Diffusion Tensor Cardiovascular Magnetic Resonance Imaging

Cardiac Magnetic Resonance Evaluation of LV Remodeling Post-Myocardial Infarction: Prognosis, Monitoring and Trial Endpoints

Adverse left ventricular remodeling (ALVR) and subsequent heart failure after myocardial infarction (MI) remain a major cause of patient morbidity and mortality worldwide. Overt inflammation has been identified as the common pathway underlying myocardial fibrosis and development of ALVR post-MI. With its ability to simultaneously provide information about cardiac structure, function, perfusion, and tissue characteristics, cardiac magnetic resonance (CMR) is well poised to inform prognosis and guide early surveillance and therapeutics in high-risk cohorts. Further, established and evolving CMR-derived biomarkers may serve as clinical endpoints in prospective trials evaluating the efficacy of novel anti-inflammatory and antifibrotic therapies. This review provides an overview of post-MI ALVR and illustrates how CMR may help clinical adoption of novel therapies via mechanistic or prognostic imaging markers.

Second-Order Motion-Compensated Echo-Planar Cardiac Diffusion-Weighted MRI: Usefulness of Compressed Sensitivity Encoding

BACKGROUND

Cardiac diffusion-weighted imaging (DWI) using second-order motion-compensated spin echo (M2C) can provide noninvasive in-vivo microstructural assessment, but limited by relatively low signal-to-noise ratio (SNR). Echo-planar imaging (EPI) with compressed sensitivity encoding (EPICS) could address these issues.

PURPOSE

To combine M2C DWI and EPCIS (M2C EPICS DWI), and compare image quality for M2C DWI.

STUDY TYPE

Prospective.

POPULATION

Ten ex-vivo hearts, 10 healthy volunteers (females, 5 [50%]; mean ± SD of age, 25 ± 4 years), and 12 patients with diseased hearts (female, 1 [8.3%]; mean ± SD of age, 44 ± 16 years; including coronary artery heart disease, congenital heart disease, dilated cardiomyopathy, amyloidosis, and myocarditis).

FIELD STRENGTH/SEQUENCE

3-T, M2C EPICS DWI, and M2C DWI.

ASSESSMENT

The apparent SNR (aSNR) and the rating scores were used to evaluate and compared image quality of all three groups. The aSNR was calculated usingaSNR = Mean intensity myocardium / Standard deviation myocardium $$ \mathrm{aSNR}={\mathrm{Mean}\ \mathrm{intensity}}_{\mathrm{myocardium}}/{\mathrm{Standard}\ \mathrm{deviation}}_{\mathrm{myocardium}} $$ , and the myocardium was segmented manually. Three observers independently rated subjective image quality using a 5-point Likert scale.

STATISTICAL TESTS

Bland-Altman analysis and paired t-tests. The threshold for statistical significance was set at P < 0.05.

RESULTS

In healthy volunteers, the aSNR with a b-value of 450 s/mm2 acquired by M2C EPICS DWI was significantly higher than M2C DWI at in-plane resolutions of 3.0 × 3.0, 2.5 × 2.5, and 2.0 × 2.0 mm2. In patients with diseased hearts, the aSNR ofM2C EPICS DWI was also significantly higher than that for M2C DWI (bias of M2C EPICS-M2C = 1.999, 95% limits of agreement, 0.362 to 3.636; mean ± SD, 7.80 ± 1.37 vs. 5.80 ± 0.81). The ADC values of M2C EPICS was significantly higher than M2C DWI in in-vivo hearts. Over 80% of the images with rating scores for M2C EPICS DWI were higher than M2C DWI in in-vivo hearts.

