European heart journal. Imaging methods and practice最新文献

Aims: Cardiac myosin inhibitors (CMIs) have revolutionized care for patients with obstructive hypertrophic cardiomyopathy (HCM), however they are associated with a risk of systolic dysfunction. Machine learning algorithms might expand access to frequent accurate assessment of left ventricular ejection fraction (LVEF). We assess the performance of a commercial ML-based LVEF model for patients with HCM.

Methods and results: Single centre prospective study of measurements of left ventricular function by Philips HeartModel® (automated) assessment, echocardiographer assessment (standard), and cardiac magnetic resonance imaging for patients with HCM. Assessments of LVEF, end diastolic volume and end systolic volume were studied across methods. 50 patients with HCM were included. Median age 64 years; 64% male; and 62% had cMRI data for analysis. Median automated LVEF was lower than standard [55.5% (IQR 9) vs. 62.5% (IQR 10), P 0.002, median difference-8% (IQR 14)] and cMRI assessment [55.5% (IQR 9) vs. 68% (IQR 9.5), P < 0.001, median difference-12% (IQR 16)]. Automated assessment traced larger EDVs and ESVs compared with standard 2D tracings [141 mL (IQR 66) vs. 114 mL (IQR 55), P 0.001, and 64 mL (IQR 35) vs. 41 mL (IQR 25), P < 0.001]. Automated assessment identified 11 (22%) patients as having LVEF < 50% vs. 6 (12%) patients identified by expert imaging assessment.

Conclusion: For patients with HCM, automated assessments of LV size and function differ significantly from standard assessments, raising concerns about the use of this ML-enabled LVEF software for this patient population and potential application to guiding CMI treatments.

Introduction: Myocardial perfusion imaging (MPI) is used to evaluate ischaemia in patients with chronic total occlusion (CTO), but its prognostic implications following percutaneous coronary intervention (PCI) of CTO remain uncertain.

Purpose: To evaluate outcomes in patients treated with CTO-PCI stratified by moderate-severe ischaemia on MPI prior to intervention.

Methods and results: Patients from the Western Danish Heart Registry assessed by nuclear MPI and subsequently treated with CTO-PCI ≤ 6 months were included. Moderate-severe ischaemia was defined as ≥10% left ventricle involvement. Primary endpoints were all-cause mortality and a composite of major adverse cardio- and cerebrovascular events [MACCE; cardiovascular death, myocardial infarction (MI), stroke, and hospitalization for heart failure (HF) or angina pectoris]. Secondary endpoints included the individual MACCE components. Outcomes were compared between patients with and without moderate-severe ischaemia using multivariable Cox regression and competing risk regression at 90-day and 5-year follow-ups. Among 319 patients, 208 (65.2%) had moderate-severe ischaemia. All-cause mortality was similar between patients with and without moderate-severe ischaemia [adjusted hazard ratio (aHR) 1.12, 95% confidence interval (CI): 0.52-2.43], P = 0.77). The estimated risk of MACCE was comparable between groups at 90 days [aHR 0.76 (0.38-1.55), P = 0.46] and 5 years [aHR 0.74 (0.45-1.20), P = 0.22]. No difference was found in MI [5 years: aHR 0.76 (0.26-2.22), P = 0.61] or hospitalization for HF [90 days: aHR 0.44 (0.16-1.21), P = 0.11]; 5 years: aHR 0.62 (0.30-1.30), P = 0.21]. Hospitalization for angina was similar at 90 days [aHR 0.75 (0.26-2.16), P = 0.60], but a decreased 5-year risk was observed in patients with moderate-severe ischaemia [aHR 0.46 (0.23-0.91), P = 0.026].

Conclusion: Moderate-severe ischaemia on nuclear MPI was not associated with differences in mortality or MACCE after CTO-PCI but was associated with a lower long-term risk of angina hospitalization.

