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NeurosciencebioRxiv
Preprint

QNPtoVox: A methods pipeline for mapping 2D quantitative neuropathology to 3D MNI voxel space.

Raghav MadaniD, Tejas S BajwaiD, Amanda KirklandiD, David HuntiD, Jason M. WebsteriD, Seo-Eun Choi, Christine L. Mac DonaldiD, Nadia O. PostupnaiD, Caitlin S. LatimeriD, Thomas J. GrabowskiiD, John H. GennariiD, Paul K. CraneiD

Abstract

1.Quantitative neuropathology has advanced through whole-slide imaging and digital histology platforms. Yet, these measurements rarely align with neuroimaging coordinate frameworks that may be useful for spatial modeling and other applications. QNPtoVox, short for quantitative neuropathology to voxels, is a reproducible, modular pipeline that transforms quantitative metrics generated by digital pathology software (HALO) into voxel-based maps registered to a standard common coordinate (MNI) template. The workflow integrates digital histopathology, gross tissue photography, ex-vivo MRI, and nonlinear registration to generate spatially standardized 3D pathology representations. This Methods article provides a complete procedural description, including required materials, step-wise instructions, operator-dependent checkpoints, expected outputs, reproducibility evaluation, and troubleshooting. QNPtoVox enables voxel-level integration of neuropathology with neuroimaging tools, unlocking existing histopathology datasets for computational modeling and cross-cohort harmonization.

PDFDOI

02 /Specification & Classification

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