Left ventricular volume regulation in heart failure with preserved ejection fraction

Left ventricular volume analysis as a basic tool to describe cardiac function

The heart is often regarded as a compression pump. Therefore, determination of pressure and volume is essential for cardiac function analysis. Traditionally, ventricular performance was described in terms of the Starling curve, i.e., output related to input. This view is based on two variables (namely, stroke volume and end-diastolic volume), often studied in the isolated (i.e., denervated) heart, and has dominated the interpretation of cardiac mechanics over the last century. The ratio of the prevailing coordinates within that paradigm is termed ejection fraction (EF), which is the popular metric routinely used in the clinic. Here we present an insightful alternative approach while describing volume regulation by relating end-systolic volume (ESV) to end-diastolic volume. This route obviates the undesired use of metrics derived from differences or ratios, as employed in previous models. We illustrate basic principles concerning ventricular volume regulation by data obtained from intact animal experiments and collected in healthy humans. Special attention is given to sex-specific differences. The method can be applied to the dynamics of a single heart and to an ensemble of individuals. Group analysis allows for stratification regarding sex, age, medication, and additional clinically relevant covariates. A straightforward procedure derives the relationship between EF and ESV and describes myocardial oxygen consumption in terms of ESV. This representation enhances insight and reduces the impact of the metric EF, in favor of the end-systolic elastance concept advanced 4 decades ago.

Arterial Wall Properties in Men and Women: Hemodynamic Analysis and Clinical Implications

The properties of arterial walls are dictated by their underlying structure, which is responsible for the adequate perfusion of conduit branching arteries and their vascular beds. Beginning with the mechanobiology of arteries in terms of their composition and individual contributions to overall viscoelastic behavior in men and women, pressure-flow relations are analyzed and noted in terms of sex differences. Hemodynamic function in terms of indices of vascular stiffness-such as pressure-strain elastic modulus, pulse wave velocity, augmentation index, and cardio-ankle vascular index-are evaluated. They all showed differences between the sexes, and these differences also were shown among people of different cultures. Recent studies also showed, in heart failure patients, a comparatively greater increase in peripheral resistance and a greater decreased arterial compliance in women. Wave separation into forward and reflected waves allows elucidation of mechanical and drug-treated similarities and differences in induced hypertension. This may provide insight into treatment strategy in terms of improving mechanobiology and designing drug therapy for the sexes. Finally, modeling studies are useful in identifying how arterial compliance and its pressure dependence can be better used in differentiating aging- and hypertension-induced changes that differentially affect the sexes.

Associations of increased arterial stiffness with left ventricular ejection performance and right ventricular systolic pressure in mitral regurgitation before and after surgery: Wave intensity analysis

Background

The effect of increased arterial stiffness on mitral regurgitation (MR) is not clear. Using wave intensity (WI) analysis, which is useful for analyzing ventriculo-arterial interaction, we aimed to elucidate associations of increased arterial stiffness with left ventricular (LV) ejection performance and right ventricular systolic pressure (RVSP) in MR.

Methods and Results

We noninvasively measured carotid arterial WI and stiffness parameter (β) in 98 patients with non-ischemic chronic MR before and after surgery, and 98 age-and-gender matched healthy subjects by ultrasonography. WI is defined as WI = (dP/dt)(dU/dt) [P: blood pressure, U: velocity, t: time]. The peak value of WI (W₁) increases with LV peak dP/dt. The temporal WI index (Q-W₁)st, which is the standardized interval between the Q wave of the ECG and W₁, is a surrogate for preejection period. Ejection fraction (EF), left atrial volume index (LAVI), effective regurgitant orifice area (ERO), RVSP, and other echocardiographic data were also obtained. W₁ was enhanced in the MR group before surgery compared with the normal group (10.7 ± 5.7 vs 8.5 ± 3.6 × 10³ mmHg m/s³, p < 0.05). However, the results of two-way ANOVA showed this enhancement of W₁ was observed only in the subgroup of MR before surgery with lower arterial stiffness (β < 13, p< 0.0001). ERO, β and LAVI were predictor variables before surgery to determine RVSP. EF and (Q-W₁)st before surgery were predictor variables for EF after surgery.

Conclusions

In the MR group before surgery, increased arterial stiffness suppresses compensatory enhancement of W₁, and increases RVSP. Prolonged (Q-W₁)st has the potential for predicting low EF after surgery.

Information maximizing component analysis of left ventricular remodeling due to myocardial infarction

BACKGROUND

Although adverse left ventricular shape changes (remodeling) after myocardial infarction (MI) are predictive of morbidity and mortality, current clinical assessment is limited to simple mass and volume measures, or dimension ratios such as length to width ratio. We hypothesized that information maximizing component analysis (IMCA), a supervised feature extraction method, can provide more efficient and sensitive indices of overall remodeling.

METHODS

IMCA was compared to linear discriminant analysis (LDA), both supervised methods, to extract the most discriminatory global shape changes associated with remodeling after MI. Finite element shape models from 300 patients with myocardial infarction from the DETERMINE study (age 31-86, mean age 63, 20 % women) were compared with 1991 asymptomatic cases from the MESA study (age 44-84, mean age 62, 52 % women) available from the Cardiac Atlas Project. IMCA and LDA were each used to identify a single mode of global remodeling best discriminating the two groups. Logistic regression was employed to determine the association between the remodeling index and MI. Goodness-of-fit results were compared against a baseline logistic model comprising standard clinical indices.

RESULTS

A single IMCA mode simultaneously describing end-diastolic and end-systolic shapes achieved best results (lowest Deviance, Akaike information criterion and Bayesian information criterion, and the largest area under the receiver-operating-characteristic curve). This mode provided a continuous scale where remodeling can be quantified and visualized, showing that MI patients tend to present larger size and more spherical shape, more bulging of the apex, and thinner wall thickness.

