Spiral tissue phase velocity mapping in a breath-hold with non-cartesian SENSE

HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis

Synthetic digital twins based on medical data accelerate the acquisition, labelling and decision making procedure in digital healthcare. A core part of digital healthcare twins is model-based data synthesis, which permits the generation of realistic medical signals without requiring to cope with the modelling complexity of anatomical and biochemical phenomena producing them in reality. Unfortunately, algorithms for cardiac data synthesis have been so far scarcely studied in the literature. An important imaging modality in the cardiac examination is three-directional CINE multi-slice myocardial velocity mapping (3Dir MVM), which provides a quantitative assessment of cardiac motion in three orthogonal directions of the left ventricle. The long acquisition time and complex acquisition produce make it more urgent to produce synthetic digital twins of this imaging modality. In this study, we propose a hybrid deep learning (HDL) network, especially for synthetic 3Dir MVM data. Our algorithm is featured by a hybrid UNet and a Generative Adversarial Network with a foreground-background generation scheme. The experimental results show that from temporally down-sampled magnitude CINE images (six times), our proposed algorithm can still successfully synthesise high temporal resolution 3Dir MVM CMR data (PSNR=42.32) with precise left ventricle segmentation (DICE=0.92). These performance scores indicate that our proposed HDL algorithm can be implemented in real-world digital twins for myocardial velocity mapping data simulation. To the best of our knowledge, this work is the first one investigating digital twins of the 3Dir MVM CMR, which has shown great potential for improving the efficiency of clinical studies via synthesised cardiac data.

Fast and Automated Segmentation for the Three-Directional Multi-Slice Cine Myocardial Velocity Mapping

Three-directional cine multi-slice left ventricular myocardial velocity mapping (3Dir MVM) is a cardiac magnetic resonance (CMR) technique that allows the assessment of cardiac motion in three orthogonal directions. Accurate and reproducible delineation of the myocardium is crucial for accurate analysis of peak systolic and diastolic myocardial velocities. In addition to the conventionally available magnitude CMR data, 3Dir MVM also provides three orthogonal phase velocity mapping datasets, which are used to generate velocity maps. These velocity maps may also be used to facilitate and improve the myocardial delineation. Based on the success of deep learning in medical image processing, we propose a novel fast and automated framework that improves the standard U-Net-based methods on these CMR multi-channel data (magnitude and phase velocity mapping) by cross-channel fusion with an attention module and the shape information-based post-processing to achieve accurate delineation of both epicardial and endocardial contours. To evaluate the results, we employ the widely used Dice Scores and the quantification of myocardial longitudinal peak velocities. Our proposed network trained with multi-channel data shows superior performance compared to standard U-Net-based networks trained on single-channel data. The obtained results are promising and provide compelling evidence for the design and application of our multi-channel image analysis of the 3Dir MVM CMR data.

Accelerated magnetic resonance imaging tissue phase mapping of the rat myocardium using compressed sensing with iterative soft-thresholding

Introduction

Tissue Phase Mapping (TPM) MRI can accurately measure regional myocardial velocities and strain. The lengthy data acquisition, however, renders TPM prone to errors due to variations in physiological parameters, and reduces data yield and experimental throughput. The purpose of the present study is to examine the quality of functional measures (velocity and strain) obtained by highly undersampled TPM data using compressed sensing reconstruction in infarcted and non-infarcted rat hearts.

Methods

Three fully sampled left-ventricular short-axis TPM slices were acquired from 5 non-infarcted rat hearts and 12 infarcted rat hearts in vivo. The datasets were used to generate retrospectively (simulated) undersampled TPM datasets, with undersampling factors of 2, 4, 8 and 16. Myocardial velocities and circumferential strain were calculated from all datasets. The error introduced from undersampling was then measured and compared to the fully sampled data in order to validate the method. Finally, prospectively undersampled data were acquired and compared to the fully sampled datasets.

Results

Bland Altman analysis of the retrospectively undersampled and fully sampled data revealed narrow limits of agreement and little bias (global radial velocity: median bias = -0.01 cm/s, 95% limits of agreement = [-0.16, 0.20] cm/s, global circumferential strain: median bias = -0.01%strain, 95% limits of agreement = [-0.43, 0.51] %strain, all for 4x undersampled data at the mid-ventricular level). The prospectively undersampled TPM datasets successfully demonstrated the feasibility of method implementation.

