Metcalfe-Smith, E., Meeus, E.M., Novak, J., Dehghani, H., Peet, A.C. and Zarinabad, N. (2019). Auto-Regressive Discrete Acquisition Points Transformation for Diffusion Weighted MRI Data. IEEE Transactions on Biomedical Engineering, 66 (9), 2617 - 2628.
Abstract
Objective: A new method for fitting diffusion-weighted magnetic resonance imaging (DW-MRI) data composed of an unknown number of multi-exponential components is presented and evaluated. Methods: The auto-regressive discrete acquisition points transformation (ADAPT) method is an adaption of the auto-regressive moving average system, which allows for the modeling of multi-exponential data and enables the estimation of the number of exponential components without prior assumptions. ADAPT was evaluated on simulated DW-MRI data. The optimum ADAPT fit was then applied to human brain DWI data and the correlation between the ADAPT coefficients and the parameters of the commonly used bi-exponential intravoxel incoherent motion (IVIM) method were investigated. Results: The ADAPT method can correctly identify the number of components and model the exponential data. The ADAPT coefficients were found to have strong correlations with the IVIM parameters. ADAPT(1,1)-β0 correlated with IVIM-D: ρ = 0.708, P <; 0.001. ADAPT(1,1)-α1 correlated with IVIM-f: ρ = 0.667, P <; 0.001. ADAPT(1,1)-β1 correlated with IVIM-D * : ρ = 0.741, P <; 0.001). Conclusion: ADAPT provides a method that can identify the number of exponential components in DWI data without prior assumptions, and determine potential complex diffusion biomarkers. Significance: ADAPT has the potential to provide a generalized fitting method for discrete multi-exponential data, and determine meaningful coefficients without prior information.
Publication DOI: | https://doi.org/10.1109/TBME.2019.2893523 |
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Divisions: | College of Health & Life Sciences > School of Psychology |
Additional Information: | This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/ |
Publication ISSN: | 1558-2531 |
Last Modified: | 06 Aug 2024 08:50 |
Date Deposited: | 20 May 2020 11:47 |
Full Text Link: |
http://www.scop ... tnerID=MN8TOARS |
Related URLs: |
https://ieeexpl ... ocument/8625389
(Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2019-08-30 |
Published Online Date: | 2019-01-24 |
Accepted Date: | 2019-01-08 |
Authors: |
Metcalfe-Smith, E.
Meeus, E.M. Novak, J. ( ![]() Dehghani, H. Peet, A.C. Zarinabad, N. |