3-Dimensional Strain Analysis of Hypertrophic Cardiomyopathy: Insights From the NHLBI International HCM Registry.

BACKGROUND: Abnormal global longitudinal strain (GLS) has been independently associated with adverse cardiac outcomes in both obstructive and nonobstructive hypertrophic cardiomyopathy. OBJECTIVES: The goal of this study was to understand predictors of abnormal GLS from baseline data from the National Heart, Lung, and Blood Institute (NHLBI) Hypertrophic Cardiomyopathy Registry (HCMR). METHODS: The study evaluated comprehensive 3-dimensional left ventricular myocardial strain from cine cardiac magnetic resonance in 2,311 patients from HCMR using in-house validated feature-tracking software. These data were correlated with other imaging markers, serum biomarkers, and demographic variables. RESULTS: Abnormal median GLS (> -11.0%) was associated with higher left ventricular (LV) mass index (93.8 ± 29.2 g/m2 vs 75.1 ± 19.7 g/m2; P < 0.0001) and maximal wall thickness (21.7 ± 5.2 mm vs 19.3 ± 4.1 mm; P < 0.0001), lower left (62% ± 9% vs 66% ± 7%; P < 0.0001) and right (68% ± 11% vs 69% ± 10%; P < 0.01) ventricular ejection fractions, lower left atrial emptying functions (P < 0.0001 for all), and higher presence and myocardial extent of late gadolinium enhancement (6 SD and visual quantification; P < 0.0001 for both). Elastic net regression showed that adjusted predictors of GLS included female sex, Black race, history of syncope, presence of systolic anterior motion of the mitral valve, reverse curvature and apical morphologies, LV ejection fraction, LV mass index, and both presence/extent of late gadolinium enhancement and baseline N-terminal pro-B-type natriuretic peptide and troponin levels. CONCLUSIONS: Abnormal strain in hypertrophic cardiomyopathy is associated with other imaging and serum biomarkers of increased risk. Further follow-up of the HCMR cohort is needed to understand the independent relationship between LV strain and adverse cardiac outcomes in hypertrophic cardiomyopathy.

Normative healthy reference values for global and segmental 3D principal and geometry dependent strain from cine cardiac magnetic resonance imaging.

3-Dimensional (3D) myocardial deformation analysis (3D-MDA) enables novel descriptions of geometry-independent principal strain (PS). Applied to routine 2D cine cardiovascular magnetic resonance (CMR), this provides unique measures of myocardial biomechanics for disease diagnosis and prognostication. However, healthy reference values remain undefined. This study describes age- and sex-stratified reference values from CMR-based 3D-MDA, including 3D PS. One hundred healthy volunteers were prospectively recruited following institutional ethics approval and underwent CMR imaging. 3D-MDA was performed using validated software. Age- and sex-stratified global and segmental strain measures were derived for conventional geometry-dependent [circumferential (CS), longitudinal (LS), and radial (RS)] and geometry-independent [minimum (minPS) and maximum principal (maxPS)] directions of deformation. Layer-specific contraction angle interactions were determined using local minPS vectors. The average age was 43 ± 15 years and 55% were women. Strain measures were higher in women versus men. 3D PS-based assessment of maximum tissue shortening (minPS) and maximum tissue thickening (maxPS) were greater than corresponding geometry-dependent markers of LS and RS, consistent with improved representation of local tissue deformations. Global maxPS amplitude best discriminated both age and sex. Segmental analyses showed greater strain amplitudes in apical segments. Transmural PS contraction angles were higher in females and showed a heterogeneous distribution across segments. In this study we provided age and sex-based reference values for 3D strain from CMR imaging, demonstrating improved capacity for 3D PS to document maximal local tissue deformations and to discriminate age and sex phenotypes. Novel markers of layer-specific strain angles from 3D PS were also described.

Machine learning prediction of atrial fibrillation in cardiovascular patients using cardiac magnetic resonance and electronic health information.

