Atlas-Based Computational Analysis of Heart Shape and Function in Congenital Heart Disease

Abstract

Approximately 1% of all babies are born with some form of congenital heart defect. Many serious forms of CHD can now be surgically corrected after birth, which has led to improved survival into adulthood. However, many patients require serial monitoring to evaluate progression of heart failure and determine timing of interventions. Accurate multidimensional quantification of regional heart shape and function is required for characterizing these patients. A computational atlas of single ventricle and biventricular heart shape and function enables quantification of remodeling in terms of z scores in relation to specific reference populations. Progression of disease can then be monitored effectively by longitudinal evaluation of z scores. A biomechanical analysis of cardiac function in relation to population variation enables investigation of the underlying mechanisms for developing pathology. Here, we summarize recent progress in this field, with examples in single ventricle and biventricular congenital pathologies.

A novel TBX5 mutation predisposes to familial cardiac septal defects and atrial fibrillation as well as bicuspid aortic valve

“…As the most prevalent type of human birth defect, congenital heart defect (CHD) occurs in about 1% of all live neonates, accounting for nearly a third of all forms of developmental abnormalities (Benjamin et al, 2019;Oliveira-Brancati et al, 2020). Although minor CHD may resolve spontaneously (Benjamin et al, 2019), serious CHD may lead to poor health-related quality of life (Amedro et al, 2018(Amedro et al, , 2019Boukovala et al, 2019), reduced exercise capacity (Müller et al, 2018;Abassi et al, 2019;Smith et al, 2019), abnormal nervous develop ment or brain injury (Peyvandi et al, 2018(Peyvandi et al, , 2019Khanna et al, 2019), hemorrhagic or ischemic stroke (Bokma et al, 2018;Giang et al, 2018;Pedersen et al, 2019), pulmonary hypertension (Brida and Gatzoulis, 2018;Dimopoulos et al, 2018;Kaemmerer et al, 2018;Pascall and Tulloh, 2018), acute kidney injury or renal dysfunction (Lui et al, 2017;Gist et al, 2018), infective endocarditis (Jortveit et al, 2018;Tutarel et al, 2018;Cahill et al, 2019), cardiac dysfunction or congestive heart failure (Gilbert et al, 2018;Lal et al, 2018;Sabanayagam et al, 2018;Chan et al, 2019), ventricular or supraventricular dysrhythmia (Labombarda et al, 2017;Barry et al, 2018;Hernández-Madrid et al, 2018;Fuchs et al, 2019), and death (Lynge et al, 2018;Yu C et al, 2018). Although vast advance in cardiac surgery allows over 90% of CHD newborns to survive into adulthood, it results i...…”

Independent Left Ventricular Morphometric Atlases Show Consistent Relationships with Cardiovascular Risk Factors: A UK Biobank Study

“…Changes in LV morphometry have been demonstrated in healthy adults who were born prematurely 14 , volunteers with titin-truncating variants 15 , genetic mutations affecting LV mass 16 , higher fat mass 17 , higher blood pressure 13 , and smoking and other risk factors in the Multi-Ethnic Study of Atherosclerosis (MESA) 9 . Atlas based methods have also been used to quantify remodeling patterns in patients with myocardial infarction 18 , shape features associated with response after cardiac resynchronization therapy 19 , and impairment of function in congenital heart disease 20 .…”

“…However, atlas-based shape measures may be influenced by the methods used in their construction, and this may affect the resulting shape analyses. Two different types of atlas have been derived to date, using either volume image registration 10,13,15–17 or surface registration 9,14,18–20 methods. The key difference between these approaches is in the non-rigid registration techniques used to map the anatomy of each patient’s heart into a common coordinate system.…”

Artificial Intelligence in Cardiac Imaging With Statistical Atlases of Cardiac Anatomy

“…An alternative approach is to jointly estimate the shape and the underlying statistical shape model so that the statistical model can be automatically updated while analyzing new cases ( 44 ). Shape model templates have been constructed to describe common congenital pathologies, such as congenitally corrected transposition of the great arteries, enabling a wide range of pathologies to be accurately characterized ( 45 ). In single-ventricle pathologies, with tricuspid atresia and Fontan repair, shape mode scores were able to quantify differences in shape and function, with more spherical ED shapes being associated with reduced longitudinal shortening ( 46 ).…”