Advancing Wearable Biosensors for Congenital Heart Disease: Patient and Clinician Perspectives: A Science Advisory From the American Heart Association.

Wearable biosensors (wearables) enable continual, noninvasive physiologic and behavioral monitoring at home for those with pediatric or congenital heart disease. Wearables allow patients to access their personal data and monitor their health. Despite substantial technologic advances in recent years, issues with hardware design, data analysis, and integration into the clinical workflow prevent wearables from reaching their potential in high-risk congenital heart disease populations. This science advisory reviews the use of wearables in patients with congenital heart disease, how to improve these technologies for clinicians and patients, and ethical and regulatory considerations. Challenges related to the use of wearables are common to every clinical setting, but specific topics for consideration in congenital heart disease are highlighted.

Artificial Intelligence to derive aligned strain in cine CMR to detect patients with myocardial fibrosis: an open and scrutinizable approach.

Cine Cardiac Magnetic Resonance (CMR) is the gold standard for cardiac function evaluation, incorporating ejection fraction (EF) and strain as vital indicators of abnormal deformation. Rare pathologies like Duchenne muscular dystrophies (DMD) are monitored with repeated late gadolinium-enhanced (LGE) CMR for identification of myocardial fibrosis. However, it is judicious to reduce repeated gadolinium exposure and rather employ strain analysis from cine CMR. This solution is limited so far since full strain curves are not comparable between individual cardiac cycles and current practice mainly neglects diastolic deformation patterns. Our novel Deep Learning-based approach derives strain values aligned by key frames throughout the cardiac cycle. In a reproducibility scenario (57+82 patients), our results reveal five times more significant differences (22 vs. 4) between patients with scar and without, enhancing scar detection by +30%, improving detection of patients with preserved EF by +61%, with an overall sensitivity/specificity of 82/81%.

Wearable Biosensors in Congenital Heart Disease: Needs to Advance the Field.

Traditional measures of clinical status and physiology have generally been based in health care settings, episodic, short in duration, and performed at rest. Wearable biosensors provide an opportunity to obtain continuous non-invasive physiologic data from patients with congenital heart disease (CHD) in the real-world setting, over longer durations, and across varying levels of activity. However, there are significant technical limitations to the use of wearable biosensors in CHD. Here, we review current applications of wearable biosensors in CHD; how clinical and research uses of wearable biosensors must consider various CHD physiologies; the technical challenges in developing wearable biosensors for CHD; and special considerations for digital biomarkers in CHD.

Wearable Seismocardiography-Based Assessment of Stroke Volume in Congenital Heart Disease.

Background Patients with congenital heart disease (CHD) are at risk for the development of low cardiac output and other physiologic derangements, which could be detected early through continuous stroke volume (SV) measurement. Unfortunately, existing SV measurement methods are limited in the clinic because of their invasiveness (eg, thermodilution), location (eg, cardiac magnetic resonance imaging), or unreliability (eg, bioimpedance). Multimodal wearable sensing, leveraging the seismocardiogram, a sternal vibration signal associated with cardiomechanical activity, offers a means to monitoring SV conveniently, affordably, and continuously. However, it has not been evaluated in a population with significant anatomical and physiological differences (ie, children with CHD) or compared against a true gold standard (ie, cardiac magnetic resonance). Here, we present the feasibility of wearable estimation of SV in a diverse CHD population (N=45 patients). Methods and Results We used our chest-worn wearable biosensor to measure baseline ECG and seismocardiogram signals from patients with CHD before and after their routine cardiovascular magnetic resonance imaging, and derived features from the measured signals, predominantly systolic time intervals, to estimate SV using ridge regression. Wearable signal features achieved acceptable SV estimation (28% error with respect to cardiovascular magnetic resonance imaging) in a held-out test set, per cardiac output measurement guidelines, with a root-mean-square error of 11.48 mL and R2 of 0.76. Additionally, we observed that using a combination of electrical and cardiomechanical features surpassed the performance of either modality alone. Conclusions A convenient wearable biosensor that estimates SV enables remote monitoring of cardiac function and may potentially help identify decompensation in patients with CHD.

Le Cœur en Sabot: shape associations with adverse events in repaired tetralogy of Fallot.