DATA CONCLUSION

Cardiac imaging by M2C EPICS DWI may demonstrate better overall image quality and higher aSNR than M2C DWI.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Back to the basics: The need for an etiological classification of chronic heart failure

The left ventricular (LV) ejection fraction (LVEF), despite its severe limitations, has had an epicentral role in heart failure (HF) classification, management, and risk stratification for decades. The major argument favoring the LVEF based HF classification has been that it defines groups of patients in which treatment is effective. However, this reasoning has recently collapsed, since medical treatment with neurohormonal inhibitors, has proved beneficial in most HF patients regardless of the LVEF. In addition, there has been compelling evidence, that the LVEF provides poor guidance for device treatment of chronic HF (implantation of cardioverter defibrillator, cardiac resynchronization therapy) since sudden cardiac death may occur and cardiac dyssynchronization may be disastrous in all HF patients. The same holds true for LV assist device implantation, in which the LVEF has been used as a surrogate for LV size. In this review article we update the evidence questioning the use of LVEF-based HF classification and argue that guidance of chronic HF treatment should transition to more contemporary concepts. Specifically, we propose an etiologic chronic HF classification predominantly based on epidemiological data, which will be foundational for further higher resolution phenotyping in the emerging era of precision medicine.

Deep learning-based diffusion tensor cardiac magnetic resonance reconstruction: a comparison study

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.

Mapping microarchitectural degeneration in the dilated ascending aorta with ex vivo diffusion tensor imaging

Aims

Thoracic aortic aneurysms (TAAs) carry a risk of catastrophic dissection. Current strategies to evaluate this risk entail measuring aortic diameter but do not image medial degeneration, the cause of TAAs. We sought to determine if the advanced magnetic resonance imaging (MRI) acquisition strategy, diffusion tensor imaging (DTI), could delineate medial degeneration in the ascending thoracic aorta.

Methods and results

Porcine ascending aortas were subjected to enzyme microinjection, which yielded local aortic medial degeneration. These lesions were detected by DTI, using a 9.4 T MRI scanner, based on tensor disorientation, disrupted diffusion tracts, and altered DTI metrics. High-resolution spatial analysis revealed that fractional anisotropy positively correlated, and mean and radial diffusivity inversely correlated, with smooth muscle cell (SMC) and elastin content (P < 0.001 for all). Ten operatively harvested human ascending aorta samples (mean subject age 61.6 ± 13.3 years, diameter range 29-64 mm) showed medial pathology that was more diffuse and more complex. Nonetheless, DTI metrics within an aorta spatially correlated with SMC, elastin, and, especially, glycosaminoglycan (GAG) content. Moreover, there were inter-individual differences in slice-averaged DTI metrics. Glycosaminoglycan accumulation and elastin degradation were captured by reduced fractional anisotropy (R2 = 0.47, P = 0.043; R2 = 0.76, P = 0.002), with GAG accumulation also captured by increased mean diffusivity (R2 = 0.46, P = 0.045) and increased radial diffusivity (R2 = 0.60, P = 0.015).

Conclusion

Ex vivo high-field DTI can detect ascending aorta medial degeneration and can differentiate TAAs in accordance with their histopathology, especially elastin and GAG changes. This non-destructive window into aortic medial microstructure raises prospects for probing the risks of TAAs beyond lumen dimensions.

Novel Imaging Approaches to Cardiac Manifestations of Systemic Inflammatory Diseases: JACC Scientific Statement

Derangements in the innate and adaptive immune responses observed in systemic inflammatory syndromes contributes to unique elevated atherosclerotic risk and incident cardiovascular disease. Novel multimodality imaging techniques may improve diagnostic precision for the screening and monitoring of disease activity. The integrated application of these technologies lead to earlier diagnosis and noninvasive monitoring of cardiac involvement in systemic inflammatory diseases that will aid in preclinical studies, enhance patient selection, and provide surrogate endpoints in clinical trials, thereby improving clinical outcomes. We review the common cardiovascular manifestations of immune-mediated systemic inflammatory diseases and address the clinical and investigational role of advanced multimodality cardiac imaging.

