Diffuse myocardial fibrosis precedes subclinical functional myocardial impairment and provides prognostic information in systemic sclerosis.

AIMS: Myocardial involvement is common in patients with systemic sclerosis (SSc) and causes myocardial fibrosis and subtle ventricular dysfunction. However, the temporal onset of myocardial involvement during the progression of the disease and its prognostic value are yet unknown. We used cardiovascular magnetic resonance (CMR) to investigate subclinical functional impairment and diffuse myocardial fibrosis in patients with very early diagnosis of SSc (VEDOSS) and established SSc and examined whether this was associated with mortality. METHODS AND RESULTS: One hundred and ten SSc patients (86 established SSc, 24 VEDOSS) and 15 healthy controls were prospectively recruited. The patients were followed-up for a median duration of 7.0 years (interquartile range 6.0-7.3 years). Study subjects underwent CMR including assessment of myocardial fibrosis [native T1 and extracellular volume (ECV)] and measurement of global longitudinal (GLS) and circumferential (GCS) myocardial strain. Native T1 values and ECV were elevated in VEDOSS and SSc patients compared with controls (P < 0.001). GLS was similar in VEDOSS and controls but significantly impaired in patients with established SSc (P < 0.001). GCS was similar over all groups (P = 0.88). There were 12 deaths during follow-up. Elevated native T1 [hazard ratio (HR) 5.8, 95% confidence interval (CI): 1.7-20.4; P = 0.006] and reduced GLS (HR 6.1, 95% CI: 1.3-29.9; P = 0.038) identified subjects with increased risk of death. Only native T1 was predictive for cardiovascular mortality (P < 0.001). CONCLUSION: Subclinical myocardial involvement first manifests as diffuse myocardial fibrosis identified by the expansion of ECV and increased native T1 in VEDOSS patients while subtle functional impairment only occurs in established SSc. Native T1 and GLS have prognostic value for all-cause mortality in SSc patients.

Pathophysiology of LV Remodeling Following STEMI: A Longitudinal Diffusion Tensor CMR Study.

BACKGROUND: Adverse LV remodeling post-ST-segment elevation myocardial infarction (STEMI) is associated with a poor prognosis, but the underlying mechanisms are not fully understood. Diffusion tensor (DT)-cardiac magnetic resonance (CMR) allows in vivo characterization of myocardial architecture and provides unique mechanistic insight into pathophysiologic changes following myocardial infarction. OBJECTIVES: This study evaluated the potential associations between DT-CMR performed soon after STEMI and long-term adverse left ventricular (LV) remodeling following STEMI. METHODS: A total of 100 patients with STEMI underwent CMR at 5 days and 12 months post-reperfusion. The protocol included DT-CMR for assessing fractional anisotropy (FA), secondary eigenvector angle (E2A) and helix angle (HA), cine imaging for assessing LV volumes, and late gadolinium enhancement for calculating infarct and microvascular obstruction size. Adverse remodeling was defined as a 20% increase in LV end-diastolic volume at 12 months. RESULTS: A total of 32 patients experienced adverse remodeling at 12 months. Compared with patients without adverse remodeling, they had lower FA (0.23 ± 0.03 vs 0.27 ± 0.04; P < 0.001), lower E2A (37 ± 6° vs 51 ± 7°; P < 0.001), and, on HA maps, a lower proportion of myocytes with right-handed orientation (RHM) (8% ± 5% vs 17% ± 9%; P < 0.001) in their acutely infarcted myocardium. On multivariable logistic regression analysis, infarct FA (odds ratio [OR]: <0.01; P = 0.014) and E2A (OR: 0.77; P = 0.001) were independent predictors of adverse LV remodeling after adjusting for left ventricular ejection fraction (LVEF) and infarct size. There were no significant changes in infarct FA, E2A, or RHM between the 2 scans. CONCLUSIONS: Extensive cardiomyocyte disorganization (evidenced by low FA), acute loss of sheetlet angularity (evidenced by low E2A), and a greater loss of organization among cardiomyocytes with RHM, corresponding to the subendocardium, can be detected within 5 days post-STEMI. These changes persist post-injury, and low FA and E2A are independently associated with long-term adverse remodeling.

