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Analysis of the Effects of Noise, DWI Sampling, and Value of Assumed Parameters in Diffusion MRI Models
Eunice Kennedy Shriver National Institute Child Health and Hum, MD USA; Henry M Jackson Fdn Adv Mil Medical Inc, MD USA.
Eunice Kennedy Shriver National Institute Child Health and Hum, MD USA.
Eunice Kennedy Shriver National Institute Child Health and Hum, MD USA; Henry M Jackson Fdn Adv Mil Medical Inc, MD USA.
National Intrepid Centre Excellence, MD USA.
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2017 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 78, no 5, p. 1767-1780Article in journal (Refereed) Published
Abstract [en]

Purpose: This study was a systematic evaluation across different and prominent diffusion MRI models to better understand the ways in which scalar metrics are influenced by experimental factors, including experimental design (diffusion-weighted imaging [DWI] sampling) and noise. Methods: Four diffusion MRI models-diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator MRI (MAP-MRI), and neurite orientation dispersion and density imaging (NODDI)-were evaluated by comparing maps and histogram values of the scalar metrics generated using DWI datasets obtained in fixed mouse brain with different noise levels and DWI sampling complexity. Additionally, models were fit with different input parameters or constraints to examine the consequences of model fitting procedures. Results: Experimental factors affected all models and metrics to varying degrees. Model complexity influenced sensitivity to DWI sampling and noise, especially for metrics reporting nonGaussian information. DKI metrics were highly susceptible to noise and experimental design. The influence of fixed parameter selection for the NODDI model was found to be considerable, as was the impact of initial tensor fitting in the MAP-MRI model. Conclusion: Across DTI, DKI, MAP-MRI, and NODDI, a wide range of dependence on experimental factors was observed that elucidate principles and practical implications for advanced diffusion MRI. (C) 2017 International Society for Magnetic Resonance in Medicine.

Place, publisher, year, edition, pages
WILEY , 2017. Vol. 78, no 5, p. 1767-1780
Keywords [en]
diffusion tensor imaging; diffusion kurtosis imaging; mean apparent propagator MRI; neurite orientation dispersion and density imaging; noise floor bias; DWI sampling
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-143738DOI: 10.1002/mrm.26575ISI: 000416390700012PubMedID: 28090658OAI: oai:DiVA.org:liu-143738DiVA, id: diva2:1166707
Note

Funding Agencies|Center for Neuroscience and Regenerative Medicine

Available from: 2017-12-15 Created: 2017-12-15 Last updated: 2017-12-15

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