Three-Dimensional Echocardiography Derived Printing: A Review of Workflow, Current, and Future Applications.

PURPOSE OF REVIEW: While most of the work pertaining to 3D printing in cardiology has been based on 3D CT and MRI datasets, due to the recent advents in 3D printing and 3D echocardiography, 3D printing from echocardiography has now become feasible. In this review, we discuss the workflow, applications, limitations, and potential future directions of 3D echocardiography-based 3D printing. RECENT FINDINGS: 3D printing using 3D echocardiographic datasets has been successfully deployed in the field of cardiovascular medicine in the twenty-first century. It was shown to provide a significant additive value particularly with regards to visualization of valves and subvalvar apparatus. Given its limitations of limited field of view and somewhat lower spatial resolution, this approach is likely ideally suited for a combined multi-modality-based printing. Patient-specific, 3D echocardiography-derived 3D-printed models are now quite feasible. This can be used for surgical/procedural planning and training for optimal outcomes.

Pressure-Strain Loops, a Novel Non-invasive Approach for Assessment of Children with Cardiomyopathy.

Non-invasive myocardial work (MW) by left ventricular (LV) pressure-strain loops (PSL) is a novel method for assessing myocardial function while adjusting for afterload, yet pediatric data remain lacking. The aims of this study were to investigate the different patterns of LV PSL and non-invasive MW in pediatric patients with hypertrophic (HCM) and dilated cardiomyopathy (DCM) and their association with exercise tolerance. We included 110 pediatric subjects (mean age, 13 ± 4 years, 35 DCM, 40 HCM, and 35 healthy controls). Standard and speckle-tracking echocardiography were performed. LV PSLs were generated, and global work index (GWI), MW efficiency (GWE), constructive work (GCW), and wasted work (GWW) were compared between groups. Regression analysis was used to assess the influence of ventricular function, dimensions, wall thickness, and wall stress on MW and to predict the association between MW and VO2 max as a surrogate of exercise capacity. Patients with DCM had significantly lower GWI compared to controls (GWI 479.6 ± 263.0 vs 1610.1 ± 211.0, P < 0.005). GWE was significantly reduced in DCM (79.3 ± 7.9 vs 95.2 ± 1.3, P < 0.005) due to significantly reduced GCW and increased GWW. HCM patients had significant reduction in GWI and GWE from normal (1237.7 ± 449.1 vs 1610.1 ± 211.0, P = 0.001 and 89.6 ± 4.9 vs 95.2 ± 1.3, P < 0.005, respectively), although less severe than with DCM. In a multivariate regression analysis, GWE had the highest association with VO2 max in both cohorts (DCM: ß = 0.68, P = 0.001, HCM: ß = 0.71, P = 0.007). Non-invasively assessed myocardial work and LV PSLs provide novel insights into the mechanisms of dysfunction in pediatric patients with cardiomyopathy with good prediction of clinical status and thus hold promise to further explore myocardial mechanistic with clinical relevance in different disease entities.

Ability of Video Telemetry to Predict Unplanned Hospital Admissions for Single Ventricle Infants.

Background Our Cardiac High Acuity Monitoring Program (CHAMP) uses home video telemetry (HVT) as an adjunct to monitor infants with single ventricle during the interstage period. This study describes the development of an objective early warning score using HVT, for identification of infants with single ventricle at risk for clinical deterioration and unplanned hospital admissions (UHA). Methods and Results Six candidate scoring parameters were selected to develop a pragmatic score for routine evaluation of HVT during the interstage period. We evaluated the individual and combined ability of these parameters to predict UHA. All infants with single ventricle monitored at home by CHAMP between March 2014 and March 2018 were included. Videos obtained within 48 hours before UHA were compared with videos obtained at baseline. We used binary logistic regression models and receiver operating characteristic curves to evaluate the parameters' performance in discriminating the outcome of interest. Thirty-nine subjects with 64 UHA were included. We compared 64 pre-admission videos to 64 paired baseline videos. Scoring was feasible for a mean of 91.6% (83.6%-98%) of all observations. Three different HVT score models were proposed, and a final model composed of respiratory rate, respiratory effort, color, and behavior exhibited an excellent discriminatory capability with an area under the receiver operating characteristic curve of 93% (89%-98%). HVT score of 5 was associated with specificity of 93.8% and sensitivity of 88.7% in predicting UHA. Conclusions We developed a feasible and reproducible HVT score that can serve as a tool to predict UHA in infants with single ventricle. Future directions involve prospective, multicenter validation of this tool.