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Abstract Whether sex differences exist in the cardiac remodeling related to aortic regurgitation (AR) is unclear. Cardiac magnetic resonance (CMR) is the current non-invasive reference standard for cardiac remodeling assessment and can evaluate tissue characteristics. This prospective cohort included patients with AR undergoing CMR between 2011 and 2020. We excluded patients with confounding causes of remodeling. We quantified left ventricular (LV) volume, mass, AR severity, replacement fibrosis by late Gadolinium enhancement (LGE), and extracellular expansion by extracellular volume fraction (ECV). We studied 280 patients (109 women), median age 59.5 (47.2, 68.6) years (P for age = 0.25 between sexes). Women had smaller absolute LV volume and mass than men across the spectrum of regurgitation volume (RVol) (P ≤ 0.01). In patients with ≥ moderate AR and with adjustment for body surface area, indexed LV end-diastolic volume and mass were not significantly different between sexes (all P > 0.5) but men had larger indexed LV end systolic volume and lower LV ejection fraction (P ≥ 0.01). Women were more likely to have NYHA class II or greater symptoms than men but underwent surgery at a similar rate. Prevalence and extent of LGE was not significantly different between sexes or across RVol. Increasing RVol was independently associated with increasing ECV in women, but not in men (adjusted P for interaction = 0.03). In conclusion, women had lower LV volumes and mass than men across AR severity but their ECV increased with higher regurgitant volume, while ECV did not change in men. Indexing to body surface area did not fully correct for the cardiac remodeling differences between men and women. Women were more likely to have symptoms but underwent surgery at a similar rate to men. Further research is needed to determine if differences in ECV would translate to differences in the course of AR and outcomes.

Background: Extracellular volume fraction (ECV), measured with contrast-enhanced magnetic resonance imaging (CE-MRI), has been utilized to study myocardial fibrosis, but its role in peripheral artery disease (PAD) remains unknown. We hypothesized that T1 mapping and ECV differ between PAD patients and matched controls. Methods and Results: A total of 37 individuals (18 PAD patients and 19 matched controls) underwent 3.0T CE-MRI. Skeletal calf muscle T1 mapping was performed before and after gadolinium contrast with a motion-corrected modified look–locker inversion recovery (MOLLI) pulse sequence. T1 values were calculated with a three-parameter Levenberg–Marquardt curve fitting algorithm. ECV and T1 maps were quantified in five calf muscle compartments (anterior [AM], lateral [LM], and deep posterior [DM] muscle groups; soleus [SM] and gastrocnemius [GM] muscles). Averaged peak blood pool T1 values were obtained from the posterior and anterior tibialis and peroneal arteries. T1 values and ECV are heterogeneous across calf muscle compartments. Native peak T1 values of the AM, LM, and DM were significantly higher in PAD patients compared to controls (all p < 0.028). ECVs of the AM and SM were significantly higher in PAD patients compared to controls (AM: 26.4% (21.2, 31.6) vs. 17.3% (10.2, 25.1), p = 0.046; SM: 22.7% (19.5, 27.8) vs. 13.8% (10.2, 19.1), p = 0.020). Conclusions: Native peak T1 values across all five calf muscle compartments, and ECV fractions of the anterior muscle group and the soleus muscle were significantly elevated in PAD patients compared with matched controls. Non-invasive T1 mapping and ECV quantification may be of interest for the study of PAD.

Abstract The Society for Cardiovascular Magnetic Resonance (SCMR) recommendations for training and competency of cardiovascular magnetic resonance (CMR) technologists document will define the knowledge, experiences and skills required for a technologist to be competent in CMR imaging. By providing a framework for CMR training and competency the overarching goal is to promote the performance of high-quality CMR and to foster the increased adoption of CMR into clinical care.

Abstract In-vivo estimation of mechanical properties of the myocardium is essential for patient-specific diagnosis and prognosis of cardiac disease involving myocardial remodeling, including myocardial infarction and heart failure with preserved ejection fraction. Current approaches use time-consuming finite-element (FE) inverse methods that involve reconstructing and meshing the heart geometry, imposing measured loading, and conducting computationally expensive iterative FE simulations. In this paper, we propose a machine learning (ML) model that feasibly and accurately predicts passive myocardial properties directly from select geometric, architectural, and hemodynamic measures, thus bypassing exhaustive steps commonly required in cardiac FE inverse problems. Geometric and fiber-orientation features were chosen to be readily obtainable from standard cardiac imaging protocols. The end-diastolic pressure-volume relationship (EDPVR), which can be obtained using a single-point pressure-volume measurement, was used as a hemodynamic (loading) feature. A comprehensive ML training dataset in the geometry-architecture-loading space was generated, including a wide variety of partially synthesized rodent heart geometry and myofiber helicity possibilities, and a broad range of EDPVRs obtained using forward FE simulations. Latin hypercube sampling was used to create 2500 examples for training, validation, and testing. A multi-layer feed-forward neural network (MFNN) was used as a deep learning agent to train the ML model. The model showed excellent performance in predicting stiffness parameters $$a_f$$ a f and $$b_f$$ b f associated with fiber direction ( $$R^2_{a_f}=99.471\%$$ R a f 2 = 99.471 % and $$R^2_{b_f}=92.837\%$$ R b f 2 = 92.837 % ). After conducting permutation feature importance analysis, the ML performance further improved for $$b_f$$ b f ( $$R^2_{b_f}=96.240\%$$ R b f 2 = 96.240 % ), and the left ventricular volume and endocardial area were found to be the most critical geometric features for accurate predictions. The ML model predictions were evaluated further in two cases: (i) rat-specific stiffness data measured using ex-vivo mechanical testing, and (ii) patient-specific estimation using FE inverse modeling. Excellent agreements with ML predictions were found for both cases. The trained ML model offers a feasible technology to estimate patient-specific myocardial properties, thus, bridging the gap between EDPVR, as a confounded organ-level metric for tissue stiffness, and intrinsic tissue-level properties. These properties provide incremental information relative to traditional organ-level indices for cardiac function, improving the clinical assessment and prognosis of cardiac diseases.

