European heart journal. Imaging methods and practice最新文献

Transthoracic echocardiography (TTE) is the most commonly used imaging modality to diagnose left ventricular thrombus (LVT), however, cardiac magnetic resonance (CMR) remains the gold standard investigation. A comparison of the diagnostic performance between two modalities is needed to inform guidelines on a diagnostic approach towards LVT. We performed a systematic review and meta-analysis to investigate the diagnostic performance of three methods of TTE (non-contrast, contrast, and apical wall motion scoring) for the detection of LVT compared to CMR as a reference test. Studies comprising 2113 patients investigated for LVT using both TTE and CMR were included in the meta-analysis. For non-contrast TTE, pooled sensitivity and specificity were 47% [95% confidence interval (CI): 32-62%], and 98% (95% CI: 96-99%), respectively. In contrast, TTE pooled sensitivity and specificity values were 58% (95% CI: 46-69%), and 98% (95% CI: 96-99%), respectively. Apical wall motion scoring on non-contrast TTE yielded a sensitivity of 100% [95% CI: 93-100%] and a specificity of 54% (95% CI: 42-65%). The area under the curve (AUC) values from our summary receiver operating characteristic curve (SROC) for non-contrast and contrast TTE were 0.87 and 0.86 respectively, with apical wall motion studies having the highest AUC of 0.93. Despite high specificity, routine contrast and non-contrast TTE are likely to miss a significant number of LVT, making it a suboptimal screening tool. The addition of apical wall motion scoring provides a promising method to reliably identify patients requiring further investigations for LVT, whilst excluding others from unnecessary testing.

Aims: Impaired standardization of echocardiograms may increase inter-operator variability. This study aimed to determine whether the real-time guidance of experienced sonographers by deep learning (DL) could improve the standardization of apical recordings.

Methods and results: Patients (n = 88) in sinus rhythm referred for echocardiography were included. All participants underwent three examinations, whereof two were performed by sonographers and the third by cardiologists. In the first study period (Period 1), the sonographers were instructed to provide echocardiograms for the analyses of the left ventricular function. Subsequently, after brief training, the DL guidance was used in Period 2 by the sonographer performing the second examination. View standardization was quantified retrospectively by a human expert as the primary endpoint and the DL algorithm as the secondary endpoint. All recordings were scored in rotation and tilt both separately and combined and were categorized as standardized or non-standardized. Sonographers using DL guidance had more standardized acquisitions for the combination of rotation and tilt than sonographers without guidance in both periods (all P ≤ 0.05) when evaluated by the human expert and DL [except for the apical two-chamber (A2C) view by DL evaluation]. When rotation and tilt were analysed individually, A2C and apical long-axis rotation and A2C tilt were significantly improved, and the others were numerically improved when evaluated by the echocardiography expert. Furthermore, all, except for A2C rotation, were significantly improved when evaluated by DL (P < 0.01).

Conclusion: Real-time guidance by DL improved the standardization of echocardiographic acquisitions by experienced sonographers. Future studies should evaluate the impact with respect to variability of measurements and when used by less-experienced operators.

Clinicaltrialsgov identifier: NCT04580095.

Aims: Left ventricular (LV) pressure-volume (PV) loops provide gold-standard physiological information but require invasive measurements of ventricular intracavity pressure, limiting clinical and research applications. A non-invasive method for the computation of PV loops from magnetic resonance imaging and brachial cuff blood pressure has recently been proposed. Here we evaluated the fidelity of the non-invasive PV algorithm against invasive LV pressures in humans.

Methods and results: Four heart failure patients with EF < 35% and LV dyssynchrony underwent cardiovascular magnetic resonance (CMR) imaging and subsequent LV catheterization with sequential administration of two different intravenous metabolic substrate infusions (insulin/dextrose and lipid emulsion), producing eight datasets at different haemodynamic states. Pressure-volume loops were computed from CMR volumes combined with (i) a time-varying elastance function scaled to brachial blood pressure and temporally stretched to match volume data, or (ii) invasive pressures averaged from 19 to 30 sampled beats. Method comparison was conducted using linear regression and Bland-Altman analysis. Non-invasively derived PV loop parameters demonstrated high correlation and low bias when compared to invasive data for stroke work (R² = 0.96, P < 0.0001, bias 4.6%), potential energy (R² = 0.83, P = 0.001, bias 1.5%), end-systolic pressure-volume relationship (R² = 0.89, P = 0.0004, bias 5.8%), ventricular efficiency (R² = 0.98, P < 0.0001, bias 0.8%), arterial elastance (R² = 0.88, P = 0.0006, bias -8.0%), mean external power (R² = 0.92, P = 0.0002, bias 4.4%), and energy per ejected volume (R² = 0.89, P = 0.0001, bias 3.7%). Variations in estimated end-diastolic pressure did not significantly affect results (P > 0.05 for all). Intraobserver analysis after one year demonstrated 0.9-3.4% bias for LV volumetry and 0.2-5.4% for PV loop-derived parameters.

Conclusion: Pressure-volume loops can be precisely and accurately computed from CMR imaging and brachial cuff blood pressure in humans.

Aims: Accurate staging of hypertension-related cardiac changes, before the development of significant left ventricular hypertrophy, could help guide early prevention advice. We evaluated whether a novel semi-supervised machine learning approach could generate a clinically meaningful summary score of cardiac remodelling in hypertension.

Methods and results: A contrastive trajectories inference approach was applied to data collected from three UK studies of young adults. Low-dimensional variance was identified in 66 echocardiography variables from participants with hypertension (systolic ≥160 mmHg) relative to a normotensive group (systolic < 120 mmHg) using a contrasted principal component analysis. A minimum spanning tree was constructed to derive a normalized score for each individual reflecting extent of cardiac remodelling between zero (health) and one (disease). Model stability and clinical interpretability were evaluated as well as modifiability in response to a 16-week exercise intervention. A total of 411 young adults (29 ± 6 years) were included in the analysis, and, after contrastive dimensionality reduction, 21 variables characterized >80% of data variance. Repeated scores for an individual in cross-validation were stable (root mean squared deviation = 0.1 ± 0.002) with good differentiation of normotensive and hypertensive individuals (area under the receiver operating characteristics 0.98). The derived score followed expected hypertension-related patterns in individual cardiac parameters at baseline and reduced after exercise, proportional to intervention compliance (P = 0.04) and improvement in ventilatory threshold (P = 0.01).

Conclusion: A quantitative score that summarizes hypertension-related cardiac remodelling in young adults can be generated from a computational model. This score might allow more personalized early prevention advice, but further evaluation of clinical applicability is required.