Consideration of cerebrospinal fluid intensity variation in diffusion weighted MRI

Colin B. Hansen; Vishwesh Nath; Allison E. Hainline; Kurt G. Schilling; Prasanna Parvathaneni; Roza G. Bayrak; Justin A. Blaber; Owen Williams; Susan Resnick; Lori Beason-Held; Okan Irfanoglu; Carlo Pierpaoli M.D.; Adam W. Anderson; Baxter P. Rogers; Bennett A. Landman

doi:10.1117/12.2512949

1 March 2019 Consideration of cerebrospinal fluid intensity variation in diffusion weighted MRI

Colin B. Hansen, Vishwesh Nath, Allison E. Hainline, Kurt G. Schilling, Prasanna Parvathaneni, Roza G. Bayrak, Justin A. Blaber, Owen Williams, Susan Resnick, Lori Beason-Held, Okan Irfanoglu, Carlo Pierpaoli M.D., Adam W. Anderson, Baxter P. Rogers, Bennett A. Landman

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Proceedings Volume 10948, Medical Imaging 2019: Physics of Medical Imaging; 109482G (2019) https://doi.org/10.1117/12.2512949
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

Diffusion weighted MRI (DW-MRI) depends on accurate quantification signal intensities that reflect directional apparent diffusion coefficients (ADC). Signal drift and fluctuations during imaging can cause systematic non-linearities that manifest as ADC changes if not corrected. Here, we present a case study on a large longitudinal dataset of typical diffusion tensor imaging. We investigate observed variation in the cerebral spinal fluid (CSF) regions of the brain, which should represent compartments with isotropic diffusivity. The study contains 3949 DW-MRI acquisitions of the human brain with 918 subjects and 542 with repeated scan sessions. We provide an analysis of the inter-scan, inter-session, and intra-session variation and an analysis of the associations with the applied diffusion gradient directions. We investigate a hypothesis that CSF models could be used in lieu of an interspersed minimally diffusion-weighted image (b0) correction. Variation in CSF signal is not largely attributable to within-scan dynamic anatomical changes (3.6%), but rather has substantial variation across scan sessions (10.6%) and increased variation across individuals (26.6%). Unfortunately, CSF intensity is not solely explained by a main drift model or a gradient model, but rather has statistically significant associations with both possible explanations. Further exploration is necessary for CSF drift to be used as an effective harmonization technique.

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Colin B. Hansen, Vishwesh Nath, Allison E. Hainline, Kurt G. Schilling, Prasanna Parvathaneni, Roza G. Bayrak, Justin A. Blaber, Owen Williams, Susan Resnick, Lori Beason-Held, Okan Irfanoglu, Carlo Pierpaoli M.D., Adam W. Anderson, Baxter P. Rogers, and Bennett A. Landman "Consideration of cerebrospinal fluid intensity variation in diffusion weighted MRI", Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109482G (1 March 2019); https://doi.org/10.1117/12.2512949

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KEYWORDS

Diffusion

Brain

Statistical modeling

Magnetic resonance imaging

Neuroimaging

Data modeling

Error analysis

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