Publications
82 results found
Huo Z, Wen K, Luo Y, et al., 2024, Referenceless Nyquist ghost correction outperforms standard navigator-based method and improves efficiency of in vivo diffusion tensor cardiovascular magnetic resonance, Magnetic Resonance in Medicine, Vol: 91, Pages: 2403-2416, ISSN: 0740-3194
PURPOSE: The study aims to assess the potential of referenceless methods of EPI ghost correction to accelerate the acquisition of in vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) data using both computational simulations and data from in vivo experiments. METHODS: Three referenceless EPI ghost correction methods were evaluated on mid-ventricular short axis DT-CMR spin echo and STEAM datasets from 20 healthy subjects at 3T. The reduced field of view excitation technique was used to automatically quantify the Nyquist ghosts, and DT-CMR images were fit to a linear ghost model for correction. RESULTS: Numerical simulation showed the singular value decomposition (SVD) method is the least sensitive to noise, followed by Ghost/Object method and entropy-based method. In vivo experiments showed significant ghost reduction for all correction methods, with referenceless methods outperforming navigator methods for both spin echo and STEAM sequences at b = 32, 150, 450, and 600 smm - 2 $$ {\mathrm{smm}}^{-2} $$ . It is worth noting that as the strength of the diffusion encoding increases, the performance gap between the referenceless method and the navigator-based method diminishes. CONCLUSION: Referenceless ghost correction effectively reduces Nyquist ghost in DT-CMR data, showing promise for enhancing the accuracy and efficiency of measurements in clinical practice without the need for any additional reference scans.
Huang J, Ferreira P, Wang L, et al., 2024, Deep learning-based diffusion tensor cardiac magnetic resonance reconstruction: a comparison study, Scientific Reports, Vol: 14, ISSN: 2045-2322
In vivo cardiac diffusion tensor imaging (cDTI) is a promising Magnetic Resonance Imaging (MRI) technique for evaluating the microstructure of myocardial tissue in living hearts, providing insights into cardiac function and enabling the development of innovative therapeutic strategies. However, the integration of cDTI into routine clinical practice poses challenging due to the technical obstacles involved in the acquisition, such as low signal-to-noise ratio and prolonged scanning times. In this study, we investigated and implemented three different types of deep learning-based MRI reconstruction models for cDTI reconstruction. We evaluated the performance of these models based on the reconstruction quality assessment, the diffusion tensor parameter assessment as well as the computational cost assessment. Our results indicate that the models discussed in this study can be applied for clinical use at an acceleration factor (AF) of ×2 and ×4, with the D5C5 model showing superior fidelity for reconstruction and the SwinMR model providing higher perceptual scores. There is no statistical difference from the reference for all diffusion tensor parameters at AF ×2 or most DT parameters at AF ×4, and the quality of most diffusion tensor parameter maps is visually acceptable. SwinMR is recommended as the optimal approach for reconstruction at AF ×2 and AF ×4. However, we believe that the models discussed in this study are not yet ready for clinical use at a higher AF. At AF ×8, the performance of all models discussed remains limited, with only half of the diffusion tensor parameters being recovered to a level with no statistical difference from the reference. Some diffusion tensor parameter maps even provide wrong and misleading information.
Roehl M, Conway M, Ghonim S, et al., 2024, STEAM-SASHA: A novel approach for blood and fat suppressed native T1 measurement in the right ventricular myocardium, Magnetic Resonance Materials in Physics, Biology and Medicine, ISSN: 0968-5243
Objective:The excellent blood and fat suppression of stimulated echo acquisition mode (STEAM) can be combined with saturation recovery single-shot acquisition (SASHA) in a novel STEAM-SASHA sequence for right ventricular (RV) native T1 mapping.Materials and methods:STEAM-SASHA splits magnetization preparation over two cardiac cycles, nulling blood signal and allowing fat signal to decay. Breath-hold T1 mapping was performed in a T1 phantom and twice in 10 volunteers using STEAM-SASHA and a modified Look-Locker sequence at peak systole at 3T. T1 was measured in 3 RV regions, the septum and left ventricle (LV).Results:In phantoms, MOLLI under-estimated while STEAM-SASHA over-estimated T1, on average by 3.0% and 7.0% respectively, although at typical 3T myocardial T1 (T1 > 1200 ms) STEAM-SASHA was more accurate. In volunteers, T1 was higher using STEAM-SASHA than MOLLI in the LV and septum (p = 0.03, p = 0.006, respectively), but lower in RV regions (p > 0.05). Inter-study, inter-observer and intra-observer coefficients of variation in all regions were < 15%. Blood suppression was excellent with STEAM-SASHA and noise floor effects were minimal.Discussion:STEAM-SASHA provides accurate and reproducible T1 in the RV with excellent blood and fat suppression. STEAM-SASHA has potential to provide new insights into pathological changes in the RV in future studies.
