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Basic Science and Pathogenesis.

Jason Webster1, Ali Shojaie1, Yiqin Alicia Shen1

  • 1University of Washington, Seattle, WA, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 25, 2025
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Summary
This summary is machine-generated.

A digital brain sampling protocol (BSP) atlas was created using neuroimaging for Alzheimer's research. This 3D atlas enhances tissue requests and integrates with existing neuroinformatics tools for better collaboration.

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Area of Science:

  • Neuroscience
  • Neuropathology
  • Bioinformatics

Background:

  • Mechanistic neuroscience research requires well-preserved brain tissue from biorepositories.
  • Alzheimer's Disease and Related Dementias (ADRD) research validity depends on standardized brain sampling protocols (BSP).
  • The University of Washington BRaIN Laboratory developed an extensive BSP for brain tissue preparation, sampling, characterization, and storage.

Purpose of the Study:

  • To develop a digital BSP atlas using a neuroimaging framework.
  • To improve the brain tissue request process and biorepository workflows.
  • To generate scientific visualizations and link to neuroimaging data.

Main Methods:

  • Virtual neuropathology was performed using the BRaIN lab BSP and standard brain templates.
  • Software including FreeSurfer, FSL, and custom scripts were used for brain extraction, segmentation, and slicing.
  • Virtual tissue sampling was conducted on a collaborative platform, with data exported and processed to create the 3D digital BSP atlas.

Main Results:

  • The Digital BSP Atlas provides volumetric labels for all fixed-tissue samples.
  • It incorporates standard neuroinformatics conventions for compatibility with software like FSL, MRICroGL, and FreeSurfer.
  • The atlas offers an explicit spatial representation of the BSP.

Conclusions:

  • The digital BSP atlas facilitates efficient location, referencing, and utilization of postmortem brain samples.
  • Integration with neuroinformatics enhances interdisciplinary collaboration, visualization, and protocol optimization.
  • Future work includes developing training software and a flexible sample identification interface.