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

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

Quantification of left ventricular strain and torsion by joint analysis of 3D tagging and cine MR images.

Cardiovascular magnetic resonance (CMR) imaging is the gold standard for the non-invasive assessment of left-ventricular (LV) function. Prognostic value of deformation metrics extracted directly from regular SSFP CMR images has been shown by numerous studies in the clinical setting, but with some limitations to detect torsion of the myocardium. Tagged CMR introduces trackable features in the myocardium that allow for the assessment of local myocardial deformation, including torsion; it is, however, limited in the quantification of radial strain, which is a decisive metric for assessing the contractility of the heart. In order to improve SSFP-only and tagged-only approaches, we propose to combine the advantages of both image types by fusing global shape motion obtained from SSFP images with the local deformation obtained from tagged images. To this end, tracking is first performed on SSFP images, and subsequently, the resulting motion is utilized to mask and track tagged data. Our implementation is based on a recent finite element-based motion tracking tool with mechanical regularization. Joint SSFP and tagged images registration performance is assessed based on deformation metrics including LV strain and twist using human and in-house porcine datasets. Results show that joint analysis of SSFP and 3DTAG images provides better quantification of LV strain and twist as either data source alone.

Dos and don'ts in large animal models of aortic insufficiency.

Aortic insufficiency caused by paravalvular leakage (PVL) is one of the most feared complications following transcatheter aortic valve replacement (TAVI) in patients. Domestic pigs (Sus scrofa domestica) are a popular large animal model to study such conditions and develop novel diagnostic and therapeutic techniques. However, the models based on prosthetic valve implantation are time intensive, costly, and often hamper further hemodynamic measurements such as PV loop and 4D MRI flow by causing implantation-related wall motion abnormalities and degradation of MR image quality. This study describes in detail, the establishment of a minimally invasive porcine model suitable to study the effects of mild-to-moderate "paravalvular" aortic regurgitation on left ventricular (LV) performance and blood flow patterns, particularly under the influence of altered afterload, preload, inotropic state, and heart rate. Six domestic pigs (Swiss large white, female, 60-70 kg of body weight) were used to establish this model. The defects on the hinge point of aortic leaflets and annulus were created percutaneously by the pierce-and-dilate technique either in the right coronary cusp (RCC) or in the non-coronary cusp (NCC). The hemodynamic changes as well as LV performance were recorded by PV loop measurements, while blood flow patterns were assessed by 4D MRI. LV performance was additionally challenged by pharmaceutically altering cardiac inotropy, chronotropy, and afterload. The presented work aims to elaborate the dos and don'ts in porcine models of aortic insufficiency and intends to steepen the learning curve for researchers planning to use this or similar models by giving valuable insights ranging from animal selection to vascular access choices, placement of PV Loop catheter, improvement of PV loop data acquisition and post-processing and finally the induction of paravalvular regurgitation of the aortic valve by a standardized and reproducible balloon induced defect in a precisely targeted region of the aortic valve.

Characterization and correction of diffusion gradient-induced eddy currents in second-order motion-compensated echo-planar and spiral cardiac DTI.

PURPOSE: Very high gradient amplitudes played out over extended time intervals as required for second-order motion-compensated cardiac DTI may violate the assumption of a linear time-invariant gradient system model. The aim of this work was to characterize diffusion gradient-related system nonlinearity and propose a correction approach for echo-planar and spiral spin-echo motion-compensated cardiac DTI. METHODS: Diffusion gradient-induced eddy currents of 9 diffusion directions were characterized at b values of 150 s/mm2 and 450 s/mm2 for a 1.5 Tesla system and used to correct phantom, ex vivo, and in vivo motion-compensated cardiac DTI data acquired with echo-planar and spiral trajectories. Predicted trajectories were calculated using gradient impulse response function and diffusion gradient strength- and direction-dependent zeroth- and first-order eddy current responses. A reconstruction method was implemented using the predicted k $$ k $$ -space trajectories to additionally include off-resonances and concomitant fields. Resulting images were compared to a reference reconstruction omitting diffusion gradient-induced eddy current correction. RESULTS: Diffusion gradient-induced eddy currents exhibited nonlinear effects when scaling up the gradient amplitude and could not be described by a 3D basis alone. This indicates that a gradient impulse response function does not suffice to describe diffusion gradient-induced eddy currents. Zeroth- and first-order diffusion gradient-induced eddy current effects of up to -1.7 rad and -16 to +12 rad/m, respectively, were identified. Zeroth- and first-order diffusion gradient-induced eddy current correction yielded improved image quality upon image reconstruction. CONCLUSION: The proposed approach offers correction of diffusion gradient-induced zeroth- and first-order eddy currents, reducing image distortions to promote improvements of second-order motion-compensated spin-echo cardiac DTI.

