Automated motion estimation for 2-D cine DENSE MRI

Automated segmentation of the left-ventricle from MRI with a fully convolutional network to investigate CTRCD in breast cancer patients

Purpose: The goal of this study was to develop a fully convolutional network (FCN) tool to automatedly segment the left-ventricular (LV) myocardium in displacement encoding with stimulated echoes MRI. The segmentation results are used for LV chamber quantification and strain analyses in breast cancer patients susceptible to cancer therapy-related cardiac dysfunction (CTRCD). Approach: A DeepLabV3+ FCN with a ResNet-101 backbone was custom-designed to conduct chamber quantification on 45 female breast cancer datasets (23 training, 11 validation, and 11 test sets). LV structural parameters and LV ejection fraction (LVEF) were measured, and myocardial strains estimated with the radial point interpolation method. Myocardial classification validation was against quantization-based ground-truth with computations of accuracy, Dice score, average perpendicular distance (APD), Hausdorff-distance, and others. Additional validations were conducted with equivalence tests and Cronbach's alpha (C - α ) intraclass correlation coefficients between the FCN and a vendor tool on chamber quantification and myocardial strain computations. Results: Myocardial classification results against ground-truth were Dice = 0.89 , APD = 2.4    mm , and accuracy = 97 % for the validation set and Dice = 0.90 , APD = 2.5    mm , and accuracy = 97 % for the test set. The confidence intervals (CI) and two one-sided t-test results of equivalence tests between the FCN and vendor-tool were CI = - 1.36 % to 2.42%, p-value < 0.001 for LVEF (58 ± 5 % versus 57 ± 6 % ), and CI = - 0.71 % to 0.63%, p-value < 0.001 for longitudinal strain (- 15 ± 2 % versus - 15 ± 3 % ). Conclusions: The validation results were found equivalent to the vendor tool-based parameter estimates, which show that accurate LV chamber quantification followed by strain analysis for CTRCD investigation can be achieved with our proposed FCN methodology.

Measuring Cardiac Dyssynchrony with DENSE (Displacement Encoding with Stimulated Echoes)-A Systematic Review

Background

In this review, we introduce the displacement encoding with stimulated echoes (DENSE) method for measuring myocardial dyssynchrony using cardiovascular magnetic resonance (CMR) imaging. We provide an overview of research findings related to DENSE from the past two decades and discuss other techniques used for dyssynchrony evaluation. Additionally, the review discusses the potential uses of DENSE in clinical practice.

Methods

A search was conducted to identify relevant articles published from January 2000 through January 2023 using the Scopus, Web of Science, PubMed and Cochrane databases. The following search term was used: (DENSE OR 'displacement encoding with stimulated echoes' OR CURE) AND (dyssynchrony* OR asynchron* OR synchron*) AND (MRI OR 'magnetic resonance' OR CMR).

Results

After removing duplicates, researchers screened a total of 174 papers. Papers that were not related to the topic, reviews, general overview articles and case reports were excluded, leaving 35 articles for further analysis. Of these, 14 studies focused on cardiac dyssynchrony estimation with DENSE, while the remaining 21 studies served as background material. The studies used various methods for presenting synchronicity, such as circumferential uniformity ratio estimate (CURE), CURE-singular value decomposition (SVD), radial uniformity ratio estimate (RURE), longitudinal uniformity ratio estimate (LURE), time to onset of shortening (TOS) and dyssynchrony index (DI). Most of the dyssynchrony studies concentrated on human heart failure, but congenital heart diseases and obesity were also evaluated. The researchers found that DENSE demonstrated high reproducibility and was found useful for detecting cardiac resynchronisation therapy (CRT) responders, optimising CRT device settings and assessing right ventricle synchronicity. In addition, studies showed a correlation between cardiac fibrosis and mechanical dyssynchrony in humans, as well as a decrease in the synchrony of contraction in the left ventricle in obese mice.

Conclusions

DENSE shows promise as a tool for quantifying myocardial function and dyssynchrony, with advantages over other cardiac dyssynchrony evaluation methods. However, there remain challenges related to DENSE due to the relatively time-consuming imaging and analysis process. Improvements in imaging and analysing technology, as well as possible artificial intelligence solutions, may help overcome these challenges and lead to more widespread clinical use of DENSE.

Compensation for respiratory motion-induced signal loss and phase corruption in free-breathing self-navigated cine DENSE using deep learning

PURPOSE

To introduce a model that describes the effects of rigid translation due to respiratory motion in displacement encoding with stimulated echoes (DENSE) and to use the model to develop a deep convolutional neural network to aid in first-order respiratory motion compensation for self-navigated free-breathing cine DENSE of the heart.

