Education

Graduate School
Biomedical Engineering, Cairo University, 2003
Graduate School
Electrical and Computer Engineering, , The Johns Hopkins University, 2006
Graduate School
Electrical and Computer Engineering, The Johns Hopkins University, 2009
Post Graduate School
Postdoctoral Fellow, Radiology, The Johns Hopkins University, 2012

Areas of Interests

Research Interests

Dr. Gabr conducts research in quantitative magnetic resonance imaging (MRI) and spectroscopy (MRS) techniques and their applications in neuroscience. His research interests include fast MRI, patient-adaptive MRI, MR image reconstruction, metabolite quantitation, brain perfusion, image processing, and spectral analysis.

Research Information

**Faculty profiles will only highlight current information (the last three years). Please see the faculty’s CV for more information.

 

PATENTS:

  1. System and method of performing magnetic resonance spectroscopic imaging, US Patent App. 14/006,069, Active.
  2. System and method for adaptive and patient-specific magnetic resonance imaging, US Patent App. 15/373,256, Pending.

 

CURRENT GRANT SUPPORT:

  1. 2 R01 NS055903-10, NIH Peggy Nopolous (PI) 09/01/19-8/31/24
    Growth and development of Striatal-Cerebellum circuitry in subjects at risk for Huntington’s Disease
    Role: Co-Investigator
  2. 1R56NS105857-01, NIH Narayana (PI) 04/01/18-03/31/20
    Predicting contrast enhancement in multiple sclerosis with real time texture analysis
    Role: Co-Investigator
    Funding: $350,000 (DC)
    Major goals: To identify inflammatory lesions in MS without contrast agent.

 

COMPLETED GRANT:

  1. SanBio, Inc. Savitz / Narayana (PI) 09/01/15-06/30/19
    Image Analysis Center
    Role: KP
    Funding: $272,028 (DC)
    Major goals: Provide MRI analysis on the traumatic brain injured patients treated with stem cells as a part of phase 2 clinical trials.
  2. Sunovian/SanBio, Inc. Narayana / Savitz (PI) 11/09/15-10/31/19
    Image Analysis Center
    Role: KP
    Funding: $279,349 (DC)
    Major goals: Provide MRI analysis on the Stroke patients treated with stem cells as a part of phase 2 clinical trials.
  3. UL1 TR000371, NIH/NCATS McPherson (PI) 06/01/16-05/31/17
    Center for Clinical and Translational Sciences
    Role: Co-Investigator
    Major goals: MRI Core Director

 

OTHER AWARDS:

  1. XSEDED BIR180001 Awarded Resources: IU/TACC (Jetstream): 48,972.0 SUs
    PI: Refaat Gabr
    Request: Real-time MRI
    Period: 2018-07-01 – 2019-06-30
    Estimated value of awarded resources: $7,292.

Publications

Publication Information

**Faculty profiles will only highlight current information (the last three years). Please see the faculty’s CV for more information.

 