BACKGROUND: Maladaptive remodelling mechanisms occur in patients with repaired tetralogy of Fallot (rToF) resulting in a cycle of metabolic and structural changes. Biventricular shape analysis may indicate mechanisms associated with adverse events independent of pulmonary regurgitant volume index (PRVI). We aimed to determine novel remodelling patterns associated with adverse events in patients with rToF using shape and function analysis. METHODS: Biventricular shape and function were studied in 192 patients with rToF (median time from TOF repair to baseline evaluation 13.5 years). Linear discriminant analysis (LDA) and principal component analysis (PCA) were used to identify shape differences between patients with and without adverse events. Adverse events included death, arrhythmias, and cardiac arrest with median follow-up of 10 years. RESULTS: LDA and PCA showed that shape characteristics pertaining to adverse events included a more circular left ventricle (LV) (decreased eccentricity), dilated (increased sphericity) LV base, increased right ventricular (RV) apical sphericity, and decreased RV basal sphericity. Multivariate LDA showed that the optimal discriminative model included only RV apical ejection fraction and one PCA mode associated with a more circular and dilated LV base (AUC = 0.77). PRVI did not add value, and shape changes associated with increased PRVI were not predictive of adverse outcomes. CONCLUSION: Pathological remodelling patterns in patients with rToF are significantly associated with adverse events, independent of PRVI. Mechanisms related to incident events include LV basal dilation with a reduced RV apical ejection fraction.

Transcatheter Device Therapy and the Integration of Advanced Imaging in Congenital Heart Disease.

Transcatheter device intervention is now offered as first line therapy for many congenital heart defects (CHD) which were traditionally treated with cardiac surgery. While off-label use of devices is common and appropriate, a growing number of devices are now specifically designed and approved for use in CHD. Advanced imaging is now an integral part of interventional procedures including pre-procedure planning, intra-procedural guidance, and post-procedure monitoring. There is robust societal and industrial support for research and development of CHD-specific devices, and the regulatory framework at the national and international level is patient friendly. It is against this backdrop that we review transcatheter implantable devices for CHD, the role and integration of advanced imaging, and explore the current regulatory framework for device approval.

Velocity encoded mitral valve inflow cine: A novel and more reproducible method to determine cardiac rest periods during coronary magnetic resonance angiography.

A high temporal resolution, 4-chamber (4CH) cine is the standard method for determining cardiac rest periods during whole heart coronary magnetic resonance angiography (CMRA). We evaluated the image quality and reproducibility between the 4CH cine method and a novel approach using a velocity encoded mitral valve inflow cine (MVI). The goal of this study was to compare the quality of CMRAs utilizing MVI versus 4CH methods. Sharpness and vessel length for the LCA and RCA using each method were determined using Soap Bubble and two blinded observers independently assessed coronary image quality. Offline analysis on a separate, retrospective cohort (n = 25) was used to compare MVI and 4CH reproducibility. In the prospectively evaluated cohort there was no difference in overall vessel sharpness (4CH vs MVI mean ± SD) (31.0 ± 5.5% vs 30.5 ± 5.7%, p = .63), LCA vessel sharpness (30.0 ± 5.4% vs 31.1 ± 8.2%, p = .44), LCA length (4.7 ± 1.4 cm vs 4.6 ± 1.6 cm, p = .66), RCA vessel sharpness (32.1 ± 6.9% vs 31.1 ± 7.7%, p = .55), RCA length (5.51 ± 2.6 cm vs 5.95 ± 2.4 cm, p = .38), or image quality rating (2.66 vs 2.62, p = .80) between methods. In the retrospective cohort, the MVI method had 5.4% lower inter-observer variability (95% CI 3.7,7.2%, p < .0001) and 3.9% lower intra-observer variability (95% CI 2.4,5.4%, p < .0001) than the 4CH method. MVI is a technically feasible and more reproducible method to determine cardiac rest periods compared to 4CH while preserving vessel sharpness, vessel length & image quality.

Advanced imaging and digitization of preserved heart specimens using virtual reality - A primer.