Background Computational fluid dynamics has shown good agreement with contrast‐enhanced magnetic resonance imaging measurements in cardiovascular disease applications. We have developed a biomechanical model of microvascular perfusion using contrast‐enhanced magnetic resonance imaging signal intensities derived from skeletal calf muscles to study peripheral artery disease (PAD). Methods and Results The computational microvascular model was used to study skeletal calf muscle perfusion in 56 individuals (36 patients with PAD, 20 matched controls). The recruited participants underwent contrast‐enhanced magnetic resonance imaging and ankle‐brachial index testing at rest and after 6‐minute treadmill walking. We have determined associations of microvascular model parameters including the transfer rate constant, a measure of vascular leakiness; the interstitial permeability to fluid flow which reflects the permeability of the microvasculature; porosity, a measure of the fraction of the extracellular space; the outflow filtration coefficient; and the microvascular pressure with known markers of patients with PAD. Transfer rate constant, interstitial permeability to fluid flow, and microvascular pressure were higher, whereas porosity and outflow filtration coefficient were lower in patients with PAD than those in matched controls (all P values ≤0.014). In pooled analyses of all participants, the model parameters (transfer rate constant, interstitial permeability to fluid flow, porosity, outflow filtration coefficient, microvascular pressure) were significantly associated with the resting and exercise ankle‐brachial indexes, claudication onset time, and peak walking time (all P values ≤0.013). Among patients with PAD, interstitial permeability to fluid flow, and microvascular pressure were higher, while porosity and outflow filtration coefficient were lower in treadmill noncompleters compared with treadmill completers (all P values ≤0.001). Conclusions Computational microvascular model parameters differed significantly between patients with PAD and matched controls. Thus, computational microvascular modeling could be of interest in studying lower extremity ischemia.

Abstract Background A comprehensive non-invasive evaluation of bioprosthetic mitral valve (BMV) function can be challenging. We describe a novel method to assess BMV effective orifice area (EOA) based on phase contrast (PC) cardiovascular magnetic resonance (CMR) data. We compare the performance of this new method to Doppler and in vitro reference standards. Methods Four sizes of normal BMVs (27, 29, 31, 33 mm) and 4 stenotic BMVs (27 mm and 29 mm, with mild or severe leaflet obstruction) were evaluated using a CMR- compatible flow loop. BMVs were evaluated with PC-CMR and Doppler methods under flow conditions of; 70 mL, 90 mL and 110 mL/beat (n = 24). PC-EOA was calculated as PC-CMR flow volume divided by the PC- time velocity integral (TVI). Results PC-CMR measurements of the diastolic peak velocity and TVI correlated strongly with Doppler values (r = 0.99, P

Abstract Measures of serum cardiac troponins and natriuretic peptides have become established as prognostic heart failure risk markers. In addition to detecting myocardial fibrosis through late gadolinium enhancement (LGE), extracellular volume fraction (ECV) measures by cardiac magnetic resonance (CMR) have emerged as a phenotypic imaging risk marker for incident heart failure outcomes. We sought to examine the relationship between cardiac troponins, natriuretic peptides, ECV and their associations with incident heart failure events in a CMR referral base. Mid short axis T1 maps were divided into 6 cardiac segments, each classified as LGE absent or present. Global ECV was derived from T1 maps using the area-weighted average of only LGE-absent segments. ECV was considered elevated if measured >30%, the upper 95% bounds of a reference healthy group without known cardiac disease (n = 28). Patients were dichotomized by presence of elevated ECV. High-sensitivity cardiac troponin T (hs-cTnT) and N-terminal B-type natriuretic peptide (NT-proBNP) were measured using serum samples acquired and stored at time of CMR scan, and patients were categorized into 3 groups for each blood marker based on recommended cutoff values. Subsequent heart failure admission and any death were ascertained. Relationships with ECV, hs-cTnT, and NT-proBNP were examined separately and as a composite with Cox proportional hazard models. Of 1,604 serial patients referred for a clinical CMR with myocardial T1 maps, 331 were eligible after exclusions and had blood available and were followed over a median 25.0 [interquartile range 21.8, 31.7] months. After adjustments for age (mean 57.3 [standard deviation (SD) 15.1 years), gender (61% male), and ethnicity (12.7% black), elevated ECV remained a predictor of a first composite heart failure outcome for patients with high levels of hs-cTnT (≥14 ng/L; hazard ratio [HR] 2.42 [95% confidence interval (CI) 1.17, 5.03]; p = 0.02) and NT-proBNP (≥300 pg/mL; HR 2.28 [95% CI 1.24, 4.29]; p = 0.01). Similar trends were seen for lower category levels of blood markers, but did not persist with minimal covariate adjustments. Elevated measures of ECV by CMR are associated with incident heart failure outcomes in patients with high hs-cTnT and NT-proBNP levels. This imaging marker may have a role for additional heart failure risk stratification.