Background: Atrial fibrillation (AF) is a commonly encountered cardiac arrhythmia associated with morbidity and substantial healthcare costs. While patients with cardiovascular disease experience the greatest risk of new-onset AF, no risk model has been developed to predict AF occurrence in this population. We hypothesized that a patient-specific model could be delivered using cardiovascular magnetic resonance (CMR) disease phenotyping, contextual patient health information, and machine learning. Methods: Nine thousand four hundred forty-eight patients referred for CMR imaging were enrolled and followed over a 5-year period. Seven thousand, six hundred thirty-nine had no prior history of AF and were eligible to train and validate machine learning algorithms. Random survival forests (RSFs) were used to predict new-onset AF and compared to Cox proportional-hazard (CPH) models. The best performing features were identified from 115 variables sourced from three data domains: (i) CMR-based disease phenotype, (ii) patient health questionnaire, and (iii) electronic health records. We evaluated discriminative performance of optimized models using C-index and time-dependent AUC (tAUC). Results: A RSF-based model of 20 variables (CIROC-AF-20) delivered an overall C-index of 0.78 for the prediction of new-onset AF with respective tAUCs of 0.80, 0.79, and 0.78 at 1-, 2- and 3-years. This outperformed a novel CPH-based model and historic AF risk scores. At 1-year of follow-up, validation cohort patients classified as high-risk of future AF by CIROC-AF-20 went on to experience a 17.3% incidence of new-onset AF, being 24.7-fold higher risk than low risk patients. Conclusions: Using phenotypic data available at time of CMR imaging we developed and validated the first described risk model for the prediction of new-onset AF in patients with cardiovascular disease. Complementary value was provided by variables from patient-reported measures of health and the electronic health record, illustrating the value of multi-domain phenotypic data for the prediction of AF.

Limits of Cardiovascular Adaptation During an Extreme Ultramarathon: Insights From Serial Multidimensional, Multiparametric CMR.

Extreme endurance athletic challenges provide unique opportunities to study the cardiovascular system's capacity for structural, functional, and hemodynamic adaptation. The authors present a case of a male subject who ran 2,469 km, with serial multiparametric cardiac magnetic resonance imaging used to demonstrate adaptive and maladaptive alterations in cardiac remodeling and myocardial tissue health. (Level of Difficulty: Advanced.).

Influence of Sex-Based Differences in Cardiac Phenotype on Atrial Fibrillation Recurrence in Patients Undergoing Pulmonary Vein Isolation.

Background: Pulmonary vein isolation (PVI) is a commonly engaged therapy for symptomatic atrial fibrillation (AF). Prior studies have documented elevated AF recurrence rates among females vs. males. Sex-specific mechanisms underlying this phenomenon are poorly understood. This prospective cohort study aimed to evaluate the sex-based differences in cardiac phenotype and their influence on (AF) recurrence following first-time PVI. Methods: A total of 204 consecutive patients referred for first-time PVI and 101 healthy subjects were prospectively studied by cardiovascular magnetic resonance (CMR) imaging. Multi-chamber volumetric and functional measures were assessed by sex-corrected Z-score analyses vs. healthy subjects. Patients were followed for a median of 2.6 years for the primary outcome of clinical AF recurrence. Multivariable analyses adjusting for age and comorbidities were performed to identify independent predictors of AF recurrence. Results: AF recurrence following first PVI occurred in 41% of males and 59% of females (p = 0.03). Females were older with higher prevalence of hypertension and thyroid disorders. Z-score-based analyses revealed significantly reduced ventricular volumes, greater left atrial (LA) volumes, and reduced LA contractility in females vs. males. Multivariable analysis revealed each of LA minimum and pre-systolic volumes and booster EF Z-scores to be independently associated with AF recurrence, providing respective hazard ratios of 1.10, 1.19, and 0.89 (p = 0.001, 0.03, and 0.01). Conclusion: Among patients referred for first time PVI, females were older and demonstrated significantly poorer LA contractile health vs. males, the latter independently associated with AF recurrence. Assessment of LA contractile health may therefore be of value to identify female patients at elevated risk of AF recurrence. Factors influencing female patient referral for PVI at more advanced stages of atrial disease warrant focused investigation.

Machine Learning Patient-Specific Prediction of Heart Failure Hospitalization Using Cardiac MRI-Based Phenotype and Electronic Health Information.

Background: Heart failure (HF) hospitalization is a dominant contributor of morbidity and healthcare expenditures in patients with systolic HF. Cardiovascular magnetic resonance (CMR) imaging is increasingly employed for the evaluation of HF given capacity to provide highly reproducible phenotypic markers of disease. The combined value of CMR phenotypic markers and patient health information to deliver predictions of future HF events has not been explored. We sought to develop and validate a novel risk model for the patient-specific prediction of time to HF hospitalization using routinely reported CMR variables, patient-reported health status, and electronic health information. Methods: Standardized data capture was performed for 1,775 consecutive patients with chronic systolic HF referred for CMR imaging. Patient demographics, symptoms, Health-related Quality of Life, pharmacy, and routinely reported CMR features were provided to both machine learning (ML) and competing risk Fine-Gray-based models (FGM) for the prediction of time to HF hospitalization. Results: The mean age was 59 years with a mean LVEF of 36 ± 11%. The population was evenly distributed between ischemic (52%) and idiopathic non-ischemic cardiomyopathy (48%). Over a median follow-up of 2.79 years (IQR: 1.59-4.04) 333 patients (19%) experienced HF related hospitalization. Both ML and competing risk FGM based models achieved robust performance for the prediction of time to HF hospitalization. Respective 90-day, 1 and 2-year AUC values were 0.87, 0.83, and 0.80 for the ML model, and 0.89, 0.84, and 0.80 for the competing risk FGM-based model in a holdout validation cohort. Patients classified as high-risk by the ML model experienced a 34-fold higher occurrence of HF hospitalization at 90 days vs. the low-risk group. Conclusion: In this study we demonstrated capacity for routinely reported CMR phenotypic markers and patient health information to be combined for the delivery of patient-specific predictions of time to HF hospitalization. This work supports an evolving migration toward multi-domain data collection for the delivery of personalized risk prediction at time of diagnostic imaging.

