Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes
Year: 2019
Type: article
Abstract: Integrating spatial information about atrial physiology and anatomy in a single patient from multimodal datasets, as well as generalizing these data across patients, requires a common coordinate system. In the atria, this is challenging due to the complexity and variability of the anatomy. We aimed to develop and validate a Universal Atrial Coordinate (UAC) system for the following applications: combination and assessment of multimodal data; comparison of spatial data across patients; 2D visualization; and construction of patient specific geometries to test mechanistic hypotheses. Left and right atrial LGE-MRI data were segmented and meshed. Two coordinates were calculated for each atrium by solving Laplace's equation, with boundary conditions assigned using five landmark points. The coordinate system was used to map spatial information between atrial meshes, including scalar fields measured using different mapping modalities, and atrial anatomic structures and fibre directions from a reference geometry. Average error in point transfer from a source mesh to a destination mesh and back again was less than 0.1 mm for the left atrium and 0.02 mm for the right atrium. Patient specific meshes were constructed using the coordinate system and phase singularity density maps from arrhythmia simulations were visualised in 2D. In conclusion, we have developed a universal atrial coordinate system allowing automatic registration of imaging and electroanatomic mapping data, 2D visualisation, and patient specific model creation.
Source: Medical Image Analysis
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,150
Funders: Institut de France, Wellcome Trust, NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research, National Institute for Health and Care Research, British Heart Foundation, Agence Nationale de la Recherche, Fondation Leducq, Partnership for Advanced Computing in Europe AISBL, King's Health Partners, Medical Research Council, Engineering and Physical Sciences Research Council, Centre For Medical Engineering, King’s College London, National Heart, Lung, and Blood Institute
Awards: G1190480411, G1247657515, G1251496372, G1271318647, G133457142, Personalised Model Based Optimal Lead Guidance in Cardiac Resynchronisation Therapy, G2607942624, Virtual Electrophysiology Laboratory, Uncertainty Quantification in Prospective and Predictive Patient Specific Cardiac Models, Predicting Atrial Fibrillation Mechanisms Through Deep Learning, G3273634535, G3773670102, G3780594362, Infarct-related Ventricular Tachycardia Mechanisms: From Micro to Clinical, G49213722, L'Institut de Rythmologie et modélisation Cardiaque, G5296857752, G5893523844, G597271902, G6562481342, Implications of Intra-Myocardial Fat Deposition upon Propensity for Malignant Arrhythmia, The role of scar morphology and location in arrhythmogenic risk following cardiac resynchronisation therapy in patients with ischaemic heart disease, G7240651115, The interdependence of anatomy and function in atrial fibrillation, Simulation Guidance of Ablation Therapy for Persistent Atrial Fibrillation, G7650934720, G8303168876, G8775246936, G938335843, G961285871
OpenAlex ID: W2897703570