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Noise estimation from averaged diffusion weighted images: Can unbiased quantitative decay parameters assist cancer evaluation?

Dikaios, N; Atkinson, D; Punwani, S; Hamy, V; Purpura, P; Rice, S; Taylor, S; ... Mendes, R; + view all (2014) Noise estimation from averaged diffusion weighted images: Can unbiased quantitative decay parameters assist cancer evaluation? Magnetic Resonance in Medicine , 71 (6) 2105 - 2117. 10.1002/mrm.24877. Green open access

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Abstract

Purpose: Multiexponential decay parameters are estimated from diffusion-weighted-imaging that generally have inherently low signal-to-noise ratio and non-normal noise distributions, especially at high b-values. Conventional nonlinear regression algorithms assume normally distributed noise, introducing bias into the calculated decay parameters and potentially affecting their ability to classify tumors. This study aims to accurately estimate noise of averaged diffusion-weighted-imaging, to correct the noise induced bias, and to assess the effect upon cancer classification. Methods: A new adaptation of the median-absolute-deviation technique in the wavelet-domain, using a closed form approximation of convolved probability-distribution-functions, is proposed to estimate noise. Nonlinear regression algorithms that account for the underlying noise (maximum probability) fit the biexponential/stretched exponential decay models to the diffusion-weighted signal. A logistic-regression model was built from the decay parameters to discriminate benign from metastatic neck lymph nodes in 40 patients. Results: The adapted median-absolute-deviation method accurately predicted the noise of simulated (R=0.96) and neck diffusion-weighted-imaging (averaged once or four times). Maximum probability recovers the true apparent-diffusion-coefficient of the simulated data better than nonlinear regression (up to 40%), whereas no apparent differences were found for the other decay parameters. Conclusions: Perfusion-related parameters were best at cancer classification. Noise-corrected decay parameters did not significantly improve classification for the clinical data set though simulations show benefit for lower signal-to-noise ratio acquisitions. © 2013 Wiley Periodicals, Inc.

Type: Article
Title: Noise estimation from averaged diffusion weighted images: Can unbiased quantitative decay parameters assist cancer evaluation?
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/mrm.24877
Publisher version: http://dx.doi.org/10.1002/mrm.24877
Additional information: © 2013 Wiley Periodicals, Inc. Full text made available to UCL Discovery by kind permission of Wiley.
Keywords: diffusion weighted magnetic resonance imaging; noise estimation; IVIM;
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > UCL Medical School
URI: http://discovery.ucl.ac.uk/id/eprint/1431559
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