Tänzer M, Ferreira P, Scott A, et al., 2024, Correction to: Faster Diffusion Cardiac MRI with Deep Learning-Based Breath Hold Reduction, Medical Image Understanding and Analysis, Publisher: Springer International Publishing, Pages: C1-C1, ISBN: 9783031120527
Zheng Y, Chan WX, Nielles-Vallespin S, et al., 2023, Effects of myocardial sheetlet sliding on left ventricular function, Biomechanics and Modeling in Mechanobiology, Vol: 22, Pages: 1313-1332, ISSN: 1617-7940
Left ventricle myocardium has a complex micro-architecture, which was revealed to consist of myocyte bundles arranged in a series of laminar sheetlets. Recent imaging studies demonstrated that these sheetlets re-orientated and likely slided over each other during the deformations between systole and diastole, and that sheetlet dynamics were altered during cardiomyopathy. However, the biomechanical effect of sheetlet sliding is not well-understood, which is the focus here. We conducted finite element simulations of the left ventricle (LV) coupled with a windkessel lumped parameter model to study sheetlet sliding, based on cardiac MRI of a healthy human subject, and modifications to account for hypertrophic and dilated geometric changes during cardiomyopathy remodeling. We modeled sheetlet sliding as a reduced shear stiffness in the sheet-normal direction and observed that (1) the diastolic sheetlet orientations must depart from alignment with the LV wall plane in order for sheetlet sliding to have an effect on cardiac function, that (2) sheetlet sliding modestly aided cardiac function of the healthy and dilated hearts, in terms of ejection fraction, stroke volume, and systolic pressure generation, but its effects were amplified during hypertrophic cardiomyopathy and diminished during dilated cardiomyopathy due to both sheetlet angle configuration and geometry, and that (3) where sheetlet sliding aided cardiac function, it increased tissue stresses, particularly in the myofibre direction. We speculate that sheetlet sliding is a tissue architectural adaptation to allow easier deformations of the LV walls so that LV wall stiffness will not hinder function, and to provide a balance between function and tissue stresses. A limitation here is that sheetlet sliding is modeled as a simple reduction in shear stiffness, without consideration of micro-scale sheetlet mechanics and dynamics.
Alemany I, Rose JN, Ferreira PF, et al., 2023, Realistic numerical simulations of diffusion tensor cardiovascular magnetic resonance: the effects of perfusion and membrane permeability, Magnetic Resonance in Medicine, Vol: 90, Pages: 1641-1656, ISSN: 0740-3194
PurposeTo study the sensitivity of diffusion tensor cardiovascular magnetic resonance (DT-CMR) to microvascular perfusion and changes in cell permeability.MethodsMonte Carlo (MC) random walk simulations in the myocardium have been performed to simulate self-diffusion of water molecules in histology-based media with varying extracellular volume fraction (ECV) and permeable membranes. The effect of microvascular perfusion on simulations of the DT-CMR signal has been incorporated by adding the contribution of particles traveling through an anisotropic capillary network to the diffusion signal. The simulations have been performed considering three pulse sequences with clinical gradient strengths: monopolar stimulated echo acquisition mode (STEAM), monopolar pulsed-gradient spin echo (PGSE), and second-order motion-compensated spin echo (MCSE).ResultsReducing ECV intensifies the diffusion restriction and incorporating membrane permeability reduces the anisotropy of the diffusion tensor. Widening the intercapillary velocity distribution results in increased measured diffusion along the cardiomyocytes long axis when the capillary networks are anisotropic. Perfusion amplifies the mean diffusivity for STEAM while the opposite is observed for short diffusion encoding time sequences (PGSE and MCSE).ConclusionThe effect of perfusion on the measured diffusion tensor is reduced using an increased reference b-value. Our results pave the way for characterization of the response of DT-CMR to microstructural changes underlying cardiac pathology and highlight the higher sensitivity of STEAM to permeability and microvascular circulation due to its longer diffusion encoding time.