Mid-wall striae fibrosis predicts heart failure admission, composite heart failure events, and life-threatening arrhythmias in dilated cardiomyopathy.

Heart failure (HF) admission is a dominant contributor to morbidity and healthcare costs in dilated cardiomyopathy (DCM). Mid-wall striae (MWS) fibrosis by late gadolinium enhancement (LGE) imaging has been associated with elevated arrhythmia risk. However, its capacity to predict HF-specific outcomes is poorly defined. We investigated its role to predict HF admission and relevant secondary outcomes in a large cohort of DCM patients. 719 patients referred for LGE MRI assessment of DCM were enrolled and followed for clinical events. Standardized image analyses and interpretations were conducted inclusive of coding the presence and patterns of fibrosis observed by LGE imaging. The primary clinical outcome was hospital admission for decompensated HF. Secondary heart failure and arrhythmic composite endpoints were also studied. Median age was 57 (IQR 47-65) years and median LVEF 40% (IQR 29-47%). Any fibrosis was observed in 228 patients (32%) with MWS fibrosis pattern present in 178 (25%). At a median follow up of 1044 days, 104 (15%) patients experienced the primary outcome, and 127 (18%) the secondary outcome. MWS was associated with a 2.14-fold risk of the primary outcome, 2.15-fold risk of the secondary HF outcome, and 2.23-fold risk of the secondary arrhythmic outcome. Multivariable analysis adjusting for all relevant covariates, inclusive of LVEF, showed patients with MWS fibrosis to experience a 1.65-fold increased risk (95% CI 1.11-2.47) of HF admission and 1-year event rate of 12% versus 7% without this phenotypic marker. Similar findings were observed for the secondary outcomes. Patients with LVEF > 35% plus MWS fibrosis experienced similar event rates to those with LVEF ≤ 35%. MWS fibrosis is a powerful and independent predictor of clinical outcomes in patients with DCM, identifying patients with LVEF > 35% who experience similar event rates to those with LVEF below this conventionally employed high-risk phenotype threshold.

Right ventricular insertion site fibrosis in a dilated cardiomyopathy referral population: phenotypic associations and value for the prediction of heart failure admission or death.

BACKGROUND: Dilated cardiomyopathy (DCM) is increasingly recognized as a heterogenous disease with distinct phenotypes on late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging. While mid-wall striae (MWS) fibrosis is a widely recognized phenotypic risk marker, other fibrosis patterns are prevalent but poorly defined. Right ventricular (RV) insertion (RVI) site fibrosis is commonly seen, but without objective criteria has been considered a non-specific finding. In this study we developed objective criteria for RVI fibrosis and studied its clinical relevance in a large cohort of patients with DCM. METHODS: We prospectively enrolled 645 DCM patients referred for LGE-CMR. All underwent standardized imaging protocols and baseline health evaluations. LGE images were blindly scored using objective criteria, inclusive of RVI site and MWS fibrosis. Associations between LGE patterns and CMR-based markers of adverse chamber remodeling were evaluated. Independent associations of LGE fibrosis patterns with the primary composite clinical outcome of heart failure admission or death were determined by multivariable analysis. RESULTS: The mean age was 56 ± 14 (28% female) with a mean left ventricular (LV) ejection fraction (LVEF) of 37%. At a median of 1061 days, 129 patients (20%) experienced the primary outcome. Any abnormal LGE was present in 306 patients (47%), inclusive of 274 (42%) meeting criteria for RVI site fibrosis and 167 (26%) for MWS fibrosis. All with MWS fibrosis showed RVI site fibrosis. Solitary RVI site fibrosis was associated with higher bi-ventricular volumes [LV end-systolic volume index (78 ± 39 vs. 66 ± 33 ml/m2, p = 0.01), RV end-diastolic volume index (94 ± 28 vs. 84 ± 22 ml/m2 (p < 0.01), RV end-systolic volume index (56 ± 26 vs. 45 ± 17 ml/m2, p < 0.01)], lower bi-ventricular function [LVEF 35 ± 12 vs. 39 ± 10% (p < 0.01), RV ejection fraction (RVEF) 43 ± 12 vs. 48 ± 10% (p < 0.01)], and higher extracellular volume (ECV). Patient with solitary RVI site fibrosis experienced a non-significant 1.4-fold risk of the primary outcome, increasing to a significant 2.6-fold risk when accompanied by MWS fibrosis. CONCLUSIONS: RVI site fibrosis in the absence of MWS fibrosis is associated with bi-ventricular remodelling and intermediate risk of heart failure admission or death. Our study findings suggest RVI site fibrosis to be pre-requisite for the incremental development of MWS fibrosis, a more advanced phenotype associated with greater LV remodeling and risk of clinical events.

