Comparison of Segmentation Algorithms for Detecting Myocardial Infarction Using Late Gadolinium Enhancement Magnetic Resonance Imaging

Objective:The aim of this study was to validate the accuracy of a new automatic method for scar segmentation and compare its performance with that of two other frequently used segmentation algorithms.Methods:Twenty-six late gadolinium enhancement cardiovascular magnetic resonance images of diseased hearts were segmented by the full width at half maximum(FWHM)method,the n standard deviations(n SD)method,and our new automatic method.The results of the three methods were compared with the consensus ground truth obtained by manual segmentation of the ventricular boundaries.Results:Our automatic method yielded the highest Dice score and the lowest volume difference compared with the consensus ground truth segmentation.The n SD method produced large variations in the Dice score and the volume difference.The FWHM method yielded the lowest Dice score and the greatest volume difference compared with the automatic,6SD,and 8SD methods,but resulted in less variation when different observers segmented the images.Conclusion:The automatic method introduced in this study is highly reproducible and objective.Because it requires no manual intervention,it may be useful for processing large datasets produced in clinical applications.

Current progress of computational modeling for guiding clinical atrial fibrillation ablation

Atrial fibrillation(AF)is one of the most common arrhythmias,associated with high morbidity,mortality,and healthcare costs,and it places a significant burden on both individuals and society.Anti-arrhythmic drugs are the most commonly used strategy for treating AF.However,drug therapy faces challenges because of its limited efficacy and potential side effects.Catheter ablation is widely used as an alternative treatment for AF.Nevertheless,because the mechanism of AF is not fully understood,the recurrence rate after ablation remains high.In addition,the outcomes of ablation can vary significantly between medical institutions and patients,especially for persistent AF.Therefore,the issue of which ablation strategy is optimal is still far from settled.Computational modeling has the advantages of repeatable operation,low cost,freedom from risk,and complete control,and is a useful tool for not only predicting the results of different ablation strategies on the same model but also finding optimal personalized ablation targets for clinical reference and even guidance.This review summarizes three-dimensional computational modeling simulations of catheter ablation for AF,from the early-stage attempts such as Maze III or circumferential pulmonary vein isolation to the latest advances based on personalized substrate-guided ablation.Finally,we summarize current developments and challenges and provide our perspectives and suggestions for future directions.