Novel Robust Threshold-Free Probabilistic 3D LGE Fibrosis Signature Technique for Left Atrial Fibrosis Quantification

Motivation: Left atrial fibrosis assessment from 3D LGE-MRI is pivotal for predicting atrial myopathy and AF recurrence. However, current methods are clinically ineffective and sensitive to data uncertainties such as noise and inter-observer variability of thin LA wall segmentationGoal(s): Hence, we propose a novel, robust, and standardized probabilistic 3D LGE fibrosis signature technique for quantifying fibrosis burden. Approach: Our threshold-free signature technique probabilistically encodes multi-billion LGE intensity comparisons from the entire LA volume (not just LA wall). Results: We evaluated feasibility of our threshold-free method in quantifying LA fibrosis burden, and its stability against Rician noise and interobserver variability of LA volume segmentation. Impact: Our signature technique as an index of fibrosis burden is highly robust to inherent scan uncertainties including high power Rician noise and inter-observer LA segmentation variability. As a result, our method increases potential clinical utility of 3D LGE MRI