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Nola Hylton

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Nola Hylton
Born
Mount Vernon
Alma materMassachusetts Institute of Technology
Stanford University
Known forBreast MRI
Scientific career
InstitutionsUniversity of California, San Francisco

Nola M. Hylton (born 1957) is a Professor of Radiology and Director of the Breast Imaging Research Group at the University of California, San Francisco. She pioneered the usage of magnetic resonance imaging for the detection, diagnosis, and staging of Breast Cancer by using MRIs to locate tumors and characterize the surrounding tissue.

Early life and education

Hylton was born in Mount Vernon, New York in 1957. Hylton studied in Mount Vernon, New York where she was one of the only black students in her physics class.[1] Hylton studied chemical engineering at Massachusetts Institute of Technology in 1979.[2][3] She was an undergraduate fellow at Bell Labs in 1975. She joined Stanford University for her PhD, earning a doctorate in applied physics in 1985, becoming one of a handful of black women with doctorates in that period.[1][4] Here she worked on analytical techniques to evaluate NMR imaging contrast, which is used in assessing MRI's.[5] She developed a hierarchical processing algorithms to characterise the tissues.[6] In her early career she was part of an international trial that compared two breast cancer screening methods, using MRI and mammographies.[7] Hylton was appointed group leader of the working group on Breast MRI systems.[8]

Research and career

Hylton designs MRI biomarkers, which allow Hylton to evaluate how breast cancer responds to treatment.[9] In the 2013 Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And molecular analysis (I-SPY TRIAL), Hylton developed workstations that allow physicians to perform analysis of breast MRI scans.[10][11][12] Hylton worked with Hologic to develop software to measure the volume of tumours and analyse images automatically. She expanded the software to include diffusion-weighted imaging (DW-MRI), which helps assess the response of tumours in patients undergoing preoperative chemotherapy.[9] She was principal investigator for ACRIN 6657 and 6698 (I-SPY 2).[13][14]

She is particularly interested in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).[15] The hologic software DCE-MRI allowed Hylton to monitor breast cancer response in real-time.[16][17] The software was FDA IDE approved in 2010.[16] Hylton demonstrated in 2010 that MRI could be used to predict how women will respond to neoadjuvant therapy.[18][19] DCE-MRI and DW-MRI provide extra functional information as the MRI becomes sensitive to the vascularity of tumours.[20] Her recent work has identified that PET and MRI can be used to personalise the treatment of breast cancer.[21]

Hylton served as the principal investigator for the National Cancer Institute International Breast MRI Consortium. She serves on the University of California, San Francisco Diversity and Inclusion committee.[22]

Her current research focuses on the development and evaluation of MRI techniques for characterizing breast cancer and assessing/monitoring their responses to treatment.

