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\begin{document}

\title{Validation Of An Algorithm For Automatic Arrhythmia Recognition And 3D
Mapping In A Porcine Model}



\author[1]{Peter Guerra}%
\author[2]{Jonathan Yarnitsky}%
\author[1]{Laurent Macle}%
\author[3]{Yannick Sablayrolles}%
\author[1]{Catherine Lavoie}%
\author[2]{Elad Nakar}%
\author[2]{Amir Ben-Dor}%
\author[2]{Meir Bartal}%
\author[1]{Paul Khairy}%
\affil[1]{Institut De Cardiologie de Montreal}%
\affil[2]{Biosense Webster Israel Ltd}%
\affil[3]{Biosense Webster Inc}%


\vspace{-1em}



  
  \date{May 22, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Introduction: Atrial tachycardias (AT) can present multiple sites of
origin or circuits which complicates mapping, requiring creation of
separate activation maps per site. Objective: To evaluate the
Intra-Cardiac Pattern Matching (ICPM) software that automatically
detects and assigns different arrhythmia sources to separate 3D
activation maps in a porcine model. Methods: To simulate different ATs,
continuous pacing at same cycle length was performed from 2-3 right
atrial (RA) sites (2 screw-in leads and mapping catheter) for 60-90
seconds before alternating. RA was continuously mapped with a
48-electrode high-density mapping catheter (Octaray). The operator
manually switched and added points to the respective maps when the AT
changed. Conversely, the ICPM algorithm (Carto Mapping system)
automatically assigned each beat to its respective map. Pacing
electrodes were repositioned to create a second set of maps. Offline
analysis (manual and automatic maps) was performed comparing local
activation times (LAT) and mesh coloring values of adjacent points
(\textless{}5 mm apart). Differences \textless{}10 msec were considered
a match. Results: Twenty-three different pacing sites were analyzed in 6
swine with 1 manual/1 automatic map per site (46 maps); and 40,176
points were compared (manual and automatic). Individual LATs for manual
and automatic maps were compared and matched 91.2\% of the time
(variance of \textless{}10 ms). Mesh coloring values matched using the
same criteria. Conclusion: The ICPM algorithm accurately identified
changing atrial activation sites and assigned points to appropriate maps
\textgreater{}90\% of the time compared to manual acquisition.%
\end{abstract}%



\sloppy


\textbf{Validation of an Algorithm for Automatic Arrhythmia Recognition
and 3D Mapping in a Porcine Model}

Peter G. Guerra, MD*, Jonathan Yarnitsky+, Laurent Macle, MD*, Yannick
Sablayrolles+, Catherine Lavoie, MS, CEPS*, Elad Nakar+, Amir Ben-Dor+,
Bar-Tel Meir+ and Paul Khairy, MDCM, PhD*

* From the Electrophysiology Service, Montreal Heart Institute,
Universit\selectlanguage{ngerman}é de Montréal, Montreal, Canada; and \selectlanguage{english}+ Biosense Webster,
Yokneam, Israel

\textbf{Correspondence} : Dr. Peter G. Guerra, Montreal Heart Institute,
5000 Belanger Street, Montreal, Quebec H1T 1C8, Canada.

Email: peter.guerra@icm-mhi.org

\textbf{Short title: \emph{Automatic Arrhythmia Recognition in a Porcine
Model}}

\textbf{Word count: 1,199}

\textbf{Funding:} This study was made possible by research support
funding from Biosense Webster.

\textbf{Disclosures:} Authors listed with a \selectlanguage{english}+ are employed by Biosense
Webster. The research was supported by funding from this company.

All procedures performed in the study were approved by the Montreal
Heart Institute Animal Ethics Committee in accordance with the Canadian
Council of Animal Care (CCAC) Guidelines.

\textbf{ABSTRACT}

\textbf{Introduction:} Atrial tachycardias (AT) can present multiple
sites of origin or circuits which complicates mapping, requiring
creation of separate activation maps per site.

\textbf{Objective:} To evaluate the Intra-Cardiac Pattern Matching
(ICPM) software that automatically detects and assigns different
arrhythmia sources to separate 3D activation maps in a porcine model.

\textbf{Methods:} To simulate different ATs, continuous pacing at same
cycle length was performed from 2-3 right atrial (RA) sites (2 screw-in
leads and mapping catheter) for 60-90 seconds before alternating. RA was
continuously mapped with a 48-electrode high-density mapping catheter
(Octaray). The operator manually switched and added points to the
respective maps when the AT changed. Conversely, the ICPM algorithm
(Carto Mapping system) automatically assigned each beat to its
respective map. Pacing electrodes were repositioned to create a second
set of maps. Offline analysis (manual and automatic maps) was performed
comparing local activation times (LAT) and mesh coloring values of
adjacent points (\textless{}5 mm apart). Differences \textless{}10 msec
were considered a match.

