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Nola Hylton, PhD

Nola Hylton, PhD

  • Professor, School of Medicine, Radiology

Contact Information

550 16th Street, #7206
San Francisco, CA 94158
Fax: 415-885-3884
[email protected]
Orchid: Orchid 0000-0002-6747-1662
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Nola Hylton, PhD, is a Professor in Residence in the Department of Radiology and Biomedical Imaging, and Director of the Breast Imaging Research Group at the University of California, San Francisco. Dr. Hylton received her BS in Chemical Engineering from the Massachusetts Institute of Technology in Cambridge, Massachusetts in 1979, and she obtained her PhD in Applied Physics from Stanford University, California in 1985.

Dr. Hylton has been integrally involved in the development of magnetic resonance imaging for the detection, diagnosis, and staging of breast cancer. Dr. Hylton is an internationally known leader in the field of breast MRI for more than 20 years. Her search has addressed the clinical optimization and evaluation of breast MRI technology. Her current research program focuses on the development and clinical evaluation of MRI techniques for characterizing breast cancers and assessing their response to treatment. Her laboratory collaborates closely with a multi-disciplinary team of radiologists, surgeons, oncologists, and science researchers nation wide. This is to optimize MRI techniques for the clinical management of breast cancer patients.

Dr. Hylton is among the first group of scholars named the Susan G. Komen for the Cure's Scientific Advisory Council. She served as co-leader for the DHHS office of Women's Health International Working Group where she identified and addressed barriers to clinical dissemination of breast MRI. She also served as the institutional Principal Investigator of the NCI International Breast MRI Consortium, which is the first large multi-center clinical trial evaluating breast MRI for breast cancer diagnosing and staging.

Dr. Hylton has over 80 published research articles, and she has written 13 book chapters and over 130 abstracts.

Expertise:
Breast Imaging

Specialty:
Breast cancer imaging, breast MRI

Professional Interests:
Breast cancer, magnetic resonance imaging, medical imaging, breast cancer detection and diagnosis, treatment assessment, optical imaging, molecular imaging, functional imaging, small animal imaging

Education and Training:
• Bachelor of Science: Massachusetts Institute of Technology (MIT), Cambridge - Chemical Engineering
• Doctor of Philosophy: Stanford University, California - Applied Physics
  Award  
  Confired By    
  Date    
  • Distinguished Investigator
  • Academy of Radiology Research
  • 2013
  • Cure Scholar Award
  • Komen
  • 2010
  • Scientific Advisory Council
  • Susan G. Komen for the Cure's
  • 2010
  • Research Scholar
  • American Cancer Society
  • 2003
  • Outstanding Contribution Award
  • American College of Radiology Imaging Network
  • 2003
  • Editor's Recognition Award with Distinction
  • Radiology
  • 1987 - 1988
  • Graduate Professional Opportunities Program Fellowship
  • Stanford University
  • 1979
  • Undergraduate Fellowship
  • Bell Telephone Laboratories
  • 1975
  • Dr. Hylton, is an imaging scientist and breast cancer researcher with broad experience in the area of biomedical research. The goal of her interdisciplinary program is to develop imaging based biomarkers that can be used in combination with clinical and molecular information to individualize treatment strategies for patients with early breast cancer. She started her career developing the sequences and software that created breast MRI and has developed functional tumor volume (FTV), which is qualified as a biomarker for decision making and is the source of the longitudinal model for the adaptive design of I-SPY2. She is the imaging leader and co-PI of the I-SPY2 NCI Program project with Dr. Esserman with whom she has collaborated for 27 years and has been continuously funded by NCI for over 25 years. 

    Opportunities include optimization of imaging biomarkers using existing and newly developed imaging assessment to predict response and submit an Investigational Device Exemption to allow their use for clinical decision making. As well, trainees can harness national imaging networks (Cancer Imaging Atlas and the Quantitative Imaging Network) to develop imaging repositories to advance both translational and regulatory science and to better incorporate imaging science into the conduct of clinical trials and to be the catalyst for innovation and change,

    Data provided by UCSF Profiles, powered by CTSI
    ORCID iD: 0000-0002-6747-1662 Additional info
    • Real-time In Vivo MRI Biomarkers for Breast Cancer Pre-Operative Treatment Trials
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      Apr 2008
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      Jun 2021
      Principal Investigator
    • Quantitative Imaging for Assessing Breast Cancer Response to Treatment
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      Sep 2011
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      Aug 2016
      Principal Investigator
    • MRI For Staging DCIS and Assessing Response to Treatment
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      Aug 2006
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      Jul 2013
      Principal Investigator
    • NMR Imaging and Spectroscopy
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      Jun 1993
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      May 2013
      Co-Investigator
    • Anatomic and Biologic Staging of Breast Disease with MRI
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      Jan 1997
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      Feb 2012
      Principal Investigator
    • Mechanism-Based Evaluations of ErbB-Targeted Agents
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      Sep 2001
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      Dec 2008
      Co-Investigator
    Data provided by UCSF Profiles, powered by CTSI
    MOST RECENT PUBLICATIONS FROM A TOTAL OF 188
    Data provided by UCSF Profiles, powered by CTSI
    1. Onishi N, Bareng TJ, Gibbs J, Li W, Price ER, Joe BN, Kornak J, Esserman LJ, Newitt DC, Hylton NM, I-SPY 2 Imaging Working Group, I-SPY 2 Investigator Network. Effect of Longitudinal Variation in Tumor Volume Estimation for MRI-guided Personalization of Breast Cancer Neoadjuvant Treatment. Radiol Imaging Cancer. 2023 07; 5(4):e220126. View in PubMed
    2. Yu K, Basu A, Yau C, Wolf DM, Goodarzi H, Bandyopadhyay S, Korkola JE, Hirst GL, Asare S, DeMichele A, Hylton N, Yee D, Esserman L, van 't Veer L, Sirota M. Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes. Front Oncol. 2023; 13:1192208. View in PubMed
    3. Arasu VA, Habel LA, Achacoso NS, Buist DSM, Cord JB, Esserman LJ, Hylton NM, Glymour MM, Kornak J, Kushi LH, Lewis DA, Liu VX, Lydon CM, Miglioretti DL, Navarro DA, Pu A, Shen L, Sieh W, Yoon HC, Lee C. Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study. Radiology. 2023 06; 307(5):e222733. View in PubMed
    4. Magbanua MJM, Brown Swigart L, Ahmed Z, Sayaman RW, Renner D, Kalashnikova E, Hirst GL, Yau C, Wolf DM, Li W, Delson AL, Asare S, Liu MC, Albain K, Chien AJ, Forero-Torres A, Isaacs C, Nanda R, Tripathy D, Rodriguez A, Sethi H, Aleshin A, Rabinowitz M, Perlmutter J, Symmans WF, Yee D, Hylton NM, Esserman LJ, DeMichele AM, Rugo HS, van 't Veer LJ. Clinical significance and biology of circulating tumor DNA in high-risk early-stage HER2-negative breast cancer receiving neoadjuvant chemotherapy. Cancer Cell. 2023 06 12; 41(6):1091-1102.e4. View in PubMed
    5. Chitalia R, Miliotis M, Jahani N, Tastsoglou S, McDonald ES, Belenky V, Cohen EA, Newitt D, Van't Veer LJ, Esserman L, Hylton N, DeMichele A, Hatzigeorgiou A, Kontos D. Radiomic tumor phenotypes augment molecular profiling in predicting recurrence free survival after breast neoadjuvant chemotherapy. Commun Med (Lond). 2023 Mar 30; 3(1):46. View in PubMed
    6. View All Publications

     

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