MULTIMODAL LEARNING TO IMPROVE CARDIAC LATE MECHANICAL ACTIVATION DETECTION FROM CINE MR IMAGES.

This paper presents a multimodal deep learning framework that utilizes advanced image techniques to improve the performance of clinical analysis heavily dependent on routinely acquired standard images. More specifically, we develop a joint learning network that for the first time leverages the accuracy and reproducibility of myocardial strains obtained from Displacement Encoding with Stimulated Echo (DENSE) to guide the analysis of cine cardiac magnetic resonance (CMR) imaging in late mechanical activation (LMA) detection. An image registration network is utilized to acquire the knowledge of cardiac motions, an important feature estimator of strain values, from standard cine CMRs.

Fatty acid composition MRI of epicardial adipose tissue: Methods and detection of proinflammatory biomarkers in ST-segment elevation myocardial infarction patients.

Purpose: To develop a method for quantifying the fatty acid composition (FAC) of human epicardial adipose tissue (EAT) using accelerated MRI and identify its potential for detecting proinflammatory biomarkers in patients with ST-segment elevation myocardial infarction (STEMI).

Methods: A multi-echo radial gradient-echo sequence was developed for accelerated imaging during a breath hold using a locally low-rank denoising technique to reconstruct undersampled images. FAC mapping was achieved by fitting the multi-echo images to a multi-resonance complex signal model based on triglyceride characterization.

In Vivo Quantification of Ascending Thoracic Aortic Aneurysm Wall Stretch Using MRI: Relationship to Repair Threshold Diameter and Ex Vivo Wall Failure Behavior.

Ascending thoracic aortic aneurysms (aTAAs) can lead to life-threatening dissection and rupture. Recent studies have highlighted aTAA mechanical properties as relevant factors associated with progression. The aim of this study was to quantify in vivo aortic wall stretch in healthy participants and aTAA patients using displacement encoding with stimulated echoes (DENSE) magnetic resonance imaging.

Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence-review of evidence and proposition of a roadmap to clinical translation.

Background: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently advancements in artificial intelligence (AI) technology have shown great potential to address many CMR limitations. While the developments are remarkable, translation of AI-based methods into real-world CMR clinical practice remains at a nascent stage and much work lies ahead to realize the full potential of AI for CMR.

Machine learning of ECG waveforms and cardiac magnetic resonance for response and survival after cardiac resynchronization therapy.

Cardiac resynchronization therapy (CRT) can lead to marked symptom reduction and improved survival in selected patients with heart failure with reduced ejection fraction (HFrEF); however, many candidates for CRT based on clinical guidelines do not have a favorable response. A better way to identify patients expected to benefit from CRT that applies machine learning to accessible and cost-effective diagnostic tools such as the 12-lead electrocardiogram (ECG) could have a major impact on clinical care in HFrEF by helping providers personalize treatment strategies and avoid delays in initiation of other potentially beneficial treatments. This study addresses this need by demonstrating that a novel approach to ECG waveform analysis using functional principal component decomposition (FPCD) performs better than measures that require manual ECG analysis with the human eye and also at least as well as a previously validated but more expensive approach based on cardiac magnetic resonance (CMR).

Diffusion Models To Predict 3D Late Mechanical Activation From Sparse 2D Cardiac MRIs.

Identifying regions of late mechanical activation (LMA) of the left ventricular (LV) myocardium is critical in determining the optimal pacing site for cardiac resynchronization therapy in patients with heart failure. Several deep learning-based approaches have been developed to predict 3D LMA maps of LV myocardium from a stack of sparse 2D cardiac magnetic resonance imaging (MRIs). However, these models often loosely consider the geometric shape structure of the myocardium.

Cardiometabolic biomarker patterns associated with cardiac MRI defined fibrosis and microvascular dysfunction in patients with heart failure with preserved ejection fraction.

Introduction: Heart failure with preserved ejection fraction (HFpEF) is a complex disease process influenced by metabolic disorders, systemic inflammation, myocardial fibrosis, and microvascular dysfunction. The goal of our study is to identify potential relationships between plasma biomarkers and cardiac magnetic resonance (CMR) imaging markers in patients with HFpEF.

Methods: Nineteen subjects with HFpEF and 15 age-matched healthy controls were enrolled and underwent multiparametric CMR and plasma biomarker analysis using the Olink® Cardiometabolic Panel (Olink Proteomics, Uppsala, Sweden).