Effect of Active Cancer on the Cardiac Phenotype: A Cardiac Magnetic Resonance Imaging-Based Study of Myocardial Tissue Health and Deformation in Patients With Chemotherapy-Naïve Cancer.

Background The overlap between cancer and cardiovascular care continues to expand, with intersections emerging before, during, and following cancer therapies. To date, emphasis has been placed on how cancer therapeutics influence downstream cardiac health. However, whether active malignancy itself influences chamber volumes, function, or overall myocardial tissue health remains uncertain. We sought to perform a comprehensive cardiovascular magnetic resonance-based evaluation of cardiac health in patients with chemotherapy-naïve cancer with comparison with a healthy volunteer population. Methods and Results Three-hundred and eighty-one patients with active breast cancer or lymphoma before cardiotoxic chemotherapy exposure were recruited in addition to 102 healthy volunteers. Both cohorts underwent standardized cardiovascular magnetic resonance imaging with quantification of chamber volumes, ejection fraction, and native myocardial T1. Left ventricular mechanics were incrementally assessed using three-dimensional myocardial deformation analysis, providing global longitudinal, circumferential, radial, and principal peak-systolic strain amplitude and systolic strain rate. The mean age of patients with cancer was 53.8±13.4 years; 79% being women. Despite similar left ventricular ejection fraction, patients with cancer showed smaller chambers, increased strain amplitude, and systolic strain rate in both conventional and principal directions, and elevated native T1 versus sex-matched healthy volunteers. Adjusting for age, sex, hypertension, and diabetes mellitus, the presence of cancer remained associated with these cardiovascular magnetic resonance parameters. Conclusions The presence of cancer is independently associated with alterations in cardiac chamber size, function, and objective markers of tissue health. Dedicated research is warranted to elucidate pathophysiologic mechanisms underlying these findings and to explore their relevance to the management of patients with cancer referred for cardiotoxic therapies.

Right Ventricular Ejection Fraction for the Prediction of Major Adverse Cardiovascular and Heart Failure-Related Events: A Cardiac MRI Based Study of 7131 Patients With Known or Suspected Cardiovascular Disease.

BACKGROUND: There is increasing evidence that right ventricular ejection fraction (RVEF) may provide incremental value to left ventricular (LV) ejection fraction for the prediction of major adverse cardiovascular events. To date, generalizable utility for RVEF quantification in patients with cardiovascular disease has not been established. Using a large prospective clinical outcomes registry, we investigated the prognostic value of RVEF for the prediction of major adverse cardiovascular events- and heart failure-related outcomes. METHODS: Seven thousand one hundred thirty-one consecutive patients with known or suspected cardiovascular disease undergoing cardiovascular magnetic resonance imaging were prospectively enrolled. Multichamber volumetric quantification was performed by standardized operational procedures. Patients were followed for the primary composite outcome of all-cause death, survived cardiac arrest, admission for heart failure, need for transplantation or LV assist device, acute coronary syndrome, need for revascularization, stroke, or transient ischemic attack. A secondary, heart failure focused outcome of heart failure admission, need for transplantation/LV assist device or death was also studied. RESULTS: Mean age was 54±15 years. The mean LV ejection fraction was 55±14% (range 6%-90%) with a mean RVEF of 54±10% (range 9%-87%). At a median follow-up of 908 days, 870 (12%) patients experienced the primary composite outcome and 524 (7%) the secondary outcome. Each 10% drop in RVEF was associated with a 1.3-fold increased risk of the primary outcome (P<0.001) and 1.5-fold increased risk of the secondary outcome (P<0.001). RVEF was an independent predictor following comprehensive covariate adjustment, inclusive of LV ejection fraction. Patients with an RVEF<40% experienced a 3.1-fold risk of the primary outcome (P<0.001) with a 1-year cumulative event rate of 22% versus 7% above this cutoff. CONCLUSIONS: RVEF is a powerful and independent predictor of major adverse cardiac events with broad generalizability across patients with known or suspected cardiovascular disease. These findings support migration towards biventricular phenotyping for the classification of risk in clinical practice. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04367220.