Introduction: Preserved congenital heart specimens are an important component of training professionals working with children and adults with congenital heart disease. They are curated in few institutions worldwide and not freely accessible. This was a proof-of-concept project to explore the use of advanced cardiac imaging modalities (computed tomography [CT] and magnetic resonance imaging [MRI]) and virtual reality (VR) simulation to assess the feasibility and identify the best method of imaging curated cardiac pathology specimens. Methods: Seven specimens in glass jars with formalin, with varied anatomic lesions, from a curated collection were imaged using MRI and high-dose CT to compare the fidelity of models created via each modality. Three-dimensional (3D) models were created and loaded into a VR headset and viewed in virtual space. Two independent physicians performed a "virtual dissection" and scored the resultant models. Results: The highest fidelity and tissue characterization of more delicate structures was achieved with T2 spoiled gradient-echo sequences on MRI (median score of 4 out of 5). CT (median score of 3), while excellent for external anatomy, lost some fidelity with delicate internal anatomy, even at high-radiation doses. No specimens were damaged. Conclusions: We believe that in vitro heart specimens can be easily scanned with high fidelity at a relatively low cost, without causing damage, using high-dose CT and MRI. The ability to "walk through" different chambers of the heart makes the understanding of anatomy easy and intuitive. VR and 3D printing are technologies that could be easily adapted to digitize preserved heart specimens, making it globally accessible for teaching and training purposes.

Myopericarditis after messenger RNA Coronavirus Disease 2019 Vaccination in Adolescents 12 to 18 Years of Age.

OBJECTIVES: To characterize the clinical course and outcomes of children 12-18 years of age who developed probable myopericarditis after vaccination with the Pfizer-BioNTech (BNT162b2) coronavirus disease 2019 (COVID-19) messenger RNA (mRNA) vaccine. STUDY DESIGN: A cross-sectional study of 25 children, aged 12-18 years, diagnosed with probable myopericarditis after COVID-19 mRNA vaccination as per the Centers for Disease Control and Prevention criteria for myopericarditis at 8 US centers between May 10, 2021, and June 20, 2021. We retrospectively collected the following data: demographics, severe acute respiratory syndrome coronavirus 2 virus detection or serologic testing, clinical manifestations, laboratory test results, imaging study results, treatment, and time to resolutions of symptoms. RESULTS: Most (88%) cases followed the second dose of vaccine, and chest pain (100%) was the most common presenting symptom. Patients came to medical attention a median of 2 days (range, <1-20 days) after receipt of Pfizer mRNA COVID-19 vaccination. All adolescents had an elevated plasma troponin concentration. Echocardiographic abnormalities were infrequent, and 92% showed normal cardiac function at presentation. However, cardiac magnetic resonance imaging, obtained in 16 patients (64%), revealed that 15 (94%) had late gadolinium enhancement consistent with myopericarditis. Most were treated with ibuprofen or an equivalent nonsteroidal anti-inflammatory drug for symptomatic relief. One patient was given a corticosteroid orally after the initial administration of ibuprofen or an nonsteroidal anti-inflammatory drug; 2 patients also received intravenous immune globulin. Symptom resolution was observed within 7 days in all patients. CONCLUSIONS: Our data suggest that symptoms owing to myopericarditis after the mRNA COVID-19 vaccination tend to be mild and transient. Approximately two-thirds of patients underwent cardiac magnetic resonance imaging, which revealed evidence of myocardial inflammation despite a lack of echocardiographic abnormalities.

Biomechanical Modeling to Inform Pulmonary Valve Replacement in Tetralogy of Fallot Patients After Complete Repair.

BACKGROUND: A biomechanical model of the heart can be used to incorporate multiple data sources (electrocardiography, imaging, invasive hemodynamics). The purpose of this study was to use this approach in a cohort of patients with tetralogy of Fallot after complete repair (rTOF) to assess comparative influences of residual right ventricular outflow tract obstruction (RVOTO) and pulmonary regurgitation on ventricular health. METHODS: Twenty patients with rTOF who underwent percutaneous pulmonary valve replacement (PVR) and cardiovascular magnetic resonance imaging were included in this retrospective study. Biomechanical models specific to individual patient and physiology (before and after PVR) were created and used to estimate the RV myocardial contractility. The ability of models to capture post-PVR changes of right ventricular (RV) end-diastolic volume (EDV) and effective flow in the pulmonary artery (Qeff) was also compared with expected values. RESULTS: RV contractility before PVR (mean 66 ± 16 kPa, mean ± standard deviation) was increased in patients with rTOF compared with normal RV (38-48 kPa) (P < 0.05). The contractility decreased significantly in all patients after PVR (P < 0.05). Patients with predominantly RVOTO demonstrated greater reduction in contractility (median decrease 35%) after PVR than those with predominant pulmonary regurgitation (median decrease 11%). The model simulated post-PVR decreased EDV for the majority and suggested an increase of Qeff-both in line with published data. CONCLUSIONS: This study used a biomechanical model to synthesize multiple clinical inputs and give an insight into RV health. Individualized modeling allows us to predict the RV response to PVR. Initial data suggest that residual RVOTO imposes greater ventricular work than isolated pulmonary regurgitation.