Refereed Original Articles in Journals

  1. Keser Z*, Hasan KM, Mwangi B, E Gabr R, M Nelson F. Diffusion Tensor Imaging-Defined Sulcal Enlargement Is Related to Cognitive Impairment in Multiple Sclerosis. J Neuroimaging. Wiley Online Library; 2017;27(3):312–7.Gabr RE*, Tefera GB, Allen WJ, Pednekar AS, Narayana PA. GRAPE: a graphical pipeline environment for image analysis in adaptive magnetic resonance imaging. Int J Comput Assist Radiol Surg. 2017;12(3):449–457.
  2. Keser Z, Hasan KM*, Mwangi B, Gabr RE, Steinberg JL, Wilken J, et al. Limbic Pathway Correlates of Cognitive Impairment in Multiple Sclerosis. J Neuroimaging. Wiley Online Library; 2017;27(1):37–42.
  3. Gabr RE*, Pednekar AS, Govindarajan KA, Sun X, Riascos RF, Ramirez MG, et al. Patient-specific 3D FLAIR for enhanced visualization of brain white matter lesions in multiple sclerosis. J Magn Reson Imaging. Wiley Online Library; 2017;46(2):557–564.
  4. Mohamed AS*, Bahig H, Aristophanous M, Blanchard P, Kamal M, Ding Y, Cardenas CE, Brock KK, Lai SY, Hutcheson KA, Phan J, Wang J, Ibbott G, Gabr RE, Narayana PA, Garden AS, Rosenthal DI, Gunn GB, Fuller CD, Prospective in silico study of the feasibility and dosimetric advantages of MRI-guided dose adaptation for human papillomavirus positive oropharyngeal cancer patients compared with standard IMRT. Clinical and Translational Radiation Oncology. 2018; 11(June 2018):11-18.
  5. Gabr RE*, Pednekar AS, Kamali A, Lincoln JA, Nelson FM, Wolinsky JS, Narayana PA. Interleaved susceptibility‐weighted and FLAIR MRI for imaging lesion‐penetrating veins in multiple sclerosis. Magnetic resonance in medicine. 2018 Sep;80(3):1132-7.
  6. Haque ME*, Gabr RE, Zhao X, Hasan KM, Valenzuela A, Narayana PA, et al. Serial quantitative neuroimaging of iron in the intracerebral hemorrhage pig model. J Cereb Blood Flow Metab. 2018; 38(3):375–381.
  7. Gabr RE, El-Sharkawy AM, Schär M*, Panjrath GS, Gerstenblith G, Weiss RG, Bottomley PA. Cardiac work is related to creatine kinase energy supply in human heart failure: a cardiovascular magnetic resonance spectroscopy study. Journal of Cardiovascular Magnetic Resonance. 2018 Dec;20(1):81.
  8. Allen WJ*, Gabr RE, Tefera GB, Pednekar, AS, Vaughn, MW, Narayana, PA. Platform for Automated Real-Time High Performance Analytics on Medical Image Data. J. Biomed. Heal. Informatics. 2018; 22(2):318–324.
  9. Sujit SJ, Coronado I, Kamali A, Narayana PA, Gabr RE*. Automated Image Quality Evaluation of Structural Brain MRI using an Ensemble of Deep Learning Networks. J. Magn. Reson. Imaging 2019; 50(4):1260–1267.
  10. Haque ME*, Gabr RE, Hasan KM, George SD, Arevalo OD, Zha AM, et al. Ongoing Secondary Degeneration of the Limbic System in Patients with Ischemic Stroke: A Longitudinal MRI Study. Front Neurol. Frontiers; 2019;10:154.
  11. Haque ME*, Gbar RE, George SD, Boren SB, Arevalo OD, Alderman S, et al. Serial Cerebral Metabolic Changes in Patients with Ischemic Stroke Treated with Autologous Bone Marrow Derived Mononuclear Cells. Front Neurol. Frontiers; 2019;10:141.
  12. Gabr RE*, Coronado I, Robinson M, Sujit SJ, Datta S, Sun X, Allen WJ, Lublin FD, Wolinsky JS, Narayana PA. Brain and lesion segmentation in multiple sclerosis using fully-convolutional neural networks: A large-scale study. Multiple Sclerosis Journal, 2019, in press.
  13. Varadhan R*, Russ DW, Gabr RE, Huang J, Kalyani RR, Xue Q, Cappola AR, Bandeen-Roche K, Fried LP. Relationship of physical frailty to phosphocreatine recovery in muscle after mild exercise stress in the oldest-old women. Journal of Frailty and Aging. 2019:1-7.
  14. Gabr RE*, Zunta-Soares G, Soares JC, Narayana PA. MRI acoustic noise-modulated computer animations for patient distraction and entertainment with application in pediatric psychiatric patients. Magnetic Resonance Imaging. 2019 Sep 1;61:16-9.
  15. Narayana PA, Coronado I, Sujit SJ, Sun X, Wolinsky JS, Gabr RE. Are multi-contrast magnetic resonance images necessary for segmenting multiple sclerosis brains? A large cohort study based on deep learning. Magnetic Resonance Imaging. 2019. In press.
  16. Narayana PA, Coronado I, Sujit SJ, Wolinsky JS, Lublin FD, Gabr RE. Deep Learning-Based Neural Tissue Segmentation of MRI in Multiple Sclerosis: Effect of Training Set Size. Journal of Magnetic Resonance Imaging. 2019. In press.
  17. Narayana PA, Coronado I, Sujit SJ, Wolinsky JS, Lublin FD, Gabr RE. Deep Learning for Predicting Enhancing Lesions in Multiple Sclerosis from Non-contrast MRI. Radiology. 2019. In press.
    *Corresponding author.

