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Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T 1 and T 2 Mapping in a PET/MR Setting
Multiparametric magnetic resonance imaging (MRI) can be used to characterize many cancer subtypes including ovarian cancer. Quantitative mapping of MRI relaxation values, such as and mapping, is promising for improving tumor assessment beyond conventional qualitative - and -weighted images. However,...
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Published in: | IEEE transactions on radiation and plasma medical sciences 2019-07, Vol.3 (4), p.509-515 |
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Main Authors: | , , , , , , , , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Multiparametric magnetic resonance imaging (MRI) can be used to characterize many cancer subtypes including ovarian cancer. Quantitative mapping of MRI relaxation values, such as
and
mapping, is promising for improving tumor assessment beyond conventional qualitative
- and
-weighted images. However, quantitative MRI relaxation mapping methods often involve long scan times due to sequentially measuring many parameters. Magnetic resonance fingerprinting (MRF) is a new method that enables fast quantitative MRI by exploiting the transient signals caused by the variation of pseudorandom sequence parameters. These transient signals are then matched to a simulated dictionary of
and
values to create quantitative maps. The ability of MRF to simultaneously measure multiple parameters, could represent a new approach to characterizing cancer and assessing treatment response. This feasibility study investigates MRF for simultaneous
,
, and relative proton density (rPD) mapping using ovarian cancer as a model system. |
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ISSN: | 2469-7311 2469-7303 |
DOI: | 10.1109/TRPMS.2019.2905366 |