work using STEAM has demonstrated novel findings of microscopic dysfunction in cardiomyopathy patients, when DT-CMR was performed at multiple cardiac phases. We compare STEAM and M2-SE using a clinical 3 T scanner in three potentially clinically interesting cardiac phases.

METHODS

Breath hold mid-ventricular short-axis DT-CMR was performed in 15 subjects using M2-SE and STEAM at end-systole, systolic sweet-spot and diastasis. Success was defined by ≥50% of the myocardium demonstrating normal helix angles. From successful acquisitions DT-CMR results relating to tensor orientation, size and shape were compared between sequences and cardiac phases using non-parametric statistics. Strain information was obtained using cine spiral displacement encoding with stimulated echoes for comparison with DT-CMR results.

RESULTS

Acquisitions were successful in 98% of STEAM and 76% of M2-SE cases and visual helix angle (HA) map scores were higher for STEAM at the sweet-spot and diastasis. There were significant differences between sequences (p < 0.05) in mean diffusivity (MD), fractional anisotropy (FA), tensor mode, transmural HA gradient and absolute second eigenvector angle (E2A). Differences in E2A between systole and diastole correlated with peak radial strain for both sequences (p ≤ 0.01).

CONCLUSION

M2-SE and STEAM can be performed equally well at peak systole at 3 T using standard gradients, but at the sweet-spot and diastole STEAM is more reliable and image quality scores are higher. Differences in DT-CMR results are potentially due to differences in motion sensitivity and the longer diffusion time of STEAM, although the latter appears to be the dominant factor. The benefits of both sequences should be considered when planning future studies and sequence and cardiac phase specific normal ranges should be used for comparison.

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

OBJECTIVE

The purpose of this paper 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.

The impact of signal-to-noise ratio, diffusion-weighted directions and image resolution in cardiac diffusion tensor imaging - insights from the ex-vivo rat heart

BACKGROUND

Cardiac diffusion tensor imaging (DTI) is limited by scan time and signal-to-noise (SNR) restrictions. This invariably leads to a trade-off between the number of averages, diffusion-weighted directions (ND), and image resolution. Systematic evaluation of these parameters is therefore important for adoption of cardiac DTI in clinical routine where time is a key constraint.

METHODS

High quality reference DTI data were acquired in five ex-vivo rat hearts. We then retrospectively set 2 ≤ SNR ≤ 97, 7 ≤ ND ≤ 61, varied the voxel volume by up to 192-fold and investigated the impact on the accuracy and precision of commonly derived parameters.

RESULTS

For maximal scan efficiency, the accuracy and precision of the mean diffusivity is optimised when SNR is maximised at the expense of ND. With typical parameter settings used clinically, we estimate that fractional anisotropy may be overestimated by up to 13% with an uncertainty of ±30%, while the precision of the sheetlet angles may be as poor as ±31°. Although the helix angle has better precision of ±14°, the transmural range of helix angles may be under-estimated by up to 30° in apical and basal slices, due to partial volume and tapering myocardial geometry.

CONCLUSIONS

These findings inform a baseline of understanding upon which further issues inherent to in-vivo cardiac DTI, such as motion, strain and perfusion, can be considered. Furthermore, the reported bias and reproducibility provides a context in which to assess cardiac DTI biomarkers.

Analysis of phase error effects in multishot diffusion-prepared turbo spin echo imaging

BACKGROUND

To characterize the effect of phase errors on the magnitude and the phase of the diffusion-weighted (DW) signal acquired with diffusion-prepared turbo spin echo (dprep-TSE) sequences.

METHODS

Motion and eddy currents were identified as the main sources of phase errors. An analytical expression for the effect of phase errors on the acquired signal was derived and verified using Bloch simulations, phantom, and in vivo experiments.

RESULTS

Simulations and experiments showed that phase errors during the diffusion preparation cause both magnitude and phase modulation on the acquired data. When motion-induced phase error (MiPe) is accounted for (e.g., with motion-compensated diffusion encoding), the signal magnitude modulation due to the leftover eddy-current-induced phase error cannot be eliminated by the conventional phase cycling and sum-of-squares (SOS) method. By employing magnitude stabilizers, the phase-error-induced magnitude modulation, regardless of its cause, was removed but the phase modulation remained. The in vivo comparison between pulsed gradient and flow-compensated diffusion preparations showed that MiPe needed to be addressed in multi-shot dprep-TSE acquisitions employing magnitude stabilizers.

CONCLUSIONS

A comprehensive analysis of phase errors in dprep-TSE sequences showed that magnitude stabilizers are mandatory in removing the phase error induced magnitude modulation. Additionally, when multi-shot dprep-TSE is employed the inconsistent signal phase modulation across shots has to be resolved before shot-combination is performed.