Neural-Network-Based Diagnosis Using 3-Dimensional Myocardial Architecture and Deformation: Demonstration for the Differentiation of Hypertrophic Cardiomyopathy.

The diagnosis of cardiomyopathy states may benefit from machine-learning (ML) based approaches, particularly to distinguish those states with similar phenotypic characteristics. Three-dimensional myocardial deformation analysis (3D-MDA) has been validated to provide standardized descriptors of myocardial architecture and deformation, and may therefore offer appropriate features for the training of ML-based diagnostic tools. We aimed to assess the feasibility of automated disease diagnosis using a neural network trained using 3D-MDA to discriminate hypertrophic cardiomyopathy (HCM) from its mimic states: cardiac amyloidosis (CA), Anderson-Fabry disease (AFD), and hypertensive cardiomyopathy (HTNcm). 3D-MDA data from 163 patients (mean age 53.1 ± 14.8 years; 68 females) with left ventricular hypertrophy (LVH) of known etiology was provided. Source imaging data was from cardiac magnetic resonance (CMR). Clinical diagnoses were as follows: 85 HCM, 30 HTNcm, 30 AFD, and 18 CA. A fully-connected-layer feed-forward neural was trained to distinguish HCM vs. other mimic states. Diagnostic performance was compared to threshold-based assessments of volumetric and strain-based CMR markers, in addition to baseline clinical patient characteristics. Threshold-based measures provided modest performance, the greatest area under the curve (AUC) being 0.70. Global strain parameters exhibited reduced performance, with AUC under 0.64. A neural network trained exclusively from 3D-MDA data achieved an AUC of 0.94 (sensitivity 0.92, specificity 0.90) when performing the same task. This study demonstrates that ML-based diagnosis of cardiomyopathy states performed exclusively from 3D-MDA is feasible and can distinguish HCM from mimic disease states. These findings suggest strong potential for computer-assisted diagnosis in clinical practice.

A novel combined fluid dynamic and strain analysis approach identified abdominal aortic aneurysm rupture.

Clinical decision-making for surgical repair of abdominal aortic aneurysms based on maximum aortic diameter presents limitations as rupture can occur below threshold for some aneurysms, whereas others are stable at large sizes. The proposed approach combines hemodynamics and geometric indices with in vivo deformation analysis to assess local weakening of the aortic wall for a case of impending rupture that was confirmed during open surgical repair. A new combined index, the Regional Rupture Potential, is introduced to help the assessment of individual aneurysms and their rupture risk, providing a rationale for clinical decisions.

Natural History of Myocardial Injury and Chamber Remodeling in Acute Myocarditis.

BACKGROUND: Cardiovascular magnetic resonance (CMR) imaging is commonly used to diagnose acute myocarditis. However, the natural history of CMR-based tissue markers and their association with left ventricular recovery is poorly explored. We prospectively investigated the natural history of CMR-based myocardial injury and chamber remodeling over 12 months in patients with suspected acute myocarditis. METHODS: One hundred patients with suspected acute myocarditis were enrolled. All underwent CMR evaluations at baseline and 12 months, inclusive of T2 and late gadolinium enhancement. Blinded quantitative analyses compared left ventricular chamber volumes, function, myocardial edema, and necrosis at each time point using predefined criteria. The predefined primary outcomes were improvement in left ventricular ejection fraction ≥10% and improvement in the indexed left ventricular end diastolic volume ≥10% at 12 months. RESULTS: The mean age was 39.9±14.5 years (82 male) with baseline left ventricular ejection fraction of 57.1±11.2%. A total of 72 patients (72%) showed late gadolinium enhancement at baseline with 57 (57%) having any T2 signal elevation. Left ventricular volumes and EF improved significantly at 12 months. Global late gadolinium enhancement extent dropped from 8.5±9.2% of left ventricular mass to 3.0±5.2% ( P=0.0001) with prevalence of any late gadolinium enhancement dropping to 48%. Reductions in global T2 signal ratio occurred at 12 months (1.85±0.3 to 1.56±0.2; P=0.0001) with prevalence of T2 ratio ≥2.0 dropping to 7%. Neither marker provided associations with the primary outcomes. CONCLUSIONS: In clinically suspected acute myocarditis, significant reductions in tissue injury markers occur during the first 12 months of convalescence. Neither the presence nor extent of the investigated CMR-based tissue injury markers were predictive of our pre-defined function or remodeling outcomes at 12 months in this referral population.