\textbf{Results:} Twenty-three different pacing sites were analyzed in 6
swine with 1 manual/1 automatic map per site (46 maps); and 40,176
points were compared (manual and automatic). Individual LATs for manual
and automatic maps were compared and matched 91.2\% of the time
(variance of \textless{}10 ms). Mesh coloring values matched using the
same criteria.

\textbf{Conclusion:} The ICPM algorithm accurately identified changing
atrial activation sites and assigned points to appropriate maps
\textgreater{}90\% of the time compared to manual acquisition.

\textbf{KEYWORDS}

ablation, atrial fibrillation, atrial tachycardia, catheter ablation,
intracardiac recordings, mapping

\par\null

\textbf{INTRODUCTION}

Electrophysiologists are increasingly called upon to ablate more complex
arrhythmia substrates. These can take the form of multi-site atrial
tachycardias (AT), flutters, scar-related substrates in ventricular
tachycardia, and nonautomatic focal AT or intra-atrial reentrant
tachycardia (IART) in the congenital heart disease population {[}1,
2{]}. Areas of discontinuity in ablation lines can lead to proarrhythmic
effects {[}3{]}. In patients post atrial fibrillation ablation, multiple
focal ATs and reentrant flutter circuits can occur {[}4, 5{]}, with 40\%
of recurrences attributable to ATs. In complex congenital heart disease
such as single ventricle physiology with Fontan palliation, the mean
number of inducible ATs/IARTs exceeds 2 per patient {[}6{]}.

Three-dimensional electroanatomic mapping systems are indispensable
tools for complex ablation procedures involving multiple sites of origin
or circuits. Separate maps must be created for each arrhythmia which is
challenging, particularly when arrhythmias transition from one site to
another and/or have similar cycle lengths. Manual mapping can become
cumbersome and subject to inaccuracies. The Intra-Cardiac Pattern
Matching (ICPM) software (CARTO, Biosense Webster, Irvine, CA) was
created to automatically identify tachycardia patterns and classify each
to their respective maps. The software instantaneously recognizes
changes in activation patterns thereby allowing continuous mapping of
different arrhythmogenic foci/circuits. The purpose of this study was to
systematically evaluate this algorithm in an animal model by comparing
manually acquired and automated maps created by pacing at various atrial
sites.

\textbf{METHODS}

\textbf{Technology and algorithm}

The ICPM algorithm distinguishes different atrial activation patterns
based on unipolar signals recorded by the coronary sinus (CS) reference
catheter. A weighted correlation mechanism applied to CS signals
counters the effect of possible physiological changes on the signals'
morphology, such as electrode tissue touch. Correlation is sensitive to
catheter movements affect reference stability and excludes inappropriate
mapping of ectopic beats. The algorithm filters unipolar signals to
remove baseline wander caused by patient movement and respiration. A
normalized correlation is then calculated for each channel (Pearson
correlation). The channels are weighted based on the maximum slope of
the pattern's signal, indicating how prominent each channel is. A
correlation score is tabulated based on the weighted sum of calculated
single channel correlations. Correlation values are calculated for each
identified activation for a window surrounding the reference annotation
using the user selected pattern of interest (POI). The final score is
determined on the basis of the highest correlation value within that
window.

\textbf{Experimental methods}

Six swine were induced with Pentothal 25 mg/kg, intubated, and
maintained on a respirator with halothane. Venous access was obtained at
3 jugular and two femoral sites. Two screw-in leads were inserted from
jugular sites, their positions captured on fluoroscopy and 3D mapping.
Leads were subsequently repositioned to different pacing sites,
simulating different focal arrhythmia sites with a minimal
inter-electrode distance of 10 mm. Screw-in leads were used for greater
stability and greater pacing consistency. A CS catheter was likewise
inserted via jugular access. Mapping was performed using a
high-resolution catheter with 8 spines and 48 electrodes (Octaray,
Biosense Webster, Irvine, CA) inserted via the femoral veins (Figure 1).
Additional pacing was performed via a mapping catheter in the femoral
vein.

For each swine, continuous pacing at the same cycle length was performed
at 2 to 3 different right atrial sites at least 10 mm apart for 60-90
seconds (Figure 1). In each animal, the electrodes were repositioned,
and a second set of maps was created. The operator was aware of the
change in pacing site and switched to the appropriate map manually.
Manually created maps were optimised to best represent each pacing site
through operator intervention. Using Carto Replay and retrospective
Parallel Mapping, the same mapping time was processed using ICPM as an
active filter, with the system automatically identifying the change in
pattern (alternating pacing site) and assigning each pattern to its
respective map, without operator intervention.

