Imperial College London
Dr Michael Koa-Wing

DrMichaelKoa-Wing

Faculty of Medicine, National Heart & Lung Institute

Honorary Clinical Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 3313 1664m.koa-wing05

 
 
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Location

 

Cardiac Catheter Laboratory (EP)Hammersmith HospitalHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Koa-Wing:2015:10.1016/j.ijcard.2015.07.017,
author = {Koa-Wing, M and Nakagawa, H and Luther, V and Jamil-Copley, S and Linton, N and Sandler, B and Qureshi, N and Peters, NS and Davies, DW and Francis, DP and Jackman, W and Kanagaratnam, P},
doi = {10.1016/j.ijcard.2015.07.017},
journal = {International Journal of Cardiology},
pages = {391--400},
title = {A diagnostic algorithm to optimize data collection and interpretation of Ripple Maps in atrial tachycardias},
url = {http://dx.doi.org/10.1016/j.ijcard.2015.07.017},
volume = {199},
year = {2015}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundRipple Mapping (RM) is designed to overcome the limitations of existing isochronal 3D mapping systems by representing the intracardiac electrogram as a dynamic bar on a surface bipolar voltage map that changes in height according to the electrogram voltage–time relationship, relative to a fiduciary point.ObjectiveWe tested the hypothesis that standard approaches to atrial tachycardia CARTO™ activation maps were inadequate for RM creation and interpretation. From the results, we aimed to develop an algorithm to optimize RMs for future prospective testing on a clinical RM platform.MethodsCARTO-XP™ activation maps from atrial tachycardia ablations were reviewed by two blinded assessors on an off-line RM workstation. Ripple Maps were graded according to a diagnostic confidence scale (Grade I — high confidence with clear pattern of activation through to Grade IV — non-diagnostic). The RM-based diagnoses were corroborated against the clinical diagnoses.Results43 RMs from 14 patients were classified as Grade I (5 [11.5%]); Grade II (17 [39.5%]); Grade III (9 [21%]) and Grade IV (12 [28%]). Causes of low gradings/errors included the following: insufficient chamber point density; window-of-interest < 100% of cycle length (CL); < 95% tachycardia CL mapped; variability of CL and/or unstable fiducial reference marker; and suboptimal bar height and scar settings.ConclusionsA data collection and map interpretation algorithm has been developed to optimize Ripple Maps in atrial tachycardias. This algorithm requires prospective testing on a real-time clinical platform.
AU  - Koa-Wing,M
AU  - Nakagawa,H
AU  - Luther,V
AU  - Jamil-Copley,S
AU  - Linton,N
AU  - Sandler,B
AU  - Qureshi,N
AU  - Peters,NS
AU  - Davies,DW
AU  - Francis,DP
AU  - Jackman,W
AU  - Kanagaratnam,P
DO  - 10.1016/j.ijcard.2015.07.017
EP  - 400
PY  - 2015///
SN  - 1874-1754
SP  - 391
TI  - A diagnostic algorithm to optimize data collection and interpretation of Ripple Maps in atrial tachycardias
T2  - International Journal of Cardiology
UR  - http://dx.doi.org/10.1016/j.ijcard.2015.07.017
UR  - http://hdl.handle.net/10044/1/39093
VL  - 199
ER  -
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