Conclusion

Through compressed sensing reconstruction, highly undersampled TPM data can be used to accurately measure the velocity and strain of the infarcted and non-infarcted rat myocardium in vivo, thereby increasing experimental throughput and simultaneously reducing error introduced by physiological variations over time.

Impact of age and cardiac disease on regional left and right ventricular myocardial motion in healthy controls and patients with repaired tetralogy of fallot

The assessment of both left (LV) and right ventricular (RV) motion is important to understand the impact of heart disease on cardiac function. The MRI technique of tissue phase mapping (TPM) allows for the quantification of regional biventricular three-directional myocardial velocities. The goal of this study was to establish normal LV and RV velocity parameters across a wide range of pediatric to adult ages and to investigate the feasibility of TPM for detecting impaired regional biventricular function in patients with repaired tetralogy of Fallot (TOF). Thirty-six healthy controls (age = 1-75 years) and 12 TOF patients (age = 5-23 years) underwent cardiac MRI including TPM in short-axis locations (base, mid, apex). For ten adults, a second TPM scan was used to assess test-retest reproducibility. Data analysis included the calculation of biventricular radial, circumferential, and long-axis velocity components, quantification of systolic and diastolic peak velocities in an extended 16 + 10 LV + RV segment model, and assessment of inter-ventricular dyssynchrony. Biventricular velocities showed good test-retest reproducibility (mean bias ≤ 0.23 cm/s). Diastolic radial and long-axis peak velocities for LV and RV were significantly reduced in adults compared to children (19-61%, p < 0.001-0.02). In TOF patients, TPM identified significantly reduced systolic and diastolic LV and RV long-axis peak velocities (20-50%, p < 0.001-0.05) compared to age-matched controls. In conclusion, tissue phase mapping enables comprehensive analysis of global and regional biventricular myocardial motion. Changes in myocardial velocities associated with age underline the importance of age-matched controls. This pilot study in TOF patients shows the feasibility to detect regionally abnormal LV and RV motion.

Typical readout durations in spiral cine DENSE yield blurred images and underestimate cardiac strains at both 3.0 T and 1.5 T

INTRODUCTION

Displacement encoding with stimulated echoes (DENSE) is a phase contrast technique that encodes tissue displacement into phase images, which are typically processed into measures of cardiac function such as strains. For improved signal to noise ratio and spatiotemporal resolution, DENSE is often acquired with a spiral readout using an 11.1 ms readout duration. However, long spiral readout durations are prone to blurring due to common phenomena such as off-resonance and T2* decay, which may alter the resulting quantifications of strain. We hypothesized that longer readout durations would reduce image quality and underestimate cardiac strains at both 3.0 T and 1.5 T and that using short readout durations could overcome these limitations.

MATERIAL AND METHODS

Computational simulations were performed to investigate the relationship between off-resonance and T2* decay, the spiral cine DENSE readout duration, and measured radial and circumferential strain. Five healthy participants subsequently underwent 2D spiral cine DENSE at both 3.0 T and 1.5 T with several different readout durations 11.1 ms and shorter. Pearson correlations were used to assess the relationship between cardiac strains and the spiral readout duration.

RESULTS

Simulations demonstrated that long readout durations combined with off-resonance and T2* decay yield blurred images and underestimate strains. With the typical 11.1 ms DENSE readout, blurring was present in the anterior and lateral left ventricular segments of participants and was markedly improved with shorter readout durations. Radial and circumferential strains from those segments were significantly correlated with the readout duration. Compared to the 1.9 ms readout, the 11.1 ms readout underestimated radial and circumferential strains in those segments at both field strengths by up to 19.6% and 1.5% (absolute), or 42% and 7% (relative), respectively.

CONCLUSIONS

Blurring is present in spiral cine DENSE images acquired at both 3.0 T and 1.5 T using the typical 11.1 ms readout duration, which yielded substantially reduced radial strains and mildly reduced circumferential strains. Clinical studies using spiral cine DENSE should consider these limitations, while future technical advances may need to leverage accelerated techniques to improve the robustness and accuracy of the DENSE acquisition rather than focusing solely on reduced acquisition time.