Grand Challenges at the Interface of Engineering and Medicine.

Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution is now equipped at varying degrees of sophistication with the ability to monitor human health in both non-invasive and invasive modes. The multiple scales at which human physiology can be interrogated provide a profound perspective on health and disease.

Endurance Exercise Training Mitigates Diastolic Dysfunction in Diabetic Mice Independent of Phosphorylation of Ulk1 at S555.

Millions of diabetic patients suffer from cardiovascular complications. One of the earliest signs of diabetic complications in the heart is diastolic dysfunction. Regular exercise is a highly effective preventive/therapeutic intervention against diastolic dysfunction in diabetes, but the underlying mechanism(s) remain poorly understood.

Cardiovascular sequelae of trastuzumab and anthracycline in long-term survivors of breast cancer.

Objectives: Long-term follow-up of patients treated with trastuzumab largely focuses on those with reduced left ventricular ejection fraction (LVEF) on treatment completion. This study sought to evaluate the prevalence of cardiovascular risk factors, overt cardiovascular disease and cardiac imaging abnormalities using cardiac magnetic resonance (CMR), in participants with normal LVEF on completion of trastuzumab±anthracycline therapy at least 5 years previously.

Methods: Participants with human epidermal growth factor receptor 2-positive breast cancer treated with trastuzumab±anthracycline ≥5 years previously were identified from a clinical database.

Cardiac Magnetic Resonance, Electromechanical Activation, Kidney Function, and Natriuretic Peptides in Cardiac Resynchronization Therapy Upgrades.

As the mechanism for worse prognosis after cardiac resynchronization therapy (CRT) upgrades in heart failure patients with RVP dependence (RVP-HF) has clinical implications for patient selection and CRT implementation approaches, this study's objective was to evaluate prognostic implications of cardiac magnetic resonance (CMR) findings and clinical factors in 102 HF patients (23.5% female, median age 66.5 years old, median follow-up 4.

Erratum to "BME 2.0: Engineering the Future of Medicine".

[This corrects the article DOI: 10.34133/bmef.0001.

BME 2.0: Engineering the Future of Medicine.

If the 20th century was the age of mapping and controlling the external world, the 21st century is the biomedical age of mapping and controlling the biological internal world. The biomedical age is bringing new technological breakthroughs for sensing and controlling human biomolecules, cells, tissues, and organs, which underpin new frontiers in the biomedical discovery, data, biomanufacturing, and translational sciences. This article reviews what we believe will be the next wave of biomedical engineering (BME) education in support of the biomedical age, what we have termed BME 2.

Noninvasive Electrical Mapping Compared with the Paced QRS Complex for Optimizing CRT Programmed Settings and Predicting Multidimensional Response.

The aim was to test the hypothesis that left ventricular (LV) and right ventricular (RV) activation from body surface electrical mapping (CardioInsight 252-electrode vest, Medtronic) identifies optimal cardiac resynchronization therapy (CRT) pacing strategies and outcomes in 30 patients. The LV80, RV80, and BIV80 were defined as the times to 80% LV, RV, or biventricular electrical activation. Smaller differences in the LV80 and RV80 (|LV80-RV80|) with synchronized LV pacing predicted better LV function post-CRT (p = 0.

Obesity-Induced Coronary Microvascular Disease Is Prevented by iNOS Deletion and Reversed by iNOS Inhibition.

Coronary microvascular disease (CMD) caused by obesity and diabetes is major contributor to heart failure with preserved ejection fraction; however, the mechanisms underlying CMD are not well understood. Using cardiac magnetic resonance applied to mice fed a high-fat, high-sucrose diet as a model of CMD, we elucidated the role of inducible nitric oxide synthase (iNOS) and 1400W, an iNOS antagonist, in CMD. Global iNOS deletion prevented CMD along with the associated oxidative stress and diastolic and subclinical systolic dysfunction.

Progressive Cardiac Metabolic Defects Accompany Diastolic and Severe Systolic Dysfunction in Spontaneously Hypertensive Rat Hearts.

Background Cardiac metabolic abnormalities are present in heart failure. Few studies have followed metabolic changes accompanying diastolic and systolic heart failure in the same model. We examined metabolic changes during the development of diastolic and severe systolic dysfunction in spontaneously hypertensive rats (SHR).