To validate ICPM performance and accuracy, each set of maps (manual and
automated) for each pacing site were compared offline using two methods.
Local activation times were compared with differences \textless{}10 msec
considered a match. Only paired points within 5 mm of one another were
included. Secondly, we compared interpolated color-coded activation maps
generated from all available information in order to assess similarity
between manual maps and those created by ICPM. For this comparison, both
maps were based on the same mesh anatomy. Manual and automatically
acquired maps were also qualitatively compared visually.

Statistical analysis

The proportion of automated points that matched the paired manual points
with respect to local activation times and mesh vertices were
calculated, along with corresponding 95\% confidence intervals.
Correlations between matched pairs were assessed by McNemar tests.
Two-tailed P-values \textless{}0.05 were considered to indicated
statistical significance. Analyses were performed using SAS software
version 9.4 (SAS Institute, Cary, NC).

\textbf{RESULTS}

A total of 23 different pacing sites were studied in 6 swine,
corresponding to 11 sets of alternating sites (Table 1). For each pacing
site, manual and automatically acquired maps were created (total 46
maps). A total of 40,176 matched map points (mean 1747+-872 points per
pacing site) and 97,912 matched vertices (mean 4257+-905 vertices per
pacing site) were compared. Figure 2 illustrates comparative manual and
automatic maps. A high concordance between local activation times
translated into qualitatively similar map appearances. Visual
comparisons revealed identical localization of the pacing sites between
manual and automated maps. Quantitatively, 91.2\% of local activation
times and 90.8\% of mesh vertices showed consistency between the two
maps as outlined in Table 1.

\textbf{DISCUSSION}

This study, in a controlled in-vivo environment, showed that the novel
ICPM software was capable of accurately recognizing and mapping changing
atrial foci. Whereas the operator was notified when the pacing site
changed and switched maps accordingly, the software determined that the
pacing site had changed on its own. Resultant maps were visually
superposable. Quantitatively, local activation times and mesh vertices
showed consistent matches \textgreater{}90\% of the time. Pacing
distances as close as 10 mm were assessed, and cycle lengths were kept
constant to test the robustness of the system for distinguishing subtle
differences in activation sites. This type of autonomous mapping
capability could be of great benefit when targeting changing arrhythmia
types, particularly in aforementioned conditions like atrial
tachycardia, congenital heart disease and ventricular arrhythmias
{[}7-9{]}. Additional advantages include automated filtering of
mechanically induced ectopic activation that could introduce
inaccuracies with manual mapping, particularly when cycle lengths are
not radically different. Moreover, automated mapping can identify slight
changes in signal morphology resulting from movements of the reference
catheter that can otherwise go undetected.

\textbf{LIMITATIONS}

Whereas the pacing protocol was intended to mimic focal ATs, the ICPM
software was not validated for reentrant arrhythmias. Also, considering
these were healthy animals, it is unclear if the reliability of the
automated algorithms would be affected by diseased conduction tissue.
Finally, because the protocol was carried out in fully anesthetized and
intubated swine, there were no undue movements. In a setting of
conscious sedation, patient or catheter movements could have an impact
on mapping procedures in general.

\textbf{CONCLUSIONS}

The current in-vivo animal data suggests that automation software for 3D
electroanatomic mapping could reliably identify and map changing foci.
This carries the potential to help localize different arrhythmia origins
and increase efficiency in complex interventions that involve multiple
arrhythmia substrates.

\textsubscript{Q:\textbackslash{}Secretariat
Central\textbackslash{}Publications\textbackslash{}Chercheurs\textbackslash{}Guerra,P\textbackslash{}Validation\textbackslash{}Validation
JCE BriefCommunicat20201026PGap.docx}

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2. Khairy P, Stevenson WG. Catheter ablation in tetralogy of Fallot.
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3. Chae S, Oral H, Good E, et al. Atrial tachycardia after
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recurrence. J Am Coll Cardiol 2007;50:1781-1787.

4. Narayan SM, Baykaner T, Clopton P, et al. Ablation of rotor and focal
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5. Takigawa M, Derval N, Martin CA, et al. Mechanism of Recurrence of
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6. Moore BM, Anderson R, Nisbet AM, et al. Ablation of atrial
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7. Moore JP, Khairy, P. Adults with congenital heart disease and
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8. Tzou WS, Frankel DS, Hegeman T, et al. Core isolation of critical
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9. Choi Y, Kim S, Baek JY, et al. Acute and long-term outcome of redo
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