Clinical Applications of Cardiovascular Magnetic Resonance in Congenital Heart Disease

Optimizing neonatal cardiac imaging (magnetic resonance/computed tomography)

Magnetic resonance imaging (MRI) and CT perform an important role in the evaluation of neonates with congenital heart disease (CHD) when echocardiography is not sufficient for surgical planning or postoperative follow-up. Cardiac MRI and cardiac CT have complementary applications in the evaluation of cardiovascular disease in neonates. This review focuses on the indications and technical aspects of these modalities and special considerations for imaging neonates with CHD.

Factors Influencing Temporal Trends in Pediatric Inpatient Imaging Utilization

BACKGROUND

Concern exists over exponential growth in cardiac imaging in adults, but there is paucity of such data for cardiac imaging trends in pediatric patients. The aims of this study were to determine temporal trends in the use of noninvasive cardiac imaging and compare these with trends in the use of noncardiac imaging and to identify factors influencing those trends using the Pediatric Health Information Service database.

METHODS

Pediatric inpatient encounter data from January 2004 to December 2017 at 35 pediatric hospitals were extracted from the Pediatric Health Information Service database. Temporal imaging utilization trends in cardiac and noncardiac ultrasound or echocardiography, magnetic resonance imaging (MRI), and computed tomography (CT) were assessed using linear mixed-effects models. Models were adjusted for case-mix index, complex chronic conditions, patient age, length of stay, payer source, and cardiac surgical volume.

RESULTS

A total of 5,869,335 encounters over 14 years were analyzed (median encounters per center per year, 11,411; median patient age, 4 years; median length of stay, 3 days). From 2004 to 2017, the rates of pediatric inpatient cardiac and noncardiac ultrasound and MRI increased, whereas the rate of noncardiac CT decreased. Cardiac CT use increased beginning in 2014 (+0.264 cardiac CT encounters per 1,000 encounters per year), surpassing the rate of rise of cardiac MRI. Case-mix index, cardiac surgical volume, and payer source affected the largest number of imaging trends.

CONCLUSIONS

Among pediatric inpatients, utilization of cardiac and noncardiac ultrasound and MRI has steadily increased. Noncardiac CT use declined and cardiac CT use increased after 2014. Factors influencing imaging trends include case-mix index, cardiac surgical volume, and payer source. This study lays a foundation for investigations of imaging-related resource utilization and outcomes among pediatric inpatients.

Predicting deterioration of ventricular function in patients with repaired tetralogy of Fallot using machine learning

Aims

Previous studies using regression analyses have failed to identify which patients with repaired tetralogy of Fallot (rTOF) are at risk for deterioration in ventricular size and function despite using common clinical and cardiac function parameters as well as cardiac mechanics (strain and dyssynchrony). This study used a machine learning pipeline to comprehensively investigate the predictive value of the baseline variables derived from cardiac magnetic resonance (CMR) imaging and provide models for identifying patients at risk for deterioration.

Methods and results

Longitudinal deterioration for 153 patients with rTOF was categorized as 'none', 'minor', or 'major' based on changes in ventricular size and ejection fraction between two CMR scans at least 6 months apart (median 2.7 years). Baseline variables were measured at the time of the first CMR. An exhaustive variable search with a support vector machine classifier and five-fold cross-validation was used to predict deterioration and identify the most useful variables. For predicting any deterioration (minor or major) vs. no deterioration, the mean area under the curve (AUC) was 0.82 ± 0.06. For predicting major deterioration vs. minor or no deterioration, the AUC was 0.77 ± 0.07. Baseline left ventricular (LV) ejection fraction, LV circumferential strain, and pulmonary regurgitation were most useful for achieving accurate predictions.

Conclusion

For the prediction of deterioration in patients with rTOF, a machine learning pipeline uncovered the utility of baseline variables that was previously lost to regression analyses. The predictive models may be useful for planning early interventions in patients with high risk.

Computed tomography and magnetic resonance imaging in neonates with congenital cardiovascular disease

Most cardiac diseases in the newborn are caused by structural abnormalities developed in utero. With few exceptions, palliative and definitive treatments require cardiac surgery. The diagnosis and management decisions regarding uncomplicated lesions, such as atrial septal defect, ventricular septal defect, patent ductus arteriosus, and tetralogy of Fallot, can be accomplished by echocardiography alone. Abnormalities beyond the sonographic window, complex 3-dimensional lesions, and detailed functional information require additional imaging. In the past, this was fulfilled by catheter angiography, but today much of the information can be obtained from noninvasive computed tomography angiography and magnetic resonance imaging. This article discusses the design and application of these imaging techniques to the newborn, with emphasis on safety, efficacy, and image quality. Understanding the capabilities and limitations of these techniques is crucial for making rational choices among imaging options based on sound risk and benefit considerations. Important examples of congenital heart lesions have been illustrated with 3-dimensional reconstruction from computed tomography and magnetic resonance images.