Wang Y, Sun C, Ghadimi S, et al., 2023, StrainNet: Improved Myocardial Strain Analysis of Cine MRI by Deep Learning from DENSE, RADIOLOGY-CARDIOTHORACIC IMAGING, Vol: 5, ISSN: 2638-6135
Moulin K, Stoeck CT, Axel L, et al., 2023, In Vivo Cardiac Diffusion Imaging Without Motion-Compensation Leads to Unreasonably High Diffusivity, JOURNAL OF MAGNETIC RESONANCE IMAGING, ISSN: 1053-1807
Alemany I, Ferreira PF, Nielles-Vallespin S, et al., 2023, The Effect of Temporal Variations in Myocardial Perfusion on Diffusion Tensor Measurements, Pages: 54-63, ISBN: 9783031353017
The aim of this study is to investigate the impact of velocity fluctuations on the perfusion signal and tensor parameters in diffusion tensor cardiovascular magnetic resonance (DT-CMR) using numerical simulations. A sinusoidal velocity function with increasing amplitude and frequency and a physiological velocity function have been considered. Both velocity functions have been analyzed using two mean inter-capillary velocity distributions with varying levels of dispersion. The results of the perfusion simulations, along with previous diffusion results, have been utilized to analyse the impact of perfusion on the diffusion tensor. The findings indicated that MCSE effectively compensated the rapid velocity changes considered in the study, while PGSE was sensitive to temporal changes in velocity. STEAM was found to be more sensitive to variations in the mean-intercapillary dispersion rather than to temporal velocity fluctuations. These simulation results provide insights regarding the potential of dispersed perfusion velocity fluctuations to affect the DT-CMR signal.
Wang L, Huang J, Xing X, et al., 2023, Style Transfer and Self-Supervised Learning Powered Myocardium Infarction Super-Resolution Segmentation
This study proposes a pipeline that incorporates a novel style transfer model and a simultaneous super-resolution and segmentation model. The proposed pipeline aims to enhance diffusion tensor imaging (DTI) images by translating them into the late gadolinium enhancement (LGE) domain, which offers a larger amount of data with high-resolution and distinct highlighting of myocardium infarction (MI) areas. Subsequently, the segmentation task is performed on the LGE style image. An end-to-end super-resolution segmentation model is introduced to generate high-resolution mask from low-resolution LGE style DTI image. Further, to enhance the performance of the model, a multi-task self-supervised learning strategy is employed to pre-train the super-resolution segmentation model, allowing it to acquire more representative knowledge and improve its segmentation performance after fine-tuning. https://github.com/wlc2424762917/Med_Img
Ferreira PF, Banerjee A, Scott AD, et al., 2022, Accelerating Cardiac Diffusion Tensor Imaging With a U-Net Based Model: Toward Single Breath-Hold, JOURNAL OF MAGNETIC RESONANCE IMAGING, Vol: 56, Pages: 1691-1704, ISSN: 1053-1807
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- Citations: 4
Teh I, Romero W, Boyle J, et al., 2022, Validation of cardiac diffusion tensor imaging sequences: A multi-centre test-retest phantom study, NMR in Biomedicine, Vol: 35, Pages: 1-18, ISSN: 0952-3480
INTRODUCTION: 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 accuracy, precision, repeatability and reproducibility of state-of-the-art pulse sequences for cardiac DTI between ten centres internationally. METHODS: 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 (STEAM; N=5) sequence suitable for cardiac DTI in vivo. A second identical scan was performed 1-9 days post, and the data analysed centrally. RESULTS: The average mean diffusivities (MD) in 0% PVP were (1.124, 1.130, 1.113) × 10-3 mm2 /s for PGSE, SE and STEAM respectively, and accurate to within 1.5% of reference data from literature. The coefficients of variation in MD across sites were 2.6%, 3.1%, 2.1% for PGSE, SE and STEAM, 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) × 10-5 mm2 /s (mean ± 1.96SD). CONCLUSION: 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.
