Standardized and automated regionalization of the atria for 3D cardiac imaging, electroanatomical mapping and computational modeling – a multidisciplinary consensus of the PersonalizeAF consortium

Christian Götz (Karlsruhe)1, P. Martinez (Karlsruhe)1, E. Invers-Rubio (Barcelona)2, S. Hussain (Bologna)3, L. Mont (Barcelona)2, C. Schmidt (Heidelberg)4, S. Mañá (Barcelona )5, M. Steghöfer (Barcelona)6, C. Corsi (Bologna)3, O. Dössel (Karlsruhe)1, A. Climent (Valencia)7, B. Rodriguez (Oxford)8, U. Schotten (Maastricht)9, A. Auricchio (Lugano)10, J. A. Cabrera Rodriguez (Pozuelo de Alarcon)11, A. Loewe (Karlsruhe)1, M. Guillem (Valencia)7, T. Althoff (Barcelona)2

1Karlsruher Institut für Technologie (KIT) Institut für Biomedizinische Technik Karlsruhe, Deutschland; 2Hospital Clinic University of Barcelona Arrhythmia Section Barcelona, Spanien; 3University of Bologna Department of Electrical, Electronic, and Information Engineering Bologna, Italien; 4Universitätsklinikum Heidelberg Klinik für Innere Med. III, Kardiologie, Angiologie u. Pneumologie Heidelberg, Deutschland; 5Adas3D Medical SL Barcelona , Spanien; 6Adas3D Medical SL Barcelona, Spanien; 7University of Valencia ITACA Institute Valencia, Spanien; 8University of Oxford Computational Cardiovascular Science Oxford, Großbritannien; 9Maastricht UMC+Heart+Vascular Center Dept. of Physiology Maastricht, Niederlande; 10Fondazione Cardiocentro Ticino Polo Scientifico Lugano, Schweiz; 11Hospital Universitario Quironsalud Madrid Cardiology Pozuelo de Alarcon, Spanien

 

 
Background
3D imaging and high-resolution electroanatomical mapping have become an integral part of cardiac electrophysiology and the management of patients with arrhythmias. With further technological advances the significance of these modalities continues to grow. Today, the spatial resolution of the various modalities allows for accurate regional characterization of morphological and electrophysiological properties. However, to perform regional quantitative analyses and intra- and inter-individual, as well as cross-modality comparisons, a universal definition of atrial regions and their boundaries is required.
While for the left ventricle there is already an established standardized regionalization (AHA 18-segment model), albeit not sufficiently precise to allow for reproducible definition of regional boundaries, there is no consensus for the regionalization of the atria.
Here we propose a standardized 15-segment bi-atrial model based on anatomical, electrophysiological and clinical considerations, with precise definition of regional boundaries allowing for reproducible and automated regionalization.
 
Methods and results
In a multidisciplinary task force of the European PersonalizeAF consortium involving cardiologists and cardiac electrophysiologists, as well as specialists in cardiac imaging and computational modeling we developed a standardized regionalization dividing the left atrium  into eight, and the right atrium  into seven segments, based on anatomical, electrophysiological and clinical considerations (15-segment bi-atrial model). This model provides regional definitions for imaging-, mapping- and computational modeling-derived atrial geometries, which are universally applicable and sufficiently precise to allow for both, manual and automated regionalization (Fig. 1A). 
 
As a proof-of-principle, two software algorithms for automatic regionalization of 3D atrial geometries based on the standardized 15-segment bi-atrial model were developed independently by different working groups of the PersonalizeAF consortium – one based on a commercially available software (ADAS-3D), the other being open-source. 
 
The algorithm based on the commercial software obtains the 15-segment bi-atrial model by dividing the surface mesh in the defined regions along geodesics using the Fast Marching Method (Fig. 1B). For the open-source solution, a publicly available semi-automatic bi-atrial division pipeline was developed: In this algorithm, after standardizing the surface mesh by remeshing and clipping the pulmonary veins, the orifices are annotated automatically. Based on these anatomical landmarks, the boundaries of each region are inferred by calculating geodesics using Dijkstra’s algorithm. The algorithms were able to annotate the regions with high accuracy and very good agreement as indicated by interrater reliability testing (kappa >0.9), in geometries derived from 50 patients and 2 imaging modalities (CT and MRI), thus demonstrating the universal applicability and reproducibility of the standardized segments.
 
Conclusion
We propose a standardized regionalization of the cardiac atria for 3D cardiac imaging, electroanatomical mapping and computational modeling, based on anatomical, electrophysiological and clinical considerations. The reproducibility and universal applicability of this 15-segment bi-atrial model was demonstrated by two independently developed software algorithms for automatic regionalization.
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