Speaker
Joshua Daniel Kaggie
(University of Cambridge)
Description
Quantitative MRI has previously shown benefits for the assessment of ovarian cancer. Magnetic Resonance Fingerprinting (MRF) is a novel technique for quantitative MRI, which exploits the transient signals caused by the variation of MRI sequence parameters.
This proof-of-concept work demonstrates the utility of MRF in two patients, with low and high grade ovarian tumours on a 3.0 T MRI. The mean value for both subjects for T1 was 2464.5 ± 100.9 / 1974.8 ± 191.3 ms, and for T2 was 225.4 ± 33.9/94.1 ± 14.5 ms. The mean T1 and T2 in the tumour was higher by ~20% and ~58% in the low grade ovarian tumour in comparison with the malignant tumour.
Primary author
Joshua Daniel Kaggie
(University of Cambridge)
Co-authors
Dimitri Kessler
(University of Cambridge)
Evis Sala
(University of Cambridge)
Dr
Ferdia Gallagher
(University of Cambridge)
Guido Buonincontri
(PI)
Helen Addley
(Cambridge University Hospitals NHS Foundation Trust)
James Brenton
(University of Cambridge, Cancer Research UK)
Martin Graves
(University of Cambridge)
Mary McLean
(University of Cambridge, Cancer Research UK)
Dr
Rolf Schulte
(GE Healthcare)
Surrin Deen
(University of Cambridge)
