The Role of Cardiovascular Magnetic Resonance in Pediatric Congenital Heart Disease

Cardiovascular magnetic resonance (CMR) has expanded its role in the diagnosis and management of congenital heart disease (CHD) and acquired heart disease in pediatric patients. Ongoing technological advancements in both data acquisition and data presentation have enabled CMR to be integrated into clinical practice with increasing understanding of the advantages and limitations of the technique by pediatric cardiologists and congenital heart surgeons. Importantly, the combination of exquisite 3D anatomy with physiological data enables CMR to provide a unique perspective for the management of many patients with CHD. Imaging small children with CHD is challenging, and in this article we will review the technical adjustments, imaging protocols and application of CMR in the pediatric population

Investigating Cardiac Motion Patters Using Synthetic High-Resolution 3D Cardiovascular Magnetic Resonance Images and Statistical Shape Analysis

Diagnosis of ventricular dysfunction in congenital heart disease is more and more based on medical imaging, which allows investigation of abnormal cardiac morphology and correlated abnormal function. Although analysis of 2D images represents the clinical standard, novel tools performing automatic processing of 3D images are becoming available, providing more detailed and comprehensive information than simple 2D morphometry. Among these, statistical shape analysis (SSA) allows a consistent and quantitative description of a population of complex shapes, as a way to detect novel biomarkers, ultimately improving diagnosis and pathology understanding. The aim of this study is to describe the implementation of a SSA method for the investigation of 3D left ventricular shape and motion patterns and to test it on a small sample of 4 congenital repaired aortic stenosis patients and 4 age-matched healthy volunteers to demonstrate its potential. The advantage of this method is the capability of analyzing subject-specific motion patterns separately from the individual morphology, visually and quantitatively, as a way to identify functional abnormalities related to both dynamics and shape. Specifically, we combined 3D, high-resolution whole heart data with 2D, temporal information provided by cine cardiovascular magnetic resonance images, and we used an SSA approach to analyze 3D motion per se. Preliminary results of this pilot study showed that using this method, some differences in end-diastolic and end-systolic ventricular shapes could be captured, but it was not possible to clearly separate the two cohorts based on shape information alone. However, further analyses on ventricular motion allowed to qualitatively identify differences between the two populations. Moreover, by describing shape and motion with a small number of principal components, this method offers a fully automated process to obtain visually intuitive and numerical information on cardiac shape and motion, which could be, once validated on a larger sample size, easily integrated into the clinical workflow. To conclude, in this preliminary work, we have implemented state-of-the-art automatic segmentation and SSA methods, and we have shown how they could improve our understanding of ventricular kinetics by visually and potentially quantitatively highlighting aspects that are usually not picked up by traditional approaches

Utility of adenosine stress perfusion CMR to assess paediatric coronary artery disease

AIMS: Cardiovascular magnetic resonance (CMR), using adenosine stress perfusion and late-gadolinium enhancement (LGE), is becoming the 'gold standard' non-invasive imaging modality in the assessment of adults with coronary artery disease (CAD). However, despite its proved feasibility in paediatric patients, clinical utility has not been demonstrated. Therefore, this study aims to establish the role of adenosine stress perfusion CMR as a screening test in paediatric patients with acquired or congenital CAD. METHODS AND RESULTS: A total of 58 paediatric patients underwent 61 consecutive clinically indicated coronary artery assessments for diagnostic and clinical decision-making purposes. The diagnosis was based on X-ray or computed tomography coronary angiography for anatomy, adenosine stress CMR imaging for myocardial perfusion and LGE for tissue characterization. Two studies were aborted because of unwanted side effects of adenosine stress, thus 59 studies were completed in 56 patients [median age 14.1 years (interquartile range 10.9-16.2)]. When compared with coronary anatomical imaging, adenosine stress perfusion CMR performed as follows: sensitivity 100% (95% confidence interval, CI: 71.6-100%), specificity 98% (95% CI: 86.7-99.9%), positive predictive value (PPV) 92.9% (95% CI: 64.2-99.6%), and negative predictive value 100% (95% CI: 89.9-100%). CONCLUSION: In paediatric CAD, adenosine stress perfusion CMR imaging is adequate as an initial, non-invasive screening test for the identification of significant coronary artery lesions, with anatomical imaging used to confirm the extent of the culprit lesion