Aims: To reveal the pattern and dynamics of myocardial oedema induced by myocardial infarction (MI) during ischaemia and subsequent reperfusion, that remain largely unknown, as are the factors that contribute to reperfusion injury. To propose a time-resolved dynamic myocardial tissue characterization by quantitative CMR, with T1&T2 mapping and Pixel-wise standardized analysis to circumvent inter-animal differences and subjective ROI positioning.

Methods and results: We measured T1&T2 relaxation times at baseline, during a 40-min transient coronary occlusion, and after reperfusion in an open-chest swine MI model (n = 20; 2 shams) using MRI. Myocardial function, early and late gadolinium enhancement were also assessed. Pixel-wise standardized analysis was used to compare the image contents at each pixel across individuals and time points. A significant increase in cardiac T1&T2 times in the ischaemic regions occurred during ischaemia compared with baseline (mean ΔT1 = 118.8 ms i.e. + 11.1%, ΔT2 = 5.6 ms i.e. + 11.3%; P < 0.05). A global significant and marked increase in T1&T2 times further appeared immediately after reperfusion (mean ΔT1 = 256.8 ms i.e. + 23.3% mean ΔT2 = 11.9 ms i.e. + 23.6%, P < 0.001). This increase was associated with myocardial wall thickness changes, with regional and global dysfunction in the ischaemic myocardium. Three different reperfusion patterns were differentiated by the pixel-wise T1 signal analysis: effective reperfusion with microvascular obstruction (MVO), effective reperfusion without MVO and absence of effective reperfusion. We found no correlations between baseline, per-ischaemia, and post-reperfusion native T1&T2 times when effective reperfusion occurred.

Conclusion: Objective quantification of tissue response by pixel-wise analysis demonstrated rapid and significant changes in myocardial water content status post-reperfusion, with three different early-reperfusion patterns observed, suggesting distinct reperfusion mechanisms. The water content after reperfusion does not reflect its state before and it does not provide insight into the final tissue status observed within 3 h after recanalization.

Point-of-care ultrasound (POCUS) has rapidly evolved from a diagnostic adjunct into an essential extension of bedside clinical reasoning in acute cardiovascular care. By providing immediate, physiologically grounded, and non-invasive information, POCUS enhances diagnostic accuracy, risk stratification, and therapeutic guidance in real time. Among its core applications, lung ultrasound enables reliable detection and monitoring of pulmonary congestion, outperforming traditional methods such as chest X-ray and physical examination. The Venous Excess Ultrasound Score offers a structured assessment of systemic venous congestion through abdominal venous Doppler patterns. The left ventricular outflow tract velocity-time integral serves as a reproducible surrogate of forward flow and cardiac output, while focused cardiac ultrasound provides rapid structural and functional evaluation of the heart. The reliability and prognostic value of these modalities have been supported by growing evidence across diverse clinical contexts, though standardization of training and acquisition protocols remains crucial for widespread implementation. Integration of POCUS into daily workflows-through structured, serial assessments of pulmonary, venous, and haemodynamic status-holds promise to refine decision-making, individualize treatment strategies, and improve outcomes. This review summarizes current evidence, methodological considerations, and practical implications of POCUS in acute cardiovascular medicine, emphasizing its complementarity to, rather than replacement of, traditional diagnostic tools.

Background: Echocardiographic measurements of the left ventricle (LV) are fundamental in diagnosing and monitoring cardiac disease. Still, current understanding of how heart rate influences these measurements is incomplete. We aimed to explore the relationship between heart rate and LV global longitudinal strain (GLS), ejection fraction (LVEF), end-diastolic (LVEDV), and end-systolic volumes (LVESV), using atrial pacing and a transparent multi-step deep learning (DL)-based method for fully automated measurements.