METHODS

The motion model includes conventional position shifts of magnetization and further describes the phase shift of the stimulated echo due to breathing. These image-domain effects correspond to linear and constant phase errors, respectively, in k-space. The model was validated using phantom experiments and Bloch-equation simulations and was used along with the simulation of respiratory motion to generate synthetic images with phase-shift artifacts to train a U-Net, DENSE-RESP-NET, to perform motion correction. DENSE-RESP-NET-corrected self-navigated free-breathing DENSE was evaluated in human subjects through comparisons with signal averaging, uncorrected self-navigated free-breathing DENSE, and breath-hold DENSE.

RESULTS

Phantom experiments and Bloch-equation simulations showed that breathing-induced constant phase errors in segmented DENSE leads to signal loss in magnitude images and phase corruption in phase images of the stimulated echo, and that these artifacts can be corrected using the known respiratory motion and the model. For self-navigated free-breathing DENSE where the respiratory motion is not known, DENSE-RESP-NET corrected the signal loss and phase-corruption artifacts and provided reliable strain measurements for systolic and diastolic parameters.

CONCLUSION

DENSE-RESP-NET is an effective method to correct for breathing-associated constant phase errors. DENSE-RESP-NET used in concert with self-navigation methods provides reliable free-breathing DENSE myocardial strain measurement.

A comprehensive comparison between shortest-path HARP refinement, SinMod, and DENSEanalysis processing tools applied to CSPAMM and DENSE images

We addressed comprehensively the performance of Shortest-Path HARP Refinement (SP-HR), SinMod, and DENSEanalysis using 2D slices of synthetic CSPAMM and DENSE images with realistic contrasts obtained from 3D phantoms. The three motion estimation techniques were interrogated under ideal and no-ideal conditions (with MR induced artifacts, noise, and through-plane motion), considering several resolutions and noise levels. Under noisy conditions, and for isotropic pixel sizes of 1.5 mm and 3.0 mm in CSPAMM and DENSE images respectively, the nRMSE obtained for the circumferential and radial strain components were 10.7 ± 10.8% and 25.5 ± 14.8% using SP-HR, 11.9 ± 2.5% and 29.3 ± 6.5% using SinMod, and 6.4 ± 2.0% and 18.2 ± 4.6% using DENSEanalysis. Overall, the results showed that SP-HR tends to fail for large tissue motions, whereas SinMod and DENSEanalysis gave accurate displacement and strain field estimations, being the last which performed the best.

HARP-I: A Harmonic Phase Interpolation Method for the Estimation of Motion From Tagged MR Images

We proposed a novel method called HARP-I, which enhances the estimation of motion from tagged Magnetic Resonance Imaging (MRI). The harmonic phase of the images is unwrapped and treated as noisy measurements of reference coordinates on a deformed domain, obtaining motion with high accuracy using Radial Basis Functions interpolations. Results were compared against Shortest Path HARP Refinement (SP-HR) and Sine-wave Modeling (SinMod), two harmonic image-based techniques for motion estimation from tagged images. HARP-I showed a favorable similarity with both methods under noise-free conditions, whereas a more robust performance was found in the presence of noise. Cardiac strain was better estimated using HARP-I at almost any motion level, giving strain maps with less artifacts. Additionally, HARP-I showed better temporal consistency as a new method was developed to fix phase jumps between frames. In conclusion, HARP-I showed to be a robust method for the estimation of motion and strain under ideal and non-ideal conditions.

Validation of a deep-learning semantic segmentation approach to fully automate MRI-based left-ventricular deformation analysis in cardiotoxicity

OBJECTIVE

Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DENSE) MRI sequence provide accurate estimates of cardiotoxicity damage related to chemotherapy for breast cancer. This study investigated an automated and supervised deep convolutional neural network (DCNN) model for LV chamber quantification before strain analysis in DENSE images.

METHODS

The DeepLabV3 +DCNN with three versions of ResNet-50 backbone was designed to conduct chamber quantification on 42 female breast cancer data sets. The convolutional layers in the three ResNet-50 backbones were varied as non-atrous, atrous and modified, atrous with accuracy improvements like using Laplacian of Gaussian filters. Parameters such as LV end-diastolic diameter (LVEDD) and ejection fraction (LVEF) were quantified, and myocardial strains analyzed with the Radial Point Interpolation Method (RPIM). Myocardial classification was validated with the performance metrics of accuracy, Dice, average perpendicular distance (APD) and others. Repeated measures ANOVA and intraclass correlation (ICC) with Cronbach's α (C-Alpha) tests were conducted between the three DCNNs and a vendor tool on chamber quantification and myocardial strain analysis.