Abstract Background Routine cine cardiovascular magnetic resonance (CMR) allows for the measurement of left atrial (LA) volumes. Normal reference values for LA volumes have been published based on a group of European individuals without known cardiovascular disease (CVD) but not on one of similar United States (US) based volunteers. Furthermore, the association between grades of LA dilatation by CMR and outcomes has not been established. We aimed to assess the relationship between grades of LA dilatation measured on CMR based on US volunteers without known CVD and all-cause mortality in a large, multicenter cohort of patients referred for a clinically indicated CMR scan. Method We identified 85 healthy US subjects to determine normal reference LA volumes using the biplane area-length method and indexed for body surface area (LAVi). Clinical CMR reports of patients with LA volume measures (n = 11,613) were obtained. Data analysis was performed on a cloud-based system for consecutive CMR exams performed at three geographically distinct US medical centers from August 2008 through August 2017. We identified 10,890 eligible cases. We categorized patients into 4 groups based on LAVi partitions derived from US normal reference values: Normal (21–52 ml/m2), Mild (52–62 ml/m2), Moderate (63–73 ml/m2) and Severe (> 73 ml/m2). Mortality data were ascertained for the patient group using electronic health records and social security death index. Cox proportional hazard risk models were used to derive hazard ratios for measuring association of LA enlargement and all-cause mortality. Results The distribution of LAVi from healthy subjects without known CVD was 36.3 ± 7.8 mL/m2. In clinical patients, enlarged LA was associated with older age, atrial fibrillation, hypertension, heart failure, inpatient status and biventricular dilatation. The median follow-up duration was 48.9 (IQR 32.1–71.2) months. On univariate analyses, mild [Hazard Ratio (HR) 1.35 (95% Confidence Interval [CI] 1.11 to 1.65], moderate [HR 1.51 (95% CI 1.22 to 1.88)] and severe LA enlargement [HR 2.14 (95% CI 1.81 to 2.53)] were significant predictors of death. After adjustment for significant covariates, moderate [HR 1.45 (95% CI 1.1 to 1.89)] and severe LA enlargement [HR 1.64 (95% CI 1.29 to 2.08)] remained independent predictors of death. Conclusion LAVi determined on routine cine-CMR is independently associated with all-cause mortality in patients undergoing a clinically indicated CMR.

Recent studies have described the occurrence of complex ventricular arrhythmias and sudden cardiac death among patients with mitral valve prolapse (MVP). The reported incidence rate of sudden cardiac death or ventricular tachycardia is about 1–1.5% among patients with MVP. Various imaging markers have been associated with this increased risk, including mitral annular disjunction, replacement fibrosis by late gadolinium enhancement, and mechanical dispersion. In this review, we briefly discuss how multimodality cardiac imaging can be applied to identify MVP patients with high risk of sudden cardiac death and complex ventricular arrhythmias.

Background Chronic aortic regurgitation (AR) can be associated with myocardial scarring. It is unknown if scarring in AR is linked to poor outcomes and whether aortic valve replacement impacts this association. We investigated the relationship of myocardial scarring to mortality in chronic AR using cardiac magnetic resonance. Methods and Results We enrolled patients with moderate or greater AR between 2009 and 2019 and performed a blinded assessment of left ventricle remodeling, AR severity, and presence and extent of myocardial scarring by late gadolinium enhancement. The primary outcome was all‐cause mortality. We followed 392 patients (median age 62 [interquartile range, 51–71] years), and 78.1% were men, and 25.8% had bicuspid valves. Median aortic valve regurgitant volume was 39 mL (interquartile range, 30–60). Myocardial scar was present in 131 (33.4%) patients. Aortic valve replacement was performed in 165 (49.1%) patients. During follow‐up, up to 10.8 years (median 32.3 months [interquartile range, 9.8–69.5]), 51 patients (13%) died. Presence of myocardial scar (hazard ratio [HR], 3.62; 95% CI, 2.06–6.36; P