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Abstract #5353

Physiological noise at low diffusion weighting reduces repeatability of apparent diffusion coefficient independent of underlying diffusion curve characteristics

Neil Peter Jerome1,2, Igor Vidic3, Liv Egnell2,3, Torill E. Sjøbakk1, Agnes Østlie2, Hans E. Fjøsne4,5, Tone F. Bathen1, and Pål Erik Goa2,3

1Department of Circulation and Medical Imaging, Norwegian University of Science and Technology - NTNU, Trondheim, Norway, 2Clinic of Radiology and Nuclear Medicine, St. Olavs University Hospital, Trondheim, Norway, 3Department of Physics, Norwegian University of Science and Technology - NTNU, Trondheim, Norway, 4Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology - NTNU, Trondheim, Norway, 5Department of Surgery, St. Olavs University Hospital, Trondheim, Norway

The apparent diffusion coefficient is a powerful imaging biomarker, sensitive to microstructure properties, and possessing excellent repeatability. Exclusion of perfusion influence (b<150 s.mm-2) reflects true diffusivity, although fewer data points reduces precision, and thus repeatability. We investigate repeatability of experimental breast diffusion data, and show an unexpected increased repeatability with low b-value data inclusion, in contrast to simulated data. This indicates that experimentally-acquired low b-values contains additional noise, perhaps modulated by the non-Gaussianity of the underlying diffusion processes, that decreases diffusion modelling repeatability independent of the true diffusion curve, and should be considered as part of the analysis strategy.

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