 

Refereed Conference Papers and Abstracts

  1. Haque ME, Gabr RE, Zhao X, Hasan KM, Narayana PA, Savitz SI, et al. Quantitative Serial Neuroimaging of Iron in the Intracerebral Hemorrhage Pig Model. In: 17th International Stroke Conference. Houston, TX, USA; 2017.
  2. Lincoln JA, Freeman L, Staine L, Hasan KM, Gabr R, Narayana PA, Wolinsky JS. Enhanced regional cerebral perfusion following acetazolamide: preliminary results. In: ECTRIMS 2017, Late Breaking News Abstracts. Multiple Sclerosis Journal. Vol. 23. ; 2017. pp. 982–983.
  3. Hasan K, Gabr R, Lincoln J, Narayana P. Toward Real Time Estimation and Quality Assurance for Myelin Water Mapping in the Human Central Nervous System. In: International Society of Magnetic Resonance in Medicine (ISMRM). Honolulu, Hawaii, USA; 2017. p. 4740.
  4. Haque M, Gabr R, Hasan K, Jeevarajan J, Izygon J, Nghiem D, et al. Serial MRI of Lateral Ventricular Enlargement to Measure Rate of Brain Atrophy in Patients with Ischemic Stroke. In: International Society of Magnetic Resonance in Medicine (ISMRM). Honolulu, HI, USA; 2017. p. 4575.
  5. Gabr R, Pednekar A, Govindarajan K, Sun X, Riascos R, Ramírez M, et al. Improving White Matter Lesion Conspicuity in Multiple Sclerosis Using Patient-Specific Optimization of 3D FLAIR. In: International Society of Magnetic Resonance in Medicine (ISMRM). Honolulu, HI, USA; 2017. p. 221.
  6. Allen W, Gabr R, Tefera G, Pednekar A, Liu S, Liu H, et al. Automated Real-Time Quantitative Magnetic Resonance Imaging. In: International Conference on Biomedical and Health Informatics (BHI). Orlando, FL, USA; 2017.
  7. Gabr R, Tefera G, Allen W, Pednekar A, Narayana P. A Graphical Programming Environment for Creating and Executing Adaptive MRI Protocols. In: International Society of Magnetic Resonance in Medicine (ISMRM). Honolulu, HI, USA; 2017. p. 1453
  8. Sujit SJ, Gabr RE, Coronado I, Robinson M, Datta S, Narayana PA. Automated Image Quality Evaluation of Structural Brain Magnetic Resonance Images using Deep Convolutional Neural Networks. In: Cairo International Biomedical Engineering Conference (CIBEC). Vol. 2018.; 2018.
  9. Narayana PA, Coronado I, Robinson M, Sujit SJ, Datta S, Sun X, Lublin FD, Wolinsky JS, Gabr RE. Multimodal MRI Segmentation of Brain Tissue and T2-Hyperintense White Matter Lesions in Multiple Sclerosis using Deep Convolutional Neural Networks and a Large Multi-center Image Database. In: Cairo International Biomedical Engineering Conference (CIBEC). ; 2018.
  10. Gabr RE, Narayana PA. Imaging Intralesional Heterogeneity in Multiple Sclerosis using a T2 Filter. In: Cairo International Biomedical Engineering Conference (CIBEC). Vol. 2018. ; 2018.
  11. Gabr R, He R, Sujit S, Narayana P. A Real-Time Quality Assurance Framework for Structural Brain MRI. In: AAPM 2018, Medical Physics. Vol. 45. ; 2018. pp. E214–E214.
  12. Gabr R, Williams C, He R, Narayana P. Effect of the Classifier Performance Criterion On Image Quality Assessment in MRI. In: AAPM 2018, Medical Physics. Vol 45.; 2018:E215–E215.
  13. Hasan KM, Gabr RE, Lincoln JA, Narayana PA. Novel multi-band accelerated, reference-less, multifaceted icosahedral and multishell diffusion MRI protocol for human whole brain clinical applications. In: International Society of Magnetic Resonance in Medicine (ISMRM). 2018. p. 1672.
  14. Gabr R, El-Sharkawy A, Schär M, Gerstenblith G, Weiss, R, Bottomley, P. Creatine kinase energy supply correlates with mechanical work and efficiency in healthy and failing human heart: a combined noninvasive MRI/MRS study. In: International Society of Magnetic Resonance in Medicine (ISMRM).Vol 2018.; 2018:1087.
  15. Gabr RE, Allen WJ, Tefera GB, Sun X, He R, Kumaravel M, Vaughn MW, Narayana PA. User-defined, scanner-integrated, and real-time MRI image analysis in a cloud-based computing environment. In: International Society of Magnetic Resonance in Medicine (ISMRM).; 2018:4065.
  16. Gabr RE. Correcting T2 Maps Calculated From Dual-Echo Fast Spin Echo MRI for the Effects of K-Space Profile Order and Stimulated Echoes. AAPM, 2019
  17. Sujit S, Gabr R, Coronado I, Narayana P. Detection and Classification of Artifacts in Structural Brain MR Images Using Deep Convolutional Neural Networks. AAPM, 2019
  18. Zandiyeh P, Warth R, Narayana P, Gabr R, Kumaravel M, Lowe W, Harner C, Tashman S. UTE T2* MRI Shows Evidence of Tissue Remodeling in ACL Grafts Between 1 and 9 Months after Surgery. ISB/ASB 2019.
  19. Lincoln JA, Freeman L, Papadimitropoulos G, Charron O, Hasan KM, Gabr RE, Narayana PA, Wolinsky JS. Enhanced Regional Cerebral Perfusion Following Acetazolamide: Preliminary Oral Dose-Escalation Results. ACTRIMS, 2019.
  20. Gabr RE, Narayana PA. Reducing Patient Anxiety in MRI using Acoustic Noise-Modulated Computer Animations: Experience in Pediatric Psychiatric Patients. In: International Society of Magnetic Resonance in Medicine (ISMRM), 2019.
  21. Sujit SJ, Gabr RE, Coronado I, Narayana PA. Cascaded Deep Learning Networks for Automated Image Quality Evaluation of Structural Brain MRI. In: International Society of Magnetic Resonance in Medicine (ISMRM), 2019.
  22. Narayana PA, Coronado I, Datta S, Sujit SJ, Lublin FD, Wolinsky JS, Gabr RE. Deep Learning for Identification of Active Lesions in Multiple Sclerosis Without Administration of Gadolinium Based Contrast Agent. In: International Society of Magnetic Resonance in Medicine (ISMRM), 2019.
  23. Coronado I, Gabr RE, Datta S, Sujit SJ, Lublin FD, Wolinsky JS, Narayana PA. Deep Learning for Characterizing Image Sequence Significance in Brain Tissue Segmentation. In: International Society of Magnetic Resonance in Medicine (ISMRM), 2019.
  24. Tashman S, Zandiyeh P, Warth R, McDermott JD, Narayana PA, Gabr RE, et al. ACL Graft Remodeling Revealed By Serial UTE T2* MRI. In: Orthopedic Research Society (ORS) Annual conference Austin, Texas. 2019.
  25. Haque ME, Hasan KM, George SD, Sitton CW, ArevaloEspejo OD, Boren SB, Alderman S, Vahidy F, Gabr R, Parsha KN, Rosenbaum DP. Autologous Bone Marrow Cells Might Repair Corticospinal Tracts in Stroke Patients. Stroke. 2020 Feb;51(Suppl_1):A9.