Segmental biventricular analysis of myocardial function using high temporal and spatial resolution tissue phase mapping

OBJECTIVE

Myocardial dysfunction of the right ventricle (RV) is an important indicator of RV diseases, e.g. RV infarction or pulmonary hypertension. Tissue phase mapping (TPM) has been widely used to determine function of the left ventricle (LV) by analyzing myocardial velocities. The analysis of RV motion is more complicated due to the different geometry and smaller wall thickness. The aim of this work was to adapt and optimize TPM to the demands of the RV.

MATERIALS AND METHODS

TPM measurements were acquired in 25 healthy volunteers using a velocity-encoded phase-contrast sequence and kt-accelerated parallel imaging in combination with optimized navigator strategy and blood saturation. Post processing was extended by a 10-segment RV model and a detailed biventricular analysis of myocardial velocities was performed.

RESULTS

High spatio-temporal resolution (1.0 × 1.0 × 6 mm³, 21.3 ms) and the optimized blood saturation enabled good delineation of the RV and its velocities. Global and segmental velocities, as well as time to peak velocities showed significant differences between the LV and RV. Furthermore, complex timing of the RV could be demonstrated by segmental time to peak analysis.

CONCLUSION

High spatio-temporal resolution TPM enables a detailed biventricular analysis of myocardial motion and might provide a reliable tool for description and detection of diseases affecting left and right ventricular function.

Reproducibility and observer variability of tissue phase mapping for the quantification of regional myocardial velocities

To systematically investigate the reproducibility of global and segmental left ventricular (LV) velocities derived from tissue phase mapping (TPM). Breath held and ECG synchronized TPM data (spatial/temporal resolution = 2 × 2 mm(2)/20.8 ms) were acquired in 18 healthy volunteers. To analyze scan-rescan variability, TPM was repeated in all subjects during a second visit separated by 16 ± 5 days. Data analysis included LV segmentation, and quantification of global and regional (AHA 16-segment modal) metrics of LV function [velocity-time curves, systolic and diastolic peak and time-to-peak (TTP) velocities] for radial (Vr), long-axis (Vz) and circumferential (VΦ) LV velocities. Mean velocity time curves in basal, mid-ventricular, and apical locations showed highly similar LV motion patterns for all three velocity components (Vr, VΦ, Vz) for scan and rescan. No significant differences for both systolic and diastolic peak and TTP myocardial velocities were observed. Segmental analysis revealed similar regional peak Vr and Vz during both systole and diastole except for three LV segments (p = 0.045, p = 0.033, and p = 0.009). Excellent (p < 0.001) correlations between scans and rescan for peak Vr (R(2) = 0.92), peak Vz (R(2) = 0.90), radial TTP (R(2) = 0.91) and long-axis TTP (R(2) = 0.88) confirmed good agreement. Bland-Altman analysis demonstrated excellent intra-observer and good inter-observer analysis agreement but increased variability for long axis peak velocities. TPM based analysis of global and regional myocardial velocities can be performed with good reproducibility. Robustness of regional quantification of long-axis velocities was limited but spatial velocity distributions across the LV could reliably be replicated.

On the influence of respiratory motion in radial tissue phase mapping cardiac MRI

PURPOSE

To investigate the impact of respiratory motion on radial tissue phase mapping (TPM) measurements, and to improve image quality and scan efficiency without compromising velocity fidelity by increasing the respiratory acceptance window with and without motion correction.

MATERIALS AND METHODS

A radial golden angle TPM sequence was measured in 10 healthy volunteers in three short axis slices at 3T. Ungated ( CFREE), self-gated with a single acceptance window ( CREF), motion-corrected averaging using all ( CMCall), or selected ( CMC) data reconstructions were compared by means of various image quality measures and resulting velocities.

