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\begin{document}

\title{Is there a need for a novel algorithm for accessory pathways
localization?}



\author[1]{Malek Nayfeh}%
\author[1]{Marwan Refaat}%
\affil[1]{American University of Beirut Medical Center}%


\vspace{-1em}



  
  \date{June 18, 2024}


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\textbf{Is there a need for a novel algorithm for accessory pathways
localization?}

Malek Nayfeh MD, Marwan M. Refaat MD

Division of Cardiology, Department of Internal Medicine, American
University of Beirut Medical Center, Beirut, Lebanon

Running Title: Is there a need for a novel algorithm for WPW
localization?

Words: 572 (excluding the title page and references)

Keywords: accessory pathways, Wolff-Parkinson-white, WPW, cardiac
arrhythmias, cardiovascular diseases, heart diseases, Inferior Lead
Discordance

Funding: None

Disclosures: None

Corresponding Author:

Marwan M. Refaat, MD, FACC, FAHA, FHRS, FASE, FESC, FACP, FRCP

Associate Professor of Medicine

Director, Cardiovascular Fellowship Program

Department of Internal Medicine, Cardiovascular Medicine/Cardiac
Electrophysiology

Department of Biochemistry and Molecular Genetics

American University of Beirut Faculty of Medicine and Medical Center

PO Box 11-0236, Riad El-Solh 1107 2020- Beirut, Lebanon

US Address: 3 Dag Hammarskjold Plaza, 8th Floor, New York, NY 10017, USA

Office: +961-1-350000/+961-1-374374 Extension 5353 or Extension 5366
(Direct)

Wolff Parkinson White Syndrome (WPW) affects between 0.1\% and 0.2\% of
the population, causes morbidity due to supraventricular tachycardia
(SVT) and can lead to sudden cardiac arrest {[}1-3{]}. The management
involves localizing the accessory pathway, and then ablating it, by
using either radiofrequency (RF) ablation or cryoablation. The
electrocardiogram has been useful over the last decades in the
localization of accessory pathways, premature ventricular contractions
site of origin and pacing sites {[}4{]}. Regarding localization of the
pathway, following a large study of RF ablation, Fitzpatrick et al
described eight anatomical locations of different pathways using
fluoroscopic landmarks: Right anteroseptal (RAS), right midseptal (RMS),
right posteroseptal (RPS), right anterolateral (RAL), right
posterolateral (RPL), left anterolateral (LAL), left posterolateral
(LPL) and left posteroseptal (LPS) {[}5{]}. Other algorithms such as the
Arruda algorithm or the D'Avila algorithm are also used by clinicians
{[}6, 7{]}. Most of the accessory pathways' localization algorithms
involve assessment of the delta wave vector (Figure 1), some focus more
on QRS morphology (Figure 2), and others combine both methods (Figure 3)
{[}8-12{]}. By using these algorithms, differentiating between right
sided and left sided accessory pathways does not generally pose a
problem. However, determining the exact location of right and left sided
pathways appears to be more challenging.

The study of Bera et al. is a retrospective cohort. Twenty-two patients
met the inclusion criteria. The aim was to assess the value of inferior
lead discordance (meaning a positive QRS in lead II and a negative QRS
in lead III) as a predictor of right anterior (RA) and RAL pathway. The
authors included participants who had undergone RF ablation and were
found to have right sided pathways. They then separated them in two
groups based on if they had RA and RAL pathway (group 1) vs other
pathways (group 2). The study found that all patients who had RA and RAL
pathway had an ECG showing ILD, while 17 out of 18 patients who were in
the other locations did not have an ECG with ILD. The sensitivity and
specificity of ILD for predicting RAL location are 100\% and 95\%
respectively.

The findings in this study are highly relevant because they represent a
clear and simple way of localizing RA/RAL pathways. Other algorithms are
also extremely helpful but have their limitations especially if they
rely on the delta wave polarity and the electrocardiogram is not fully
pre-excited. Another advantage to the algorithm used in this study is
that it focuses on limb leads, instead of pericardial leads, which are
highly susceptible to variability due to possible displacement.

This was a well conducted study, but has some limitations, most notably
the small sample size of 22, with only 4 being RA and RAL pathways.
There are many algorithms that help cardiologists and cardiac
electrophysiologists in localizing accessory pathways before ablation,
however, none has specifically focused on RA and RAL pathways. With the
advances in artificial intelligence and machine learning, more
algorithms using them might be developed in the future.

Figure Legends

Figure 1: Examples of algorithms that rely on delta wave polarity such
as Fitzpatrick (top) {[}5{]}, Chiang (bottom left) {[}8{]} and Arruda
(bottom right) {[}6{]}

Figure 2: Example of algorithms that rely on QRS morphology such as
D'Avilla (top left) {[}7{]}, Taguchi (top right) {[}9{]} and St George's
(bottom) {[}10{]}.

Figure 3: Examples of algorithms that rely both on delta waves and QRS
morphology, such as Pambrun (top) {[}11{]} and Baek (bottom) {[}12{]}.