3-Dimensional regional and global strain abnormalities in hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is characterized by myocardial disarray, hypertrophy, and fibrosis. Reduced global longitudinal strain and presence of late gadolinium enhancement (LGE) by cardiac magnetic resonance imaging (CMR) have been associated with an adverse prognosis. This study evaluated 3D principal and conventional strain characteristics of non-enhanced myocardium in patients with HCM. 3D principal and conventional strain analysis was conducted in 51 HCM patients and 38 healthy controls. Principal strain was reduced within the non-enhanced myocardium of HCM as compared with controls (maximum principal: 51.5 ± 23.7 vs. 75.1 ± 21.4%, P < 0.0001; minimum principal: - 18.4 ± 4.0 vs. - 20.1 ± 2.9%, P < 0.05). Principal strain within the non-enhanced myocardium was incrementally reduced in HCM patients with extensive global LGE ( ≥ 15%) (maximum principal: 41.6 ± 17.5 vs. 56.9 ± 25.9%, P < 0.05; minimum principal: - 16.9 ± 3.9 vs. - 19.1 ± 4.0%, P = 0.1), as was longitudinal ( - 10.5 ± 2.6 vs. - 12.7 ± 2.6%, P < 0.05) and circumferential strain ( - 11.0 ± 2.7 vs. - 14.0 ± 2.9%, P < 0.01). Principal strain within non-enhanced myocardium was significantly correlated with indexed LV mass (P < 0.0001), maximum (P = 0.0008), and mean wall thickness (P < 0.0001), but not LGE (P = 0.0841). In adjusted analysis, all strain measures within non-enhanced myocardium were independently associated with indexed LV mass (maximum principal: P = 0.0003; minimum principal: P = 0.0039; longitudinal: P = 0.0015; circumferential: P = 0.0002; radial: P = 0.0023). 3D principal strain of non-enhanced myocardium was significantly reduced in HCM patients as compared with controls, and was incrementally reduced among patients with more extensive global LGE. Comprehensive strain assessment may be considered in routine CMR assessment of HCM patients.

Intra-thoracic adiposity is associated with impaired contractile function in patients with coronary artery disease: a cardiovascular magnetic resonance imaging study.

The influence of visceral adiposity on left ventricular remodeling following coronary artery disease (CAD)-related events has not been examined to date. Using magnetic resonance imaging (MRI) we explored intra-thoracic fat volume (ITFV) and strain-based markers of adverse remodeling in patients with CAD. Forty-seven patients with known CAD (25 with prior MI, 22 without prior MI) were studied. ITFV was quantified using previously validated imaging techniques. Myocardial strain was derived from cine MRI using a validated 3D feature-tracking (FT) software. Segmental LGE quantification was performed and was used to incrementally constrain strain analyses to non-infarcted (i.e. remote) segments. Remote myocardial strain was compared to the non-MI control cohort and was explored for associations with ITFV. Mean age was 57 ± 13 years with a mean BMI of 30.0 ± 6.2 kg/m2 (range 20.3-38.4 kg/m2). Patients with versus without prior MI had similar demographics and BMI (29.4 ± 4.4 vs. 30.4 ± 7.9 kg/m2, p = 0.62). Patients with prior MI had lower mean peak strain than non-MI patients (p = 0.02), consistent with remote tissue contractile dysfunction. Inverse associations were identified between ITFV and mean peak strain in both the MI group (circumferential: r = 0.43, p = 0.03; radial: - 0.41, p = 0.04; minimum principal: r = 0.41, p = 0.04; maximum principal: r = - 0.43, p = 0.03) and non-MI group (circumferential: r = 0.42, p = 0.05; minimum principal: r = 0.45, p = 0.03). In those with prior MI higher ITFV was associated with a greater reduction in remote tissue strain. ITFV is associated with contractile dysfunction in patients with CAD. This association is prominent in the post-MI setting suggesting relevant influence on remote tissue health following ischemic injury. Expanded study of intra-thoracic adiposity as a modulator of myocardial health in patients with CAD is warranted.

Characterization of Right Ventricular Deformation in Pulmonary Arterial Hypertension Using Three-Dimensional Principal Strain Analysis.