Lifespan Perspective on Congenital Heart Disease Research: JACC State-of-the-Art Review.

More than 90% of patients with congenital heart disease (CHD) are nowadays surviving to adulthood and adults account for over two-thirds of the contemporary CHD population in Western countries. Although outcomes are improved, surgery does not cure CHD. Decades of longitudinal observational data are currently motivating a paradigm shift toward a lifespan perspective and proactive approach to CHD care. The aim of this review is to operationalize these emerging concepts by presenting new constructs in CHD research. These concepts include long-term trajectories and a life course epidemiology framework. Focusing on a precision health, we propose to integrate our current knowledge on the genome, phenome, and environome across the CHD lifespan. We also summarize the potential of technology, especially machine learning, to facilitate longitudinal research by embracing big data and multicenter lifelong data collection.

Left Ventricular Torsion Obtained Using Equilibrated Warping in Patients with Repaired Tetralogy of Fallot.

Patients after surgical repair of Tetralogy of Fallot (rTOF) may suffer a decrease in left ventricular (LV) function. The aim of our study is to evaluate a novel method of assessing LV torsion in patients with rTOF, as an early indicator of systolic LV dysfunction. Motion tracking based on image registration regularized by the equilibrium gap principle, known as equilibrated warping, was employed to assess LV torsion. Seventy-six cases of rTOF and ten normal controls were included. The group of controls was assessed for reproducibility using both equilibrated warping and standard clinical tissue tracking software (CVI42, version 5.10.1, Calgary, Canada). Patients were dichotomized into two groups: normal vs. loss of torsion. Torsion by equilibrated warping was successfully obtained in 68 of 76 (89%) patients and 9 of 10 (90%) controls. For equilibrated warping, the intra- and interobserver coefficients of variation were 0.095 and 0.117, respectively, compared to 0.260 and 0.831 for tissue tracking by standard clinical software. The intra- and inter-observer intraclass correlation coefficients for equilibrated warping were 0.862 and 0.831, respectively, compared to 0.992 and 0.648 for tissue tracking. Loss of torsion was noted in 32 of the 68 (47%) patients with rTOF. There was no difference in LV or RV volumes or ejection fraction between these groups. The assessment of LV torsion by equilibrated warping is feasible and shows good reliability. Loss of torsion is common in patients with rTOF and its robust assessment might contribute into uncovering heart failure in an earlier stage.

Retraining Convolutional Neural Networks for Specialized Cardiovascular Imaging Tasks: Lessons from Tetralogy of Fallot.

Ventricular contouring of cardiac magnetic resonance imaging is the gold standard for volumetric analysis for repaired tetralogy of Fallot (rTOF), but can be time-consuming and subject to variability. A convolutional neural network (CNN) ventricular contouring algorithm was developed to generate contours for mostly structural normal hearts. We aimed to improve this algorithm for use in rTOF and propose a more comprehensive method of evaluating algorithm performance. We evaluated the performance of a ventricular contouring CNN, that was trained on mostly structurally normal hearts, on rTOF patients. We then created an updated CNN by adding rTOF training cases and evaluated the new algorithm's performance generating contours for both the left and right ventricles (LV and RV) on new testing data. Algorithm performance was evaluated with spatial metrics (Dice Similarity Coefficient (DSC), Hausdorff distance, and average Hausdorff distance) and volumetric comparisons (e.g., differences in RV volumes). The original Mostly Structurally Normal (MSN) algorithm was better at contouring the LV than the RV in patients with rTOF. After retraining the algorithm, the new MSN + rTOF algorithm showed improvements for LV epicardial and RV endocardial contours on testing data to which it was naïve (N = 30; e.g., DSC 0.883 vs. 0.905 for LV epicardium at end diastole, p < 0.0001) and improvements in RV end-diastolic volumetrics (median %error 8.1 vs 11.4, p = 0.0022). Even with a small number of cases, CNN-based contouring for rTOF can be improved. This work should be extended to other forms of congenital heart disease with more extreme structural abnormalities. Aspects of this work have already been implemented in clinical practice, representing rapid clinical translation. The combined use of both spatial and volumetric comparisons yielded insights into algorithm errors.