 

Book Chapters

  1. El-Sayed H. Ibrahim, Refaat E. Gabr, “MRI Basics” In “Heart Mechanics Magnetic Resonance Imaging: Mathematical Modeling, Pulse Sequences, and Image Analysis”, 2017.
  2. El-Sayed H. Ibrahim, Refaat E. Gabr, Michael Salerno. “Image Acquisition Sequences in Myocardial Tagging” In “Heart Mechanics Magnetic Resonance Imaging: Advanced Techniques, Clinical Applications, and Future Trends”, 2017.

 

Other Professional Communications

  1. “Improving White Matter Lesion Conspicuity in Multiple Sclerosis Using Patient-Specific Optimization of 3D FLAIR,”.ISMRM, Honolulu, HI, USA; 2017. (Oral Presentation).
  2. “A Graphical Programming Environment for Creating and Executing Adaptive MRI Protocols,” ISMRM, Honolulu, HI, USA; 2017. (Poster Presentation)
  3. “Personalized MRI”, Invited talk at the Saudi Scientific Society of Biomedical Engineering, SSSBE. 2017. (Webinar Presentation).
  4. “A Real-Time Quality Assurance Framework for Structural Brain MRI”, AAPM 2018, Nashville, TN. (Poster Presentation)
  5. “Effect of the Classifier Performance Criterion On Image Quality Assessment in MRI”, AAPM 2018, Nashville, TN. (Poster Presentation)
  6. “Reducing Patient Anxiety in MRI using Acoustic Noise-Modulated Computer Animations: Experience in Pediatric Psychiatric Patients”, ISMRM 2019 (Poster Presentation)
  7. “Detection and Classification of Artifacts in Structural Brain MR Images Using Deep Convolutional Neural Networks”, AAPM 2019, San Antonio, TX. (Poster Presentation)
  8. “Correcting T2 Maps Calculated From Dual-Echo Fast Spin Echo MRI for the Effects of K-Space Profile Order and Stimulated Echoes”, AAPM 2019, San Antonio, TX. (Snap Oral Presentation)
  9. “Novel MRI approaches for multiple sclerosis”, department of Diagnostic and Interventional Imaging Research Retreat, 2020

Honors and Awards

**Faculty profiles will only highlight current information (the last three years). Please see the faculty’s CV for more information.

 

Abstract Finalist, Highlights of the Joint Annual Meeting ISMRM-ESMRMB, 2018