Rina Ariga

Relationship Between Left Ventricular Structural and Metabolic Remodeling in Type 2 Diabetes

Concentric left ventricular (LV) remodeling is associated with adverse cardiovascular events and is frequently observed in patients with type 2 diabetes mellitus (T2DM). Despite this, the cause of concentric remodeling in diabetes per se is unclear, but it may be related to cardiac steatosis and impaired myocardial energetics. Thus, we investigated the relationship between myocardial metabolic changes and LV remodeling in T2DM. Forty-six nonhypertensive patients with T2DM and 20 matched control subjects underwent cardiovascular magnetic resonance to assess LV remodeling (LV mass–to–LV end diastolic volume ratio), function, tissue characterization before and after contrast using T1 mapping, and 1H and 31P magnetic resonance spectroscopy for myocardial triglyceride content (MTG) and phosphocreatine-to-ATP ratio, respectively. When compared with BMI- and blood pressure–matched control subjects, subjects with diabetes were associated with concentric LV remodeling, higher MTG, impaired myocardial energetics, and impaired systolic strain indicating a subtle contractile dysfunction. Importantly, cardiac steatosis independently predicted concentric remodeling and systolic strain. Extracellular volume fraction was unchanged, indicating the absence of fibrosis. In conclusion, cardiac steatosis may contribute to concentric remodeling and contractile dysfunction of the LV in diabetes. Because cardiac steatosis is modifiable, strategies aimed at reducing MTG may be beneficial in reversing concentric remodeling and improving contractile function in the hearts of patients with diabetes.

Ectopic and Visceral Fat Deposition in Lean and Obese Patients With Type 2 Diabetes

Background Type 2 diabetes (T2D) and obesity are associated with nonalcoholic fatty liver disease, cardiomyopathy, and cardiovascular mortality. Both show stronger links between ectopic and visceral fat deposition, and an increased cardiometabolic risk compared with subcutaneous fat. Objectives This study investigated whether lean patients (Ln) with T2D exhibit increased ectopic and visceral fat deposition and whether these are linked to cardiac and hepatic changes. Methods Twenty-seven obese patients (Ob) with T2D, 15 Ln-T2D, and 12 normal-weight control subjects were studied. Subjects underwent cardiac computed tomography, cardiac magnetic resonance imaging (MRI), proton and phosphorus MR spectroscopy, and multiparametric liver MR, including hepatic proton MRS, T1- and T2*-mapping yielding “iron-corrected T1” [cT1]. Results Diabetes, with or without obesity, was associated with increased myocardial triglyceride content (p = 0.01), increased hepatic triglyceride content (p = 0.04), and impaired myocardial energetics (p = 0.04). Although cardiac structural changes, steatosis, and energetics were similar between the T2D groups, epicardial fat (p = 0.04), hepatic triglyceride (p = 0.01), and insulin resistance (p = 0.03) were higher in Ob-T2D. Epicardial fat, hepatic triglyceride, and insulin resistance correlated negatively with systolic strain and diastolic strain rates, which were only significantly impaired in Ob-T2D (p < 0.001 and p = 0.006, respectively). Fibroinflammatory liver disease (elevated cT1) was only evident in Ob-T2D patients. cT1 correlated with hepatic and epicardial fat (p < 0.001 and p = 0.01, respectively). Conclusions Irrespective of body mass index, diabetes is related to significant abnormalities in cardiac structure, energetics, and cardiac and hepatic steatosis. Obese patients with T2D show a greater propensity for ectopic and visceral fat deposition.

