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Kaggie JD, Deen S, Kessler DA, et al. Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T. IEEE Trans Radiat Plasma Med Sci. 2019;3(4):509-515doi: 10.1109/TRPMS.2019.2905366.
Kaggie, J. D., Deen, S., Kessler, D. A., McLean, M. A., Buonincontri, G., Schulte, R. F., Addley, H., Sala, E., Brenton, J., Graves, M. J., & Gallagher, F. A. (2019). Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T. IEEE transactions on radiation and plasma medical sciences, 3(4), 509-515. https://doi.org/10.1109/TRPMS.2019.2905366
Kaggie, Joshua D, et al. "Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T." IEEE transactions on radiation and plasma medical sciences vol. 3,4 (2019): 509-515. doi: https://doi.org/10.1109/TRPMS.2019.2905366
Kaggie JD, Deen S, Kessler DA, McLean MA, Buonincontri G, Schulte RF, Addley H, Sala E, Brenton J, Graves MJ, Gallagher FA. Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T. IEEE Trans Radiat Plasma Med Sci. 2019 Jul;3(4):509-515. doi: 10.1109/TRPMS.2019.2905366. Epub 2019 Mar 15. PMID: 32066996; PMCID: PMC7025887.
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IEEE Trans Radiat Plasma Med Sci. 2019 Jul;3(4):509-515. doi: 10.1109/TRPMS.2019.2905366. Epub 2019 Mar 15.

Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T.

IEEE transactions on radiation and plasma medical sciences

Joshua D Kaggie, Surrin Deen, Dimitri A Kessler, Mary A McLean, Guido Buonincontri, Rolf F Schulte, Helen Addley, Evis Sala, James Brenton, Martin J Graves, Ferdia A Gallagher

Affiliations

  1. Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, U.K.; Cambridge University Hospitals, NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, U.K.
  2. Cancer Research U.K. Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, U.K.
  3. IMAGO7 Foundation, 56128 Pisa, Italy.
  4. GE Healthcare, D-80807 Munich, Germany.
  5. Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, U.K.; Cambridge University Hospitals, NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, U.K.; Cancer Research U.K. Cambridge Institute, Cambridge CB2 0RE, U.K.

PMID: 32066996 PMCID: PMC7025887 DOI: 10.1109/TRPMS.2019.2905366

Abstract

Multiparametric magnetic resonance imaging (MRI) can be used to characterize many cancer subtypes including ovarian cancer. Quantitative mapping of MRI relaxation values, such as

Keywords: Cancer applications; clinical imaging; imaging techniques; magnetic resonance imaging (MRI); oncology; ovarian cancer

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