RESULTS

Validation results in the same test-set for myocardial classification were accuracy = 97%, Dice = 0.92, APD = 1.2 mm with the modified ResNet-50, and accuracy = 95%, Dice = 0.90, APD = 1.7 mm with the atrous ResNet-50. The ICC results between the modified ResNet-50, atrous ResNet-50 and vendor-tool were C-Alpha = 0.97 for LVEF (55±7%, 54±7%, 54±7%, p = 0.6), and C-Alpha = 0.87 for LVEDD (4.6 ± 0.3 cm, 4.6 ± 0.3 cm, 4.6 ± 0.4 cm, p = 0.7).

CONCLUSION

Similar performance metrics and equivalent parameters obtained from comparisons between the atrous networks and vendor tool show that segmentation with the modified, atrous DCNN is applicable for automated LV chamber quantification and subsequent strain analysis in cardiotoxicity.

ADVANCES IN KNOWLEDGE

A novel deep-learning technique for segmenting DENSE images was developed and validated for LV chamber quantification and strain analysis in cardiotoxicity detection.

A deep-learning semantic segmentation approach to fully automated MRI-based left-ventricular deformation analysis in cardiotoxicity

Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DENSE) MRI sequence provide accurate estimates of cardiotoxicity damage related to breast cancer chemotherapy. This study investigated an automated LV chamber quantification tool via segmentation with a supervised deep convolutional neural network (DCNN) before strain analysis with DENSE images. Segmentation for chamber quantification analysis was conducted with a custom DeepLabV3+ DCNN with ResNet-50 backbone on 42 female breast cancer datasets (22 training-sets, eight validation-sets and 12 independent test-sets). Parameters such as LV end-diastolic diameter (LVEDD) and ejection fraction (LVEF) were quantified, and myocardial strains analyzed with the Radial Point Interpolation Method (RPIM). Myocardial classification was validated against ground-truth with sensitivity-specificity analysis, the metrics of Dice, average perpendicular distance (APD) and Hausdorff-distance. Following segmentation, validation was conducted with the Cronbach's Alpha (C-Alpha) intraclass correlation coefficient between LV chamber quantification results with DENSE and Steady State Free Precession (SSFP) acquisitions and a vendor tool-based method to segment the DENSE data, and similarly for myocardial strain analysis in the chambers. The results of myocardial classification from segmentation of the DENSE data were accuracy = 97%, Dice = 0.89 and APD = 2.4 mm in the test-set. The C-Alpha correlations from comparing chamber quantification results between the segmented DENSE and SSFP data and vendor tool-based method were 0.97 for LVEF (56 ± 7% vs 55 ± 7% vs 55 ± 6%, p = 0.6) and 0.77 for LVEDD (4.6 ± 0.4 cm vs 4.5 ± 0.3 cm vs 4.5 ± 0.3 cm, p = 0.8). The validation metrics against ground-truth and equivalent parameters obtained from the SSFP segmentation and vendor tool-based comparisons show that the DCNN approach is applicable for automated LV chamber quantification and subsequent strain analysis in cardiotoxicity.

Comprehensive enhanced methodology of an MRI-based automated left-ventricular chamber quantification algorithm and validation in chemotherapy-related cardiotoxicity

Purpose: To comprehensively outline the methodology of a fully automated, MRI motion-guided, left-ventricular (LV) chamber quantification algorithm that enhances a similar, existing semi-automated approach. Additionally, to validate the motion-guided technique in comparison to chamber quantification with a vendor tool in post-chemotherapy breast cancer patients susceptible to cardiotoxicity. Approach: LV deformation data were acquired with the displacement encoding with stimulated echoes (DENSE) sequence on N = 21 post-chemotherapy female patients and N = 21 age-matched healthy females. The new chamber quantification algorithm consists of detecting LV boundary motion via a combination of image quantization and DENSE phase-encoded displacements. LV contractility was analyzed via chamber quantification and computations of 3D strains and torsion. For validation, estimates of chamber quantification with the motion-guided algorithm on DENSE and steady-state free precession (SSFP) acquisitions, and similar estimates with an existing vendor tool on DENSE acquisitions were compared via repeated measures analysis. Patient results were compared to healthy subjects for observing abnormalities. Results: Repeated measures analysis showed similar LV ejection fractions (LVEF), 59 % ± 6 % , 58 % ± 6 % , and 58 % ± 6 % , p = 0.2 , by applying the motion-guided algorithm on DENSE and SSFP and vendor tool on DENSE acquisitions, respectively. Differences found between patients and healthy subjects included enlarged basal diameters ( 5.0 ± 0.5    cm versus 4.4 ± 0.5    cm , p < 0.01 ), torsions ( p < 0.001 ), and longitudinal strains ( p < 0.001 ), but not LVEF ( p = 0.1 ). Conclusions: Measurement similarities between new and existing tools, and between DENSE and SSFP validated the motion-guided algorithm and differences found between subpopulations demonstrate the ability to detect contractile abnormalities.

