Opensource Neuroimaging Platforms: Gaps in Demographic Data

Elizabeth A Rizzoni, BA

Brigham and Women’s Hospital
Opensource Neuroimaging Platforms: Gaps in Demographic Data

Scientific Abstract

 

Background: An important goal of big data is to make large, high-quality datasets public via opensource platforms. This focus reflects the goals shared across a number of fields to address questions that can only be answered with large datasets. In the field of neuroimaging, numerous information gaps currently exist on opensource platforms, importantly information about the very subjects from whom the imaging data were procured. For example, a lack of demographic data prevents answering questions relevant to sex, race, age, or diagnosis if that information is not included. Comparisons based on these categories are the basis of many studies, so the prevalent absence of demographic information limits the research that can be conducted on data from these platforms. Here we will present a list of current opensource neuroimaging platforms used by a variety of neuropsychiatric researchers and the data available from each, particularly demographic information. Recommendations for future platform models will be made to ensure data completeness.

Methods: A list of opensource neuroimaging platforms (Dec 2020 – Feb 2021) was compiled. Platforms were organized in a tiered fashion according to the ease of accessibility by which each platform makes its datasets available to the both the general public and research community. Datasets were checked for available imaging modalities, clinical data, and subject demographics.

Results: The tiered organization of opensource sites, as well their available image types, clinical data, and subject demographics will be reported.

Conclusions: We predict that the majority of available opensource neuroimaging datasets will not include extensive demographic data, especially in regard to subjects’ racial and ethnic information. The NIMH Data Archive (NDA) serves as an exemplary model of data completeness that we recommend as a source model for future opensource neuroimaging platforms.

Live Zoom Session – April 21st

research Areas

Authors

Elizabeth A Rizzoni, BA, Michael J Coleman, MA, Martha E Shenton, PhD, Sylvain Bouix, PhD

Principal Investigator

Martha E Shenton, PhD

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