Unsupervised Domain Adaptation From Axial to Short-Axis Multi-Slice Cardiac MR Images by Incorporating Pretrained Task Networks.

Anisotropic multi-slice Cardiac Magnetic Resonance (CMR) Images are conventionally acquired in patient-specific short-axis (SAX) orientation. In specific cardiovascular diseases that affect right ventricular (RV) morphology, acquisitions in standard axial (AX) orientation are preferred by some investigators, due to potential superiority in RV volume measurement for treatment planning. Unfortunately, due to the rare occurrence of these diseases, data in this domain is scarce. Recent research in deep learning-based methods mainly focused on SAX CMR images and they had proven to be very successful. In this work, we show that there is a considerable domain shift between AX and SAX images, and therefore, direct application of existing models yield sub-optimal results on AX samples. We propose a novel unsupervised domain adaptation approach, which uses task-related probabilities in an attention mechanism. Beyond that, cycle consistency is imposed on the learned patient-individual 3D rigid transformation to improve stability when automatically re-sampling the AX images to SAX orientations. The network was trained on 122 registered 3D AX-SAX CMR volume pairs from a multi-centric patient cohort. A mean 3D Dice of 0.86 ± 0.06 for the left ventricle, 0.65 ± 0.08 for the myocardium, and 0.77 ± 0.10 for the right ventricle could be achieved. This is an improvement of 25% in Dice for RV in comparison to direct application on axial slices. To conclude, our pre-trained task module has neither seen CMR images nor labels from the target domain, but is able to segment them after the domain gap is reduced. Code: https://github.com/Cardio-AI/3d-mri-domain-adaptation.

Fully automated segmentation of the right ventricle in patients with repaired Tetralogy of Fallot using U-Net.

Cardiac magnetic resonance (CMR) imaging is considered the standard imaging modality for volumetric analysis of the right ventricle (RV), an especially important practice in the evaluation of heart structure and function in patients with repaired Tetralogy of Fallot (rTOF). In clinical practice, however, this requires time-consuming manual delineation of the RV endocardium in multiple 2-dimensional (2D) slices at multiple phases of the cardiac cycle. In this work, we employed a U-Net based 2D convolutional neural network (CNN) classifier in the fully automatic segmentation of the RV blood pool. Our dataset was comprised of 5,729 short-axis cine CMR slices taken from 100 individuals with rTOF. Training of our CNN model was performed on images from 50 individuals while validation was performed on images from 10 individuals. Segmentation results were evaluated by Dice similarity coefficient (DSC) and Hausdorff distance (HD). Use of the CNN model on our testing group of 40 individuals yielded a median DSC of 90% and a median 95th percentile HD of 5.1 mm, demonstrating good performance in these metrics when compared to literature results. Our preliminary results suggest that our deep learning-based method can be effective in automating RV segmentation.

3D advanced imaging overlay with rapid registration in CHD to reduce radiation and assist cardiac catheterisation interventions.

Novel commercially available software has enabled registration of both CT and MRI images to rapidly fuse with X-ray fluoroscopic imaging. We describe our initial experience performing cardiac catheterisations with the guidance of 3D imaging overlay using the VesselNavigator system (Philips Healthcare, Best, NL). A total of 33 patients with CHD were included in our study. Demographic, advanced imaging, and catheterisation data were collected between 1 December, 2016 and 31 January, 2019. We report successful use of this technology in both diagnostic and interventional cases such as placing stents and percutaneous valves, performing angioplasties, occlusion of collaterals, and guidance for lymphatic interventions. In addition, radiation exposure was markedly decreased when comparing our 10-15-year-old coarctation of the aorta stent angioplasty cohort to cases without the use of overlay technology and the most recently published national radiation dose benchmarks. No complications were encountered due to the application of overlay technology. 3D CT or MRI overlay for CHD intervention with rapid registration is feasible and aids decisions regarding access and planned angiographic angles. Operators found intraprocedural overlay fusion registration using placed vessel guidewires to be more accurate than attempts using bony structures.