Synthetically trained convolutional neural networks for improved tensor estimation from free-breathing cardiac DTI.

Cardiac diffusion tensor imaging (cDTI) provides invaluable information about the state of myocardial microstructure. For further clinical dissemination, free-breathing acquisitions are desired, which however require image registration prior to tensor estimation. Due to the varying contrast and the intrinsically low signal-to-noise ratio (SNR), registration is very challenging and thus can introduce additional errors in the tensor estimation. In the work at hand it is hypothesized, that by incorporating spatial information and physiologically plausible priors into the fitting algorithm, the robustness of diffusion tensor estimation can be improved. To this end, we present a parameterized pipeline to generate synthetic data, that captures the statistics including spatial correlations of diffusion tensors and motion of the heart. The synthetic data is used to train a residual convolutional neural network (CNN) to estimate diffusion tensors from unregistered in-vivo cDTI data. Using in-silico data, the synthetically trained CNN is demonstrated to yield increased tensor estimation accuracy and precision when compared to conventional registration followed by least squares fitting. The network outputs fewer outliers especially at the myocardial borders. In-vivo feasibility using data from five healthy subjects demonstrates the utility of the synthetically trained network. The in-vivo results predicted by the synthetically trained CNN are found to be consistent with the registered least-squares estimates while showing fewer outliers and reduced noise. Even in low SNR regimes, the network results in robust tensor estimation, enabling scan time reduction by reduced-average acquisition in-vivo. Finally, to investigate the network's capability of discriminating between healthy and lesioned tissue, the in-vivo data was artificially augmented showing preserved classification of tissue states based on diffusion metrics.

Rapid inference of personalised left-ventricular meshes by deformation-based differentiable mesh voxelization.

We propose a differentiable volumetric mesh voxelization technique based on deformation of a shape-model, and demonstrate that it can be used to predict left-ventricular anatomies directly from magnetic resonance image slice data. The predicted anatomies are volumetric meshes suitable for direct inclusion in biophysical simulations. The proposed method can leverage existing (pixel-based) segmentation networks, and does not require any ground truth paired image and mesh training data. We demonstrate that this approach produces accurate predictions from few slices, and can combine information from images acquired in different views (e.g. fusing shape information from short axis and long axis slices). We demonstrate that the proposed method is several times faster than a state-of-the-art registration based method. Additionally, we show that our method can correct for slice misalignment, and is robust to incomplete and inaccurate input data. We further demonstrate that by fitting a mesh to every frame of 4D data we can determine ejection fraction, stroke volume and strain.

Detection of Intramyocardial Iron in Patients Following ST-Elevation Myocardial Infarction Using Cardiac Diffusion Tensor Imaging.