References:

1. Refaat MM, Hotait M, Tseng ZH (2014). Utility of the Exercise
Electrocardiogram Testing in Sudden Cardiac Death Risk Stratification.
Ann Noninvasive Electrocardiol, 19(4): 311-318.

2. Lu, C. W., Wu, M. H., Chen, H. C., Kao, F. Y., \& Huang, S. K.
(2014). Epidemiological profile of Wolff-Parkinson-White syndrome in a
general population younger than 50 years of age in an era of
radiofrequency catheter ablation. International journal of cardiology,
174(3), 530--534. https://doi.org/10.1016/j.ijcard.2014.04.134

3. Arai, A., \& Kron, J. (1990). Current management of the
Wolff-Parkinson-White syndrome. The Western journal of medicine, 152(4),
383--391.

4. Refaat M, Mansour M, Singh JP, Ruskin JN, Heist EK (2011).
Electrocardiographic Characteristics in Right Ventricular Versus
Biventricular Pacing in Patients With Paced Right Bundle Branch Block
QRS Pattern. J Electrocardiol, 44 (2): 289-95.

5. Fitzpatrick, A. P., Gonzales, R. P., Lesh, M. D., Modin, G. W., Lee,
R. J., \& Scheinman, M. M. (1994). New algorithm for the localization of
accessory atrioventricular connections using a baseline
electrocardiogram. Journal of the American College of Cardiology, 23(1),
107--116. https://doi.org/10.1016/0735-1097(94)90508-8

6. Arruda, M. S., McClelland, J. H., Wang, X., Beckman, K. J., Widman,
L. E., Gonzalez, M. D., Nakagawa, H., Lazzara, R., \& Jackman, W. M.
(1998). Development and validation of an ECG algorithm for identifying
accessory pathway ablation site in Wolff-Parkinson-White syndrome.
Journal of cardiovascular electrophysiology, 9(1), 2--12.
https://doi.org/10.1111/j.1540-8167.1998.tb00861.x

7. d'Avila, A., Brugada, J., Skeberis, V., Andries, E., Sosa, E., \&
Brugada, P. (1995). A fast and reliable algorithm to localize accessory
pathways based on the polarity of the QRS complex on the surface ECG
during sinus rhythm. Pacing and clinical electrophysiology : PACE, 18(9
Pt 1), 1615--1627. https://doi.org/10.1111/j.1540-8159.1995.tb06983.x

8. Chiang, C. E., Chen, S. A., Teo, W. S., Tsai, D. S., Wu, T. J.,
Cheng, C. C., Chiou, C. W., Tai, C. T., Lee, S. H., \& Chen, C. Y.
(1995). An accurate stepwise electrocardiographic algorithm for
localization of accessory pathways in patients with
Wolff-Parkinson-White syndrome from a comprehensive analysis of delta
waves and R/S ratio during sinus rhythm. The American journal of
cardiology, 76(1), 40--46. https://doi.org/10.1016/s0002-9149(99)80798-x

9. Taguchi, N., Yoshida, N., Inden, Y., Yamamoto, T., Miyata, S.,
Fujita, M., Yokoi, K., Kyo, S., Shimano, M., Hirai, M., \&amp; Murohara,
T. (2013, December 22). A simple algorithm for localizing accessory
pathways in patients with Wolff-Parkinson-White syndrome using only the
R/S ratio. Journal of Arrhythmia. Retrieved February 10, 2022, from
https://www.sciencedirect.com/science/article/pii/S1880427613001658

10. Xie, B., Heald, S. C., Bashir, Y., Katritsis, D., Murgatroyd, F. D.,
Camm, A. J., Rowland, E., \& Ward, D. E. (1994). Localization of
accessory pathways from the 12-lead electrocardiogram using a new
algorithm. The American journal of cardiology, 74(2), 161--165.
https://doi.org/10.1016/0002-9149(94)90090-6

11. Pambrun, T., El Bouazzaoui, R., Combes, N., Combes, S., Sousa, P.,
Le Bloa, M., Massoulli\selectlanguage{ngerman}é, G., Cheniti, G., Martin, R., Pillois, X.,
Duchateau, J., Sacher, F., Hocini, M., Jaïs, P., Derval, N., Bortone,
A., Boveda, S., Denis, A., Haïssaguerre, M., \& Albenque, J. P. (2018).
Maximal Pre-Excitation Based Algorithm for Localization of Manifest
Accessory Pathways in Adults. JACC. Clinical electrophysiology, 4(8),
1052--1061. https://doi.org/10.1016/j.jacep.2018.03.018

12. Baek, S. M., Song, M. K., Uhm, J. S., Kim, G. B., \& Bae, E. J.
(2020). New algorithm for accessory pathway localization focused on
screening septal pathways in pediatric patients with
Wolff-Parkinson-White syndrome. Heart rhythm, 17(12), 2172--2179.
https://doi.org/10.1016/j.hrthm.2020.07.016.\selectlanguage{english}
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