Abstract #4436
Stochastic Fibrosis Signatures from 3D LGE: Novel Threshold-Free Quantification of Left Atrial Fibrosis
Mehri Mehrnia1,2, Eugene Kholmovski3, Rod Passman4, Aggelos Katsaggelos1,5,6, Saman Nazarian7, Daniel Kim1, and Mohammed Elbaz1
1Radiology, Northwestern University, Chicago, IL, United States, 2Biomedical Engineering, Northwestern University, Chicago, IL, United States, 3Johns Hopkins University, Baltimore, MD, United States, 4Cardiology, Northwestern University, Chicago, IL, United States, 5Electrical and Computer Engineering, Northwestern University, Chicago, IL, United States, 6Computer Science, Northwestern Universiy, Chicago, IL, United States, 7Division of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
Synopsis
Assessment of left atrial (LA) fibrosis in atrial fibrillation (AF) patients from 3D LGE MRI have shown promise in evaluating atrial myopathy for selecting patients for catheter ablation and to predict AF recurrence post intervention. Nevertheless, current methods for fibrosis quantification suffer from lack of standardization and reproducibility as they rely on different thresholds for defining fibrosis. Hence, limiting the clinical translation of 3D LA LGE MRI. Here, we propose the first threshold-free technique to quantify LA fibrosis burden using novel stochastic fibrosis signature technique. We demonstrated feasibility and correlations to four of the previously published methods for fibrosis quantification.
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