BACKGROUND: Intramyocardial hemorrhage (IMH) following ST-elevation myocardial infarction (STEMI) is associated with poor prognosis. In cardiac magnetic resonance (MR), T2* mapping is the reference standard for detecting IMH while cardiac diffusion tensor imaging (cDTI) can characterize myocardial architecture via fractional anisotropy (FA) and mean diffusivity (MD) of water molecules. The value of cDTI in the detection of IMH is not currently known. HYPOTHESIS: cDTI can detect IMH post-STEMI. STUDY TYPE: Prospective. SUBJECTS: A total of 50 patients (20% female) scanned at 1-week (V1) and 3-month (V2) post-STEMI. FIELD STRENGTH/SEQUENCE: A 3.0 T; inversion-recovery T1-weighted-imaging, multigradient-echo T2* mapping, spin-echo cDTI. ASSESSMENT: T2* maps were analyzed to detect IMH (defined as areas with T2* < 20 msec within areas of infarction). cDTI images were co-registered to produce averaged diffusion-weighted-images (DWIs), MD, and FA maps; hypointense areas were manually planimetered for IMH quantification. STATISTICS: On averaged DWI, the presence of hypointense signal in areas matching IMH on T2* maps constituted to true-positive detection of iron. Independent samples t-tests were used to compare regional cDTI values. Results were considered statistically significant at P ≤ 0.05. RESULTS: At V1, 24 patients had IMH on T2*. On averaged DWI, all 24 patients had hypointense signal in matching areas. IMH size derived using averaged-DWI was nonsignificantly greater than from T2* (2.0 ± 1.0 cm2 vs 1.89 ± 0.96 cm2 , P = 0.69). Compared to surrounding infarcted myocardium, MD was significantly reduced (1.29 ± 0.20 × 10-3  mm2 /sec vs 1.75 ± 0.16 × 10-3  mm2 /sec) and FA was significantly increased (0.40 ± 0.07 vs 0.23 ± 0.03) within areas of IMH. By V2, all 24 patients with acute IMH continued to have hypointense signals on averaged-DWI in the affected area. T2* detected IMH in 96% of these patients. Overall, averaged-DWI had 100% sensitivity and 96% specificity for the detection of IMH. DATA CONCLUSION: This study demonstrates that the parameters MD and FA are susceptible to the paramagnetic properties of iron, enabling cDTI to detect IMH. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study.

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

Comparison of interpolation methods of predominant cardiomyocyte orientation from in vivo and ex vivo cardiac diffusion tensor imaging data.

Cardiac electrophysiology and cardiac mechanics both depend on the average cardiomyocyte long-axis orientation. In the realm of personalized medicine, knowledge of the patient-specific changes in cardiac microstructure plays a crucial role. Patient-specific computational modelling has emerged as a tool to better understand disease progression. In vivo cardiac diffusion tensor imaging (cDTI) is a vital tool to non-destructively measure the average cardiomyocyte long-axis orientation in the heart. However, cDTI suffers from long scan times, rendering volumetric, high-resolution acquisitions challenging. Consequently, interpolation techniques are needed to populate bio-mechanical models with patient-specific average cardiomyocyte long-axis orientations. In this work, we compare five interpolation techniques applied to in vivo and ex vivo porcine input data. We compare two tensor interpolation approaches, one rule-based approximation, and two data-driven, low-rank models. We demonstrate the advantage of tensor interpolation techniques, resulting in lower interpolation errors than do low-rank models and rule-based methods adapted to cDTI data. In an ex vivo comparison, we study the influence of three imaging parameters that can be traded off against acquisition time: in-plane resolution, signal to noise ratio, and number of acquired short-axis imaging slices.

Pathology and Advanced Imaging-Characterization of a Congenital Cardiac Defect and Complex Hemodynamics in a Pig: A Case Report.

Domestic pigs are widely used in cardiovascular research as the porcine circulatory system bears a remarkable resemblance to that of humans. In order to reduce variability, only clinically healthy animals enter the study as their health status is assessed in entry examination. Like humans, pigs can also suffer from congenital heart disease, such as an atrial septal defect (ASD), which often remains undetected. Due to the malformation of the endocardial cushion during organ development, mitral valve defects (e.g., mitral clefts) are sometimes associated with ASDs, further contributing to hemodynamic instability. In this work, we report an incidental finding of a hemodynamically highly relevant ASD in the presence of incompetent mitral and tricuspid valves, in an asymptomatic, otherwise healthy juvenile pig. In-depth characterization of the cardiac blood flow by four-dimensional (4D) flow magnetic resonance imaging (MRI) revealed a prominent diastolic left-to-right and discrete systolic right-to-left shunt, resulting in a pulmonary-to-systemic flow ratio of 1.8. Severe mitral (15 mL/stroke) and tricuspid (22 mL/stroke) regurgitation further reduced cardiac output. Pathological examination confirmed the presence of an ostium primum ASD and found a serous cyst of lymphatic origin that was filled with clear fluid partially occluding the ASD. A large mitral cleft was identified as the most likely cause of severe regurgitation, and histology showed mild to moderate endocardiosis in the coaptation area of both atrio-ventricular valves. In summary, although not common, congenital heart defects could play a role as a cause of experimental variability or even intra-experimental mortality when working with apparently heathy, juvenile pigs.

