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The investigator's project proposes the development of a 3D hybrid guidance system which has the aim of avoidance of scar and septal perforation through targeted lead deployment via a personalised septal real time image overlay onto x-ray fluoroscopy imaging during left bundle branch pacing. The investigators hypothesise that the use of cardiac anatomy and myocardial scar distribution derived from cardiac magnetic resonance imaging (MRI) as well as 3D position of the pacing lead, may improve LBBAP lead deployment success and improve clinical outcomes by guiding the physician towards optimal lead positioning.
The study will use anonymised imaging data from the TACTIC-CRT (IRAS 250715) , Cardiac CT to guide Cardiac Resynchronisation Therapy (CRT) implantation (IRAS 150161) study (IRAS 150161) and anonymous cardiac MRI, CT and fluoroscopy imaging data from patients who underwent LBBA pacing to develop a 3D hybrid guidance system using machine learning methods. The developed 3D hybrid guidance system will be tested on anonymised retrospectively collected x-ray fluoroscopy images from patients who underwent LBBAP and had a cardiac MRI. The 3D hybrid guidance system will collect data from the retrospective anonymised X-ray fluoroscopic images, detect the pacing lead and reconstruct the 3D position of the pacing lead and test the accuracy of the 3D hybrid guidance system.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Left bundle branch pacing group | Patients who underwent left bundle branch pacing |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Machine learning with artificial intelligence software program | Other | This is a retrospective observational study using cardiac MRI, cardiac CT and x-ray fluoroscopy images to develop a 3D hybrid guidance system with the use of deep learning methods. |
| Measure | Description | Time Frame |
|---|---|---|
| Detection of the position of the left bundle branch area on x-ray fluoroscopy | The accuracy of left bundle branch area detection will be measured as intersection-over-union (IoU) with the use of a convolutional neural network | 12 months |
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Inclusion Criteria:
Exclusion Criteria:
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Anonymised images from patients who took part in the TACTIC-CRT (IRAS 250715) and Cardiac CT to guide Cardiac Resynchronisation Therapy (CRT) implantation (IRAS 150161) or who received left bundle branch pacing and had a cardiac MRI
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Aldo Rinaldi, MD, MBBS, FRCP, FHRS | Contact | 0207 188 9275 | aldo.rinaldi@gstt.nhs.uk | |
| Sandra Howell, MBBS, MSc, MSc | Contact | 0207 188 9275 | sandra.howell@kcl.ac.uk |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Imperial College Nhs Healthcare Trust | London | W12 0HS | United Kingdom |
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| ID | Term |
|---|---|
| D006333 | Heart Failure |
| D001919 | Bradycardia |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D001145 | Arrhythmias, Cardiac |
| D010335 | Pathologic Processes |
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| ID | Term |
|---|---|
| D000069550 | Machine Learning |
| ID | Term |
|---|---|
| D001185 | Artificial Intelligence |
| D000465 | Algorithms |
| D055641 | Mathematical Concepts |
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| D013568 |
| Pathological Conditions, Signs and Symptoms |