Mimicking Transmural Helical Cardiomyofibre Orientation Using Bouligand-like Pore Structures in Ice-Templated Collagen Scaffolds

The helical arrangement of cardiac muscle fibres underpins the contractile properties of the heart chamber. Across the heart wall, the helical angle of the aligned fibres changes gradually across the range of 90-180°. It is essential to recreate this structural hierarchy in vitro for developing functional artificial tissue. Ice templating can achieve single-oriented pore alignment via unidirectional ice solidification with a flat base mould design. We hypothesise that the orientation of aligned pores can be controlled simply via base topography, and we propose a scalable base design to recapitulate the transmural fibre orientation. We have utilised finite element simulations for rapid testing of base designs, followed by experimental confirmation of the Bouligand-like orientation. X-ray microtomography of experimental samples showed a gradual shift of 106 ± 10°, with the flexibility to tailor pore size and spatial helical angle distribution for personalised medicine.

Realistic numerical simulations of diffusion tensor cardiovascular magnetic resonance: The effects of perfusion and membrane permeability

PURPOSE

To study the sensitivity of diffusion tensor cardiovascular magnetic resonance (DT-CMR) to microvascular perfusion and changes in cell permeability.

METHODS

Monte 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).

RESULTS

Reducing 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).

CONCLUSION

The 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.

Phenotyping heart failure by cardiac magnetic resonance imaging of cardiac macro- and microscopic structure: state of the art review

Heart failure demographics have evolved in past decades with the development of improved diagnostics, therapies, and prevention. Cardiac magnetic resonance (CMR) has developed in a similar timeframe to become the gold-standard non-invasive imaging modality for characterizing diseases causing heart failure. CMR techniques to assess cardiac morphology and function have progressed since their first use in the 1980s. Increasingly efficient acquisition protocols generate high spatial and temporal resolution images in less time. This has enabled new methods of characterizing cardiac systolic and diastolic function such as strain analysis, exercise real-time cine imaging and four-dimensional flow. A key strength of CMR is its ability to non-invasively interrogate the myocardial tissue composition. Gadolinium contrast agents revolutionized non-invasive cardiac imaging with the late gadolinium enhancement technique. Further advances enabled quantitative parametric mapping to increase sensitivity at detecting diffuse pathology. Novel methods such as diffusion tensor imaging and artificial intelligence-enhanced image generation are on the horizon. Magnetic resonance spectroscopy (MRS) provides a window into the molecular environment of the myocardium. Phosphorus (31P) spectroscopy can inform the status of cardiac energetics in health and disease. Proton (1H) spectroscopy complements this by measuring creatine and intramyocardial lipids. Hyperpolarized carbon (13C) spectroscopy is a novel method that could further our understanding of dynamic cardiac metabolism. CMR of other organs such as the lungs may add further depth into phenotypes of heart failure. The vast capabilities of CMR should be deployed and interpreted in context of current heart failure challenges.

Assessment of Microvascular Disease in Heart and Brain by MRI: Application in Heart Failure with Preserved Ejection Fraction and Cerebral Small Vessel Disease

The objective of this review is to investigate the commonalities of microvascular (small vessel) disease in heart failure with preserved ejection fraction (HFpEF) and cerebral small vessel disease (CSVD). Furthermore, the review aims to evaluate the current magnetic resonance imaging (MRI) diagnostic techniques for both conditions. By comparing the two conditions, this review seeks to identify potential opportunities to improve the understanding of both HFpEF and CSVD.

Physical model of end-diastolic and end-systolic pressure-volume relationships of a heart

Left ventricular stiffness and contractility, characterized by the end-diastolic pressure-volume relationship (EDPVR) and the end-systolic pressure-volume relationship (ESPVR), are two important indicators of the performance of the human heart. Although much research has been conducted on EDPVR and ESPVR, no model with physically interpretable parameters combining both relationships has been presented, thereby impairing the understanding of cardiac physiology and pathology. Here, we present a model that evaluates both EDPVR and ESPVR with physical interpretations of the parameters in a unified framework. Our physics-based model fits the available experimental data and in silico results very well and outperforms existing models. With prescribed parameters, the new model is used to predict the pressure-volume relationships of the left ventricle. Our model provides a deeper understanding of cardiac mechanics and thus will have applications in cardiac research and clinical medicine.

