Precision Phenotyping in Heart Failure and Pattern Clustering of Ultrasound Data for the Assessment of Diastolic Dysfunction

Omar, Alaa Mabrouk Salem; Narula, Sukrit; Rahman, Mohamed Ahmed Abdel; Pedrizzetti, Gianni; Raslan, Hala M.; Rifaie, Osama; Narula, Jagat; Sengupta, Partho P.

doi:10.1016/j.jcmg.2016.10.012

Cited by 83 publications

(51 citation statements)

References 28 publications

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“…Our findings support the hypothesis that HFpEF could be a result of lower subendocardial contractility linked with increased subepicardial contractility (Sengupta and Narula, 2008; Shah and Solomon, 2012; Omar et al, 2016, 2017). When subendocardial contractility was zero, LVEF decreased by 23.9% (Table 2: 53.2% in scenario 1 vs. 40.5% in scenario 2).…”

Section: Discussionsupporting

confidence: 90%

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Relationship of Transmural Variations in Myofiber Contractility to Left Ventricular Ejection Fraction: Implications for Modeling Heart Failure Phenotype With Preserved Ejection Fraction

et al. 2018

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The pathophysiological mechanisms underlying preserved left ventricular (LV) ejection fraction (EF) in patients with heart failure and preserved ejection fraction (HFpEF) remain incompletely understood. We hypothesized that transmural variations in myofiber contractility with existence of subendocardial dysfunction and compensatory increased subepicardial contractility may underlie preservation of LVEF in patients with HFpEF. We quantified alterations in myocardial function in a mathematical model of the human LV that is based on the finite element method. The fiber-reinforced material formulation of the myocardium included passive and active properties. The passive material properties were determined such that the diastolic pressure-volume behavior of the LV was similar to that shown in published clinical studies of pressure-volume curves. To examine changes in active properties, we considered six scenarios: (1) normal properties throughout the LV wall; (2) decreased myocardial contractility in the subendocardium; (3) increased myocardial contractility in the subepicardium; (4) myocardial contractility decreased equally in all layers, (5) myocardial contractility decreased in the midmyocardium and subepicardium, (6) myocardial contractility decreased in the subepicardium. Our results indicate that decreased subendocardial contractility reduced LVEF from 53.2 to 40.5%. Increased contractility in the subepicardium recovered LVEF from 40.5 to 53.2%. Decreased contractility transmurally reduced LVEF and could not be recovered if subepicardial and midmyocardial contractility remained depressed. The computational results simulating the effects of transmural alterations in the ventricular tissue replicate the phenotypic patterns of LV dysfunction observed in clinical practice. In particular, data for LVEF, strain and displacement are consistent with previous clinical observations in patients with HFpEF, and substantiate the hypothesis that increased subepicardial contractility may compensate for subendocardial dysfunction and play a vital role in maintaining LVEF.

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Section: Discussionsupporting

confidence: 90%

“…Recent studies have suggested that HFpEF is associated with transmural changes in myocardial deformation (Shah and Solomon, 2012; Omar et al, 2016, 2017). Understanding the transmural variations in left ventricular (LV) mechanics associated with HFpEF may offer pathophysiological insights for developing potential therapeutic targets.…”

Section: Introductionmentioning

confidence: 99%

Relationship of Transmural Variations in Myofiber Contractility to Left Ventricular Ejection Fraction: Implications for Modeling Heart Failure Phenotype With Preserved Ejection Fraction

et al. 2018

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“…Making sense of all this information is a challenge that can likely be met by machine learning. Recent studies suggest that it may be useful for diagnosis and for defining pathophysiology, 15 , 295 , 296 but long‐term studies in large populations are needed to unravel which features best predict clinical outcomes and responses to treatment. Molecular phenotyping for a better identification of distinct HFpEF phenotypes is emerging and may also help to develop targeted therapies.…”