CONCLUSIONS

IMCA enables better characterization of global remodeling than LDA, and can be used to quantify progression of disease and the effect of treatment. These data and results are available from the Cardiac Atlas Project ( http://www.cardiacatlas.org ).

Left Ventricle-Arterial System Interaction in Heart Failure

Ejection fraction (EF) has been viewed as an important index in assessing the contractile state of the left ventricle (LV). However, it is frequently inadequate for the diagnosis and management of heart failure (HF), as a significant subset of HF patients have been found to have reduced EF (HFrEF) whereas others have preserved EF (HFpEF). It should be noted that the function of the LV is dependent on both preload and afterload, as well as its intrinsic contractile state. Furthermore, stroke volume (SV) is dependent on the properties of the arterial system (AS). Thus, the LV-arterial system interaction plays an important role in those patients with HF. This aspect is investigated through the analysis of the specific parameters involved in the coupling of the LV and AS. This includes contractility and the systolic/diastolic indices of the LV. Furthermore, AS afterload parameters such as vascular stiffness and arterial compliance, and their derived coupling coefficient, are also investigated. We conclude that those parameters, which relate to LV structural changes, are most appropriate in quantifying the LV-AS interaction.

Exploring Guidelines for Classification of Major Heart Failure Subtypes by Using Machine Learning

BACKGROUND

Heart failure (HF) manifests as at least two subtypes. The current paradigm distinguishes the two by using both the metric ejection fraction (EF) and a constraint for end-diastolic volume. About half of all HF patients exhibit preserved EF. In contrast, the classical type of HF shows a reduced EF. Common practice sets the cut-off point often at or near EF = 50%, thus defining a linear divider. However, a rationale for this safe choice is lacking, while the assumption regarding applicability of strict linearity has not been justified. Additionally, some studies opt for eliminating patients from consideration for HF if 40 < EF < 50% (gray zone). Thus, there is a need for documented classification guidelines, solving gray zone ambiguity and formulating crisp delineation of transitions between phenotypes.

METHODS

Machine learning (ML) models are applied to classify HF subtypes within the ventricular volume domain, rather than by the single use of EF. Various ML models, both unsupervised and supervised, are employed to establish a foundation for classification. Data regarding 48 HF patients are employed as training set for subsequent classification of Monte Carlo-generated surrogate HF patients (n = 403). Next, we map consequences when EF cut-off differs from 50% (as proposed for women) and analyze HF candidates not covered by current rules.

RESULTS

The training set yields best results for the Support Vector Machine method (test error 4.06%), covers the gray zone, and other clinically relevant HF candidates. End-systolic volume (ESV) emerges as a logical discriminator rather than EF as in the prevailing paradigm.

CONCLUSIONS

Selected ML models offer promise for classifying HF patients (including the gray zone), when driven by ventricular volume data. ML analysis indicates that ESV has a role in the development of guidelines to parse HF subtypes. The documented curvilinear relationship between EF and ESV suggests that the assumption concerning a linear EF divider may not be of general utility over the complete clinically relevant range.

The Volume Regulation Graph versus the Ejection Fraction as Metrics of Left Ventricular Performance in Heart Failure with and without a Preserved Ejection Fraction: A Mathematical Model Study

In left ventricular heart failure, often a distinction is made between patients with a reduced and a preserved ejection fraction (EF). As EF is a composite metric of both the end-diastolic volume (EDV) and the end-systolic ventricular volume (ESV), the lucidity of the EF is sometimes questioned. As an alternative, the ESV-EDV graph is advocated. This study identifies the dependence of the EF and the EDV-ESV graph on the major determinants of ventricular performance. Numerical simulations were made using a model of the systemic circulation, consisting of an atrium-ventricle valves combination; a simple constant pressure as venous filling system; and a three-element Windkessel extended with a venous system. ESV-EDV graphs and EFs were calculated using this model while varying one by one the filling pressure, diastolic and systolic ventricular elastances, and diastolic pressure in the aorta. In conclusion, the ESV-EDV graph separates between diastolic and systolic dysfunction while the EF encompasses these two pathologies. Therefore, the ESV-EDV graph can provide an advantage over EF in heart failure studies.

Characterizing heart failure in the ventricular volume domain

Heart failure (HF) may be accompanied by considerable alterations of left ventricular (LV) volume, depending on the particular phenotype. Two major types of HF have been identified, although heterogeneity within each category may be considerable. All variants of HF show substantially elevated LV filling pressures, which tend to induce changes in LV size and shape. Yet, one type of HF is characterized by near-normal values for LV end-diastolic volume (EDV) and even a smaller end-systolic volume (ESV) than in matched groups of persons without cardiac disease. Furthermore, accumulating evidence indicates that, both in terms of shape and size, in men and women, the heart reacts differently to adaptive stimuli as well as to certain pharmacological interventions. Adjustments of ESV and EDV such as in HF patients are associated with (reverse) remodeling mechanisms. Therefore, it is logical to analyze HF subtypes in a graphical representation that relates ESV to EDV. Following this route, one may expect that the two major phenotypes of HF are identified as distinct entities localized in different areas of the LV volume domain. The precise coordinates of this position imply unique characteristics in terms of the actual operating point for LV volume regulation. Evidently, ejection fraction (EF; equal to 1 minus the ratio of ESV and EDV) carries little information within the LV volume representation. Thus far, classification of HF is based on information regarding EF combined with EDV. Our analysis shows that ESV in the two HF groups follows different patterns in dependency of EDV. This observation suggests that a superior HF classification system should primarily be founded on information embodied by ESV.