Replication and generalization in applied neuroimaging
Date
2019Author
Lerma-Usabiaga, Garikoitz
Mukherjee, Pratik
Ren, Zhimei
Perry, Michael L.
Wandell, Brian A.
Metadata
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Garikoitz Lerma-Usabiaga, Pratik Mukherjee, Zhimei Ren, Michael L. Perry, Brian A. Wandell, Replication and generalization in applied neuroimaging, NeuroImage, Volume 202, 2019, 116048, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2019.116048.
Abstract
There is much interest in translating neuroimaging findings into meaningful clinical diagnostics. The goal of
scientific discoveries differs from clinical diagnostics. Scientific discoveries must replicate under a specific set of
conditions; to translate to the clinic we must show that findings using purpose-built scientific instruments will be
observable in clinical populations and instruments. Here we describe and evaluate data and computational
methods designed to translate a scientific observation to a clinical setting. Using diffusion weighted imaging
(DWI), Wahl et al. (2010) observed that across subjects the mean fractional anisotropy (FA) of homologous pairs
of tracts is highly correlated. We hypothesize that this is a fundamental biological trait that should be present in
most healthy participants, and deviations from this assessment may be a useful diagnostic metric. Using this
metric as an illustration of our methods, we analyzed six pairs of homologous white matter tracts in nine different
DWI datasets with 44 subjects each. Considering the original FA measurement as a baseline, we show that the new
metric is between 2 and 4 times more precise when used in a clinical context. Our framework to translate research
findings into clinical practice can be applied, in principle, to other neuroimaging results.