Methods and results: Fifty participants with permanent pacemakers were enrolled. Heart rate was increased by atrial pacing in increments of 10 beats/min, from 50 to 140 beats/min, with echocardiographic 10-beat cine-loops recorded at each step. A DL-based method was utilized to measure GLS, LVEF, LVEDV, and LVESV at all levels.A total of 10 161 heart cycles were analysed, with 97% feasibility. As heart rate increased, all LV measures displayed significant and near-linear reductions. From 60 to 140 beats/min, GLS decreased by 32% (95% CI: 19-44%), LVEF by 33% (95% CI: 19-47%), LVEDV by 31% (95% CI: 19-43%), and LVESV by 10% (95% CI: -5% to 24%). Processing time per cardiac cycle was 1.3 (0.4) s, corresponding to 3.7 h for the entire dataset.

Conclusion: Heart rate significantly influences echocardiographic measures of LV function and volume, emphasizing the necessity of incorporating heart rate into clinical interpretation and reporting of echocardiographic measurements. This study further demonstrates the potential of DL to advance cardiovascular research by enabling rapid, accurate, and reproducible analyses, previously unachievable due to the inherent constraints of manual measurements.

Background: Reference ranges for myocardial work indices are limited by the scarcity of data from the clinically relevant group of elderly individuals. Myocardial work indices constitute load-adjusted left ventricular function, and main components include global work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE).

Aims: To establish reference values for myocardial work indices and pressure-strain loop shape from guideline-directed recordings in a healthy population spanning a broad age range.

Methods and results: We assessed myocardial work in healthy participants from the HUNT4Echo study. Global longitudinal strain was obtained by two expert cardiologists using two-dimensional speckle tracking, and systolic blood pressure from brachial measurements. Timing of valve events was performed by a single observer supervised by the expert cardiologists. Among 1239 participants (mean age 57, 55% female), reference ranges for myocardial work indices were as follows: GWI 1367-2583 mmHg%, GCW 1664-2972 mmHg%, GWW 38-328 mmHg%, and GWE 88-98%. Age was associated with lower GWI and GWE, and higher GCW and GWW (all P < 0.05). Sex influenced myocardial work indices, with somewhat higher GWI and GCW in females (P ≤ 0.001). The shape of the pressure-strain loops was narrower in older groups, while GWI (the area encompassed by the loop) remained constant across age groups.

Conclusion: Myocardial work indices were influenced by age and sex, but effects were minor and have limited clinical relevance. Despite preserved GWI by higher age, the pressure-strain loop shape changes significantly - underscoring the importance of integrating strain and afterload when assessing left ventricular function.

Trial registration number: Not applicable.

Introduction: Grading of aortic stenosis (AS) is paramount to determine the ideal timing for aortic valve replacement. However, echocardiographic assessment of AS is challenging and subject to inaccuracy. Increased turbulent kinetic energy (TKE) in the aorta, created by a restricted opening stenotic aortic valve, could serve as a new marker for assessing AS severity. However, in this contest, TKE evaluated with ultrasound colour Doppler have not yet been clinically validated.

Methods and results: Porcine aortic valves were tested ex-vivo in a left heart mock loop under various flowrates (1, 2.5, and 4 L/min) and three stiffness grades (SGa, SGb, SGc as native, stiffer, and stiffest stiffness grade, respectively). Reference TKE values were obtained using backlight particle tracking velocimetry. In parallel, TKE was estimated from ultrasound colour Doppler measurements by computing the local spatial fluctuations of blood flow velocities. Transvalvular pressure gradients were evaluated both with continuous wave Doppler and pressure sensors (PGaolv). At 4 L/min, pressure gradients with continuous wave Doppler for SGc reached severe AS levels (41 mmHg ± 14). Both TKE measurement methods, adjusted for flow rates, increased significantly across all stiffness grades and distinguished between severe (SGc) and non-severe (SGa and SGb) AS.

Conclusion: In this ex-vivo AS model, both TKE measurement methods successfully differentiated severe from non-severe AS. These findings underscore the potential importance of ultrasound colour Doppler echocardiography in estimating energy loss through turbulence, paving the way for the development of a new diagnostic tool for grading AS severity.