Section: Calculating and Interpreting The Hfa–peff Scorementioning

confidence: 99%

“…Additional diagnostic criteria for HFpEF have been published, including one scoring system, but they differ in echocardiographic cut‐off values, the role of comorbidities, the inclusion of biomarkers, the role of invasive haemodynamic assessment, and the role of exercise stress testing , 4 , 6–8 . Understanding of the pathophysiology of HFpEF has advanced, 9–13 diagnostic options have evolved, 14–17 and this novel information needs to be integrated into a new comprehensive diagnostic algorithm for suspected HFpEF.…”

Section: Introductionmentioning

confidence: 99%

How to diagnose heart failure with preserved ejection fraction: the HFA–PEFF diagnostic algorithm: a consensus recommendation from the Heart Failure Association (HFA) of the European Society of Cardiology (ESC)

Pieske

Tschöpe

Boer

et al. 2020

European J of Heart Fail

406

643

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Making a firm diagnosis of chronic heart failure with preserved ejection fraction (HFpEF) remains a challenge. We recommend a new stepwise diagnostic process, the ‘HFA–PEFF diagnostic algorithm’. Step 1 (P=Pre‐test assessment) is typically performed in the ambulatory setting and includes assessment for heart failure symptoms and signs, typical clinical demographics (obesity, hypertension, diabetes mellitus, elderly, atrial fibrillation), and diagnostic laboratory tests, electrocardiogram, and echocardiography. In the absence of overt non‐cardiac causes of breathlessness, HFpEF can be suspected if there is a normal left ventricular (LV) ejection fraction, no significant heart valve disease or cardiac ischaemia, and at least one typical risk factor. Elevated natriuretic peptides support, but normal levels do not exclude a diagnosis of HFpEF. The second step (E: Echocardiography and Natriuretic Peptide Score) requires comprehensive echocardiography and is typically performed by a cardiologist. Measures include mitral annular early diastolic velocity (e′), LV filling pressure estimated using E/e′, left atrial volume index, LV mass index, LV relative wall thickness, tricuspid regurgitation velocity, LV global longitudinal systolic strain, and serum natriuretic peptide levels. Major (2 points) and Minor (1 point) criteria were defined from these measures. A score ≥5 points implies definite HFpEF; ≤1 point makes HFpEF unlikely. An intermediate score (2–4 points) implies diagnostic uncertainty, in which case Step 3 (F1: Functional testing) is recommended with echocardiographic or invasive haemodynamic exercise stress tests. Step 4 (F2: Final aetiology) is recommended to establish a possible specific cause of HFpEF or alternative explanations. Further research is needed for a better classification of HFpEF.

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“…What we need are new methods to integrate all the information from sophisticated non‐invasive diagnostic tests at rest and during exercise, and to identify from large prospective studies which tools are the best for diagnosis, prognosis, and monitoring; they may be different. The application of machine learning to this field is one way in which we might achieve these results …”

mentioning

confidence: 99%

Non‐invasive estimation of left heart filling pressures: another nail in the coffin for E/e'?

Donal

Galli

Fraser

2017

European J of Heart Fail

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Precision Phenotyping in Heart Failure and Pattern Clustering of Ultrasound Data for the Assessment of Diastolic Dysfunction

Abstract: Tracking deformation of the left-sided cardiac chambers from routine cardiac ultrasound images provides accurate information for Doppler-independent phenotypic characterization of LV diastolic function and noninvasive assessment of LV filling pressures.

Cited by 83 publications

References 28 publications

Relationship of Transmural Variations in Myofiber Contractility to Left Ventricular Ejection Fraction: Implications for Modeling Heart Failure Phenotype With Preserved Ejection Fraction

Relationship of Transmural Variations in Myofiber Contractility to Left Ventricular Ejection Fraction: Implications for Modeling Heart Failure Phenotype With Preserved Ejection Fraction

How to diagnose heart failure with preserved ejection fraction: the HFA–PEFF diagnostic algorithm: a consensus recommendation from the Heart Failure Association (HFA) of the European Society of Cardiology (ESC)

Non‐invasive estimation of left heart filling pressures: another nail in the coffin for E/e'?

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