AI-ECG Accessory Pathway Localisation Study
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age13-100
SponsorImperial College London
About this trial
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
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
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
Disqualifiers
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
Trial population
Patients referred for an electrophysiology study +/- ablation, with evidence of previous pre-excitation on their 12-lead ECG.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
100 Participants
are grouped into 1 trial groupGroup A: Patients with manifest pre-excitation
Trial outcomes
Primary outcomes
1
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.
Time frame
At completion of recruitment, anticipated at 18 monthsSecondary outcomes
1
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
Time frame
At completion of recruitment, anticipated at 18 months2
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)
Time frame
At completion of recruitment, anticipated at 18 months3
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
Time frame
At completion of recruitment, anticipated at 18 monthsSponsors and contacts
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Source ClinicalTrials.gov
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