Improving how AF is diagnosed and treated

Atrial Fibrillation (AF) is the most frequent arrhythmic disorder of the heart with 60 million AF patients worldwide. Prevalence in the U.S. is 2.3 million patients and is projected to increase to more than 6 million by 2050.

Atrial fibrillation (AF) is an abnormal heart rhythm characterized by rapid and irregular beating of the atria.

Thromboembolic events caused by AF are one main cause of stroke. Up to 36% of elderly AF patients experience a stroke and those strokes are particularly severe.

Traditionally, patients with AF receive oral pharmacological treatment. If long lasting AF episodes occur, they are treated with atrial defibrillation (cardioversion). Recent statistics showed that this therapeutic strategy does not sustainably cure AF or reduce the risk of stroke. This catalyzed a paradigm shift towards catheter ablation which is the only potentially curative treatment besides open-heart surgery.

According to 2016 guidelines, catheter ablation of AF is the standard treatment to prevent recurrent AF. Yet, only 5% of the patients are treated with catheter ablation; 95% still receive medication and defibrillation. The global AF Market has an annual compound growth rate of 13.3% to reach $16.17 billion by 2020 as catheter ablation drives the industry growth. This growth is carried by new innovative mapping, navigation, and ablation technologies. The associated health cost increase is balanced by the reduction in cost associated with AF related strokes (today, $12 billion per year in the U.S.).

There are two different types of AF: paroxysmal and persistent. Patients with persistent AF have a higher risk for stroke than those with paroxysmal disease. Structural changes of the atrial tissue underlying persistent AF are partially induced by long lasting AF episodes through epigenomic modifications. Therefore, an early effective Catheter Ablation treatment is recommended to stop the progress of the atrial destruction and has a clear preventive benefit together with other preventive measures like diet, sleep, and physiotherapy.

Persistent AF has become a major public health issue because of high prevalence, relative therapy resistance, and the elevated stroke risk. Thus, a high medical need exists for a specialized diagnostic and therapeutic platform for persistent AF treatment that would be reasonably priced and yield effective treatment results.

Ablacon® has focused on creating a system to precisely localize and characterize the sources of Atrial Fibrillation in persistent AF patients and guide a precisely targeted therapy, with real-time treatment success and long-term outcome success.

Ablamap® is the first precise diagnostic technology for the fibrillating atrium. Its output is a highly reproducible and precise description of active sources and stable rotors over long observation times and their exact localization. The unprecedented precision and reproducibility of Ablamap® allows immediate therapy control, long-term disease monitoring, disease characterization, and comparison between patients.

Electrographic Flow

A novel system for the identification of AF drivers based on Ablacon`s proprietary patented Electrographic Flow (EGF®) algorithm technology. The concept of EGF has been invented by Ablacon and its collaborators. It is based on certain well-known algorithms and their implementation on a high-speed workstation which are Ablacon’s IP in the general field of electrophysiology (of all excitable tissues) and provide significant advantages over other mapping technologies. Competitor’s technologies are based on Electrocardiogram (ECG) peak detection (Activation Mapping) and Fourier and Hilbert Transforms (Phase Mapping) for rotor analysis.

A basket catheter records intracardial signals. Our algorithm pre-processes the 64 spike trains in order to expose the signals stemming from the atrial fibrillation. Hence, at each point of time, we have 64 numbers. These numbers can be re-arranged according to the catheter geometry. We interpolate the values between the electrodes and obtain a time series of 2D pictures. We then compute the Electrographic Flow by tracking where activations move (cf. EGF Map). Our algorithm is able to average out the noise in the data and yield a vector field that reveals structures such as focal impulses and rotors. Finally, we present a summary of the flow indicating the spatial and temporal prevalence (cf. Prevalence map) of the objects found (cf. Active Sources).

In this video you can see a visualization of the Electrographic Flow. It shows the flow of action potentials at a given point in time. There are two active rotors for which our algorithm computes a fingerprint. Based on a large database, our machine learning model can predict which source (rotors or focal impulses) is the driver of a patient’s AF. After an ablation at an appropriate location, the AF stops and the scars can be seen in the Electrographic Flow.

Who we are:

Peter Ruppersberg

Frank Rodrigues
VP of Quality Assurance, Regulatory Affairs, & Operations

Philip Haeusser

Dirk Schuermann
Director Clinical Services Europe

Lana Kasyanchik
Director of Finance and Administration