In-silico study of accuracy and precision of left-ventricular strain quantification from 3D tagged MRI.

Cardiac Magnetic Resonance Imaging (MRI) allows quantifying myocardial tissue deformation and strain based on the tagging principle. In this work, we investigate accuracy and precision of strain quantification from synthetic 3D tagged MRI using equilibrated warping. To this end, synthetic biomechanical left-ventricular tagged MRI data with varying tag distance, spatial resolution and signal-to-noise ratio (SNR) were generated and processed to quantify errors in radial, circumferential and longitudinal strains relative to ground truth. Results reveal that radial strain is more sensitive to image resolution and noise than the other strain components. The study also shows robustness of quantifying circumferential and longitudinal strain in the presence of geometrical inconsistencies of 3D tagged data. In conclusion, our study points to the need for higher-resolution 3D tagged MRI than currently available in practice in order to achieve sufficient accuracy of radial strain quantification.

Cardiovascular magnetic resonance imaging of functional and microstructural changes of the heart in a longitudinal pig model of acute to chronic myocardial infarction.

BACKGROUND: We examined the dynamic response of the myocardium to infarction in a longitudinal porcine study using relaxometry, functional as well as diffusion cardiovascular magnetic resonance (CMR). We sought to compare non contrast CMR methods like relaxometry and in-vivo diffusion to contrast enhanced imaging and investigate the link of microstructural and functional changes in the acute and chronically infarcted heart. METHODS: CMR was performed on five myocardial infarction pigs and four healthy controls. In the infarction group, measurements were obtained 2 weeks before 90 min occlusion of the left circumflex artery, 6 days after ischemia and at 5 as well as 9 weeks as chronic follow-up. The timing of measurements was replicated in the control cohort. Imaging consisted of functional cine imaging, 3D tagging, T2 mapping, native as well as gadolinium enhanced T1 mapping, cardiac diffusion tensor imaging, and late gadolinium enhancement imaging. RESULTS: Native T1, extracellular volume (ECV) and mean diffusivity (MD) were significantly elevated in the infarcted region while fractional anisotropy (FA) was significantly reduced. During the transition from acute to chronic stages, native T1 presented minor changes (< 3%). ECV as well as MD increased from acute to the chronic stages compared to baseline: ECV: 125 ± 24% (day 6) 157 ± 24% (week 5) 146 ± 60% (week 9), MD: 17 ± 7% (day 6) 33 ± 14% (week 5) 29 ± 15% (week 9) and FA was further reduced: - 31 ± 10% (day 6) - 38 ± 8% (week 5) - 36 ± 14% (week 9). T2 as marker for myocardial edema was significantly increased in the ischemic area only during the acute stage (83 ± 3 ms infarction vs. 58 ± 2 ms control p < 0.001 and 61 ± 2 ms in the remote area p < 0.001). The analysis of functional imaging revealed reduced left ventricular ejection fraction, global longitudinal strain and torsion in the infarct group. At the same time the transmural helix angle (HA) gradient was steeper in the chronic follow-up and a correlation between longitudinal strain and transmural HA gradient was detected (r = 0.59 with p < 0.05). Comparing non-gadolinium enhanced data T2 mapping showed the largest relative change between infarct and remote during the acute stage (+ 33 ± 4% day 6, with p = 0.013 T2 vs. MD, p = 0.009 T2 vs. FA and p = 0.01 T2 vs. T1) while FA exhibited the largest relative change between infarct and remote during the chronic follow-up (+ 31 ± 2% week 5, with p = N.S. FA vs. MD, p = 0.03 FA vs. T2 and p = 0.003 FA vs. T1). Overall, diffusion parameters provided a higher contrast (> 23% for MD and > 27% for FA) during follow-up compared to relaxometry (T1 17-18%/T2 10-20%). CONCLUSION: During chronic follow-up after myocardial infarction, cardiac diffusion tensor imaging provides a higher sensitivity for mapping microstructural alterations when compared to non-contrast enhanced relaxometry with the added benefit of providing directional tensor information to assess remodelling of myocyte aggregate orientations, which cannot be otherwise assessed.

