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Nader S. Metwalli, Ph.D.

Nader Metwalli.
Scientific Focus Areas: Biomedical Engineering and Biophysics, Clinical Research

Professional Experience

  • Ph.D., Bioengineering (major) and Electrical Engineering (minor), The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
  • M.S., Biomedical Engineering (major), Faculty of Engineering, Cairo University, Giza, Egypt
  • B.S., Biomedical Engineering, Faculty of Engineering, Cairo University, Giza, Egypt

Current Research

The purpose behind my research from the beginning of my career has been the use of MRI to come up with and develop non-invasive imaging biomarkers to characterize anatomical as well as physiologically associated changes in diseased human organs.

Our current research in our lab focuses on discovery and development of quantifiable non-invasive MRI biomarkers through MR pulse sequence development and image analysis to characterize tissue changes in the liver and kidney resulting from metabolic disorders. Our long-term goal is to identify quantifiable non-invasive MR biomarkers that are consistently reproducible in characterizing fibrosis and inflammation in the liver and kidney to ultimately replace the need for invasive biopsy procedures. We are also actively applying machine learning techniques in order to accelerate the MR image acquisition and analysis processes to minimize time spent by patients inside the MR scanner.

Select Publications

Single Breath-Hold 3-Dimensional Magnetic Resonance Elastography Depicts Liver Fibrosis and Inflammation in Obese Patients.
Darwish OI, Gharib AM, Jeljeli S, Metwalli NS, Feeley J, Rotman Y, Brown RJ, Ouwerkerk R, Kleiner DE, Stäb D, Speier P, Sinkus R, Neji R.
Invest Radiol (2023 Jun 1) 58:413-419. 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
View More Publications

Research in Plain Language

Our team is trying to come up with and develop quantitative and reproducible non-invasive measures from MRI to improve diagnosis and follow-up experiences for patients with chronic liver and kidney disease. We also look for ways to apply artificial intelligence and machine learning techniques in our work to also improve patient experiences.

Last Reviewed June 2024