Cardiovascular magnetic resonance imaging in myocardial involvement of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder that primarily affects young women. Myocardial involvement in SLE frequently occurs and it is rather challenging to make the diagnosis in current clinical settings, mainly due to the extensive clinical presentation of signs and symptoms. As a noninvasive imaging reference in diagnosing cardiomyopathy and myocarditis, cardiovascular magnetic resonance (CMR) imaging can provide new insight into myocardial abnormalities including inflammation, fibrosis, and microcirculation. Therefore, the main aim of this work was to systematically review the pathology, clinical features, and diagnosis, while illustrating the clinical role of CMR on myocardial involvement of SLE.

Ultra-high field cardiac MRI in large animals and humans for translational cardiovascular research

A key step in translational cardiovascular research is the use of large animal models to better understand normal and abnormal physiology, to test drugs or interventions, or to perform studies which would be considered unethical in human subjects. Ultrahigh field magnetic resonance imaging (UHF-MRI) at 7 T field strength is becoming increasingly available for imaging of the heart and, when compared to clinically established field strengths, promises better image quality and image information content, more precise functional analysis, potentially new image contrasts, and as all in-vivo imaging techniques, a reduction of the number of animals per study because of the possibility to scan every animal repeatedly. We present here a solution to the dual use problem of whole-body UHF-MRI systems, which are typically installed in clinical environments, to both UHF-MRI in large animals and humans. Moreover, we provide evidence that in such a research infrastructure UHF-MRI, and ideally combined with a standard small-bore UHF-MRI system, can contribute to a variety of spatial scales in translational cardiovascular research: from cardiac organoids, Zebra fish and rodent hearts to large animal models such as pigs and humans. We present pilot data from serial CINE, late gadolinium enhancement, and susceptibility weighted UHF-MRI in a myocardial infarction model over eight weeks. In 14 pigs which were delivered from a breeding facility in a national SARS-CoV-2 hotspot, we found no infection in the incoming pigs. Human scanning using CINE and phase contrast flow measurements provided good image quality of the left and right ventricle. Agreement of functional analysis between CINE and phase contrast MRI was excellent. MRI in arrested hearts or excised vascular tissue for MRI-based histologic imaging, structural imaging of myofiber and vascular smooth muscle cell architecture using high-resolution diffusion tensor imaging, and UHF-MRI for monitoring free radicals as a surrogate for MRI of reactive oxygen species in studies of oxidative stress are demonstrated. We conclude that UHF-MRI has the potential to become an important precision imaging modality in translational cardiovascular research.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Application of postmortem imaging modalities in cases of sudden death due to cardiovascular diseases-current achievements and limitations from a pathology perspective : Endorsed by the Association for European Cardiovascular Pathology and by the International Society of Forensic Radiology and Imaging

Postmortem imaging (PMI) is increasingly used in postmortem practice and is considered a potential alternative to a conventional autopsy, particularly in case of sudden cardiac deaths (SCD). In 2017, the Association for European Cardiovascular Pathology (AECVP) published guidelines on how to perform an autopsy in such cases, which is still considered the gold standard, but the diagnostic value of PMI herein was not analyzed in detail. At present, significant progress has been made in the PMI diagnosis of acute ischemic heart disease, the most important cause of SCD, while the introduction of postmortem CT angiography (PMCTA) has improved the visualization of several parameters of coronary artery pathology that can support a diagnosis of SCD. Postmortem magnetic resonance (PMMR) allows the detection of acute myocardial injury-related edema. However, PMI has limitations when compared to clinical imaging, which severely impacts the postmortem diagnosis of myocardial injuries (ischemic versus non-ischemic), the age-dating of coronary occlusion (acute versus old), other potentially SCD-related cardiac lesions (e.g., the distinctive morphologies of cardiomyopathies), aortic diseases underlying dissection or rupture, or pulmonary embolism. In these instances, PMI cannot replace a histopathological examination for a final diagnosis. Emerging minimally invasive techniques at PMI such as image-guided biopsies of the myocardium or the aorta, provide promising results that warrant further investigations. The rapid developments in the field of postmortem imaging imply that the diagnosis of sudden death due to cardiovascular diseases will soon require detailed knowledge of both postmortem radiology and of pathology.