Detecting Clinically Meaningful Shape Clusters in Medical Image Data: Metrics Analysis for Hierarchical Clustering applied to Healthy and Pathological Aortic Arches

OBJECTIVE: Today's growing medical image databases call for novel processing tools to structure the bulk of data and extract clinically relevant information. Unsupervised hierarchical clustering may reveal clusters within anatomical shape data of patient populations as required for modern Precision Medicine strategies. Few studies have applied hierarchical clustering techniques to three-dimensional patient shape data and results depend heavily on the chosen clustering distance metrics and linkage functions. In this study, we sought to assess clustering classification performance of various distance/linkage combinations and of different types of input data to obtain clinically meaningful shape clusters. METHODS: We present a processing pipeline combining automatic segmentation, statistical shape modelling and agglomerative hierarchical clustering to automatically subdivide a set of 60 aortic arch anatomical models into healthy controls, two groups affected by congenital heart disease, and their respective subgroups as defined by clinical diagnosis. Results were compared with traditional morphometrics and principal component analysis of shape features. RESULTS: Our pipeline achieved automatic division of input shape data according to primary clinical diagnosis with high F-score (0.902/pm0.042) and Matthews Correlation Coefficient (0.851/pm0.064) using the Correlation/Weighted distance/linkage combination. Meaningful subgroups within the three patient groups were obtained and benchmark scores for automatic segmentation and classification performance are reported. CONCLUSION: Clustering results vary depending on the distance/linkage combination used to divide the data. Yet, clinically relevant shape clusters and subgroups could be found with high specificity and low misclassification rates. SIGNIFICANCE: Detecting disease-specific clusters within medical image data could improve image-based risk assessment, treatment planning and medical device development in complex disease

The growth and evolution of cardiovascular magnetic resonance: a 20-year history of the Society for Cardiovascular Magnetic Resonance (SCMR) annual scientific sessions

Background and purpose: The purpose of this work is to summarize cardiovascular magnetic resonance (CMR) research trends and highlights presented at the annual Society for Cardiovascular Magnetic Resonance (SCMR) scientific sessions over the past 20 years. Methods: Scientific programs from all SCMR Annual Scientific Sessions from 1998 to 2017 were obtained. SCMR Headquarters also provided data for the number and the country of origin of attendees and the number of accepted abstracts according to type. Data analysis included text analysis (key word extraction) and visualization by ‘word clouds’ representing the most frequently used words in session titles for 5-year intervals. In addition, session titles were sorted into 17 major subject categories to further evaluate research and clinical CMR trends over time. Results: Analysis of SCMR annual scientific sessions locations, attendance, and number of accepted abstracts demonstrated substantial growth of CMR research and clinical applications. As an international field of study, significant growth of CMR was documented by a strong increase in SCMR scientific session attendance (> 500%, 270 to 1406 from 1998 to 2017, number of accepted abstracts (> 700%, 98 to 701 from 1998 to 2018) and number of international participants (42–415% increase for participants from Asia, Central and South America, Middle East and Africa in 2004–2017). ‘Word clouds’ based evaluation of research trends illustrated a shift from early focus on ‘MRI technique feasibility’ to new established techniques (e.g. late gadolinium enhancement) and their clinical applications and translation (key words ‘patient’, ‘disease’) and more recently novel techniques and quantitative CMR imaging (key words ‘mapping’, ‘T1’, ‘flow’, ‘function’). Nearly every topic category demonstrated an increase in the number of sessions over the 20-year period with ‘Clinical Practice’ leading all categories. Our analysis identified three growth areas ‘Congenital’, ‘Clinical Practice’, and ‘Structure/function/flow’. Conclusion: The analysis of the SCMR historical archives demonstrates a healthy and internationally active field of study which continues to undergo substantial growth and expansion into new and emerging CMR topics and clinical application areas