Greg Zaharchuk

Professor of Radiology (Neuroimaging and Neurointervention)

Clinical Focus

Diagnostic Neuroimaging
Diagnostic Radiology

Academic Appointments

Professor, Radiology
Member, Bio-X
Faculty Affiliate, Institute for Human-Centered Artificial Intelligence (HAI)
Member, Wu Tsai Neurosciences Institute

Honors & Awards

Fellow, American Institute for Medical and Biological Engineering (AIMBE) (2020)
Distinguished Investigator Award, The Academy for Radiology & Biomedical Imaging Research (2016)
Scholar Award, Neuroradiology Education and Research Foundation (2009)
Executive Council Award, American Roentgen Ray Society (2006)
Resident/Fellow Research Award, Radiological Society of North America (2002)
Young Investigator Award in Stroke, American Heart Association (1998)
Young Investigator Finalist, International Society of Magnetic Resonance in Medicine (1998)
Phi Beta Kappa, Stanford University (1989)
Valedictorian, Materials Science and Engineering, Stanford University (1989)
Tau Beta Pi, Stanford University (1987)

Boards, Advisory Committees, Professional Organizations

President-Elect, American Society of Functional Neuroradiology (2020 - Present)
Deputy Editor, Journal of Magnetic Resonance Imaging (2018 - Present)
Editorial Board, Radiology (2016 - Present)
Scientific Program Committee, Neuroradiology/Head & Neck Subcommittee, Radiological Society of North America (RSNA) (2012 - Present)
Annual Meeting Program Committee, International Society of Magnetic Resonance in Medicine (2012 - 2015)
Special Consultant to the Editor - Physics, American Journal of Neuroradiology (2011 - Present)

Professional Education

Board Certification: American Board of Radiology, Neuroradiology (2023)
Board Certification: American Board of Radiology, Diagnostic Radiology (2023)
Fellowship: University of California San Francisco (2006) CA
Residency: University of California San Francisco (2005) CA
Internship: Robert Wood Johnson University Hospital (2001) NJ
MD, Harvard Medical School, Medicine (2000)
PhD, Harvard University / Massachusetts Institute of Technology, Applied Physics (HST Program) (1999)
BS & BA, Stanford, Materials Science & Engineering/German Studies (1990)

Patents

Greg Zaharchuk, Enhao Gong, John Pauly. "United States Patent submitted Improving Quality of Medical Images Using Multi-Contrast and Deep Learning", Leland Stanford Junior University, Mar 6, 2017
Greg Zaharchuk, Roland Bammer. "United States Patent 8,929,972 Arterial Spin Labeling MRI-based Correction Factor for Improving Quantitative Accuracy of Blood Flow and Volume Images", Leland Stanford Junior University,, Jan 6, 2015
Greg Zaharchuk, Jean Brittain. "United States Patent 7,064,545 Method and Apparatus of Background Suppression in MR imaging using Spin Locking", General Electric Company, The Regents Of The University Of California, Jun 20, 2006
Kookrin Char, Stephen M. Garrison, Nathan Newman, Greg Zaharchuk. "United States Patent 5,157,466 Grain Boundary Junctions in High Temperature Superconductor Films", Conductus, Inc., Oct 20, 1992
Reed Busse, John Pauly, Greg Zaharchuk. "United States Patent 7,276,904 Method for Generating T1-weighted Magnetic Resonance Images and Quantitative T1 Maps", Leland Stanford Junior University, Oct 2, 0007

Contact

Academic gregz@stanford.edu Tel: (650) 736-6172

Alternate Contact Susan Mir Administrative Associate susanmir@stanford.edu Tel: 650-736-6172

Clinical (Primary)

This is the primary clinic for this clinical provider. For additional clinical locations and information, please visit the link(s) listed below in the 'Additional Clinical Info' section.

