Coronary artery disease (CAD) represents the most common cardiovascular disease, with high morbidity and mortality. Historically patients with chest pain of suspected coronary origin have been assessed with functional tests, capable to detect haemodynamic consequences of coronary obstructions through depiction of electrocardiographic changes, myocardial perfusion defects or regional wall motion abnormalities under stress condition. Stress echocardiography (SE), single-photon emission computed tomography (SPECT), positron emission tomography (PET) and cardiovascular magnetic resonance (CMR) represent the functional techniques currently available, and technical developments contributed to increased diagnostic performance of these techniques. More recently, cardiac computed tomography angiography (cCTA) has been developed as a non-invasive anatomical test for a direct visualisation of coronary vessels and detailed description of atherosclerotic burden. Cardiovascular imaging techniques have dramatically enhanced our knowledge regarding physiological aspects and myocardial implications of CAD. Recently, after the publication of important trials, international guidelines recognised these changes, updating indications and level of recommendations. This review aims to summarise current standards with main novelties and specific limitations, and a diagnostic algorithm for up-to-date clinical management is also proposed.

Cardiovascular imaging is developing at a rapid pace and the newer modalities, in particular three-dimensional echocardiography, allow better analysis of heart structures. Identifying valve lesions and grading their severity represents crucial information and nowadays is strengthened by the introduction of new software, such as transillumination, which provide detailed morphology descriptions. Chambers quantification has never been so rapid and accurate: machine learning algorithms generate automated volume measurements, including left ventricular systolic and diastolic function, which is extremely important for clinical decisions. This review provides an overview of the latest innovations in the echocardiography field, and is helpful by providing a better insight into heart diseases.

We aimed to evaluate the feasibility and accuracy of machine learning-based automated dynamic quantification of left ventricular (LV) and left atrial (LA) volumes in an unselected population. We enrolled 600 unselected patients (12% in atrial fibrillation) clinically referred for transthoracic echocardiography (2DTTE), who also underwent 3D echocardiography (3DE) imaging. LV ejection fraction (EF), LV, and LA volumes were obtained from 2D images; 3D images were analyzed using dynamic heart model (DHM) software (Philips) resulting in LV and LA volume–time curves. A subgroup of 140 patients also underwent cardiac magnetic resonance (CMR) imaging. Average time of analysis, feasibility, and image quality were recorded, and results were compared between 2DTTE, DHM, and CMR. The use of DHM was feasible in 522/600 cases (87%). When feasible, the boundary position was considered accurate in 335/522 patients (64%), while major (n = 38) or minor (n = 149) border corrections were needed. The overall time required for DHM datasets was approximately 40 seconds. As expected, DHM LV volumes were larger than 2D ones (end-diastolic volume: 173 ± 64 vs. 142 ± 58 mL, respectively), while no differences were found for LV EF and LA volumes (EF: 55% ± 12 vs. 56% ± 14; LA volume 89 ± 36 vs. 89 ± 38 mL, respectively). The comparison between DHM and CMR values showed a high correlation for LV volumes (r = 0.70 and r = 0.82, p < 0.001 for end-diastolic and end-systolic volume, respectively) and an excellent correlation for EF (r = 0.82, p < 0.001) and LA volumes. The DHM software is feasible, accurate, and quick in a large series of unselected patients, including those with suboptimal 2D images or in atrial fibrillation.