Cardiac MRI Myocardial Functional and Tissue Characterization Detects Early Cardiac Dysfunction in a Mouse Model of Chemotherapy-Induced Cardiotoxicity

BACKGROUND

Doxorubicin and doxorubicin-trastuzumab combination chemotherapy have been associated with cardiotoxicity that eventually leads to heart failure and may limit dose-effective cancer treatment. Current diagnostic strategies rely on decreased ejection fraction (EF) to diagnose cardiotoxicity.

PURPOSE

The aim of this study is to explore the potential of cardiac MR (CMR) imaging to identify imaging biomarkers in a mouse model of chemotherapy-induced cardiotoxicity.

METHODS

A cumulative dose of 25 mg/kg doxorubicin was administered over three weeks using subcutaneous pellets (n = 9, Dox). Another group (n = 9) received same dose of Dox and a total of 10 mg/kg trastuzumab (DT). Mice were imaged at baseline, 5/6 weeks and 10 weeks post-treatment on a 7T MRI system. The protocol included short-axis cine MRI covering the left ventricle (LV) and mid-ventricular short-axis tissue phase mapping (TPM), pre- and post-contrast T1 mapping, T2 mapping and Displacement Encoding with Stimulated Echoes (DENSE) strain encoded MRI. EF, peak myocardial velocities, native T1, T2, extracellular volume (ECV), and myocardial strain were quantified. N = 7 mice were sacrificed for histopathologic assessment of apoptosis at 5/6 weeks.

RESULTS

Global peak systolic longitudinal velocity was reduced at 5/6 weeks in Dox (0.6 ± 0.3 vs 0.9 ± 0.3, p = 0.02). In the Dox group, native T1 was reduced at 5/6 weeks (1.3 ± 0.2 ms vs 1.6 ± 0.2 ms, p = 0.02), and relatively normalized at week 10 (1.4 ± 0.1 ms vs 1.6 ± 0.2 ms, p > 0.99). There was no change in EF and other MRI parameters and histopathologic results demonstrated minimal apoptosis in all mice (~1-2 apoptotic cell/high power field), suggesting early-stage cardiotoxicity.

CONCLUSIONS

In a mouse model of chemotherapy-induced cardiotoxicity using doxorubicin and trastuzumab, advanced CMR shows promise in identifying treatment-related decrease in myocardial velocity and native T1 prior to the onset of cardiomyocyte apoptosis and reduction of EF.

The feasibility of a novel limited field of view spiral cine DENSE sequence to assess myocardial strain in dilated cardiomyopathy

Objective

Develop an accelerated cine displacement encoding with stimulated echoes (DENSE) cardiovascular magnetic resonance (CMR) sequence to enable clinically feasible myocardial strain evaluation in patients with dilated cardiomyopathy (DCM).

Materials and methods

A spiral cine DENSE sequence was modified by limiting the field of view in two dimensions using in-plane slice-selective pulses in the stimulated echo. This reduced breath hold duration from 20RR to 14RR intervals. Following phantom and pilot studies, the feasibility of the sequence to assess peak radial, circumferential, and longitudinal strain was tested in control subjects (n = 18) and then applied in DCM patients (n = 29).

Results

DENSE acquisition was possible in all participants. Elements of the data were not analysable in 1 control (6%) and 4 DCM r(14%) subjects due to off-resonance or susceptibility artefacts and low signal-to-noise ratio. Peak radial, circumferential, short-axis contour strain and longitudinal strain was reduced in DCM patients (p < 0.001 vs. controls) and strain measurements correlated with left ventricular ejection fraction (with circumferential strain r = − 0.79, p < 0.0001; with vertical long-axis strain r = − 0.76, p < 0.0001). All strain measurements had good inter-observer agreement (ICC > 0.80), except peak radial strain.

Discussion

We demonstrate the feasibility of CMR strain assessment in healthy controls and DCM patients using an accelerated cine DENSE technique. This may facilitate integration of strain assessment into routine CMR studies.

Electronic supplementary material

The online version of this article (10.1007/s10334-019-00735-5) contains supplementary material, which is available to authorized users.

Predictors of segmental myocardial functional recovery in patients after an acute ST-Elevation myocardial infarction

Objective

We hypothesized that Displacement Encoding with Stimulated Echoes (DENSE) and feature-tracking derived circumferential strain would provide incremental prognostic value over the extent of infarction for recovery of segmental myocardial function.

Methods

Two hundred and sixty-one patients (mean age 59 years, 73% male) underwent MRI 2 days post-ST elevation myocardial infarction (STEMI) and 241 (92%) underwent repeat imaging 6 months later.