BACKGROUND: Pulmonary arterial hypertension (PAH) can cause maladaptive right ventricular (RV) functional changes associated with adverse prognosis that are challenging to accurately quantify noninvasively. The aim of this study was to explore principal strain (PS) with contraction angle analysis using three-dimensional echocardiography to characterize RV deformation changes in patients with PAH. METHODS: Three-dimensional echocardiography was performed in 37 patients with PAH and 20 healthy control subjects with two-component (primary and secondary) PS and principal contraction angle analysis. Patients were stratified according to World Health Organization (WHO) functional class. RESULTS: Primary PS differed significantly between patients with PAH and healthy control subjects (-20.2 ± 3.3% vs -26.8 ± 3.3%, P = .01), while secondary PS was not significantly different (3.6 ± 5.1% vs -2.5 ± 4.7%, P = .12). Principal contraction angle was significantly lower in patients with PAH (63 ± 22° vs 71 ± 7°, P = .01), with the greatest reduction for the RV free wall. Primary PS and principal contraction angle differed significantly between WHO class I and II and class III and IV patients (-23.9 ± 4.7% vs -18.1 ± 4.8% [P = .03] and 69 ± 9° vs 58 ± 14° [P = .03], respectively), while secondary PS was not significantly different between groups (P = .13). Compared with healthy control subjects, septal principal contraction angle was not different in patients with WHO class I and II PAH (P = .62), but it was significantly reduced in those with WHO class III and IV PAH (P < .01). The area under the curve for primary PS to differentiate patients with PAH by WHO functional class was 0.81 (95% CI, 0.77-0.89; P = .01). Primary PS intraclass correlation coefficients for intraobserver and interobserver variability were 0.91 (95% CI, 0.88-0.93) and 0.86 (95% CI, 0.81-0.88), respectively. CONCLUSIONS: PS analysis using three-dimensional echocardiography provides comprehensive quantification of RV deformation and characterizes alterations occurring in PAH that are associated with WHO functional class.

3D myocardial deformation analysis from cine MRI as a marker of amyloid protein burden in cardiac amyloidosis: validation versus T1 mapping.

Cardiac amyloidosis (CA) is a significant contributor to heart failure with preserved ejection fraction and is appreciating expanding therapeutic options. Non-invasive tools aimed at accurate identification and surveillance of therapeutic response are of immediate and expanding need. While native and post-contrast T1 mapping quantify expansion of the extra-cellular compartment from amyloid protein deposition, 3D strain analysis of non-contrast cine images offers unique advantages relevant to high prevalence of renal insufficiency in this population and reduced dependency on field strength, pulse sequence, and vendor implementation. We aimed to evaluate global and segmental associations between 3D strain and T1 mapping in patients with cardiac amyloidosis. Twenty consecutive patients with confirmed CA were recruited and underwent a standardized cardiovascular magnetic resonance imaging protocol at 3 T including using multi-planar cine imaging and T1 mapping using a shortened modified look-locker inversion recovery sequence. T1 mapping was performed pre- and (when permitted by renal function) post-contrast and measured for segmental T1 values. Spatially-matched 3D strain-based measures were similarly calculated. Mean left ventricular ejection fraction was 61 ± 21% (range 30-73%). Mean global native T1 was 1308 ± 96 ms. Post-contrast T1 and partition coefficient were 558 ± 104 ms and 0.85 ± 0.31, respectively. Global myocardial strain values were 8.1 ± 2.9% in the longitudinal direction, - 9.2 ± 3.4% in the circumferential direction, and 41.7 ± 22.8% in the maximum principal direction. Segmental analyses confirmed relative worsening in T1 values and reductions in strain values in the basal myocardial segments with relative sparing of the apical segments. Significant associations between T1 and strain-based measures were observed globally and segmentally, with the strongest associations found both globally and segmentally in the circumferential and minimum principal directions of deformation. This study identifies strong associations between 3D myocardial strain and T1-mapping based markers of regional amyloid protein deposition. These findings support expanded investigation of myocardial strain as a surrogate marker of response to novel therapeutic strategies in patients with cardiac amyloidosis.

Three-dimensional thoracic aorta principal strain analysis from routine ECG-gated computerized tomography: feasibility in patients undergoing transcatheter aortic valve replacement.