Accelerating Cardiac Diffusion Tensor Imaging With a U-Net Based Model: Toward Single Breath-Hold

BACKGROUND

In vivo cardiac diffusion tensor imaging (cDTI) characterizes myocardial microstructure. Despite its potential clinical impact, considerable technical challenges exist due to the inherent low signal-to-noise ratio.

PURPOSE

To reduce scan time toward one breath-hold by reconstructing diffusion tensors for in vivo cDTI with a fitting-free deep learning approach.

STUDY TYPE

Retrospective.

POPULATION

A total of 197 healthy controls, 547 cardiac patients.

FIELD STRENGTH/SEQUENCE

A 3 T, diffusion-weighted stimulated echo acquisition mode single-shot echo-planar imaging sequence.

ASSESSMENT

A U-Net was trained to reconstruct the diffusion tensor elements of the reference results from reduced datasets that could be acquired in 5, 3 or 1 breath-hold(s) (BH) per slice. Fractional anisotropy (FA), mean diffusivity (MD), helix angle (HA), and sheetlet angle (E2A) were calculated and compared to the same measures when using a conventional linear-least-square (LLS) tensor fit with the same reduced datasets. A conventional LLS tensor fit with all available data (12 ± 2.0 [mean ± sd] breath-holds) was used as the reference baseline.

STATISTICAL TESTS

Wilcoxon signed rank/rank sum and Kruskal-Wallis tests. Statistical significance threshold was set at P = 0.05. Intersubject measures are quoted as median [interquartile range].

RESULTS

For global mean or median results, both the LLS and U-Net methods with reduced datasets present a bias for some of the results. For both LLS and U-Net, there is a small but significant difference from the reference results except for LLS: MD 5BH (P = 0.38) and MD 3BH (P = 0.09). When considering direct pixel-wise errors the U-Net model outperformed significantly the LLS tensor fit for reduced datasets that can be acquired in three or just one breath-hold for all parameters.

DATA CONCLUSION

Diffusion tensor prediction with a trained U-Net is a promising approach to minimize the number of breath-holds needed in clinical cDTI studies.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 1.

Quantitative susceptibility mapping (QSM) of the cardiovascular system: challenges and perspectives

Quantitative susceptibility mapping (QSM) is a powerful, non-invasive, magnetic resonance imaging (MRI) technique that relies on measurement of magnetic susceptibility. So far, QSM has been employed mostly to study neurological disorders characterized by iron accumulation, such as Parkinson's and Alzheimer's diseases. Nonetheless, QSM allows mapping key indicators of cardiac disease such as blood oxygenation and myocardial iron content. For this reason, the application of QSM offers an unprecedented opportunity to gain a better understanding of the pathophysiological changes associated with cardiovascular disease and to monitor their evolution and response to treatment. Recent studies on cardiovascular QSM have shown the feasibility of a non-invasive assessment of blood oxygenation, myocardial iron content and myocardial fibre orientation, as well as carotid plaque composition. Significant technical challenges remain, the most evident of which are related to cardiac and respiratory motion, blood flow, chemical shift effects and susceptibility artefacts. Significant work is ongoing to overcome these challenges and integrate the QSM technique into clinical practice in the cardiovascular field.

