Artificial Intelligence Software Standardizes Electrogram based
Ablation Outcome for Persistent Atrial Fibrillation
( JCE-22-0260.R1)
Title: Electrogram-based AF ablation –finally, reproducibility!
Isabel Deisenhofer , MD
Department of Electrophysiology, German Heart Center Munich, Technical
University of Munich (TUM), Munich, Germany
Funding: none
Disclosures: None
Since the landmark publication of Koonlawee Nademanee in 2004 (1),
electrogram based ablation (mostly) in addition to systematic PVI has
been an often and most often controversially discussed ablation strategy
for substrate modification in persistent atrial fibrillation. In most
studies, complex fractionated atrial electrograms (CFAE) are detected
using single bipolar recordings from ablation catheters or circular
mapping catheters. These (singular) electrograms are then adjudicated to
“CFAE” or “no CFAE” using the expertise of the operator aided by
relatively simple mathematical algorithms (measuring e.g. the mean cycle
length of the recorded electrogram); the subsequent ablation of CFAE
aims at AF regularization and finally termination by eliminating the AF
maintaining substrate. In several (single center) studies, the results
of this approach were very encouraging, but it relied heavily on the
experience of the operators, and the main criticism was its mediocre
reproducibility (2-3). This limitation proved to be crucial in the
multicenter STAR AF II trial, where the addition of CFAE ablation to PVI
did not improve the ablation success (4).
A the same time, mapping technologies and tools that allowed the
simultaneous analysis of adjacent electrograms and aimed at simultaneous
representation of the meandering activation patterns in ongoing AF were
developed. In contrast to the morphological description of singular
bipolar electrograms, these technologies were designed to detect in a
more comprehensive, “panoramic” way (either for both atria from
surface ECG or for a whole atrium with a large basket catheter)
recurrent patterns of focal and reentrant activation in many (adjacent)
electrograms (5-6). In these technologies, more complex mathematical
algorithms and much more filtering and alteration of the recorded
bipolar electrograms were used to determine activation directions/focal
firing and to identify by this AF rotors or drivers as targets for
ablation.
However, changing the field of view from single bipolar recordings (with
high resolution) to whole chamber/whole heart mapping (with very low
resolution) was maybe a step to far. At the same time, due to the
important transformation of local ECGs by filtering and
“recalculation” and the application of advanced mathematical
algorithms, it was almost impossible for operators to “understand” the
diagnosis of the mapping system: you had to trust the system blindly,
because it is impossible to counter-check by looking at the recorded
electrograms.
Eventually, it turned out that even by using these highly sophisticated
systems, the reproducibility of results in multicenter studies including
also non-expert centers is still low (7).
In a previous publication (8) Seitz e al introduced the concept of
atrial substrate identification by mapping spatiotemporal dispersion,
depicting an atrial area with local fractionated electrograms and/or
special conduction properties as detected by the unfiltered, original
bipolar recordings in one position of a multipolar mapping catheter
(e.g. the Pentarray® catheter). It is important to note that (a) the
electrograms remain unchanged and that (b) the relationship of the
electrograms, i.e. the conduction timing and patterns, are an important
point of the analysis. Since only one position of a multipolar mapping
catheter is analyzed at a time, the total surface mapped simultaneously
approaches 1-2cm²..
The results regarding AF termination and long-term maintenance of sinus
rhythm were very encouraging (95% termination; 85% sinus rhythm after
1.4 ablation procedures), but needed to be confirmed in a multicenter
study including “non-expert” operators.
In this edition of the Journal, Seitz et al. present a multicenter study
with one expert and 7 “satellite centers” that focusses exactly on the
two major weaknesses of electrogram based approaches: (a)reproducibility
and (b)an advanced electrogram analysis technology, that combines
advanced mathematical algorithms with operators’ experience – the
latter enhanced by the addition of artificial intelligence (AI) (9).
The authors included 85 ablation-naïve patients with persistent AF in 8
centers (one primary center and 7 satellite centers) with a total of 17
operators performing the ablation. Of note, almost 30% of the patients
suffered from long-lasting persistent AF, the mean age was 70 years,
mean CHADSvasc score was 2.5 and mean LA volume was 165±31 ml, with a
majority of patients suffering of at least one cardiovascular
co-morbidity – an overall challenging patients’ cohort.
The used mapping tool – the VX1 system- provides an online, AI enhanced
detection of spatio-temporal dispersion areas by evaluating the local
EGM morphology but also the complex relationship of adjacent
electrograms and thus analyzing conduction patterns between bipolar
electrograms recorded in one position of a multipolar mapping catheter.
The whole EGM adjudication process is enhanced by the use of AI that
takes formerly adjudicated EGMs into account. Thus, the system improves
in the going by addition of adjudicated EGMs.
Acute AF termination occurred in as many as 88% of patients and was
similar high in the expert center as the satellite centers (92% vs.
84%). The very good intraprocedural results translated also in very
satisfying numbers after a FU of 12 months: after a single ablation
procedure, freedom from atrial fibrillation with/without AAD was reached
in 86% of patients, whereas 54% of patients were free of any atrial
tachyarrhythmia. After a mean of 1.3 procedures, the number of patients
free from any atrial tachyarrhythmia increased to 73%.
Most importantly, no statistical difference could be found between
expert center and the satellite centers, no matter which subgroup or FU
was analyzed and the procedural safety was very high (one AV block).
Thus, Seitz and colleagues could demonstrate a high reproducibility of
their electrogram-based approach of spatiotemporal dispersion using the
VX1 software, even in non-expert hands and with a large number of
operators.
Furthermore, they could also reach very encouraging long-term success
rates regarding the maintenance of sinus rhythm, moreover after a
comparably low number of re-do procedures.
Regarding the procedures, there are also many very interesting points,
that should lead to further research: Only 42% of patients underwent in
the course of the ablation additional PVI and with 25% of patients, an
unusual high number of patients converted directly to sinus rhythm
without a transition via ATs. The mean RF time to reach SR was also very
short with 27min, meaning this approach is no “carpet-bombing” and
probably provides a maintained atrial transport function.
Regarding the long-term FU, the study confirms the finding that
intra-procedural termination is a positive predictor for sinus rhythm in
FU, with >60% of the terminated patients experiencing no
atrial tachyarrhythmia anymore after a single ablation procedure.
In summary, Seitz and colleagues showed that their AI enhanced VX1
software is finally able to provide reliability and reproducibility in
an EGM based approach – the holy grail of EGM based ablation
approaches. Together with very encouraging success rates regarding
long-term restoration of sinus rhythm, the Volta system has shown a high
clinical usefulness for treating the complex persistent AF patients.
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- Seitz J et al.. Artificial Intelligence Software Standardizes
Electrogram based Ablation Outcome for Persistent Atrial Fibrillation
(JCE-22-0260.R1)