MitraClip (MC) is the most common percutaneous treatment for severe mitral regurgitation (MR). An accurate two-dimensional and three-dimensional echocardiographic (3DTEE) imaging is mandatory for the optimal procedural result. Recently transillumination 3DTEE rendering (3DTr) has been introduced integrating a virtual light source into the dataset and with the addition of glass effect (3DGl) allows to adjust tissue transparency improving depth perception and anatomical structure delineation in comparison with the standard 3DTEE (3DSt). The aim of this retrospective study in 30 patients undergoing MC, was to compare 3DSt, 3DTr, and 3DGl in mitral valve (MV) evaluation and procedural result assessment. 3DTEE acquisitions obtained before and after MC were processed with 3DSt, 3DTr, and 3DGl rendering. Each reconstruction was scored for quality and for ability to recognize MV anatomy, MR origin, clip position, dimension and grasping. Imaging quality was judged good or optimal in 52%, 76%, and 96% in 3DSt, 3DTr, and 3DGl reconstructions respectively. In 26/30 patients a diagnostic incremental value was found with 3DTr vs. 3DSt and in 15/26 with 3DGl vs. 3DTr and 3DSt. Only 3DGl with perpendicular cropping of the clip allowed to visualize and measure the grasped portion of each mitral leaflets. 3DTEE imaging during MC may be improved by 3DTr and 3DGl providing a better evaluation of MV, of leaflet grasping and of residual MR jets after MC.

Background: Percutaneous left atrial appendage closure (LAAC) requires accurate pre- and intraprocedural measurements, and multimodality imaging is an essential tool for guiding the procedure. Two-dimensional (2D TOE) and three-dimensional (3D TOE) transoesophageal echocardiography, cardiac computed tomography (CCT), and conventional cardiac angiography (CCA) are commonly used to evaluate left atrial appendage (LAA) size. However, standardized approaches in measurement methods by different imaging modalities are lacking. The aims of the study were to evaluate the LAA dimension and morphology in patients undergoing LAAC and to compare data obtained by different imaging modalities: 2D and 3D TOE, CCT, and CCA. Methods: A total of 200 patients (mean age 70 ± 8 years, 128 males) were examined by different imaging techniques (161 2D TOE, 103 3D TOE, 98 CCT, and 200 CCA). Patients underwent preoperative CCT and intraoperative 2D and 3D TOE and CCA. Results: A significant correlation was found among all measurements obtained by different modalities. In particular, 3D TOE and CCT measurements were highly correlated with an excellent agreement for the landing zone (LZ) dimensions (LZ diameter: r = 0.87; LAA depth: r = 0.91, p < 0.001). Conclusions: Head-to-head comparison among imaging techniques (2D and 3D TOE, CCT, and CCA) showed a good correlation among LZ diameter measurements obtained by different imaging modalities, which is a parameter of paramount importance for the choice of the LAAC device size. LZ diameters and area by 3D TOE had the best correlation with CCT.

PurposeWe aimed to evaluate the feasibility and accuracy of machine learning based automated dynamic quantification of left ventricular (LV) and left atrial (LA) volumes in an unselected population.MethodsWe enrolled 600 unselected patients (12% in atrial fibrillation) clinically referred for transthoracic echocardiography (2DTTE), who also underwent 3D echocardiography (3DE) imaging. LV ejection fraction (EF), LV and LA volumes were obtained from 2D images; 3D images were analysed using Dynamic Heart Model (DHM) software resulting in LV and LA volume-time curves. A subgroup of 140 patients underwent also cardiac magnetic resonance (CMR) imaging. Average time of analysis, feasibility, and image quality were recorded and results were compared between 2DTTE, DHM and CMR.ResultsThe use of DHM was feasible in 529/600 cases (88%). When feasible, the boundary position was considered accurate in 335/522 patients (64%), while major (n=43) or minor (n=156) borders corrections were needed. The overall time required for DHM datasets was approximately 40 seconds, resulting in physiologically appearing LV and LA volume–time curves in all cases. As expected, DHM LV volumes were larger than 2D ones (end-diastolic volume: 173±64 vs 142±58 mL, respectively), while no differences were found for LV EF and LA volumes (EF: 55%±12 vs 56%±14; LA volume 89±36 vs 89±38 mL, respectively). The comparison between DHM and CMR values showed a high correlation for LV volumes (r=0.70 and r=0.82, p<0.001 for end-diastolic and end-systolic volume, respectively) and an excellent correlation for EF (r= 0.82, p<0.001) and LA volumes.ConclusionsThe DHM software is feasible, accurate and quick in a large series of unselected patients, including those with suboptimal 2D images or in atrial fibrillation.