Evaluation of Right Ventricular Function and Myocardial Microstructure in Fetal Hypoplastic Left Heart Syndrome

Right ventricular (RV) function is one of the critical factors affecting the prognosis of fetuses with hypoplastic left heart syndrome (HLHS). Our study objectives included assessment of cardiac function and comprehensive measurement of cardiac microstructure. We retrospectively studied 42 fetuses diagnosed as HLHS by echocardiography. Myocardial deformation of the right ventricular wall was calculated automatically in offline software. Postmortem cardiac imaging for three control fetal hearts and four HLHS specimens was performed by a 9.4T DTI scanner. Myocardial deformation parameters of the RV (including strain, strain rate, and velocity) were significantly lower in HLHS fetuses (all p < 0.01). FA values increased (0.18 ± 0.01 vs. 0.21 ± 0.02; p < 0.01) in HLHS fetuses, but MD reduced (1.3 ± 0.15 vs. 0.88 ± 0.13; p < 0.001). The HLHS fetuses’ RV lateral base wall (−7.31 ± 51.91 vs. −6.85 ± 31.34; p = 0.25), middle wall (1.71 ± 50.92 vs. −9.38 ± 28.18; p < 0.001), and apical wall (−6.19 ± 46.61 vs. −11.16 ± 29.86, p < 0.001) had HA gradient ascent but HA gradient descent in the anteroseptal wall (p < 0.001) and inferoseptal wall (p < 0.001). RV basal lateral wall HA degrees were correlated with RVGLS (R2 = 0.97, p = 0.02). MD values were positively correlated with RVGLS (R2 = 0.93, p = 0.04). Our study found morphological and functional changes of the RV in HLHS fetuses, and cardiac function was related to the orientation patterns of myocardial fibers. It may provide insight into understanding the underlying mechanisms of impaired RV performance in HLHS.

The role of cardiac magnetic resonance imaging in the assessment of heart failure with preserved ejection fraction

Heart failure (HF) is a major cause of morbidity and mortality worldwide. Current classifications of HF categorize patients with a left ventricular ejection fraction of 50% or greater as HF with preserved ejection fraction or HFpEF. Echocardiography is the first line imaging modality in assessing diastolic function given its practicality, low cost and the utilization of Doppler imaging. However, the last decade has seen cardiac magnetic resonance (CMR) emerge as a valuable test for the sometimes challenging diagnosis of HFpEF. The unique ability of CMR for myocardial tissue characterization coupled with high resolution imaging provides additional information to echocardiography that may help in phenotyping HFpEF and provide prognostication for patients with HF. The precision and accuracy of CMR underlies its use in clinical trials for the assessment of novel and repurposed drugs in HFpEF. Importantly, CMR has powerful diagnostic utility in differentiating acquired and inherited heart muscle diseases presenting as HFpEF such as Fabry disease and amyloidosis with specific treatment options to reverse or halt disease progression. This state of the art review will outline established CMR techniques such as transmitral velocities and strain imaging of the left ventricle and left atrium in assessing diastolic function and their clinical application to HFpEF. Furthermore, it will include a discussion on novel methods and future developments such as stress CMR and MR spectroscopy to assess myocardial energetics, which show promise in unraveling the mechanisms behind HFpEF that may provide targets for much needed therapeutic interventions.

Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics

Personalized computational cardiac models are considered to be a unique and powerful tool in modern cardiology, integrating the knowledge of physiology, pathology and fundamental laws of mechanics in one framework. They have the potential to improve risk prediction in cardiac patients and assist in the development of new treatments. However, in order to use these models for clinical decision support, it is important that both the impact of model parameter perturbations on the predicted quantities of interest as well as the uncertainty of parameter estimation are properly quantified, where the first task is a priori in nature (meaning independent of any specific clinical data), while the second task is carried out a posteriori (meaning after specific clinical data have been obtained). The present study addresses these challenges for a widely used constitutive law of passive myocardium (the Holzapfel-Ogden model), using global sensitivity analysis (SA) to address the first challenge, and inverse-uncertainty quantification (I-UQ) for the second challenge. The SA is carried out on a range of different input parameters to a left ventricle (LV) model, making use of computationally efficient Gaussian process (GP) surrogate models in place of the numerical forward simulator. The results of the SA are then used to inform a low-order reparametrization of the constitutive law for passive myocardium under consideration. The quality of this parameterization in the context of an inverse problem having observed noisy experimental data is then quantified with an I-UQ study, which again makes use of GP surrogate models. The I-UQ is carried out in a Bayesian manner using Markov Chain Monte Carlo, which allows for full uncertainty quantification of the material parameter estimates. Our study reveals insights into the relation between SA and I-UQ, elucidates the dependence of parameter sensitivity and estimation uncertainty on external factors, like LV cavity pressure, and sheds new light on cardio-mechanic model formulation, with particular focus on the Holzapfel-Ogden myocardial model.

Assessment of Myocardial Microstructure in a Murine Model of Obesity-Related Cardiac Dysfunction by Diffusion Tensor Magnetic Resonance Imaging at 7T

Background

Obesity exerts multiple deleterious effects on the heart that may ultimately lead to cardiac failure. This study sought to characterize myocardial microstructure and function in an experimental model of obesity-related cardiac dysfunction.

Methods

Male C57BL/6N mice were fed either a high-fat diet (HFD; 60 kcal% fat, n = 12) or standard control diet (9 kcal% fat, n = 10) for 15 weeks. At the end of the study period, cardiac function was assessed by ultra-high frequency echocardiography, and hearts were processed for further analyses. The three-dimensional myocardial microstructure was examined ex vivo at a spatial resolution of 100 × 100 × 100 μm3 by diffusion tensor magnetic resonance imaging (DT-MRI) at 7T. Myocardial deformation, diffusion metrics and fiber tract geometry were analyzed with respect to the different myocardial layers (subendocardium/subepicardium) and segments (base/mid-cavity/apex). Results were correlated with blood sample analyses, histopathology, and gene expression data.

Results

HFD feeding induced significantly increased body weight combined with a pronounced accumulation of visceral fat (body weight 42.3 ± 5.7 vs. 31.5 ± 2.2 g, body weight change 73.7 ± 14.8 vs. 31.1 ± 6.6%, both P &lt; 0.001). Obese mice showed signs of diastolic dysfunction, whereas left-ventricular ejection fraction and fractional shortening remained unchanged (E/e’ 41.6 ± 16.6 vs. 24.8 ± 6.0, P &lt; 0.01; isovolumic relaxation time 19 ± 4 vs. 14 ± 4 ms, P &lt; 0.05). Additionally, global longitudinal strain was reduced in the HFD group (−15.1 ± 3.0 vs. −20.0 ± 4.6%, P = 0.01), which was mainly driven by an impairment in basal segments. However, histopathology and gene expression analyses revealed no myocardial fibrosis or differences in cardiomyocyte morphology. Mean diffusivity and eigenvalues of the diffusion tensor were lower in the basal subepicardium of obese mice as assessed by DT-MRI (P &lt; 0.05). The three-dimensional fiber tract arrangement of the left ventricle (LV) remained preserved.

Conclusion

Fifteen weeks of high-fat diet induced alterations in myocardial diffusion properties in mice, whereas no remodeling of the three-dimensional myofiber arrangement of the LV was observed. Obese mice showed reduced longitudinal strain and lower mean diffusivity predominantly in the left-ventricular base, and further investigation into the significance of this regional pattern is required.

Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications

Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid-structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.