Auger DA, Ghadimi S, Cai X, et al., 2022, Reproducibility of global and segmental myocardial strain using cine DENSE at 3 T: a multicenter cardiovascular magnetic resonance study in healthy subjects and patients with heart disease, Journal of Cardiovascular Magnetic Resonance, Vol: 24, Pages: 23-23, ISSN: 1097-6647
BACKGROUND: While multiple cardiovascular magnetic resonance (CMR) methods provide excellent reproducibility of global circumferential and global longitudinal strain, achieving highly reproducible segmental strain is more challenging. Previous single-center studies have demonstrated excellent reproducibility of displacement encoding with stimulated echoes (DENSE) segmental circumferential strain. The present study evaluated the reproducibility of DENSE for measurement of whole-slice or global circumferential (Ecc), longitudinal (Ell) and radial (Err) strain, torsion, and segmental Ecc at multiple centers. METHODS: Six centers participated and a total of 81 subjects were studied, including 60 healthy subjects and 21 patients with various types of heart disease. CMR utilized 3 T scanners, and cine DENSE images were acquired in three short-axis planes and in the four-chamber long-axis view. During one imaging session, each subject underwent two separate DENSE scans to assess inter-scan reproducibility. Each subject was taken out of the scanner and repositioned between the scans. Intra-user, inter-user-same-site, inter-user-different-site, and inter-user-Human-Deep-Learning (DL) comparisons assessed the reproducibility of different users analyzing the same data. Inter-scan comparisons assessed the reproducibility of DENSE from scan to scan. The reproducibility of whole-slice or global Ecc, Ell and Err, torsion, and segmental Ecc were quantified using Bland-Altman analysis, the coefficient of variation (CV), and the intraclass correlation coefficient (ICC). CV was considered excellent for CV ≤ 10%, good for 10% < CV ≤ 20%, fair for 20% < CV ≤ 40%, and poor for CV > 40. ICC values were considered excellent for ICC > 0.74, good for ICC 0.6 < ICC ≤ 0.74, fair for ICC 0.4 < ICC ≤ 0.59
Dwornik M, Khalique Z, Rajakulasingam R, et al., 2022, Cardiovascular Magnetic Resonance in Cardiomyopathy, International Journal of Cardiodiabetes
Scott A, Jackson T, Khalique Z, et al., 2022, Development of a CMR compatible large animal isolated heart model for direct comparison of beating and arrested hearts, NMR in Biomedicine, Vol: 35, ISSN: 0952-3480
BackgroundCardiac motion results in image artefacts and quantification errors in many cardiovascular magnetic resonance (CMR) techniques, including microstructural assessment using diffusion tensor cardiovascular magnetic resonance (DT-CMR). Here we develop a CMR compatible isolated perfused porcine heart model that allows comparison of data obtained in beating and arrested states.Methods10 porcine hearts (8/10 for protocol optimisation) were harvested using a donor heart retrieval protocol and transported to the remote CMR facility. Langendorff perfusion in a 3D printed chamber and perfusion circuit re-established contraction. Hearts were imaged using cine, parametric mapping and STEAM DT-CMR at cardiac phases with the minimum and maximum wall thickness. High potassium and lithium perfusates were then used to arrest the heart in a slack and contracted state respectively. Imaging was repeated in both arrested states. After imaging, tissue was removed for subsequent histology in a location matched to the DT-CMR data using fiducial markers.ResultsRegular sustained contraction was successfully established in 6/10 hearts, including the final 5 hearts. Imaging was performed in 4 hearts and one underwent the full protocol including co-localised histology. Image quality was good and there was good agreement between DT-CMR data in equivalent beating and arrested states. Despite the use of autologous blood and dextran within the perfusate, T2, DT-CMR measures and an increase in mass was consistent with development of myocardial edema resulting in failure to achieve a true diastolic-like state. A contiguous stack of 313 5μm histological sections at and a 100μm thick section showing cell morphology on 3D fluorescent confocal microscopy co-localised to DT-CMR data were obtained.ConclusionsA CMR compatible isolated perfused beating heart setup for large animal hearts allows direct comparisons of beating and arrested heart data with subsequent co-localised histology without
Tanzer M, Ferreira P, Scott A, et al., 2022, Faster Diffusion Cardiac MRI with Deep Learning-Based Breath Hold Reduction, MEDICAL IMAGE UNDERSTANDING AND ANALYSIS, MIUA 2022, Vol: 13413, Pages: 101-115, ISSN: 0302-9743
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- Citations: 1