RESULTS

Using all data ( CFREE) resulted in significantly higher perceived signal-to-noise ratio (SNR) (P < 0.001), but significantly reduced sharpness (P < 0.001) and contrast (P = 0.02), when compared to CREF. Coefficient of variation (CV) and perceived sharpness were not significantly different (P > 0.05). With motion-correction, perceived sharpness could be significantly improved ( CMC: P = 0.002; CMCall: P = 0.002) in comparison to CFREE. Velocity peaks of CFREE were significantly reduced compared to CREF (all peaks: P < 0.001; except the longitudinal "E" peak: P = 0.03). The peak velocities in CMC and CMCall were not significantly different from CREF (all peaks: P > 0.08; except longitudinal "E"/"A" peaks: P > 0.01).

CONCLUSION

Free-breathing reconstruction results in good perceived image sharpness and velocity information with slightly, but significantly, reduced peak velocities. For achieving velocities and image quality comparable to data from a single acceptance window, but higher gating efficiency, selected motion-corrected TPM (CMC) can be applied. J. Magn. Reson. Imaging 2016;44:1218-1228.

Analyzing myocardial torsion based on tissue phase mapping cardiovascular magnetic resonance

BACKGROUND

The purpose of this work is to analyze differences in left ventricular torsion between volunteers and patients with non-ischemic cardiomyopathy based on tissue phase mapping (TPM) cardiovascular magnetic resonance (CMR).

METHODS

TPM was performed on 27 patients with non-ischemic cardiomyopathy and 14 normal volunteers. Patients underwent a standard CMR including late gadolinium enhancement (LGE) for the assessment of myocardial scar and ECG-gated cine CMR for global cardiac function. TPM was acquired in short-axis orientation at base, mid, and apex for all subjects. After evaluation by experienced observers, the patients were divided in subgroups according to the presence or absence of LGE (LGE+/LGE-), local wall motion abnormalities (WM+/WM-), and having a preserved (≥50%) or reduced (<50%) ejection fraction (EF+/EF-). TPM data was semi-automatically segmented and global LV torsion was computed for each cardiac time frame for endocardial and epicardial layers, and for the entire myocardium.

RESULTS

Maximum myocardial torsion was significantly lower for patients with reduced EF compared to controls (0.21 ± 0.15°/mm vs. 0.36 ± 0.11°/mm, p = 0.018), but also for patients with wall motion abnormalities (0.21 ± 0.13°/mm vs. 0.36 ± 0.11°/mm, p = 0.004). Global myocardial torsion showed a positive correlation (r = 0.54, p < 0.001) with EF. Moreover, endocardial torsion was significantly higher than epicardial torsion for EF+ subjects (0.56 ± 0.33°/mm vs. 0.34 ± 0.18°/mm, p = 0.039) and for volunteers (0.46 ± 0.16°/mm vs. 0.30 ± 0.09°/mm, p = 0.004). The difference in maximum torsion between endo- and epicardial layers was positively correlated with EF (r = 0.47, p = 0.002) and age (r = 0.37, p = 0.016) for all subjects.

CONCLUSIONS

TPM can be used to detect significant differences in LV torsion in patients with reduced EF and in the presence of local wall motion abnormalities. We were able to quantify torsion differences between the endocardium and epicardium, which vary between patient subgroups and are correlated to age and EF.

Rapid breath-hold assessment of myocardial velocities using spiral UNFOLD-ed SENSE tissue phase mapping

PURPOSE

To develop and validate a rapid breath-hold tissue phase mapping (TPM) sequence.

MATERIALS AND METHODS

The sequence was based on an efficient uniform density spiral acquisition, combined with data acceleration. A novel acquisition and reconstruction strategy enabled combination of UNFOLD (2×) and SENSE (3×): UNFOLD-ed SENSE. The sequence was retrospectively cardiac-gated, and a graphics processing unit (GPU) was used for rapid "online" reconstruction. The optimal UNFOLD parameters for the data were calculated using an in silico model. The technique was validated on a 1.5T MR scanner in 15 patients with known aortic valve disease, against a respiratory self-navigated free-breathing TPM technique. Quantitative image quality measures (velocity-to-noise and edge sharpness) were made as well as calculation of longitudinal, radial, and tangential myocardial velocities in the left ventricle.

RESULTS

The proposed breath-hold TPM data took eight heartbeats to acquire. The breath-hold TPM images had significantly higher edge sharpness (P = 0.0014) than the self-navigated TPM images, but with significantly lower velocity-to-noise ratio (P < 0.0001). There was excellent agreement (r > 0.94) in the longitudinal, radial, and tangential velocities between the self-navigated data and the proposed breath-hold TPM sequence.