Cardiac energetics, oxygenation, and perfusion during increased workload in patients with type 2 diabetes mellitus

Aims Patients with type 2 diabetes mellitus (T2DM) are known to have impaired resting myocardial energetics and impaired myocardial perfusion reserve, even in the absence of obstructive epicardial coronary artery disease (CAD). Whether or not the pre-existing energetic deficit is exacerbated by exercise, and whether the impaired myocardial perfusion causes deoxygenation and further energetic derangement during exercise stress, is uncertain. Methods and results Thirty-one T2DM patients, on oral antidiabetic therapies with a mean HBA1c of 7.4 ± 1.3%, and 17 matched controls underwent adenosine stress cardiovascular magnetic resonance for assessment of perfusion [myocardial perfusion reserve index (MPRI)] and oxygenation [blood-oxygen level-dependent (BOLD) signal intensity change (SIΔ)]. Cardiac phosphorus-MR spectroscopy was performed at rest and during leg exercise. Significant CAD (>50% coronary stenosis) was excluded in all patients by coronary computed tomographic angiography. Resting phosphocreatine to ATP (PCr/ATP) was reduced by 17% in patients (1.74 ± 0.26, P = 0.001), compared with controls (2.07 ± 0.35); during exercise, there was a further 12% reduction in PCr/ATP (P = 0.005) in T2DM patients, but no change in controls. Myocardial perfusion and oxygenation were decreased in T2DM (MPRI 1.61 ± 0.43 vs. 2.11 ± 0.68 in controls, P = 0.002; BOLD SIΔ 7.3 ± 7.8 vs. 17.1 ± 7.2% in controls, P < 0.001). Exercise PCr/ATP correlated with MPRI (r = 0.50, P = 0.001) and BOLD SIΔ (r = 0.32, P = 0.025), but there were no correlations between rest PCr/ATP and MPRI or BOLD SIΔ. Conclusion The pre-existing energetic deficit in diabetic cardiomyopathy is exacerbated by exercise; stress PCr/ATP correlates with impaired perfusion and oxygenation. Our findings suggest that, in diabetes, coronary microvascular dysfunction exacerbates derangement of cardiac energetics under conditions of increased workload.

Lone Atrial Fibrillation Is Associated With Impaired Left Ventricular Energetics That Persists Despite Successful Catheter Ablation

Background: Lone atrial fibrillation (AF) may reflect a subclinical cardiomyopathy that persists after sinus rhythm (SR) restoration, providing a substrate for AF recurrence. To test this hypothesis, we investigated the effect of restoring SR by catheter ablation on left ventricular (LV) function and energetics in patients with AF but no significant comorbidities. Methods: Fifty-three patients with symptomatic paroxysmal or persistent AF and without significant valvular disease, uncontrolled hypertension, coronary artery disease, uncontrolled thyroid disease, systemic inflammatory disease, diabetes mellitus, or obstructive sleep apnea (ie, lone AF) undergoing ablation and 25 matched control subjects in SR were investigated. Magnetic resonance imaging quantified LV ejection fraction (LVEF), peak systolic circumferential strain (PSCS), and left atrial volumes and function, whereas phosphorus-31 magnetic resonance spectroscopy evaluated ventricular energetics (ratio of phosphocreatine to ATP). AF burden was determined before and after ablation by 7-day Holter monitoring; intermittent ECG event monitoring was also undertaken after ablation to investigate for asymptomatic AF recurrence. Results: Before ablation, both LV function and energetics were significantly impaired in patients compared with control subjects (LVEF, 61% [interquartile range (IQR), 52%–65%] versus 71% [IQR, 69%–73%], P<0.001; PSCS, –15% [IQR, –11 to –18%] versus −18% [IQR, –17% to –19%], P=0.002; ratio of phosphocreatine to ATP, 1.81±0.35 versus 2.05±0.29, P=0.004). As expected, patients also had dilated and impaired left atria compared with control subjects (all P<0.001). Early after ablation (1–4 days), LVEF and PSCS improved in patients recovering SR from AF (LVEF, 7.0±10%, P=0.005; PSCS, –3.5±4.3%, P=0.001) but were unchanged in those in SR during both assessments (both P=NS). At 6 to 9 months after ablation, AF burden reduced significantly (from 54% [IQR, 1.5%–100%] to 0% [IQR 0%–0.1%]; P<0.001). However, LVEF and PSCS did not improve further (both P=NS) and remained impaired compared with control subjects (P<0.001 and P=0.003, respectively). Similarly, there was no significant improvement in atrial function from before ablation (P=NS), and this remained lower than in control subjects (P<0.001). The ratio of phosphocreatine to ATP was unaffected by heart rhythm during assessment and AF burden before ablation (both P=NS). It was unchanged after ablation (P=0.57), remaining lower than in control subjects regardless of both recovery of SR and freedom from recurrent AF (P=0.006 and P=0.002, respectively). Conclusions: Patients with lone AF have impaired myocardial energetics and subtle LV dysfunction, which do not normalize after ablation. These findings suggest that AF may be the consequence (rather than the cause) of an occult cardiomyopathy, which persists despite a significant reduction in AF burden after ablation.

Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting.

Distinct ECG Phenotypes Identified in Hypertrophic Cardiomyopathy Using Machine Learning Associate With Arrhythmic Risk Markers

Aims: Ventricular arrhythmia triggers sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM), yet electrophysiological biomarkers are not used for risk stratification. Our aim was to identify distinct HCM phenotypes based on ECG computational analysis, and characterize differences in clinical risk factors and anatomical differences using cardiac magnetic resonance (CMR) imaging. Methods: High-fidelity 12-lead Holter ECGs from 85 HCM patients and 38 healthy volunteers were analyzed using mathematical modeling and computational clustering to identify phenotypic subgroups. Clinical features and the extent and distribution of hypertrophy assessed by CMR were evaluated in the subgroups. Results: QRS morphology alone was crucial to identify three HCM phenotypes with very distinct QRS patterns. Group 1 (n = 44) showed normal QRS morphology, Group 2 (n = 19) showed short R and deep S waves in V4, and Group 3 (n = 22) exhibited short R and long S waves in V4-6, and left QRS axis deviation. However, no differences in arrhythmic risk or distribution of hypertrophy were observed between these groups. Including T wave biomarkers in the clustering, four HCM phenotypes were identified: Group 1A (n = 20), with primary repolarization abnormalities showing normal QRS yet inverted T waves, Group 1B (n = 24), with normal QRS morphology and upright T waves, and Group 2 and Group 3 remaining as before, with upright T waves. Group 1A patients, with normal QRS and inverted T wave, showed increased HCM Risk-SCD scores (1A: 4.0%, 1B: 1.8%, 2: 2.1%, 3: 2.5%, p = 0.0001), and a predominance of coexisting septal and apical hypertrophy (p < 0.0001). HCM patients in Groups 2 and 3 exhibited predominantly septal hypertrophy (85 and 90%, respectively). Conclusion: HCM patients were classified in four subgroups with distinct ECG features. Patients with primary T wave inversion not secondary to QRS abnormalities had increased HCM Risk-SCD scores and coexisting septal and apical hypertrophy, suggesting that primary T wave inversion may increase SCD risk in HCM, rather than T wave inversion secondary to depolarization abnormalities. Computational ECG phenotyping provides insight into the underlying processes captured by the ECG and has the potential to be a novel and independent factor for risk stratification.

Adenosine stress native T1 mapping detects microvascular disease in diabetic cardiomyopathy, without the need for gadolinium-based contrast

Background Patients with diabetes mellitus (DM) are known to have microvascular coronary artery disease (CAD), in the absence of hypertension and flow limiting stenoses on epicardial coronary arteries. Microvascular coronary dysfunction can be detected on CMR using adenosine stress perfusion imaging. Native T1 values can detect tissue water content of intra/extracellular or intra/extravascular origin. We hypothesised that increased myocardial blood volume in the intravascular space under adenosine vasodilator stress will have a measurable effect on T1 values. Therefore, we compared adenosine stress T1 response and myocardial perfusion reserve in patients with type-2 DM (T2DM) without macrovascular CAD against controls.