Tanzer M, Yook SH, Ferreira P, et al., 2022, Review of Data Types and Model Dimensionality for Cardiac DTI SMS-Related Artefact Removal, STATISTICAL ATLASES AND COMPUTATIONAL MODELS OF THE HEART: REGULAR AND CMRXMOTION CHALLENGE PAPERS, STACOM 2022, Vol: 13593, Pages: 123-132, ISSN: 0302-9743
Le B, Ferreira P, Merchant S, et al., 2021, Microarchitecture of the hearts in term andformer-pretermlambs using diffusion tensor imaging, ANATOMICAL RECORD-ADVANCES IN INTEGRATIVE ANATOMY AND EVOLUTIONARY BIOLOGY, Vol: 304, Pages: 803-817, ISSN: 1932-8486
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- Citations: 5
Ferreira PF, Martin RR, Scott AD, et al., 2020, Automating in vivo cardiac diffusion tensor postprocessing with deep learning-based segmentation, Magnetic Resonance in Medicine, Vol: 84, Pages: 2801-2814, ISSN: 0740-3194
PurposeIn this work we develop and validate a fully automated postprocessing framework for in vivo diffusion tensor cardiac magnetic resonance (DT‐CMR) data powered by deep learning.MethodsA U‐Net based convolutional neural network was developed and trained to segment the heart in short‐axis DT‐CMR images. This was used as the basis to automate and enhance several stages of the DT‐CMR tensor calculation workflow, including image registration and removal of data corrupted with artifacts, and to segment the left ventricle. Previously collected and analyzed scans (348 healthy scans and 144 cardiomyopathy patient scans) were used to train and validate the U‐Net. All data were acquired at 3 T with a STEAM‐EPI sequence. The DT‐CMR postprocessing and U‐Net training/testing were performed with MATLAB and Python TensorFlow, respectively.ResultsThe U‐Net achieved a median Dice coefficient of 0.93 [0.92, 0.94] for the segmentation of the left‐ventricular myocardial region. The image registration of diffusion images improved with the U‐Net segmentation (P < .0001), and the identification of corrupted images achieved an F1 score of 0.70 when compared with an experienced user. Finally, the resulting tensor measures showed good agreement between an experienced user and the fully automated method.ConclusionThe trained U‐Net successfully automated the DT‐CMR postprocessing, supporting real‐time results and reducing human workload. The automatic segmentation of the heart improved image registration, resulting in improvements of the calculated DT parameters.
Nielles-Vallespin S, Scott A, Ferreira P, et al., 2020, Cardiac Diffusion: Technique and Practical Applications, JOURNAL OF MAGNETIC RESONANCE IMAGING, Vol: 52, Pages: 348-368, ISSN: 1053-1807
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- Citations: 22
Khalique Z, Ferreira PF, Scott AD, et al., 2020, Diffusion tensor cardiovascular magnetic resonance in cardiac amyloidosis, Circulation: Cardiovascular Imaging, Vol: 13, ISSN: 1941-9651
Background Cardiac amyloidosis (CA) is a disease of interstitial myocardial infiltration, usually by light chains or transthyretin. We used diffusion tensor cardiovascular magnetic resonance (DT-CMR) to noninvasively assess the effects of amyloid infiltration on the cardiac microstructure. Methods DT-CMR was performed at diastole and systole in 20 CA, 11 hypertrophic cardiomyopathy, and 10 control subjects with calculation of mean diffusivity, fractional anisotropy, and sheetlet orientation (secondary eigenvector angle). Results Mean diffusivity was elevated and fractional anisotropy reduced in CA compared with both controls and hypertrophic cardiomyopathy (P<0.001). In CA, mean diffusivity was correlated with extracellular volume (r=0.68, P=0.004), and fractional anisotropy was inversely correlated with circumferential strain (r=-0.65, P=0.02). In CA, diastolic secondary eigenvector angle was elevated, and secondary eigenvector angle mobility was reduced compared with controls (both P<0.001). Diastolic secondary eigenvector angle was correlated with amyloid burden measured by extracellular volume in transthyretin, but not light chain amyloidosis. Conclusions DT-CMR can characterize the microstructural effects of amyloid infiltration and is a contrast-free method to identify the location and extent of the expanded disorganized myocardium. The diffusion biomarkers mean diffusivity and fractional anisotropy effectively discriminate CA from hypertrophic cardiomyopathy. DT-CMR demonstrated that failure of sheetlet relaxation in diastole correlated with extracellular volume in transthyretin, but not light chain amyloidosis. This indicates that different mechanisms may be responsible for impaired contractility in CA, with an amyloid burden effect in transthyretin, but an idiosyncratic effect in light chain amyloidosis. Consequently, DT-CMR offers a contrast-free tool to identify novel pathophysiology, improve diagnostics, and monitor disease through noninvasive micr
Khalique Z, Ferreira P, Scott A, et al., 2020, Diffusion tensor cardiovascular magnetic resonance: a clinical perspective, JACC: Cardiovascular Imaging, Vol: 13, Pages: 1235-1255, ISSN: 1936-878X
