Student Projects

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LGE CMR imaging is the clinical gold standard for visualizing myocardial fibrosis. The distribution and extent of scar provide important diagnostic and prognostic information in patients with cardiomyopathy. Cardiomyopathies are a heterogeneous group of myocardial diseases, many of which have a genetic basis. Pathogenic variants in genes such as _TTN_, _DSP_, and _MYH7_ are associated with distinct cardiomyopathy phenotypes, including dilated and hypertrophic forms [1-5]. Emerging evidence suggests that different genetic variants may be associated with characteristic scar patterns visible on LGE imaging. However, the extent to which these patterns can be used to identify genotypes remains unclear. In this project, the student will investigate genotype-phenotype relationships using a dataset of LGE CMR images, scar segmentations, and genetic information. After reviewing the relevant literature, the student will develop and evaluate machine learning models to predict the presence of selected disease-causing genetic variants from imaging data. Potential approaches include convolutional neural networks (CNNs), graph neural networks (GNNs), autoencoders, or other deep learning architectures. The project offers hands-on experience in medical image analysis, machine learning, and cardiovascular imaging. **Prerequisites:** - Strong interest in machine learning and medical data analysis - Strong Python programming skills - Familiarity with deep learning frameworks (preferably PyTorch) - Basic knowledge of image processing **References:** [1] de Frutos F, Ochoa JP, Fernández AI, et al. Late gadolinium enhancement distribution patterns in non-ischaemic dilated cardiomyopathy: genotype-phenotype correlation. Eur Heart J Cardiovasc Imaging. 2023;25(1):75-85. doi:10.1093/ehjci/jead184 [2] Castrichini M, De Luca A, De Angelis G, et al. Magnetic resonance imaging characterization and clinical outcomes of dilated and arrhythmogenic left ventricular cardiomyopathies. J Am Coll Cardiol. 2024;83(19):1841-1851. doi:10.1016/j.jacc.2024.02.041 [3] Akhtar MM, Lorenzini M, Cicerchia M, Ochoa JP, Morris Hey T, Sabater Molina M, et al. Clinical phenotypes and prognosis of dilated cardiomyopathy caused by truncating variants in the TTN gene. Circ Heart Fail. 2020;13(10):e006832. doi:10.1161/CIRCHEARTFAILURE.119.006832 [4] Smith ED, Lakdawala NK, Papoutsidakis N, Aubert G, Mazzanti A, McCanta AC, et al. Desmoplakin cardiomyopathy, a fibrotic and inflammatory form of cardiomyopathy distinct from typical dilated or arrhythmogenic right ventricular cardiomyopathy. Circulation. 2020;141(23):1872-1884. doi:10.1161/CIRCULATIONAHA.119.044934 [5] Domínguez F, Cuenca S, Bilińska Z, Toro R, Villard E, Barriales-Villa R, et al. Dilated cardiomyopathy due to BLC2-associated athanogene 3 (BAG3) mutations. J Am Coll Cardiol. 2018;72(20):2471-2481. doi:10.1016/j.jacc.2018.08.2181

Isabel Margolis (margolis@biomed.ee.ethz.ch)