Ventricular Tachycardia Clinical Trial
Official title:
Development and Clinical Validation of an In Silico Pace Mapping Approach Utilising Implanted Device Electrograms to Accurately Guide Ventricular Tachycardia Ablation
People who suffer from incessant cardiac arrhythmias receive a small electrical device implanted into their chest that automatically senses when the heart beats arrhythmically and applies electrical pulse to re-establish normal activity. However, if problems persist, people can have an operation called catheter ablation therapy, which involves 'burning' small areas of the heart tissue in order to permanently disrupt the problematic electrical pathways driving these arrhythmias. However, procedure times and complication rates are high, whist success rates are punitively low (~50% success), largely due to the significant challenge clinicians face in identifying the ideal 'target' to ablate within the patient's heart. In this project, the investigators aim to develop, and clinically validate, an in silico tool that reconstructs a personalised computational model of a patient's heart using advanced MRI data, upon which a virtual 'mapping' procedure is then performed in order to identify (in the model) the optimal ablation target. This pre-procedural planning tool utilises stored information about the patient's specific arrhythmia from their implanted device, ensuring optimal targets are selected. The approach aims to reduce procedure times whilst increasing their safety, and ensure significantly increased long-term effectiveness of these invasive ablation procedures, increasing survival rates and quality-of-life. This study is concerned with the clinical arm of the study, specifically, in the collection of data from patients in order to (retrospectively) validate the computational model. The model itself will not be applied or used to treat these patients.
Status | Not yet recruiting |
Enrollment | 25 |
Est. completion date | October 1, 2025 |
Est. primary completion date | April 1, 2025 |
Accepts healthy volunteers | |
Gender | All |
Age group | 18 Years to 99 Years |
Eligibility | Inclusion Criteria: - Age 18 to 99 years - Ability to provide informed consent to participate and willing to comply with the clinical investigation plan and follow-up schedule. - Ventricular tachycardia secondary to ischemic heart disease clinically indicated for catheter ablation therapy - Cardiac implanted electronic device in situ Exclusion Criteria: 1. Standard contra-indications to VT ablation 2. Female participants who are pregnant, lactating or planning pregnancy during the course of the study. 3. Contra-indication to contrast agent for Cardiac MRI scan 4. Implanted device that is not MRI-conditional |
Country | Name | City | State |
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n/a |
Lead Sponsor | Collaborator |
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Guy's and St Thomas' NHS Foundation Trust | King's College London |
Monaci S, Strocchi M, Rodero C, Gillette K, Whitaker J, Rajani R, Rinaldi CA, O'Neill M, Plank G, King A, Bishop MJ. In-silico pace-mapping using a detailed whole torso model and implanted electronic device electrograms for more efficient ablation plannin — View Citation
Yokokawa M, Kim HM, Sharaf Dabbagh G, Siontis KC, Lathkar-Pradhan S, Jongnarangsin K, Latchamsetty R, Morady F, Bogun F. Targeting Noninducible Clinical Ventricular Tachycardias in Patients With Prior Myocardial Infarctions Based on Stored Electrograms. Circ Arrhythm Electrophysiol. 2019 Jul;12(7):e006978. doi: 10.1161/CIRCEP.118.006978. Epub 2019 Jun 20. — View Citation
Yoshida K, Liu TY, Scott C, Hero A, Yokokawa M, Gupta S, Good E, Morady F, Bogun F. The value of defibrillator electrograms for recognition of clinical ventricular tachycardias and for pace mapping of post-infarction ventricular tachycardia. J Am Coll Cardiol. 2010 Sep 14;56(12):969-79. doi: 10.1016/j.jacc.2010.04.043. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Performance of in silico derived pace map | The primary outcome measure will be the geometrical distance between the exit site (site of highest correlation) identified from the in silico pace map (created from the collected patient data) and the actual pace map derived from the patient. | At the time of the procedure. |
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