- M.H.Sc., Clinical Research, School of Medicine, Duke University, Durham, NC, USA, 2016
- Ph.D., Electrical and Computer Engineering Department, Johns Hopkins University, Baltimore, MD, USA, 2007
- M.Sc., Electrical and Computer Engineering Department, Johns Hopkins University, Baltimore, MD, USA, 2003
- M.Sc., Biomedical Engineering Department, Cairo University, Cairo, Egypt, 2000
- B.S., Biomedical Engineering Department, Cairo University, Cairo, Egypt, 1997
To assess and understand early manifestations of cardiovascular and metabolic diseases in relation with obesity, and other systemic metabolic, inflammatory, and immunodeficiency diseases from radiology and biomedical engineering perspectives.
Developing MRI and image processing techniques to improve direct visualization of the coronary arterial wall and plaques, and cardiac function to provide tools for study and for eventual diagnostic use in multi-organ assessment of cardiovascular disease. These techniques help moving toward the goal of establishing techniques and parameters for early detection based on up-stream systemic abnormalities.
Applying our Research
The tools developed and knowledge gained from our research may tell us more about possible early warning signs that may help us save patients before obesity causes irreparable damage and how to guide life-saving interventions.
Need for Further Study
The interplay between diseases of multiple organs with common biological pathways underlies the need for a modern systems approach to investigation and diagnosis. This is particularly true in cardiovascular disease (CVD) where early detection remains a major challenge particularly in response to obesity, diabetes, and metabolic disorders. A multi-organ multimodality imaging approach holds greater opportunity for early detection of CVD through improved assessment and understanding of the effects of deregulation of metabolism, inflammation and immunity that manifest in CVD. This is the intent for future investigations of atherosclerosis in obesity and metabolic syndrome as they are presenting a major and epidemic risk factor for CVD. This approach promises even greater advances in early pre-symptomatic detection and prevention of the substantial downstream medical consequences of these precursor conditions.
- Reduced coronary artery luminal area in pheochromocytoma and paraganglioma patients.
- Nazari MA, Abd-Elmoniem KZ, Jha A, Matta J, Talvacchio S, Charles K, Feeley J, Patel M, Feelders R, Pacak K, Gharib AM.
- J Endocrinol Invest (2023 Jul) 46:1483-1487. Abstract/Full Text
- Native-resolution myocardial principal Eulerian strain mapping using convolutional neural networks and Tagged Magnetic Resonance Imaging.
- Yassine IA, Ghanem AM, Metwalli NS, Hamimi A, Ouwerkerk R, Matta JR, Solomon MA, Elinoff JM, Gharib AM, Abd-Elmoniem KZ.
- Comput Biol Med (2022 Feb) 141:105041. Abstract/Full Text
Research in Plain Language
We use medical imaging modalities such as magnetic resonance imaging and computerized tomography, as well as engineering, artificial intelligence, and computer programming tools to develop new liver and cardiovascular imaging techniques, software, and statistical analysis tools in the field of cardiovascular and metabolic imaging to explore novel image-based risk factors that may help us understand how cardiovascular disease is associated with obesity and other metabolic diseases.