The MRI protocol included cine, 2D-cine DENSE, T2 mapping and late enhancement.

Wall motion scoring was assessed by 2-blinded observers and adjudicated by a third. (WMS: 1=normal, 2=hypokinetic, 3=akinetic, 4=dyskinetic). WMS improvement was defined as a decrease in WMS ≥ 1, and normalization where WMS = 1 on follow-up. Segmental circumferential strain was derived utilizing DENSE and feature-tracking.

A generalized linear mixed model with random effect of subject was constructed and used to account for repeated sampling when investigating predictors of segmental myocardial improvement or normalization

Results

At baseline and follow-up, 1416 segments had evaluable data for all parameters. Circumferential strain by DENSE (p < 0.001) and feature-tracking (p < 0.001), extent of oedema (p < 0.001), infarct size (p < 0.001), and microvascular obstruction (p < 0.001) were associates of both improvement and normalization of WMS. Circumferential strain provided incremental predictive value even after accounting for infarct size, extent of oedema and microvascular obstruction, for segmental improvement (DENSE: odds ratio, 95% confidence intervals: 1.08 per −1% peak strain, 1.05–1.12, p < 0.001, feature-tracking: odds ratio, 95% confidence intervals: 1.05 per −1% peak strain, 1.03–1.07, p < 0.001) and segmental normalization (DENSE: 1.08 per −1% peak strain, 1.04–1.12, p < 0.001, feature-tracking: 1.06 per −1% peak strain, 1.04–1.08, p < 0.001).

Conclusions

Circumferential strain provides incremental prognostic value over segmental infarct size in patients post STEMI for predicting segmental improvement or normalization by wall-motion scoring.

Free-breathing cine DENSE MRI using phase cycling with matchmaking and stimulated-echo image-based navigators

PURPOSE

This study aimed to develop a self-navigated method for free-breathing spiral cine displacement encoding with stimulated echoes (DENSE), a myocardial strain imaging technique that uses phase-cycling for artifact suppression. The method needed to address 2 consequences of motion for DENSE: striping artifacts from incomplete suppression of the T1 -relaxation echo and blurring.

METHODS

The method identifies phase-cycled spiral interleaves at matched respiratory phases by minimizing the residual signal due to T1 relaxation after phase-cycling subtraction. Next, the method reconstructs image-based navigators from matched phase-cycled interleaves that are comprised of the stimulated echo (ste-iNAVs). Ste-iNAVs are used for motion estimation and compensation of k-space data. The method was demonstrated in phantoms and compared to diaphragm-based navigator (dNAV) and conventional iNAV (c-iNAV) methods for the reconstruction of free-breathing volunteer data sets (N = 10).

RESULTS

Phantom experiments demonstrated that the proposed method removes striping artifacts and blurring due to motion. Volunteer results showed that respiratory motion measured by ste-iNAVs was better correlated than c-iNAVs to dNAV data (R2  = 0.82 ± 0.03 vs. 0.70 ± 0.05, P < 0.05). Match-making reconstructions of free-breathing data sets achieved lower residual T1 -relaxation echo energy (1.04 ± 0.01 vs. 1.18 ± 0.04 for dNAV and 1.18 ± 0.03 for c-iNAV, P < 0.05), higher apparent SNR (11.93 ± 1.05 vs. 10.68 ± 1.06 for dNAV and 10.66 ± 0.99 for c-iNAV, P < 0.05), and better phase quality (0.147 ± 0.012 vs. 0.166 ± 0.017 for dNAV, P = 0.06, and 0.168 ± 0.015 for c-iNAV, P < 0.05) than dNAV and c-iNAV methods.

CONCLUSION

For free-breathing cine DENSE, the proposed method addresses both types of breathing-induced artifacts and provides better quality images than conventional dNAV and iNAV methods.

Introduction to a mechanism for automated myocardium boundary detection with displacement encoding with stimulated echoes (DENSE)

Objective:

Displacement ENcoding with Stimulated Echoes (DENSE) is an MRI technique developed to encode phase related to myocardial tissue displacements, and the displacement information directly applied towards detecting left-ventricular (LV) myocardial motion during the cardiac cycle. The purpose of this study is to present a novel, three-dimensional (3D) DENSE displacement-based and magnitude image quantization-based, semi-automated detection technique for myocardial wall motion, whose boundaries are used for rapid and automated computation of 3D myocardial strain.

Methods:

The architecture of this boundary detection algorithm is primarily based on pixelwise spatiotemporal increments in LV tissue displacements during the cardiac cycle and further reinforced by radially searching for pixel-based image gradients in multithreshold quantized magnitude images. This spatiotemporal edge detection methodology was applied to all LV partitions and their subsequent timeframes that lead to full 3D LV reconstructions. It was followed by quantifications of 3D chamber dimensions and myocardial strains, whose rapid computation was the primary motivation behind developing this algorithm. A pre-existing two-dimensional (2D) semi-automated contouring technique was used in parallel to validate the accuracy of the algorithm and both methods tested on DENSE data acquired in (N = 14) healthy subjects. Chamber quantifications between methods were compared using paired t-tests and Bland–Altman analysis established regional strain agreements.

