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Download the internship proposal

Type of internship

Master’s 2 Internship or Final Year of Engineering School

Internship date or duration

6-month internship

Context

Atrial fibrillation (AF) is the most common cardiac arrhythmia and is characterized by complex, disorganized atrial electrical activity leading to irregular heartbeats. With over 37 million people affected worldwide and a sharply increasing incidence, AF is now considered a major public health problem. Indeed, AF is a significant cause of strokes, accounting for up to 20% of cases.

Catheter ablation is a common treatment for patients with AF, targeting specific areas of the atrial myocardium using radiofrequency, cryotherapy, or electroporation to restore normal electrical and mechanical activity in the left atrium. The accurate detection of the substrate responsible for these arrhythmias in the heart muscle – such as fibrosis or fat deposits– is crucial for identifying patients at risk of recurrence after ablation and for improving long-term ablation outcomes.

Computed tomography (CT) and magnetic resonance imaging (MRI) have advanced significantly in identifying the arrhythmogenic substrate in the atrial myocardium, which has a very thin wall (2-3mm). While CT provides 3D imaging of the heart and its walls with fine, isotropic spatial resolution at the cost of radiation exposure, MRI allows for the unique identification of fibrosis and dynamic (strain or deformation) imaging of the heart muscle, albeit with lower resolution and contrast compared to CT. LIB cardiovascular imaging team has been working on these biomarkers, generating 2D imaging maps of left atrial lesions.

Objective

The objective of the current project is to reconstruct interpolated left atrial strain map from multiple MRI views and to fuse such map along with other imaging maps (fibrosis, fat, …) with electrophysiological maps collected during ablation procedure.

To test the developed methodologies, we already have CT, MRI and electrophysiology data acquired from AF patients, (N=100), within the framework of the PHRC CT-AF.

Tasks

This internship will include several steps:
1. Literature review on imaging substrate of AF and fusion between imaging and electrophysiology
2. Initiation to programming into 3D slicer with LIB post-docs and PhD students
3. Development of 3D interpolation algorithm to fuse strain measures performed from multiple MRI views
4. Familiarization with imaging maps in AF patients
5. Development of an algorithm to fuse 3D imaging maps with electrorheology (voltage maps)
6. Analysis of possible correlations between locale voltages and imaging quantitative biomarkers
7. Drafting the final report and presentation for the Master evaluation

Skills

1. Reading and synthesizing scientific documents in English
2. Image processing and AI
3. Basic statistical analyses
4. Programming in Python/Matlab

Compensation

Internship grant

Contact

Nadjia Kachenoura
nadjia.kachenoura[at]inserm.fr