Septaly Oriented Mild Aortic Regurgitant Jets Negatively Influence Left Ventricular Blood Flow-Insights From 4D Flow MRI Animal Study.

Objectives: Paravalvular leakage (PVL) and eccentric aortic regurgitation remain a major clinical concern in patients receiving transcatheter aortic valve replacement (TAVR), and regurgitant volume remains the main readout parameter in clinical assessment. In this work we investigate the effect of jet origin and trajectory of mild aortic regurgitation on left ventricular hemodynamics in a porcine model. Methods: A pig model of mild aortic regurgitation/PVL was established by transcatheter piercing and dilating the non-coronary (NCC) or right coronary cusp (RCC) of the aortic valve close to the valve annulus. The interaction between regurgitant blood and LV hemodynamics was assessed by 4D flow cardiovascular MRI. Results: Six RCC, six NCC, and two control animals were included in the study and with one dropout in the NCC group, the success rate of model creation was 93%. Regurgitant jets originating from NCC were directed along the ventricular side of the anterior mitral leaflet and integrated well into the diastolic vortex forming in the left ventricular outflow tract. However, jets from the RCC were orientated along the septum colliding with flow within the vortex, and progressing down to the apex. As a consequence, the presence as well as the area of the vortex was reduced at the site of impact compared to the NCC group. Impairment of vortex formation was localized to the area of impact and not the entire vortex ring. Blood from the NCC jet was largely ejected during the following systole, whereas ejection of large portion of RCC blood was protracted. Conclusions: Even for mild regurgitation, origin and trajectory of the regurgitant jet does cause a different effect on LV hemodynamics. Septaly oriented jets originating from RCC collide with the diastolic vortex, reduce its size, and reach the apical region of the left ventricle where blood resides extendedly. Hence, RCC jets display hemodynamic features which may have a potential negative impact on the long-term burden to the heart.

A 3D personalized cardiac myocyte aggregate orientation model using MRI data-driven low-rank basis functions.

Cardiac myocyte aggregate orientation has a strong impact on cardiac electrophysiology and mechanics. Studying the link between structural characteristics, strain, and stresses over the cardiac cycle and cardiac function requires a full volumetric representation of the microstructure. In this work, we exploit the structural similarity across hearts to extract a low-rank representation of predominant myocyte orientation in the left ventricle from high-resolution magnetic resonance ex-vivo cardiac diffusion tensor imaging (cDTI) in porcine hearts. We compared two reduction methods, Proper Generalized Decomposition combined with Singular Value Decomposition and Proper Orthogonal Decomposition. We demonstrate the existence of a general set of basis functions of aggregated myocyte orientation which defines a data-driven, personalizable, parametric model featuring higher flexibility than existing atlas and rule-based approaches. A more detailed representation of microstructure matching the available patient data can improve the accuracy of personalized computational models. Additionally, we approximate the myocyte orientation of one ex-vivo human heart and demonstrate the feasibility of transferring the basis functions to humans.

Investigating the reference domain influence in personalised models of cardiac mechanics : Effect of unloaded geometry on cardiac biomechanics.