Improved computation of Lagrangian tissue displacement and strain for cine DENSE MRI using a regularized spatiotemporal least squares method.

Introduction: In displacement encoding with stimulated echoes (DENSE), tissue displacement is encoded in the signal phase such that the phase of each pixel in space and time provides an independent measurement of absolute tissue displacement. Previously for DENSE, estimation of Lagrangian displacement used two steps: first a spatial interpolation and, second, least squares fitting through time to a Fourier or polynomial model. However, there is no strong rationale for such a through-time model.

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

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

Methods: The motion model includes conventional position shifts of magnetization and further describes the phase shift of the stimulated echo due to breathing. These image-domain effects correspond to linear and constant phase errors, respectively, in k-space.

Machine learning for multidimensional response and survival after cardiac resynchronization therapy using features from cardiac magnetic resonance.

Background: Cardiac resynchronization therapy (CRT) response is complex, and better approaches are required to predict survival and need for advanced therapies.

Objective: The objective was to use machine learning to characterize multidimensional CRT response and its relationship with long-term survival.

Methods: Associations of 39 baseline features (including cardiac magnetic resonance [CMR] findings and clinical parameters such as glomerular filtration rate [GFR]) with a multidimensional CRT response vector (consisting of post-CRT left ventricular end-systolic volume index [LVESVI] fractional change, post-CRT B-type natriuretic peptide, and change in peak VO) were evaluated.

Cardiac magnetic resonance defines mechanisms of sex-based differences in outcomes following cardiac resynchronization therapy.

Background: Mechanisms of sex-based differences in outcomes following cardiac resynchronization therapy (CRT) are poorly understood.

Objective: To use cardiac magnetic resonance (CMR) to define mechanisms of sex-based differences in outcomes after CRT and describe distinct CMR-based phenotypes of CRT candidates based on sex and non-ischemic/ischemic cardiomyopathy type.

Materials And Methods: In a prospective study, sex-based differences in three short-term CRT response measures [fractional change in left ventricular end-systolic volume index 6 months after CRT (LVESVI-FC), B-type natriuretic peptide (BNP) 6 months after CRT, change in peak VO 6 months after CRT], and long-term survival were evaluated with respect to 39 baseline parameters from CMR, exercise testing, laboratory testing, electrocardiograms, comorbid conditions, and other sources.

Accelerated fatty acid composition MRI of epicardial adipose tissue: Development and application to eplerenone treatment in a mouse model of obesity-induced coronary microvascular disease.

Purpose: To develop an accelerated MRI method to quantify the epicardial adipose tissue (EAT) fatty acid composition (FAC) and test the hypothesis that eplerenone (EPL) shifts the EAT FAC toward unsaturation in obese mice.

Methods: Undersampled multi-echo gradient echo imaging employing a dictionary-based compressed-sensing reconstruction and iterative decomposition with echo asymmetry and least-squares-based mapping (IDEAL) was developed, validated, and used to study EAT in obese mice scanned at 7T. Fully sampled and rate 2, 2.

A Slice-Low-Rank Plus Sparse (slice-L + S) Reconstruction Method for k-t Undersampled Multiband First-Pass Myocardial Perfusion MRI.

Purpose: The synergistic use of k-t undersampling and multiband (MB) imaging has the potential to provide extended slice coverage and high spatial resolution for first-pass perfusion MRI. The low-rank plus sparse (L + S) model has shown excellent performance for accelerating single-band (SB) perfusion MRI.

Methods: A MB data consistency method employing ESPIRiT maps and through-plane coil information was developed.

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.

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 (E), longitudinal (E) and radial (E) strain, torsion, and segmental E at multiple centers.

Cardiac Magnetic Resonance Assessment of Response to Cardiac Resynchronization Therapy and Programming Strategies.

Objectives: The objective was to determine the feasibility and effectiveness of cardiac magnetic resonance (CMR) cine and strain imaging before and after cardiac resynchronization therapy (CRT) for assessment of response and the optimal resynchronization pacing strategy.

Background: CMR with cardiac implantable electronic devices can safely provide high-quality right ventricular/left ventricular (LV) ejection fraction (RVEF/LVEF) assessments and strain.

Methods: CMR with cine imaging, displacement encoding with stimulated echoes for the circumferential uniformity ratio estimate with singular value decomposition (CURE-SVD) dyssynchrony parameter, and scar assessment was performed before and after CRT.