AI-ECG Accessory Pathway Localisation Study (AAPLS)

This study seeks to validate the real-world accuracy of an AI-based algorithm for identifying the location of an accessory pathway from the 12-lead electrocardiogram

Study Overview

• Status: Not yet recruiting
• Conditions: Accessory Pathway; ECG; Artifical Intelligence

Detailed Description

Silent validation study of an AI-ECG (artificial intelligence applied to electrocardiography) accessory pathway localisation algorithm, applied to prospective and consecutive cases in clinical practice, to determine its true accuracy and performance.

A pre-existing AI-ECG algorithm will be applied to participant ECG data, collected at the time of their clinical electrophysiology study (EPS) for ablation of their accessory pathway. This will be compared to the ground truth of the successful ablation location, determined by fluoroscopy and/or 3D electroanatomical mapping from their procedure.

• Study Type: Observational
• Enrollment (Estimated): 100

Contacts and Locations

• Study Contact: Name: Keenan Saleh, MBBS; Phone Number: +442033132243; Email: keenan.saleh10@imperial.ac.uk

Study Locations

• United Kingdom
  • London, United Kingdom, W12 0HS
    • Imperial College Healthcare NHS Trust
    • Contact: Keenan Saleh, MBBS; Phone Number: 02033132243; Email: k.saleh@nhs.net
    • Contact: Ahran Arnold, PhD; Phone Number: 02033132243; Email: ahran.arnold@imperial.ac.uk
    • Principal Investigator: Ahran Arnold, PhD
    • Sub-Investigator: Zachary Whinnett, PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients referred for an electrophysiology study +/- ablation, with evidence of previous pre-excitation on their 12-lead ECG.

Description

Inclusion Criteria:

• Referred for EPS procedure as part of their clinical care, with a finding of pre-excitation on their ECG
• Manifest pre-excitation on their ECG any time prior to their procedure
• Able to give consent
• Minimum age 13 years old
• Maximum age 100 years old

Exclusion Criteria:

• Unable to give consent
• Adults > 100 years old
• Children < 13 years old
• Patients with known location of their accessory pathway from a previous EP study

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
Patients with manifest pre-excitation; Patients with a previous ECG demonstrating manifest pre-excitation, referred for an electrophysiology study as part of their clinical care

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Performance and accuracy of the AI-ECG accessory pathway localisation algorithm	Performance metrics of the AI-ECG accessory pathway localisation algorithm, including accuracy, F1-score, sensitivity, specificity, positive and negative predictive values. Benchmarked against the ground truth of human operator assessment from fluoroscopy and/or 3D electroanatomical mapping.	At completion of recruitment, anticipated at 18 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Relative performance of the AI-ECG algorithm compared to human estimation	Difference in performance/accuracy between the AI-ECG accessory pathway localisation algorithm and human estimation from the 12-lead ECG	At completion of recruitment, anticipated at 18 months
Relative performance of the AI-ECG algorithm compared to manual localisation algorithms	Difference in performance/accuracy between the AI algorithm and pre-specified, established manual localisation algorithms (Arruda, Milstein, Pambrun, Boersma, D'Avila and Chiang)	At completion of recruitment, anticipated at 18 months
Accuracy of the ground truth locations from the human operator compared to the successful ablation location	The ground truth of successful ablation location determined by operator assessment of fluoroscopy ± 3D mapping will be compared to the true ablation location on a complete 3D electroanatomical annular map	At completion of recruitment, anticipated at 18 months

Collaborators and Investigators

• Sponsor: Imperial College London
• Investigators: Principal Investigator: Ahran Arnold, PhD, Imperial College London

Study record dates

Study Major Dates

• Study Start (Estimated): August 1, 2025
• Primary Completion (Estimated): March 1, 2027
• Study Completion (Estimated): March 1, 2027

Study Registration Dates

• First Submitted: July 9, 2025
• First Submitted That Met QC Criteria: July 21, 2025
• First Posted (Actual): July 24, 2025

Study Record Updates

• Last Update Posted (Actual): July 24, 2025
• Last Update Submitted That Met QC Criteria: July 21, 2025
• Last Verified: July 1, 2025

More Information

Terms related to this study

• Keywords: AI; ECG; AI-ECG; Accessory pathway; Accessory pathway localisation
• Additional Relevant MeSH Terms: Cardiac Conduction System Disease; Cardiovascular Diseases; Pathological Conditions, Anatomical; Heart Diseases; Arrhythmias, Cardiac; Pre-Excitation Syndromes; Accessory Atrioventricular Bundle
• Other Study ID Numbers: IRAS 347921

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No