Memorial Hospital Research Laboratories
The Ricardo Otazo Lab
The Ricardo Otazo lab develops novel magnetic resonance imaging (MRI) techniques for cancer applications including fast imaging, motion resistant imaging, quantitative imaging of physical tissue parameters, and real-time MRI-guided radiotherapy using advances in MRI acquisition and computational models.
The lab develops novel magnetic resonance imaging (MRI) techniques to increase imaging speed, improve motion tolerance, image physical tissue parameters, and guide radiotherapy in real-time using advances in MRI acquisition (pulse sequences) and image reconstruction algorithms. Highlights include:
- Non-Cartesian k-space acquisitions for motion-resistant and motion navigated imaging
- Deep learning reconstruction of undersampled k-space data for fast 3D and 4D MRI
- Real-time 4D MRI for radiotherapy guidance
- Fast motion-resistant pediatric MRI with reduced anesthesia
- Deep learning quantification of dynamic contrast-enhanced MRI
- High-resolution distortion-free diffusion MRI in the body
- Fast motion-resistant T1-rho mapping
Feng L, Block KT, Grimm R, Chandarana H, Kim S, Xu J, Axel L, Sodickson DK, Otazo R. Golden-Angle Radial Sparse Parallel MRI: Combination of compressed sensing, parallel imaging and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn Reson Med. 2014 Sep;72(3):707-17 https://pubmed.ncbi.nlm.nih.gov/24142845/
Otazo R, Candès E, Sodickson DK. Low-rank plus sparse matrix decomposition for accelerated dynamic MRI with separation of background and dynamic components. Magn Reson Med. 2015 Mar;73(3):1125-36. https://pubmed.ncbi.nlm.nih.gov/24760724/
Feng L, Tyagi N, Otazo R. MRSIGMA: Magnetic Resonance SIGnature MAtching for real-time volumetric imaging. Magn Reson Med. 2020 Sep;84(3):1280-1292. Epub 2020 Feb 21 https://pubmed.ncbi.nlm.nih.gov/32086858/
Jafari R, Do RKG, LaGratta MD, Fung M, Bayram E, Cashen T, Otazo R. GRASPNET: Fast spatiotemporal deep learning reconstruction of golden-angle radial data for free-breathing dynamic contrast-enhanced magnetic resonance imaging. NMR Biomed. 2023 Mar;36(3):e4861. Epub 2022 Nov 25 https://pubmed.ncbi.nlm.nih.gov/36305619/
Wu C, Krishnamoorthy G, Yu V, Subashi E, Rimner A, Otazo R. 4D lung MRI with high-isotropic-resolution using half-spoke (UTE) and full-spoke 3D radial acquisition and temporal compressed sensing reconstruction. Phys Med Biol. 2023 Jan 27;68(3). https://pubmed.ncbi.nlm.nih.gov/36535035/
Ricardo Otazo, PhD
Vice-Chair for Research, Chief of MRI Physics; Member in Medical Physics and Radiology
- The Ricardo Otazo lab develops novel magnetic resonance imaging (MRI) techniques for cancer applications including fast imaging, motion resistant imaging, quantitative imaging of physical tissue parameters, and real-time MRI-guided radiotherapy using advances in MRI acquisition and computational models.
- [email protected]
- Email Address
- NIH R01 grant to develop real-time 4D MRI for adaptive radiotherapy of pancreatic cancer
- NIH R01 grant to develop quantitative MRI assessment of cervical cancer
- Dr. Otazo received the Distinguished Investigator Award from the Academy of Radiology and Biomedical Imaging Research in December 2022
- Dr. Otazo became a Senior Fellow of the International Society for Magnetic Resonance in Medicine (ISMRM) in June 2021
- The paper on XD-GRASP was the most cited paper in Magnetic Resonance in Medicine (MRM) for 2016 - MRM is the premier journal of MRI research
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Doctors and faculty members often work with pharmaceutical, device, biotechnology, and life sciences companies, and other organizations outside of MSK, to find safe and effective cancer treatments, to improve patient care, and to educate the health care community.
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Ricardo Otazo discloses the following relationships and financial interests:
NYU Langone Health
Intellectual Property Rights
The information published here is for a specific annual disclosure period. There may be differences between information on this and other public sites as a result of different reporting periods and/or the various ways relationships and financial interests are categorized by organizations that publish such data.
This page and data include information for a specific MSK annual disclosure period (January 1, 2022 through disclosure submission in spring 2023). This data reflects interests that may or may not still exist. This data is updated annually.