AugmentA: Patient-specific Augmented Atrial model Generation Tool

Digital twins of patients’ hearts are a promising tool to assess arrhythmia vulnerability and to personalize therapy. However, the process of building personalized computational models can be challenging and requires a high level of human interaction. A pipeline to standardize the generation of a patient’s atrial digital twin from clinical data is therefore desirable. We propose a patient-specific Augmented Atria generation pipeline (AugmentA) as a highly automated framework which, starting from clinical geometrical data, provides ready-to-use atrial personalized computational models. AugmentA consists firstly of a preprocessing step applied to the input geometry. Secondly, the atrial orifices are identified and labelled using only one reference point per atrium. If the user chooses to fit a statistical shape model (SSM) to the input geometry, it is first rigidly aligned with the given mean shape before a nonrigid fitting procedure is applied. AugmentA automatically generates the fiber orientation and finds local conduction velocities by minimizing the error between the simulated and clinical local activation time (LAT) map. The pipeline was tested on a cohort of 29 patients on both segmented magnetic resonance images (MRI) and electroanatomical maps of the left atrium. Moreover, the pipeline was applied to a bi-atrial volumetric mesh derived from MRI. The pipeline robustly integrated fiber orientation and anatomical region annotations in 38.4±5.7 s. The error between insilico and clinical LAT maps was on average 12.7 ms. In conclusion, AugmentA offers an automated and comprehensive pipeline delivering atrial digital twins from clinical data in procedural time.