Results:

There were no significant differences in the results of chamber quantifications between the 3D semi-automated and existing 2D boundary detection techniques. This included comparisons of ejection fractions, which were 0.62 ± 0.04 vs 0.60 ± 0.06 (p = 0.23) for apical, 0.60 ± 0.04 vs 0.59 ± 0.05 (p = 0.76) for midventricular and 0.56 ± 0.04 vs 0.58 ± 0.05 (p = 0.07) for basal segments, that were quantified using the 3D semi-automated and 2D pre-existing methodologies, respectively. Bland–Altman agreement between regional strains generated biases of 0.01 ± 0.06, –0.01 ± 0.01 and 0.0 ± 0.06 for the radial, circumferential and longitudinal directions, respectively.

Conclusion:

A new, 3D semi-automated methodology for contouring the entire LV and rapidly generating chamber quantifications and regional strains is presented that was validated in relation to an existing 2D contouring technique.

Advances in knowledge:

This study introduced a scientific tool for rapid, semi-automated generation of clinical information regarding shape and function in the 3D LV.

Magnetic Resonance Imaging of Myocardial Strain After Acute ST-Segment-Elevation Myocardial Infarction: A Systematic Review

The purpose of this systematic review is to provide a clinically relevant, disease-based perspective on myocardial strain imaging in patients with acute myocardial infarction or stable ischemic heart disease. Cardiac magnetic resonance imaging uniquely integrates myocardial function with pathology. Therefore, this review focuses on strain imaging with cardiac magnetic resonance. We have specifically considered the relationships between left ventricular (LV) strain, infarct pathologies, and their associations with prognosis. A comprehensive literature review was conducted in accordance with the PRISMA guidelines. Publications were identified that (1) described the relationship between strain and infarct pathologies, (2) assessed the relationship between strain and subsequent LV outcomes, and (3) assessed the relationship between strain and health outcomes. In patients with acute myocardial infarction, circumferential strain predicts the recovery of LV systolic function in the longer term. The prognostic value of longitudinal strain is less certain. Strain differentiates between infarcted versus noninfarcted myocardium, even in patients with stable ischemic heart disease with preserved LV ejection fraction. Strain recovery is impaired in infarcted segments with intramyocardial hemorrhage or microvascular obstruction. There are practical limitations to measuring strain with cardiac magnetic resonance in the acute setting, and knowledge gaps, including the lack of data showing incremental value in clinical practice. Critically, studies of cardiac magnetic resonance strain imaging in patients with ischemic heart disease have been limited by sample size and design. Strain imaging has potential as a tool to assess for early or subclinical changes in LV function, and strain is now being included as a surrogate measure of outcome in therapeutic trials.

Imaging left-ventricular mechanical activation in heart failure patients using cine DENSE MRI: Validation and implications for cardiac resynchronization therapy

PURPOSE

To image late mechanical activation and identify effective left-ventricular (LV) pacing sites for cardiac resynchronization therapy (CRT). There is variability in defining mechanical activation time, with some studies using the time to peak strain (TPS) and some using the time to the onset of circumferential shortening (TOS). We developed improved methods for imaging mechanical activation and evaluated them in heart failure (HF) patients undergoing CRT.

MATERIALS AND METHODS

We applied active contours to cine displacement encoding with stimulated echoes (DENSE) strain images to detect TOS. Six healthy volunteers underwent magnetic resonance imaging (MRI) at 1.5T, and 50 patients underwent pre-CRT MRI (strain, scar, volumes) and echocardiography, assessment of the electrical activation time (Q-LV) at the LV pacing site, and echocardiography assessment of LV reverse remodeling 6 months after CRT. TPS at the LV pacing site was also measured by DENSE.

RESULTS

The latest TOS was greater in HF patients vs. healthy subjects (112 ± 28 msec vs. 61 ± 7 msec, P < 0.01). The correlation between TOS and Q-LV was strong (r > 0.75; P < 0.001) and better than between TPS and Q-LV (r < 0.62; P ≥ 0.006). Twenty-three of 50 patients had the latest activating segment in a region other than the mid-ventricular lateral wall, the most common site for the CRT LV lead. Using a multivariable model, TOS/QRS was significantly associated with LV reverse remodeling even after adjustment for overall dyssynchrony and scar (P < 0.05), whereas TPS was not (P = 0.49).