Imaging the heart is central to cardiac phenotyping but in clinical practice this has been restricted to macroscopic interrogation. Diffusion tensor cardiovascular magnetic resonance (DT-CMR) is a novel, non-invasive technique which is beginning to unlock details of this microstructure in humans in-vivo. DT-CMR demonstrates the helical cardiomyocyte arrangement that drives rotation and torsion. Sheetlets (functional units of cardiomyocytes, separated by shear layers) have been shown to reorientate between diastole and systole, revealing how microstructural function facilitates cardiac thickening. Measures of tissue diffusion can also be made; fractional anisotropy (a measure of myocyte organisation) and mean diffusivity (a measure of myocyte packing). Abnormal myocyte orientation and sheetlet function has been demonstrated in congenital heart disease, cardiomyopathy and after myocardial infarction. It is too early to predict the clinical importance of DT-CMR, but such unique in-vivo information will likely prove valuable in early diagnosis and risk prediction of cardiac dysfunction and arrhythmias.
Stoeck CT, Scott AD, Ferreira PF, et al., 2020, Motion-induced signal loss in In vivo cardiac diffusion-weighted imaging, Journal of Magnetic Resonance Imaging, Vol: 51, Pages: 319-320, ISSN: 1053-1807
Khalique Z, Scott AD, Ferreira PF, et al., 2019, Diffusion tensor cardiovascular magnetic resonance in hypertrophic cardiomyopathy: a comparison of motion-compensated spin echo and stimulated echo techniques, Magnetic Resonance Materials in Physics, Biology and Medicine, Vol: 33, Pages: 331-342, ISSN: 0968-5243
ObjectivesDiffusion 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 methodsBiphasic 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.ResultsAdequate 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).DiscussionIn 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.
Gulati A, Ismail TF, Ali A, et al., 2019, Microvascular Dysfunction in Dilated Cardiomyopathy A Quantitative Stress Perfusion Cardiovascular Magnetic Resonance Study, JACC-CARDIOVASCULAR IMAGING, Vol: 12, Pages: 1699-1708, ISSN: 1936-878X
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- Citations: 37
Tayal U, Wage R, Ferreira P, et al., 2019, The feasibility of a novel limited field of view spiral cine DENSE sequence to assess myocardial strain in dilated cardiomyopathy, Magnetic Resonance Materials in Physics, Biology and Medicine, Vol: 32, Pages: 317-329, ISSN: 0968-5243
ObjectiveDevelop 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 methodsA 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).ResultsDENSE 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.DiscussionWe 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.
Rose JN, Nielles-Vallespin S, Ferreira PF, et al., 2019, Novel insights into in-vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology-based virtual microstructure, Magnetic Resonance in Medicine, Vol: 81, Pages: 2759-2773, ISSN: 0740-3194
PurposeTo develop histology‐informed simulations of diffusion tensor cardiovascular magnetic resonance (DT‐CMR) for typical in‐vivo pulse sequences and determine their sensitivity to changes in extra‐cellular space (ECS) and other microstructural parameters.MethodsWe synthesised the DT‐CMR signal from Monte Carlo random walk simulations. The virtual tissue was based on porcine histology. The cells were thickened and then shrunk to modify ECS. We also created idealised geometries using cuboids in regular arrangement, matching the extra‐cellular volume fraction (ECV) of 16–40%. The simulated voxel size was 2.8 × 2.8 × 8.0 mm3 for pulse sequences covering short and long diffusion times: Stejskal–Tanner pulsed‐gradient spin echo, second‐order motion‐compensated spin echo, and stimulated echo acquisition mode (STEAM), with clinically available gradient strengths.ResultsThe primary diffusion tensor eigenvalue increases linearly with ECV at a similar rate for all simulated geometries. Mean diffusivity (MD) varies linearly, too, but is higher for the substrates with more uniformly distributed ECS. Fractional anisotropy (FA) for the histology‐based geometry is higher than the idealised geometry with low sensitivity to ECV, except for the long mixing time of the STEAM sequence. Varying the intra‐cellular diffusivity (DIC) results in large changes of MD and FA. Varying extra‐cellular diffusivity or using stronger gradients has minor effects on FA. Uncertainties of the primary eigenvector orientation are reduced using STEAM.ConclusionsWe found that the distribution of ECS has a measurable impact on DT‐CMR parameters. The observed sensitivity of MD and FA to ECV and DIC has potentially interesting applications for interpreting in‐vivo DT‐CMR parameters.