BACKGROUND: Functional impairment of the aorta is a recognized complication of aortic and aortic valve disease. Aortic strain measurement provides effective quantification of mechanical aortic function, and 3-dimenional (3D) approaches may be desirable for serial evaluation. Computerized tomographic angiography (CTA) is routinely performed for various clinical indications, and offers the unique potential to study 3D aortic deformation. We sought to investigate the feasibility of performing 3D aortic strain analysis in a candidate population of patients undergoing transcatheter aortic valve replacement (TAVR). METHODS: Twenty-one patients with severe aortic valve stenosis (AS) referred for TAVR underwent ECG-gated CTA and echocardiography. CTA images were analyzed using a 3D feature-tracking based technique to construct a dynamic aortic mesh model to perform peak principal strain amplitude (PPSA) analysis. Segmental strain values were correlated against clinical, hemodynamic and echocardiographic variables. Reproducibility analysis was performed. RESULTS: The mean patient age was 81±6 years. Mean left ventricular ejection fraction was 52±14%, aortic valve area (AVA) 0.6±0.3 cm2 and mean AS pressure gradient (MG) 44±11 mmHg. CTA-based 3D PPSA analysis was feasible in all subjects. Mean PPSA values for the global thoracic aorta, ascending aorta, aortic arch and descending aorta segments were 6.5±3.0, 10.2±6.0, 6.1±2.9 and 3.3±1.7%, respectively. 3D PSSA values demonstrated significantly more impairment with measures of worsening AS severity, including AVA and MG for the global thoracic aorta and ascending segment (p<0.001 for all). 3D PSSA was independently associated with AVA by multivariable modelling. Coefficients of variation for intra- and inter-observer variability were 5.8 and 7.2%, respectively. CONCLUSIONS: Three-dimensional aortic PPSA analysis is clinically feasible from routine ECG-gated CTA. Appropriate reductions in PSSA were identified with increasing AS hemodynamic severity. Expanded study of 3D aortic PSSA for patients with various forms of aortic disease is warranted.

Mechano-electric finite element model of the left atrium.

Mechanical stretch plays a major role in modulating atrial function, being responsible for beat-by-beat responses to changes in chamber preload, enabling a prompt regulation of cardiac function. Mechano-electric coupling (MEC) operates through many mechanisms and has many targets, making it experimentally difficult to isolate causes and effects especially under sinus conditions where effects are more transient and subtle. Therefore, modelling is a powerful tool to help understand the role of MEC with respect to the atrial electromechanical interaction. We propose a cellular-based computational model of the left atrium that includes a strongly coupled MEC component and mitral flow component to account for correct pressure generation in the atrial chamber as a consequence of blood volume and contraction. The method was applied to a healthy porcine left atrium. Results of the strongly coupled simulation show that strains are higher in the areas adjacent to the mitral annulus, the rim of the appendage, around the pulmonary venous trunks and at the location of the Bachmann's bundle, approximately between the mitral annulus and the region where the venous tissue transitions into atrial. These are regions where arrhythmias are likely to originate. The role of stretch-activated channels was very small for sinus rhythm for the single cardiac beat simulation, although tension development was very sensitive to stretch. The method could be applied to investigate potential therapeutic interventions acting on the mechano-electrical properties of the left atrium.

Clinical feasibility and validation of 3D principal strain analysis from cine MRI: comparison to 2D strain by MRI and 3D speckle tracking echocardiography.

Two-dimensional (2D) strain analysis is constrained by geometry-dependent reference directions of deformation (i.e. radial, circumferential, and longitudinal) following the assumption of cylindrical chamber architecture. Three-dimensional (3D) principal strain analysis may overcome such limitations by referencing intrinsic (i.e. principal) directions of deformation. This study aimed to demonstrate clinical feasibility of 3D principal strain analysis from routine 2D cine MRI with validation to strain from 2D tagged cine analysis and 3D speckle tracking echocardiography. Thirty-one patients undergoing cardiac MRI were studied. 3D strain was measured from routine, multi-planar 2D cine SSFP images using custom software designed to apply 4D deformation fields to 3D cardiac models to derive principal strain. Comparisons of strain estimates versus those by 2D tagged cine, 2D non-tagged cine (feature tracking), and 3D speckle tracking echocardiography (STE) were performed. Mean age was 51 ± 14 (36% female). Mean LV ejection fraction was 66 ± 10% (range 37-80%). 3D principal strain analysis was feasible in all subjects and showed high inter- and intra-observer reproducibility (ICC range 0.83-0.97 and 0.83-0.98, respectively-p < 0.001 for all directions). Strong correlations of minimum and maximum principal strain were respectively observed versus the following: 3D STE estimates of longitudinal (r = 0.81 and r = -0.64), circumferential (r = 0.76 and r = -0.58) and radial (r = -0.80 and r = 0.63) strain (p < 0.001 for all); 2D tagged cine estimates of longitudinal (r = 0.81 and r = -0.81), circumferential (r = 0.87 and r = -0.85), and radial (r = -0.76 and r = 0.81) strain (p < 0.0001 for all); and 2D cine (feature tracking) estimates of longitudinal (r = 0.85 and -0.83), circumferential (r = 0.88 and r = -0.87), and radial strain (r = -0.79 and r = 0.84, p < 0.0001 for all). 3D principal strain analysis is feasible using routine, multi-planar 2D cine MRI and shows high reproducibility with strong correlations to 2D conventional strain analysis and 3D STE-based analysis. Given its independence from geometry-related directions of deformation this technique may offer unique benefit for the detection and prognostication of myocardial disease, and warrants expanded investigation.