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The concept of ventricular-arterial coupling (VAC) was first introduced in the early 1980s to quantify the relationship between left ventricular contractility and arterial load. The mathematical formulation of VAC, expressed as the ratio of arterial elastance to ventricular elastance, has since then been refined with adjustments to allow for non-invasive assessment. By the early 2000s, advancements in echocardiography, cardiac magnetic resonance and arterial tonometry provided non-invasive alternatives to the traditional invasive method of cardiac catheterization, broadening the clinical application of VAC. Emerging technologies, such as machine learning and computational models, have further enhanced the precision and personalization of VAC, with potential applications in heart failure, hypertension and other clinical scenarios. This review describes the physiological basis and the historical development of VAC, highlights the non-invasive assessment techniques, and discusses the potential for personalized treatment based on VAC insights. Machine learning models trained on large datasets from non-invasive imaging modalities may open new avenues in predicting individual patient responses to therapies. However, lack of standardized protocols across imaging modalities represents a challenge, making the call for standardization critical for consistent clinical application. This review underscores the need for harmonized methodologies to better utilize VAC in personalized medicine, aiming to improve cardiovascular outcomes through tailored therapies.

Abstract We sought to assess cardiac magnetic resonance derived left ventricular hemodynamic forces (HDF) in athletes compared to patients with hypertension. Sixty athletes and 48 hypertensive patients were studied. HDF were measured during the entire cardiac cycle, the systolic phase, suction, early LV filling, and atrial thrust. Statistical comparisons were made between athletes and hypertensive patients, and between endurance and strength athletes. The slope of the systolic ejection was higher in athletes compared to hypertensive patients (541.5 vs. 435 1/sec; p = 0.033). Athletes showed higher HDF during the first phase of systole (4.53 vs. 3.86; p = 0.047) and the systolic impulse (11.26 vs. 8.76; p = 0.045). Compared to hypertensive patients, the AUC of the elastic rebound in athletes was lower (-0.31 vs. -0.44; p = 0.011). Moreover, hypertensive patients had an abnormal suction as revealed by a divergent direction (apex-to-base) of the HDF. The atrial thrust was higher in hypertensive patients than in athletes (-0.31 vs. -0.05; p

Abstract Background Physical activity contributes to changes in cardiac morphology, which are known as “athlete’s heart”. Therefore, these modifications can be characterized using different imaging modalities such as echocardiography, including Doppler (flow Doppler and Doppler myocardial imaging) and speckle-tracking, along with cardiac magnetic resonance, and cardiac computed tomography. Main text Echocardiography is the most common method for assessing cardiac structure and function in athletes due to its availability, repeatability, versatility, and low cost. It allows the measurement of parameters like left ventricular wall thickness, cavity dimensions, and mass. Left ventricular myocardial strain can be measured by tissue Doppler (using the pulse wave Doppler principle) or speckle tracking echocardiography (using the two-dimensional grayscale B-mode images), which provide information on the deformation of the myocardium. Cardiac magnetic resonance provides a comprehensive evaluation of cardiac morphology and function with superior accuracy compared to echocardiography. With the addition of contrast agents, myocardial state can be characterized. Thus, it is particularly effective in differentiating an athlete’s heart from pathological conditions, however, is less accessible and more expensive compared to other techniques. Coronary computed tomography is used to assess coronary artery anatomy and identify anomalies or diseases, but its use is limited due to radiation exposure and cost, making it less suitable for young athletes. A novel approach, hemodynamic forces analysis, uses feature tracking to quantify intraventricular pressure gradients responsible for blood flow. Hemodynamic forces analysis has the potential for studying blood flow within the heart and assessing cardiac function. Conclusions In conclusion, each diagnostic technique has its own advantages and limitations for assessing cardiac adaptations in athletes. Examining and comparing the cardiac adaptations resulting from physical activity with the structural cardiac changes identified through different diagnostic modalities is a pivotal focus in the field of sports medicine. Graphical Abstract

The purpose of this review is to describe the impact of endurance and strength physical training on the cardiovascular system by reviewing the molecular signaling pathways, which plays a key role in different muscle adaptations, and the cardiac changes in terms of metabolic and cardiac remodeling, and hemodynamics. In response to endurance-exercise, multiple signaling pathways, including Ca2+-dependent pathways, reactive oxygen species (ROS), AMP-dependent protein kinase (AMPK), and mitogen activated protein kinases (p38 MAPK), are involved in the regulation of peroxisome-proliferator-activated receptor-γ coactivator-1α (PGC-1α), which controls the mitochondrial biogenesis. Strength training increases the insulin-like growth factor (IGF-1) which initiates the phosphatidylinositol 3-kinase (PI3-k)-(AKT)-(mTOR) signaling cascade, resulting in the synthesis of proteins and the muscle hypertrophy. In addition to the well-documented changes in skeletal muscle, a critical component of the response to exercise training is the dynamic cardiac remodeling, which is classified as either pathological or physiological depending on triggers.

BackgroundHemodynamic forces (HDF) analysis has been proposed as a method to quantify intraventricular pressure gradients, however data on its reliability are still scanty. Thus, the aim of this study is to assess the reliability of HDF parameters derived from cardiac magnetic resonance (CMR).MethodsCMR studies of 25 athletes were analysed by two independent observers and then re-analysed by the same observer one week apart. Intraclass Correlation Coefficient (ICC [95% CI]) and Bland-Altman plots were used to assess association, agreement, and bias of the longitudinal (A-B) HDF, transverse (L-S) HDF, and Impulse Angle. The sample size required to detect a relative change in the HDF parameters was also calculated.ResultsIn terms of inter-observer variability, there was a good correlation for the A-B and L-S (ICC 0.85 [0.67-0.93] and 0.86 [0.69-0.94]; pConclusionsThe results of this study showed a low inter- and intra-observer variability of HDF parameters derived from feature-tracking CMR. This provides the fundamental basis for their use both in research and clinical practice, which could eventually lead to the detection of significant changes at follow-up studies.