Heart Failure with Preserved Ejection Fraction (HFpEF) is a major public health disorder, accounting for at least 50% of all heart failure patients, with an increasing prevalence.
The primary complaint of HFpEF patients is exercise intolerance. However, accurately assessing this symptom solely based on patient-reported outcomes can be challenging. The typical HFpEF phenotype, often referred to as "Garden Variety HFpEF" (an English term describing something ordinary or standard, lacking exceptional characteristics), typically includes at least four comorbidities, such as obesity, hypertension, atrial fibrillation, and kidney disease. These comorbidities complicate the differential diagnosis, making it difficult to distinguish between reduced exercise capacity caused by the comorbid conditions and the heart failure syndrome itself.
In this context, echocardiography plays a crucial role in evaluating patients with suspected HFpEF, and strain imaging can indeed provide critical information to improve diagnostic performance.
The technical requirements for obtaining high-quality GLS have been detailed in the guidelines.
The score proposed by the European Society of Cardiology (HFA-PEFF)
Evaluating GLS in conjunction with other features is crucial, as an abnormal GLS has been associated with various clinical conditions known to impair the myocardium, such as hypertension, diabetes mellitus, aortic stenosis, and amyloidosis. These conditions may act as risk factors or HFpEF mimics.
Abnormalities in GLS without other pathophysiological impairments may not fulfill all conditions to increase filling pressures and cause HFpEF syndrome. Indeed, other studies have shown that GLS only moderately correlates with filling pressures.
Nonetheless, there is evidence that GLS may have a significant role in the physiological cardiocirculatory adaptations that determine exercise capacity. A recent meta-analysis of 25 studies, comprising 2136 patients with preserved and reduced EF, demonstrated that both GLS and EF have a linear relationship with peak oxygen uptake (VO2). However, the correlation between VO2 and GLS was twice as strong as the correlation between VO2 and EF.
Patients with HFpEF may exhibit functional abnormalities primarily during hemodynamic overload, with the exercise test using a cycle ergometer being the preferred modality for inducing such stress.
It is crucial to recognize that GLS is a load-sensitive parameter,
Despite that, there is a notable gap in research concerning how pathological deviations in HFpEF might affect or alter GLS patterns during exercise.
One of the key technical considerations when assessing GLS during exercise echocardiography is the trade-off between frame rate and heart rate. As the heart rate increases during exercise, the cardiac cycle shortens, necessitating a higher frame rate to capture sufficient detail of myocardial motion throughout the cycle. High frame rates are crucial for accurately tracking myocardial deformation, especially at higher heart rates.
However, achieving higher frame rates often involves compromising spatial resolution, which can impact the accuracy of strain measurements.
Optimizing frame rate during exercise echocardiography is essential to balance the need for detailed temporal resolution and the limitations of spatial resolution. An inadequate frame rate can lead to under-sampling of myocardial motion, resulting in inaccurate GLS measurements and potential misinterpretation of myocardial function.
In clinical practice, it's essential to adjust ultrasound settings dynamically during exercise to maintain optimal frame rates as heart rates increase. This dynamic adjustment helps ensure that GLS measurements remain reliable and reflective of true myocardial performance under exercise conditions. For an accurate evaluation of peak longitudinal and peak circumferential strain, a proportion of 30 frames per cardiac cycle is recommended. This means that the minimum frame rate must be adjusted to ensure that at least 30 frames are captured during each cardiac cycle to provide reliable strain measurements. For instance, for a heart rate of 80 bpm, the minimum frame rate would be > 40 fps, while for a heart rate of 160 bpm, the minimum frame rate would be > 85 fps. From a practical point of view, it is recommended to aim to maintain a frame rate above 70% of the heart rate. Of note, this does not apply to the evaluation of the isovolumic phases, where frame rates as high as 500 fps would be required, which is an area to be explored with the new algorithms of high-frame-rate speckle tracking imaging.
In certain clinical settings or due to technical limitations, patients may be unable to undergo standard exercise tests. In such cases, alternative stress modalities, such as preload or afterload challenge, can provide valuable insights into myocardial function.
These methods can be used either individually or in combination. Afterload challenges may offer distinct advantages over standard dynamic exercise, as they induce a controlled hemodynamic overload without significantly raising heart and respiratory rates. This leads to less noise in echocardiographic signals, thereby enhancing the accuracy of advanced deformation imaging.
Nonetheless, it is important to recognize the fundamental differences between standard dynamic exercise and afterload challenge. Standard dynamic exercise primarily induces a "forward perturbation," which sequentially increases central venous pressure, pulmonary artery wedge pressure, left atrial preload, and the left atrium-left ventricle (LA-LV) gradient, raising the mitral E wave. This type of stress challenges the left ventricle (LV) to enhance the velocity of relaxation (e'), thereby assessing diastolic reserve.
In contrast, an afterload challenge creates a "backward perturbation" by increasing systemic resistance, which reduces the velocity of LV relaxation. This results in lower e' velocities and a diminished LA-LV gradient (lower mitral E wave). Consequently, echocardiographic features such as the E/e' ratio exhibit different behavior under this type of stress, often without a significant increase. The normal ventricular response to increased afterload typically involves a reduction in the velocity and extent of ventricular contraction, leading to a compensatory increase in preload and activation of the Frank-Starling mechanism for heart contraction. Notably, LV longitudinal function assessed through strain imaging appears particularly sensitive to these contraction changes.
Studies investigating GLS during hemodynamic stress induced by afterload challenge can provide significant insights.
Therefore, the afterload challenge presents characteristics that make it the modality of choice to study changes in myocardial deformation and ventricular-arterial coupling during stress.
The GLS measures the average amount of longitudinal contraction performed by the LV from the onset of isovolumetric contraction to the end of ventricular ejection. Consequently, valuable information about other phases of the cardiac cycle, such as isovolumetric relaxation, is not captured by GLS.
Mechanical dispersion (MD) is a strain feature that expresses the degree of temporal heterogeneity of contraction, serving as an indicator of mechanical dyssynchrony (
The rationale for using this index in HFpEF is that, theoretically, a heterogeneous cardiac contraction, as stated by a high MD, leads to regional contractions that do not reach the reciprocal force from the opposite cardiac walls. Therefore, part of cardiac deformation will not be translated into an effective force to expel blood towards the aorta. Furthermore, dyssynchrony will affect both AV and VA coupling. This double hit in LV performance makes the heart more prone to higher increases in left atrium (LA) pressure during exercise adaptations such as increased preload and tachycardia. Thus, in the context of relatively preserved GLS, information on the synchronicity of contraction may help explain the subtle impairments observed in a subset of patients with HFpEF.
Recent data suggest that MD is more associated with exercise capacity in patients with pre-HFpEF and HFpEF when compared to GLS and other components of HFA-PEFF score, and it may provide new insights into how the heart could be more prone to the steep increase in filling pressures during exercise that characterizes this syndrome.
Currently, there is no precise cutoff for MD, but recent data indicate that values greater than 65 ms have high specificity for identifying subjects with a high probability of HFpEF.
The patterns of different indices of strain imaging can help identify specific phenogroups within HFpEF.
Conversely, 18-48% of HFpEF patients retain preserved GLS (HFpEF-pLS), yet they may still have other pathophysiological issues such as atrial dysfunction and pulmonary vascular disease.