Awards and honours

References

  1. ^ a b "These Shocking Charts Show How Hard It Is for Black Women in Science". mic.com. Retrieved 2019-02-07.
  2. ^ "Nola Hylton | UCSF Profiles". profiles.ucsf.edu. Retrieved 2019-02-07.
  3. ^ "Chemical Engineering Alumni/ae News" (PDF). MIT. Retrieved 2019-02-07.
  4. ^ Ph.D, Omoviekovwa A. Nakireru (2010-04-19). The Physics Queen: Authorized Biography of Dr. Elvira Louvenia Williams. Xlibris Corporation. ISBN 9781450080965.
  5. ^ Hylton, N. M.; Ortendahl, D. A.; Kaufman, L.; Crooks, L. E.; Feinberg, D. A. (February 1985). "Analytical Techniques for Post-Imaging Evaluation of NMR Tissue Contrast". IEEE Transactions on Nuclear Science. 32 (1): 803–806. Bibcode:1985ITNS...32..803H. doi:10.1109/TNS.1985.4336944. ISSN 0018-9499.
  6. ^ Ortendahl, Douglas A.; Hylton, Nola M.; Kaufman, Leon; Crooks, Lawrence E. (1985). "Tissue Characterization Using Intrinsic NMR Parameters and a Hierarchical Processing Algorithm". IEEE Transactions on Nuclear Science. 32 (1): 875–879. Bibcode:1985ITNS...32..875O. doi:10.1109/tns.1985.4336958. ISSN 0018-9499.
  7. ^ "International Trial Finds Benefits of Breast MRI in Women at High Risk". www.radiologyinfo.org. Retrieved 2019-02-07.
  8. ^ Hylton, Nola (1999). "Dedicated Breast MRI Systems Working Group Report". Journal of Magnetic Resonance Imaging. 10 (6): 1006–1009. doi:10.1002/(SICI)1522-2586(199912)10:6<1006::AID-JMRI18>3.0.CO;2-5. ISSN 1522-2586.
  9. ^ a b Newitt, David; Hylton-Watson, Nola. "Real-time In Vivo MRI Biomarkers for Breast Cancer Pre-Operative Treatment Trials". Grantome.
  10. ^ Hylton, Nola M.; Blume, Jeffrey D.; Bernreuter, Wanda K.; Pisano, Etta D.; Rosen, Mark A.; Morris, Elizabeth A.; Weatherall, Paul T.; Lehman, Constance D.; Newstead, Gillian M.; Polin, Sandra; Marques, Helga S.; Esserman, Laura J.; Schnall, Mitchell D.; ACRIN 6657 Trial Team I-SPY 1 TRIAL Investigators (2012). "Locally Advanced Breast Cancer: MR Imaging for Prediction of Response to Neoadjuvant Chemotherapy—Results from ACRIN 6657/I-SPY TRIAL - Dimensions". Radiology. 263 (3): 663–672. doi:10.1148/radiol.12110748. PMC 3359517. PMID 22623692. Retrieved 2019-02-07.{{cite journal}}: CS1 maint: numeric names: authors list (link)
  11. ^ "The I-SPY Clinical Trials". www.ispytrials.org. Retrieved 2019-02-07.
  12. ^ "ISPY1 - The Cancer Imaging Archive (TCIA) Public Access - Cancer Imaging Archive Wiki". wiki.cancerimagingarchive.net. Retrieved 2019-02-07.
  13. ^ Hylton, Nola M.; Blume, Jeffrey D.; Bernreuter, Wanda K.; Pisano, Etta D.; Rosen, Mark A.; Morris, Elizabeth A.; Weatherall, Paul T.; Lehman, Constance D.; Newstead, Gillian M. (June 2012). "Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy--results from ACRIN 6657/I-SPY TRIAL". Radiology. 263 (3): 663–672. doi:10.1148/radiol.12110748. ISSN 1527-1315. PMC 3359517. PMID 22623692.
  14. ^ Esseman, L.; L'Heureux, D. Z.; Kim, E.; Rosen, M.; Partridge, S. C.; Hylton, N. M. (2011-12-15). "OT2-03-06: ACRIN 6698 MR Imaging Biomarkers for Assessment of Breast Cancer Response to Neoadjuvant Chemotherapy: A Sub-Study of the I-SPY 2 TRIAL (Investigation of Serial Studies To Predict Your Therapeutic Response with Imaging And moLecular Analysis)". Cancer Research. 71 (24 Supplement): OT2–03–06–OT2–03–06. doi:10.1158/0008-5472.SABCS11-OT2-03-06. ISSN 0008-5472.
  15. ^ Hylton, Nola (2006-07-10). "Dynamic contrast-enhanced magnetic resonance imaging as an imaging biomarker". Journal of Clinical Oncology. 24 (20): 3293–3298. doi:10.1200/JCO.2006.06.8080. ISSN 1527-7755. PMID 16829653.
  16. ^ a b "Nola M. Hylton, PhD | UCSF Helen Diller Family Comprehensive Cancer Center". cancer.ucsf.edu. Retrieved 2019-02-07.
  17. ^ "Our Calling". UCSF Radiology. Retrieved 2019-02-07.
  18. ^ Crees, Alex (2015-03-27). "MRI may predict chemotherapy effectiveness early in breast cancer patients". Fox News. Retrieved 2019-02-07.
  19. ^ "Breast MRI Best at Tracking Response to Chemo: Study". Consumer HealthDay. Retrieved 2019-02-07.
  20. ^ "Breast Cancer Response to NAC: How Reliable is MRI?" (PDF). ISMRM. Retrieved 2019-02-07.
  21. ^ "PET and MRI Radiomic Features Can Help Personalize Breast Cancer Diagnosis & Treatment". UCSF Radiology. 2018-10-10. Retrieved 2019-02-07.
  22. ^ "Commitment to Diversity". UCSF Radiology. 2016-08-09. Retrieved 2019-02-07.
  23. ^ "ACRIN 6657" (PDF). ACRIN. Retrieved 2019-02-07.
  24. ^ ""Ultimate Think Tank" Next Step in Breast Cancer Research from Susan G. Komen for the Cure®". www.businesswire.com. 2010-06-02. Retrieved 2019-02-07.
  25. ^ "UCSF Radiologists Named Distinguished Investigators of the Academy of Radiology Research!". UCSF Radiology. 2013-07-08. Retrieved 2019-02-07.
  26. ^ admin (2015-01-31). "2013 Distinguished Investigators Award". The Academy for Radiology & Biomedical Imaging Research. Retrieved 2019-02-07.
  27. ^ admin. "2017 Fellows of the Society". ISMRM. Retrieved 2019-02-07.
  28. ^ "Nola Hylton". www.nsbp.org. Retrieved 2019-02-07.
  29. ^ "Awards and Distinctions". www.sbi-online.org. Retrieved 2019-02-07.
  30. ^ "Highlights from UCSF Radiology at RSNA 2018". UCSF Radiology. 2018-12-05. Retrieved 2019-02-07.
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