CONCLUSION

Late activation by cine DENSE TOS analysis is associated with improved LV reverse remodeling with CRT and deserves further study as a tool to achieve optimal LV lead placement in CRT.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:887-896.

Reproducibility of cine displacement encoding with stimulated echoes (DENSE) in human subjects

OBJECTIVES

To test the hypothesis that two-dimensional (2D) displacement encoding via stimulated echoes (DENSE) is a reproducible technique for the depiction of segmental myocardial motion in human subjects.

MATERIALS AND METHODS

Following the approval of the institutional review board (IRB), 17 healthy volunteers without documented history of cardiovascular disease were recruited. For each participant, 2D DENSE were performed twice (at different days) and the images were obtained at basal, midventricular and apical levels of the left ventricle (LV) with a short-axis view. The radial thickening strain (Err), circumferential strain (Ecc), twist and torsion were calculated. The intra-, inter-observer and inter-study variations of DENSE-derived myocardial motion indices were evaluated using coefficient of variation (CoV) and intra-class correlation coefficient (ICC).

RESULTS

In total, there are 272 pairs of myocardial segments (data points) for comparison. There is good intra- and inter-observer reproducibility for all DENSE-derived measures in 17 participants. There is good inter-study reproducibility for peak Ecc (CoV=19.64%, ICC=0.8896, p<0.001), twist (CoV=33.11%, ICC=0.9135, p<0.001) and torsion (CoV=13.96%, ICC=0.8684, p<0.001). There is moderate inter-study reproducibility for Err (CoV=38.89%, ICC=0.7022, p<0.001).

CONCLUSION

DENSE is a reproducible technique for characterizing LV regional systolic myocardial motion on a per-segment basis in healthy volunteers.

Accelerated two-dimensional cine DENSE cardiovascular magnetic resonance using compressed sensing and parallel imaging

BACKGROUND

Cine Displacement Encoding with Stimulated Echoes (DENSE) provides accurate quantitative imaging of cardiac mechanics with rapid displacement and strain analysis; however, image acquisition times are relatively long. Compressed sensing (CS) with parallel imaging (PI) can generally provide high-quality images recovered from data sampled below the Nyquist rate. The purposes of the present study were to develop CS-PI-accelerated acquisition and reconstruction methods for cine DENSE, to assess their accuracy for cardiac imaging using retrospective undersampling, and to demonstrate their feasibility for prospectively-accelerated 2D cine DENSE imaging in a single breathhold.

METHODS

An accelerated cine DENSE sequence with variable-density spiral k-space sampling and golden angle rotations through time was implemented. A CS method, Block LOw-rank Sparsity with Motion-guidance (BLOSM), was combined with sensitivity encoding (SENSE) for the reconstruction of under-sampled multi-coil spiral data. Seven healthy volunteers and 7 patients underwent 2D cine DENSE imaging with fully-sampled acquisitions (14-26 heartbeats in duration) and with prospectively rate-2 and rate-4 accelerated acquisitions (14 and 8 heartbeats in duration). Retrospectively- and prospectively-accelerated data were reconstructed using BLOSM-SENSE and SENSE. Image quality of retrospectively-undersampled data was quantified using the relative root mean square error (rRMSE). Myocardial displacement and circumferential strain were computed for functional assessment, and linear correlation and Bland-Altman analyses were used to compare accelerated acquisitions to fully-sampled reference datasets.

RESULTS

For retrospectively-undersampled data, BLOSM-SENSE provided similar or lower rRMSE at rate-2 and lower rRMSE at rate-4 acceleration compared to SENSE (p < 0.05, ANOVA). Similarly, for retrospective undersampling, BLOSM-SENSE provided similar or better correlation with reference displacement and strain data at rate-2 and better correlation at rate-4 acceleration compared to SENSE. Bland-Altman analyses showed similar or better agreement for displacement and strain data at rate-2 and better agreement at rate-4 using BLOSM-SENSE compared to SENSE for retrospectively-undersampled data. Rate-2 and rate-4 prospectively-accelerated cine DENSE provided good image quality and expected values of displacement and strain.

CONCLUSIONS

BLOSM-SENSE-accelerated spiral cine DENSE imaging with 2D displacement encoding can be acquired in a single breathhold of 8-14 heartbeats with high image quality and accurate assessment of myocardial displacement and circumferential strain.

Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics

BACKGROUND

Cardiovascular magnetic resonance using displacement encoding with stimulated echoes (DENSE) is capable of assessing advanced measures of cardiac mechanics such as strain and torsion. A potential hurdle to widespread clinical adoption of DENSE is the time required to manually segment the myocardium during post-processing of the images. To overcome this hurdle, we proposed a radical approach in which only three contours per image slice are required for post-processing (instead of the typical 30-40 contours per image slice). We hypothesized that peak left ventricular circumferential, longitudinal and radial strains and torsion could be accurately quantified using this simplified analysis.