Cardiac Mesh Reconstruction from Sparse, Heterogeneous Contours

We introduce a tool to reconstruct a geometrical surface mesh from sparse, heterogeneous, non coincidental contours and show its application to cardiac data. In recent years much research has looked at creating personalised 3D anatomical models of the heart. These models usually incorporate a geometrical reconstruction of the anatomy in order to understand better cardiovascular functions as well as predict different processes after a clinical event. The ability to accurately reconstruct heart anatomy from MRI in three dimensions commonly comes with fundamental challenges, notably the trade off between data fitting and regularization. Most current techniques requires data to be either parallel, or coincident, and bias the final result due to prior shape models or smoothing terms. Our approach uses a composition of smooth approximations towards the maximization of the data fitting. Assessment of our method was performed on synthetic data obtained from a mean cardiac shape model as well as on clinical data belonging to one normal subject and one affected by hypertrophic cardiomyopathy. Our method is both used on epicardial and endocardial left ventricle surfaces, but as well as on the right ventricle.

Extraction of morphological QRS-based biomarkers in hypertrophic cardiomyopathy for risk stratification using L1 regularized logistic regression

Hypertrophic cardiomyopathy (HCM) is an inherited cardiac disease characterized by an unexplained thickening of the heart ventricles. It is the first cause of sudden cardiac death in young adults. No reliable biomarkers for risk assessment have been presented so far, but the electrocardiograms of HCM patients are often abnormal due to structural and electrical abnormalities. The goal of our study was to extract morphological QRS biomarkers in order to discriminate between HCM patients and control patients by analyzing fifty 12-lead Holter recordings (29 HCM - 21 control). Morphological features such as QRS width or slopes from the QRS complex directly and the coefficients of the first four Hermite transform basis were extracted. Classification was then performed using those features in an L1 regularized logistic regression algorithm. Classification between control and HCM patients reached 95.7% of accuracy (sensitivity of 94.96% for HCM and specificity of 96.90%) using only two main features: the percentage of negative regions of the QRS complex with respect to the isoelectric level and the 3rd coefficient of its Hermite fitting showing interesting connections to cardiac electrophysiology.

Myocardial diffusion tensor imaging using diffusion-prepared SSFP

Background Diffusion tensor imaging of the myocardium is challenging due to the large bulk motion of the heart relative to the distance water diffuses. One solution is to use diffusion gradients on two consecutive heartbeats, with EPI to readout the stimulated echo [1]. The technique has not been widely adopted, primarily due to the long imaging times required to overcome the low SNR of the technique. Recent new technology such as 3T scanners and 32-channel cardiac arrays improve the SNR, helping to make this approach feasible clinically. SSFP provides reduced distortion and high image quality, therefore we investigated the feasibility of replacing the EPI readout with SSFP for myocardial diffusion tensor imaging at 3T. Methods The modified ECG-gated SSFP sequence including a diffusion preparation module is shown in Figure 1a. A final 90° tip-up pulse was required to enable an SSFP readout module rather than EPI. In order to avoid signal voids due to phase accrued from sub-millimetre bulk motion between the two diffusion gradients, a dephase gradient in the slice direction was included before the tip-up pulse, with this residual phase gradient rewound during each readout [2]. The sequence was tested on a 3T Siemens Trio using a 32-channel coil. Images were acquired in diastole (650 ms after the R-wave). Two heartbeats for T1 recovery were included between each imaging module, and the following readout parameters were used: TR/TE=2.5/1.3 ms,a=120°, bandwidth 1021 Hz/px, GRAPPA (R=2), matrix size 96x92, voxel size 2.7x2.7x10 mm. One b=0 image and 3 directions with prescribed b=300 s/mm 2 were acquired in each 14-heartbeat breathhold, with three averages, requiring six breathholds for a single slice. Data were analysed in Matlab and mean diffusivity (MD), fractional anisotropy (FA) and helix angle (HA) calculated. A mid-ventricular slice was acquired in three normal volunteers and one patient with known hypertrophic cardiomyopathy (HCM). Results