Reentrant Drivers Anchoring to Structural Heterogenies: A Major Pathophysiological Mechansism of Human Persistant AF
Dr. Natalia Trayanova's talk at AF2017 highlighted the mechanisms underlying persistent atrial fibrillation.
The mechanisms underlying persistent atrial fibrillation (AF) in patients with atrial fibrosis are poorly understood. Evidence from recent clinical and experimental studies suggests that persistent AF might be maintained by reentrant drivers (i.e., rotors), but the mechanisms linking reentrant driver formation and persistent AF perpetuation remain unknown.
"A large number of patients with persistent AF have extensive atrial structural remodeling, especially fibrosis, which can lead to the establishment of an arrhythmogenic atrial substrate and increased likelihood of reentrant driver formation,” Natalia Trayanova, PhD (Johns Hopkins University, Baltimore, MD) told AF Symposium News ahead of her presentation. “Since spatial patterns of atrial fibrosis are complex and vary widely between individuals, the precise link between fibrotic remodeling and reentrant drivers in patients with persistent AF remains elusive. A better understanding of this relationship will help pave the way toward personalized antiarrhythmic treatment planning."
The goal of this study was to determine how AF reentrant driver locations relate to the spatial distribution of fibrosis in the human atria. "To achieve the goal, we developed a personalized approach based on cardiac imaging and computational modeling," said Dr. Trayanova. "We constructed individualized three-dimensional computer models of the patient's atria from cardiac magnetic resonance imaging (MRI) data and assessed the propensity of each model to develop arrhythmia. We then generated 20 personalized atrial models that incorporated patient-specific representations of fibrosis derived from late gadolinium-enhanced MRI (LGE-MRI) scans." Next, segmented images were 'populated' with biophysically realistic atrial cell and tissue electrophysiology to arrive at virtual representations of the electrical functioning of the patient's fibrotic atria. Programmed electrical stimulation in the virtual atria was then conducted from a large number of biatrial pacing sites to comprehensively evaluate the arrhythmogenic propensity of the fibrotic substrate, and to determine how the locations where the organizing centers of reentrant drivers persist relate to the fibrosis spatial patterns.
What did their research demonstrate? The analysis of AF dynamics in inducible atrial models showed a combination of sustained reentrant drivers and transient reentries. Fibrosis patterns in regions where reentrant drivers persisted were characterized by computing maps of fibrosis density and entropy. Dr. Trayanova explained: "We found that AF was perpetuated by a few (2 to 5) spatially confined reentrant drivers. Compared with the remaining atrial tissue, regions where re-entrant drivers persisted had higher fibrosis density and entropy. Reentrant drivers did not persist in both completely nonfibrotic sites and regions of deep fibrosis. Regions with both high fibrosis density and entropy were found to be a potent substrate for the initiation and perpetuation of rotors, because such locations are associated with steep spatial gradients in excitability and refractoriness, rendering them highly prone to conduction failure due to the extensive intermingling of fibrotic and nonfibrotic tissue." She continued: "Using machine learning, we identified a subset of fibrotic boundary zones present in about 13% of atrial tissue, where 83% of all reentrant driver-organizing centers were located."
Their study concluded that in the patient-derived atrial models with individualized fibrosis distributions created from LGE-MRI: (1) AF was inducible by programmed electrical stimulation in models that have a sufficient amount of fibrosis, (2) the induced AF was perpetuated by reentrant drivers that persisted in spatially confined regions, and (3) the latter regions constituted boundary zones between fibrotic and nonfibrotic tissue that were characterized with high fibrosis density and entropy values.
"Our results demonstrate that only a limited subset of fibrosis border zones has the characteristics (i.e., high density and entropy) needed to sustain reentrant drivers," said Dr. Trayanova. "The use of sophisticated machine learning tools enabled us to devise a sensitive and specific classification scheme capable of pinpointing the combination of fibrosis density and entropy metric values associated with rotor localization. Overlaying machine learning-predicted areas on clinical ECGI maps displaying areas where rotors were observed most frequently in each patient's atria showed very good co-localization."
Knowledge regarding the link between dynamic AF rotor localization and the spatial characteristics of the fibrotic substrate has important implications for clinical strategies to manage and treat persistent AF. Multiple centers have reported that ablation of rotor-harboring sites could terminate persistent AF or convert it to a more clinically manageable tachycardia, but it remains unclear why this type of targeting has therapeutic value. "Our results suggest that it may be attributable to the fact that such ablations homogenize the tissue in rotor-anchoring regions, rendering it more like a deeper fibrotic region (i.e., lower values of density/entropy). It is also conceivable that locations with density/entropy favoring reentrant driver localization, as identified by processing the LGE-MRI images, could be directly targeted for ablation in a substrate modification approach," concluded Dr. Trayanova. "Our results also suggest that following ablation of a region sustaining a rotor, new emergent rotors will localize to sites with the same (high density/entropy) fibrosis spatial characteristics. Finally, the approach used in this study paves the way for the use of personalized virtual-atria models in determining noninvasively the optimal targets of ablation in patients with persistent AF."