A major concern in personalised models of heart mechanics is the unknown zero-pressure domain, a prerequisite for accurately predicting cardiac biomechanics. As the reference configuration cannot be captured by clinical data, studies often employ in-vivo frames which are unlikely to correspond to unloaded geometries. Alternatively, zero-pressure domain is approximated through inverse methodologies, which, however, entail assumptions pertaining to boundary conditions and material parameters. Both approaches are likely to introduce biases in estimated biomechanical properties; nevertheless, quantification of these effects is unattainable without ground-truth data. In this work, we assess the unloaded state influence on model-derived biomechanics, by employing an in-silico modelling framework relying on experimental data on porcine hearts. In-vivo images are used for model personalisation, while in-situ experiments provide a reliable approximation of the reference domain, creating a unique opportunity for a validation study. Personalised whole-cycle cardiac models are developed which employ different reference domains (image-derived, inversely estimated) and are compared against ground-truth model outcomes. Simulations are conducted with varying boundary conditions, to investigate the effect of data-derived constraints on model accuracy. Attention is given to modelling the influence of the ribcage on the epicardium, due to its close proximity to the heart in the porcine anatomy. Our results find merit in both approaches for dealing with the unknown reference domain, but also demonstrate differences in estimated biomechanical quantities such as material parameters, strains and stresses. Notably, they highlight the importance of a boundary condition accounting for the constraining influence of the ribcage, in forward and inverse biomechanical models.

Acute Microstructural Changes after ST-Segment Elevation Myocardial Infarction Assessed with Diffusion Tensor Imaging.

Background Cardiac diffusion tensor imaging (cDTI) allows for in vivo characterization of myocardial microstructure. In cDTI, mean diffusivity and fractional anisotropy (FA)-markers of magnitude and anisotropy of diffusion of water molecules-are known to change after myocardial infarction. However, little is known about regional changes in helix angle (HA) and secondary eigenvector angle (E2A), which reflects orientations of laminar sheetlets, and their association with long-term recovery of left ventricular ejection fraction (LVEF). Purpose To assess serial changes in cDTI biomarkers in participants following ST-segment elevation myocardial infarction (STEMI) and to determine their associations with long-term left ventricular remodeling. Materials and Methods In this prospective study, 30 participants underwent cardiac MRI (3 T) after STEMI at 5 days and 3 months after reperfusion (National Institute of Health Research study no. 33963 and Research Ethics no. REC17/YH/0062). Spin-echo cDTI with second-order motion-compensation (approximate duration, 13 minutes; three sections; 18 noncollinear diffusion-weighted scans with b values of 100 sec/mm2 [three acquisitions], 200 sec/mm2 [three acquisitions], and 500 sec/mm2 [12 acquisitions]), functional images, and late gadolinium enhancement images were obtained. Multiple regression analysis was used to assess associations between acute cDTI parameters and 3-month LVEF. Results Acutely infarcted myocardium had reduced FA, E2A, and myocytes with right-handed orientation (RHM) on HA maps compared with remote myocardium (mean remote FA = 0.36 ± 0.02 [standard deviation], mean infarcted FA = 0.25 ± 0.03, P < .001; mean remote E2A = 55° ± 9, mean infarcted E2A = 49° ± 10, P < .001; mean remote RHM = 16% ± 6, mean infarcted RHM = 9% ± 5, P < .001). All three parameters (FA, E2A, and RHM) correlated with 3-month LVEF (r = 0.68, r = 0.59, and r = 0.53, respectively), with acute FA being independently predictive of 3-month LVEF (standardized ß = 0.56, P = .008) after multivariable analysis adjusting for factors, including acute LVEF and infarct size. Conclusion After ST-segment elevation myocardial infarction, diffusion becomes more isotropic in acutely infarcted myocardium as reflected by decreased fractional anisotropy. Reductions in secondary eigenvector angle suggest that the myocardial sheetlets are unable to adopt their usual steep orientations in systole, whereas reductions in myocytes with right-handed orientation on helix angle maps are likely reflective of a loss of organization among subendocardial myocytes. Correlations between these parameters and 3-month left ventricular ejection fraction highlight the potential clinical use of cardiac diffusion tensor imaging after myocardial infarction in predicting long-term remodeling. © RSNA, 2021 Online supplemental material is available for this article.