  Atrial arrhythmia can be categorized into tachycardia, flutter, and
fibrillation. Atrial fibrillation is a prevalent heart disease that results in
weak and irregular contractions of the atria. It affects millions people
worldwide and contributes to hundreds of thousands deaths annually. Cardiac
ablation is among the most successful treatment options, involving the use of
radio frequency energy to kill diseased cells or create lesion lines that
obstruct abnormal activation waves. During the procedure, catheters are
inserted into the left atrium to map the atrium geometry and record endocardium
electrograms that are then converted into electroanatomical maps to pinpoint
the arrhythmia source locations.
  However, identifying these sources is challenging. The electrograms are
asynchronous and can be susceptible to noise. The spatial distribution of
sampling sites is non-uniform, which leads to inaccurate maps. Identifying
arrhythmia source locations is not a trivial task. Therefore, an ablation
procedure often lasts from 3 to 6 hours, and arrhythmia recurrence within 12
months after first ablation is around 50%. To address these challenges, we
developed an integrated computational heart mode for clinical left atrium
arrhythmia ablation. Our system takes in the left atrium geometry and
electrograms, processes them to extract regional tissue properties, which are
used to tune a heart model, creating a patient-specific whole-atrium model.
With this model, we can simulate and detect arrhythmia sources, and provide
ablation assistance. To build such a system, we investigated the fiber effects
on atrial activation patterns. We developed a fast heart model tuning method
which takes only a few seconds of computation time on a personal computer,
enabling real-time assistance during the ablation procedure. We achieved high
accuracy in simulating arrhythmias, which we validated on patient data.