CONCLUSION

We demonstrate the feasibility of using spiral UNFOLD-ed SENSE to measure myocardial velocities using a rapid breath-hold spiral TPM sequence. This novel technique might enable accurate measurement of myocardial velocities, in a short scan time, which is especially important in a busy clinical workflow. J. MAGN. RESON. IMAGING 2016;44:1003-1009.

Left ventricular diastolic dysfunction in pulmonary hypertension predicts functional capacity and clinical worsening: a tissue phase mapping study

BACKGROUND

The function of the right and left ventricles is intimately related through a shared septum and pericardium. Therefore, right ventricular (RV) disease in pulmonary hypertension (PH) can result in abnormal left ventricular (LV) myocardial mechanics. To assess this, we implemented novel cardiovascular magnetic resonance (CMR) tissue phase mapping (TPM) to assess radial, longitudinal and tangential LV myocardial velocities in patients with PH.

METHODS

Respiratory self-gated TPM was performed using a rotating golden-angle spiral acquisition with retrospective cardiac gating. TPM of a mid ventricular slice was acquired in 40 PH patients and 20 age- and sex-matched healthy controls. Endocardial and epicardial LV borders were manually defined, and myocardial velocities calculated using in-house software. Patients without proximal CTEPH (chronic thromboembolic PH) and not receiving intravenous prostacyclin therapy (n = 34) were followed up until the primary outcome of disease progression (death, transplantation, or progression to intravenous therapy) or the end of the study. Physicians who determined disease progression were blinded to CMR data. Conventional ventricular volumetric indices and novel TPM metrics were analyzed for prediction of 6-min walk distance (6MWD) and disease progression.

RESULTS

Peak longitudinal (p < 0.0001) and radial (p = 0.001) early diastolic (E) wave velocities were significantly lower in PH patients compared with healthy volunteers. Reversal of tangential E waves was observed in all patients and was highly discriminative for the presence of PH (p < 0.0001). The global radial E wave (β = 0.41, p = 0.017) and lateral wall radial systolic (S) wave velocities (β = 0.33, p = 0.028) were the only independent predictors of 6MWD in a model including RV ejection fraction (RVEF) and LV stroke volume. Over a median follow-up period of 20 months (IQR 7.9 months), 8 patients commenced intravenous therapy and 1 died. Global longitudinal E wave was the only independent predictor of clinical worsening (6.3× increased risk, p = 0.009) in a model including RVEF and septal curvature.

CONCLUSIONS

TPM metrics of LV diastolic function are significantly abnormal in PH. More importantly, abnormal LV E wave velocities are the only independent predictors of functional capacity and clinical worsening in a model that includes conventional metrics of biventricular function.

Distributed MRI reconstruction using Gadgetron-based cloud computing

PURPOSE

To expand the open source Gadgetron reconstruction framework to support distributed computing and to demonstrate that a multinode version of the Gadgetron can be used to provide nonlinear reconstruction with clinically acceptable latency.

METHODS

The Gadgetron framework was extended with new software components that enable an arbitrary number of Gadgetron instances to collaborate on a reconstruction task. This cloud-enabled version of the Gadgetron was deployed on three different distributed computing platforms ranging from a heterogeneous collection of commodity computers to the commercial Amazon Elastic Compute Cloud. The Gadgetron cloud was used to provide nonlinear, compressed sensing reconstruction on a clinical scanner with low reconstruction latency (eg, cardiac and neuroimaging applications).

RESULTS

The proposed setup was able to handle acquisition and 11 -SPIRiT reconstruction of nine high temporal resolution real-time, cardiac short axis cine acquisitions, covering the ventricles for functional evaluation, in under 1 min. A three-dimensional high-resolution brain acquisition with 1 mm(3) isotropic pixel size was acquired and reconstructed with nonlinear reconstruction in less than 5 min.

CONCLUSION

A distributed computing enabled Gadgetron provides a scalable way to improve reconstruction performance using commodity cluster computing. Nonlinear, compressed sensing reconstruction can be deployed clinically with low image reconstruction latency.