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Abstract #3476

Microstructural Precision: Assessing the Reproducibility and Sensitivity of Multidimensional Diffusion Metrics

Matthew Bowdler1, Gareth Barker2, and Flavio Dell'Acqua1
1Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom, 2Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom

Synopsis

Keywords: Microstructure, Diffusion/other diffusion imaging techniques, Multidimensional Diffusion

Motivation: The reproducibility and sensitivity of Multidimensional Diffusion (MDD) measures have not been extensively investigated.

Goal(s): Our goal was to assess reproducibility and sensitivity of µFA in comparison with conventional FA metrics for multiple white and grey matter regions.

Approach: Test-retest data was acquired to compute ICC scores (reproducibility) and power calculations (sensitivity) to predict the number of subjects required to detect 1%, 2%, 4% and 5% changes for each metric across multiple regions.

Results: While FA shows the highest reproducibility for both WM and GM, µFA demonstrates enhanced sensitivity to detect microstructural changes for the same percentage difference.

Impact: Our test-retest study demonstrates that Multidimensional Diffusion (MDD) metrics, like µFA, show good reproducibility scores and increased sensitivity in the detection of microstructural changes when compared to equivalent FA changes in both white and grey matter.

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