METHODS AND RESULTS

We tested our hypothesis on a large multi-institutional dataset consisting of 541 DENSE image slices from 135 mice and 234 DENSE image slices from 62 humans. We compared measures of cardiac mechanics derived from the simplified post-processing to those derived from original post-processing utilizing the full set of 30-40 manually-defined contours per image slice. Accuracy was assessed with Bland-Altman limits of agreement and summarized with a modified coefficient of variation. The simplified technique showed high accuracy with all coefficients of variation less than 10% in humans and 6% in mice. The accuracy of the simplified technique was also superior to two previously published semi-automated analysis techniques for DENSE post-processing.

CONCLUSIONS

Accurate measures of cardiac mechanics can be derived from DENSE cardiac magnetic resonance in both humans and mice using a simplified technique to reduce post-processing time by approximately 94%. These findings demonstrate that quantifying cardiac mechanics from DENSE data is simple enough to be integrated into the clinical workflow.

Interrogation of living myocardium in multiple static deformation states with diffusion tensor and diffusion spectrum imaging

Diffusion tensor magnetic resonance imaging (MRI) reveals valuable insights into tissue histo-anatomy and microstructure, and has steadily gained traction in the cardiac community. Its wider use in small animal cardiac imaging in vivo has been constrained by its extreme sensitivity to motion, exaggerated by the high heart rates usually seen in rodents. Imaging of the isolated heart eliminates respiratory motion and, if conducted on arrested hearts, cardiac pulsation. This serves as an important intermediate step for basic and translational studies. However, investigating the micro-structural basis of cardiac deformation in the same heart requires observations in different deformation states.

Here, we illustrate the imaging of isolated rat hearts in three mechanical states mimicking diastole (cardioplegic arrest), left-ventricular (LV) volume overload (cardioplegic arrest plus LV balloon inflation), and peak systole (lithium-induced contracture). An optimised MRI-compatible Langendorff perfusion setup with the radio-frequency (RF) coil integrated into the wet chamber was developed for use in a 9.4T horizontal bore scanner. Signal-to-noise ratio improved significantly, by 75% compared to a previous design with external RF coil, and stability tests showed no significant changes in mean T₁, T₂ or LV wall thickness over a 170 min period. In contracture, we observed a significant reduction in mean fractional anisotropy from 0.32 ± 0.02 to 0.28 ± 0.02, as well as a significant rightward shift in helix angles with a decrease in the proportion of left-handed fibres, as referring to the locally prevailing cell orientation in the heart, from 24.9% to 23.3%, and an increase in the proportion of right-handed fibres from 25.5% to 28.4%. LV overload, in contrast, gave rise to a decrease in the proportion of left-handed fibres from 24.9% to 21.4% and an increase in the proportion of right-handed fibres from 25.5% to 26.0%. The modified perfusion and coil setup offers better performance and control over cardiac contraction states.

We subsequently performed high-resolution diffusion spectrum imaging (DSI) and 3D whole heart fibre tracking in fixed ex vivo rat hearts in slack state and contracture. As a model-free method, DSI augmented the measurements of water diffusion by also informing on multiple intra-voxel diffusion orientations and non-Gaussian diffusion. This enabled us to identify the transition from right- to left-handed fibres from the subendocardium to the subepicardium, as well as voxels in apical regions that were traversed by multiple fibres. We observed that both the mean generalised fractional anisotropy and mean kurtosis were lower in hearts in contracture compared to the slack state, by 23% and 9.3%, respectively. While its heavy acquisition burden currently limits the application of DSI in vivo, ongoing work in acceleration techniques may enable its use in live animals and patients. This would provide access to the as yet unexplored dimension of non-Gaussian diffusion that could serve as a highly sensitive marker of cardiac micro-structural integrity.

Accurate high-resolution measurements of 3-D tissue dynamics with registration-enhanced displacement encoded MRI

Displacement fields are important to analyze deformation, which is associated with functional and material tissue properties often used as indicators of health. Magnetic resonance imaging (MRI) techniques like DENSE and image registration methods like Hyperelastic Warping have been used to produce pixel-level deformation fields that are desirable in high-resolution analysis. However, DENSE can be complicated by challenges associated with image phase unwrapping, in particular offset determination. On the other hand, Hyperelastic Warping can be hampered by low local image contrast. The current work proposes a novel approach for measuring tissue displacement with both DENSE and Hyperelastic Warping, incorporating physically accurate displacements obtained by the latter to improve phase characterization in DENSE. The validity of the proposed technique is demonstrated using numerical and physical phantoms, and in vivo small animal cardiac MRI.