Removing rician bias in diffusional kurtosis of the prostate using real-data reconstruction.
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Embargo End Date
ICR Authors
Authors
Goodburn, RJ
Barrett, T
Patterson, I
Gallagher, FA
Lawrence, EM
Gnanapragasam, VJ
Kastner, C
Priest, AN
Barrett, T
Patterson, I
Gallagher, FA
Lawrence, EM
Gnanapragasam, VJ
Kastner, C
Priest, AN
Document Type
Journal Article
Date
2020-06-01
Date Accepted
2019-10-23
Abstract
PURPOSE: To compare prostate diffusional kurtosis imaging (DKI) metrics generated using phase-corrected real data with those generated using magnitude data with and without noise compensation (NC). METHODS: Diffusion-weighted images were acquired at 3T in 16 prostate cancer patients, measuring 6 b-values (0-1500 s/mm2 ), each acquired with 6 signal averages along 3 diffusion directions, with noise-only images acquired to allow NC. In addition to conventional magnitude averaging, phase-corrected real data were averaged in an attempt to reduce rician noise-bias, with a range of phase-correction low-pass filter (LPF) sizes (8-128 pixels) tested. Each method was also tested using simulations. Pixelwise maps of apparent diffusion (D) and apparent kurtosis (K) were calculated for magnitude data with and without NC and phase-corrected real data. Average values were compared in tumor, normal transition zone (NTZ), and normal peripheral zone (NPZ). RESULTS: Simulations indicated LPF size can strongly affect K metrics, where 64-pixel LPFs produced accurate metrics. Relative to metrics estimated from magnitude data without NC, median NC K were lower (P < 0.0001) by 6/11/8% in tumor/NPZ/NTZ, 64-LPF real-data K were lower (P < 0.0001) by 4/10/7%, respectively. CONCLUSION: Compared with magnitude data with NC, phase-corrected real data can produce similar K, although the choice of phase-correction LPF should be chosen carefully.
Citation
Magnetic resonance in medicine, 2020, 83 (6), pp. 2243 - 2252
Source Title
Publisher
WILEY
ISSN
0740-3194
eISSN
1522-2594
Collections
Research Team
Magnetic Resonance Imaging in Radiotherapy