Neuroradiology 1201 Welch Rd Rm PS04 MC 5488 Stanford CA 94305 Tel: (650) 723-5393 Fax: (650) 723-9222

Additional Clinical Info

Current Research and Scholarly Interests

Improving medical image quality using deep learning artificial intelligence
Imaging of cerebral hemodynamics with MRI and CT
Noninvasive oxygenation measurement with MRI
Clinical imaging of cerebrovascular disease
Imaging of cervical artery dissection
MR/PET in Neuroradiology
Resting-state fMRI for perfusion imaging and stroke

Clinical Trials

Quantifying Collateral Perfusion in Cerebrovascular Disease-Moyamoya Disease and Stroke Patients Not Recruiting
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Quantifying Collateral Perfusion in Cerebrovascular Disease-Moyamoya disease and stroke patients

Stanford is currently not accepting patients for this trial. For more information, please contact Sandra Dunn, 650-724-8278.

Lead Sponsor
- Stanford University
Stanford Investigators
- Greg Zaharchuk
- Huy M. Do, MD
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Imaging Collaterals in Acute Stroke (iCAS) Not Recruiting
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Stroke is caused by a sudden blockage of a blood vessel that delivers blood to the brain. Unblocking the blood vessel with a blood clot removal device restores blood flow and if done quickly may prevent the disability that can be caused by a stroke. However, not all stroke patients benefit from having their blood vessel unblocked. The aim of this study is to determine if special brain imaging, called MRI, can be used to identify which stroke patients are most likely to benefit from attempts to unblock their blood vessel with a special blood clot removal device. In particular, we will assess in this trial whether a noncontrast MR imaging sequence, arterial spin labeling (ASL), can demonstrate the presence of collateral blood flow (compared with a gold standard of the angiogram) and whether it is useful to predict who will benefit from treatment.

Stanford is currently not accepting patients for this trial. For more information, please contact Gregory Zaharchuk, MD, 650-723-4448.

Lead Sponsor
- Stanford University
Stanford Investigators
View full details
Computed Tomography Perfusion (CTP) to Predict Response to Recanalization in Ischemic Stroke Project (CRISP) Not Recruiting
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The overall goal of the CTP to predict Response to recanalization in Ischemic Stroke Project (CRISP) is to develop a practical tool to identify acute stroke patients who are likely to benefit from endovascular therapy. The project has two main parts. During the first part, the investigators propose to develop a fully automated system (RAPID) for processing of CT Perfusion (CTP) images that will generate brain maps of the ischemic core and penumbra. There will be no patient enrollment in part one of this project. During the second part, the investigators aim to demonstrate that physicians in the emergency setting, with the aid of a fully automated CTP analysis program (RAPID), can accurately predict response to recanalization in stroke patients undergoing revascularization. To achieve this aim the investigators will conduct a prospective cohort study of 240 consecutive stroke patients who will undergo a CTP scan prior to endovascular therapy. The study will be conducted at four sites (Stanford University, St Luke's Hospital, University of Pittsburgh Medical Center, and Emory University/Grady Hospital). Patients will have an early follow-up MRI scan within 12+/-6 hours to assess reperfusion and a late follow-up MRI scan at day 5 to determine the final infarct.

Stanford is currently not accepting patients for this trial. For more information, please contact Stephanie M Kemp, BS, 650-723-4481.

Lead Sponsor
- Stanford University
Stanford Investigators
View full details

Stanford Advisees

Postdoctoral Faculty Sponsor
Donghoon Kim, Yongkai Liu
Doctoral Dissertation Advisor (AC)
Ashwin Kumar

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Clinics & Services

Research Resources

Professional Training

Education Resources

Greg Zaharchuk

Professor of Radiology (Neuroimaging and Neurointervention)

Lead Sponsor

Stanford Investigators

Lead Sponsor

Stanford Investigators

Lead Sponsor

Stanford Investigators

2024-25 Courses

2023-24 Courses

2022-23 Courses

2021-22 Courses

Stanford Advisees