Gorodezky M, Ferreira P, Nielles-Vallespin S, et al., 2019, High resolution in-vivo DT-CMR using an interleaved variable density spiral STEAM sequence, Magnetic Resonance in Medicine, Vol: 81, Pages: 1580-1594, ISSN: 0740-3194
Purpose: Diffusion tensor cardiovascular magnetic resonance (DT-CMR) has a limited spatial resolution. Thepurpose of this study was to demonstrate high-resolution DT-CMR using a segmented variable density spiralsequence with correction for motion, off-resonance and T2* related blurring.Methods: A single-shot STEAM EPI DT-CMR sequence at 2.8x2.8x8mm3 and 1.8x1.8x8mm3 was compared to asingle shot spiral at 2.8x2.8x8mm3 and an interleaved spiral sequence at 1.8x1.8x8mm3resolution in 10 healthyvolunteers at peak-systole and diastasis. Motion-induced phase was corrected using the densely sampledcentral k-space data of the spirals. STEAM field maps and T2* measures were obtained using a pair ofstimulated echoes each with a double spiral readout, the first used to correct the motion-induced phase of thesecond.Results: The high resolution spiral sequence produced similar DT-CMR results and quality measures to thestandard resolution sequence in both cardiac phases. Residual differences in fractional anisotropy and helixangle gradient between the resolutions could be due to spatial resolution and/or signal to noise ratio. The dataquality increased after both motion-induced phase correction and off-resonance correction and sharpnessincreased after T2* correction. The high resolution EPI sequence failed to provide sufficient data quality forDT-CMR reconstruction.Conclusion: In this study an in-vivo DT-CMR acquisition at 1.8x1.8mm2in-plane resolution was demonstratedusing a segmented spiral STEAM sequence. The motion-induced phase and off-resonance corrections areessential for high resolution spiral DT-CMR. Segmented variable density spiral STEAM was found to be theoptimal method for acquiring high resolution DT-CMR data.
Khalique Z, Ferreira P, Scott A, et al., 2018, Diffusion Tensor Cardiovascular Magnetic Resonance of Microstructural Recovery in Dilated Cardiomyopathy, JACC: Cardiovascular Imaging, Vol: 11, Pages: 1548-1550, ISSN: 1936-878X
Schlemper J, Yang G, Ferreira P, et al., 2018, Stochastic deep compressive sensing for the reconstruction of diffusion tensor cardiac MRI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol: 11070 LNCS, Pages: 295-303, ISSN: 0302-9743
© Springer Nature Switzerland AG 2018. Understanding the structure of the heart at the microscopic scale of cardiomyocytes and their aggregates provides new insights into the mechanisms of heart disease and enables the investigation of effective therapeutics. Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is a unique non-invasive technique that can resolve the microscopic structure, organisation, and integrity of the myocardium without the need for exogenous contrast agents. However, this technique suffers from relatively low signal-to-noise ratio (SNR) and frequent signal loss due to respiratory and cardiac motion. Current DT-CMR techniques rely on acquiring and averaging multiple signal acquisitions to improve the SNR. Moreover, in order to mitigate the influence of respiratory movement, patients are required to perform many breath holds which results in prolonged acquisition durations (e.g., ~ 30 min using the existing technology). In this study, we propose a novel cascaded Convolutional Neural Networks (CNN) based compressive sensing (CS) technique and explore its applicability to improve DT-CMR acquisitions. Our simulation based studies have achieved high reconstruction fidelity and good agreement between DT-CMR parameters obtained with the proposed reconstruction and fully sampled ground truth. When compared to other state-of-the-art methods, our proposed deep cascaded CNN method and its stochastic variation demonstrated significant improvements. To the best of our knowledge, this is the first study using deep CNN based CS for the DT-CMR reconstruction. In addition, with relatively straightforward modifications to the acquisition scheme, our method can easily be translated into a method for online, at-the-scanner reconstruction enabling the deployment of accelerated DT-CMR in various clinical applications.
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