The Utility of Advanced Cardiovascular Imaging in Cancer Patients-When, Why, How, and the Latest Developments

Cardio-oncology encompasses the risk stratification, prognostication, identification and management of cancer therapeutics related cardiac dysfunction (CTRCD). Cardiovascular imaging (CVI) plays a significant role in each of these scenarios and has broadened from predominantly quantifying left ventricular function (specifically ejection fraction) to the identification of earlier bio-signatures of CTRCD. Recent data also demonstrate the impact of chemotherapy on the right ventricle, left atrium and pericardium and highlight a possible role for CVI in the identification of CTRCD through tissue characterization and assessment of these cardiac chambers. This review aims to provide a contemporary perspective on the role of multi-modal advanced cardiac imaging in cardio-oncology.

Role of cardiovascular magnetic resonance imaging in cardio-oncology

Advances in cancer therapy have led to significantly longer cancer-free survival times over the last 40 years. Improved survivorship coupled with increasing recognition of an expanding range of adverse cardiovascular effects of many established and novel cancer therapies has highlighted the impact of cardiovascular disease in this population. This has led to the emergence of dedicated cardio-oncology services that can provide pre-treatment risk stratification, surveillance, diagnosis, and monitoring of cardiotoxicity during cancer therapies, and late effects screening following completion of treatment. Cardiovascular imaging and the development of imaging biomarkers that can accurately and reliably detect pre-clinical disease and enhance our understanding of the underlying pathophysiology of cancer treatment-related cardiotoxicity are becoming increasingly important. Multi-parametric cardiovascular magnetic resonance (CMR) is able to assess cardiac structure, function, and provide myocardial tissue characterization, and hence can be used to address a variety of important clinical questions in the emerging field of cardio-oncology. In this review, we discuss the current and potential future applications of CMR in the investigation and management of cancer patients.

Role of Cardiac Magnetic Resonance Imaging in Heart Failure

This review describes the current role and potential future applications of cardiac magnetic resonance (CMR) for the management of heart failure (HF). CMR allows noninvasive morphologic and functional assessment, tissue characterization, blood flow, and perfusion evaluation. CMR overcomes echocardiography limitations (geometric assumptions, interobserver variability and poor acoustic window) and provides incremental information in relation to cause, prognosis, and treatment monitoring of patients with HF.

Cardiac magnetic resonance imaging: insights into developmental programming and its consequences for aging

Cardiovascular diseases (CVD) are important consequences of adverse perinatal conditions such as fetal hypoxia and maternal malnutrition. Cardiac magnetic resonance imaging (CMR) can produce a wealth of physiological information related to the development of the heart. This review outlines the current state of CMR technologies and describes the physiological biomarkers that can be measured. These phenotypes include impaired ventricular and atrial function, maladaptive ventricular remodeling, and the proliferation of myocardial steatosis and fibrosis. The discussion outlines the applications of CMR to understanding the developmental pathways leading to impaired cardiac function. The use of CMR, both in animal models of developmental programming and in human studies, is described. Specific examples are given in a baboon model of intrauterine growth restriction (IUGR). CMR offers great potential as a tool for understanding the sequence of dysfunctional adaptations of developmental origin that can affect the human cardiovascular system.

Cardiovascular Magnetic Resonance for the Differentiation of Left Ventricular Hypertrophy

PURPOSE OF REVIEW

Left ventricular hypertrophy (LVH) is a common presentation encountered in clinical practice with a diverse range of potential aetiologies. Differentiation of pathological from physiological hypertrophy can be challenging but is crucial for further management and prognostication. Cardiovascular magnetic resonance (CMR) with advanced myocardial tissue characterisation is a powerful tool that may help to differentiate these aetiologies in the assessment of LVH.

RECENT FINDINGS

The use of CMR for detailed morphological assessment of LVH is well described. More recently, advanced CMR techniques (late gadolinium enhancement, parametric mapping, diffusion tensor imaging, and myocardial strain) have been used. These techniques are highly promising in helping to differentiate key aetiologies of LVH and provide valuable prognostic information. Recent advancements in CMR tissue characterisation, such as parametric mapping, in combination with detailed morphological assessment and late gadolinium enhancement, provide a powerful resource that may help assess and differentiate important causes of LVH.