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Diffusion-relaxation MRI as virtual histology: separable microstructural signatures of AD pathology in ex vivo human brain

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Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

Shell · 97 lines · 2.9 KB · Apache-2.0

  1. #!/bin/bash
  2. set -x -e
  3. pip install --upgrade pip setuptools wheel cmake ninja
  4. echo "Check CMAKE version"
  5. cmake --version
  6. mkdir -p be/install && cd be
  7. echo "Checking folder structure"
  8. ls -lh .
  9. ls -lh ..
  10. # Download and build VTK
  11. LIB_LOCATION=build
  12. if [[ $1 =~ ubuntu-.* ]]; then
  13. VTK_BINARY=vtk-wheel-sdk-9.3.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.tar.xz
  14. DYLD_SUFFIX=so
  15. MAKEFLAGS="-- -j 8"
  16. elif [[ $1 == macos-13 ]]; then
  17. VTK_BINARY=vtk-wheel-sdk-9.3.1-cp310-cp310-macosx_10_10_x86_64.tar.xz
  18. DYLD_SUFFIX=dylib
  19. MAKEFLAGS="-- -j 8"
  20. elif [[ $1 == macos-14 ]]; then
  21. VTK_BINARY=vtk-wheel-sdk-9.3.1-cp310-cp310-macosx_11_0_arm64.tar.xz
  22. DYLD_SUFFIX=dylib
  23. elif [[ $1 =~ windows-.* ]]; then
  24. VTK_BINARY=vtk-wheel-sdk-9.3.1-cp310-cp310-win_amd64.tar.xz
  25. DYLD_SUFFIX=dll
  26. LIB_LOCATION=bin
  27. CMAKE_RELEASE_COMMAND="--config Release"
  28. else
  29. exit 255
  30. fi
  31. # Install Eigen
  32. git clone -b 3.4.0 https://gitlab.com/libeigen/eigen.git
  33. cmake \
  34. -DBUILD_EXAMPLES=OFF \
  35. -DBUILD_TESTING=OFF \
  36. -DCMAKE_BUILD_TYPE=Release \
  37. -DCMAKE_INSTALL_PREFIX=./install \
  38. -B eigen/build \
  39. eigen
  40. cmake --build eigen/build --target install $MAKEFLAGS $CMAKE_RELEASE_COMMAND
  41. # Install VTK from binary wheels provided by Kitware
  42. mkdir -p install/vtk install/vtk/shared
  43. curl -L https://www.vtk.org/files/release/9.3/${VTK_BINARY} -o ./install/vtk/vtk-wheel-sdk.tar.xz
  44. tar -xJvf ./install/vtk/vtk-wheel-sdk.tar.xz --strip-components 1 -C $PWD/install/vtk
  45. ln $(find $PWD/install/vtk/${LIB_LOCATION} -name "*.${DYLD_SUFFIX}") install/vtk/shared
  46. # Link the shared libraries needed for delocate into a simple directory
  47. # Build ITK
  48. git clone -b v5.2.1 https://github.com/InsightSoftwareConsortium/ITK.git ITK
  49. cmake \
  50. -DModule_MorphologicalContourInterpolation=ON \
  51. -DBUILD_EXAMPLES=OFF \
  52. -DBUILD_TESTING=OFF \
  53. -DCMAKE_BUILD_TYPE=Release \
  54. -DCMAKE_INSTALL_PREFIX=./install \
  55. -DCMAKE_POSITION_INDEPENDENT_CODE=ON \
  56. -DCMAKE_POLICY_VERSION_MINIMUM=3.5 \
  57. -B ITK/build \
  58. ITK
  59. cmake --build ITK/build --target install $MAKEFLAGS $CMAKE_RELEASE_COMMAND
  60. #git clone -b v9.3.1 https://github.com/Kitware/VTK.git VTK
  61. #cmake \
  62. # -DBUILD_EXAMPLES=OFF \
  63. # -DBUILD_TESTING=OFF \
  64. # -DCMAKE_BUILD_TYPE=Release \
  65. # -DBUILD_SHARED_LIBS=OFF \
  66. # -DVTK_REQUIRED_OBJCXX_FLAGS="" \
  67. # -DCMAKE_INSTALL_PREFIX=./install \
  68. # -B VTK/build \
  69. # VTK
  70. #cmake --build VTK/build --target install --config Release
  71. # Build Greedy
  72. # git clone -b master https://github.com/pyushkevich/greedy.git greedy
  73. cmake \
  74. -DCMAKE_BUILD_TYPE=Release \
  75. -DCMAKE_INSTALL_PREFIX=./install \
  76. -DGREEDY_BUILD_LMSHOOT=ON \
  77. -DGREEDY_BUILD_WRAPPING=ON \
  78. -DCMAKE_PREFIX_PATH="$PWD/install" \
  79. -DCMAKE_POSITION_INDEPENDENT_CODE=ON \
  80. -DVTK_DIR=$PWD/install/vtk/vtk-9.3.1.data/headers/cmake \
  81. -B greedy/build \
  82. ..
  83. cmake --build greedy/build --target install $MAKEFLAGS $CMAKE_RELEASE_COMMAND

prebuild.sh at commit f5212c5, under Apache-2.0 · at the source

Overview

Authors: Eppu Manninen1, Courtney J Comrie2, Geidy E Serrano3, Thomas G Beach3, Elizabeth B Hutchinson2, Dan Benjamini1
  1. National Institute on Aging, NIH
  2. University of Arizona
  3. Banner Sun Health Research Institute
Journal: Research square, pages rs.3.rs-9657671
Dates: published online 25 May 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI · PMCID PMC13232456
Status: code verified
Categories: structural MRI / diffusion (modality), histology / microscopy (modality), human (organism), Alzheimer's / dementia (population), cellular / molecular (subfield)
Methods: Statistics, Machine learning, Preprocessing, Connectivity, fMRI & imaging
Keywords: Alzheimer’s disease, multidimensional MRI, myelin, microglia, phosphorylated tau, amyloid beta
Citations: 91 references in the paper

Abstract

Cognitive decline in Alzheimer's disease (AD) reflects progressive disruption of cellular and microstructural organization, yet the biological specificity of conventional MRI signals remains poorly understood. Multidimensional diffusion–relaxation MRI (MD-MRI) resolves sub-voxel tissue heterogeneity and may offer a framework for linking imaging signals to underlying neuropathology. We tested the hypothesis that neuronal, glial, and white matter pathologies in AD occupy separable regions of diffusion–relaxation space and generate spatially organized signatures associated with cognitive impairment. We integrated ex vivo MD-MRI with co-registered histology from 12 human donors spanning a range of Braak stages and pathological severity. Nested cross-validated elastic net models predicted voxelwise Aβ, pTau, microglia, and myelin burden from the multidimensional diffusion–relaxation density distribution. Regional associations were assessed across hippocampal subfields and white matter, and MRI-predicted pathology was related to ante-mortem Mini-Mental State Examination scores. Distinct diffusion–relaxation components were preferentially associated with different pathological markers, indicating separable microstructural signatures. MRI-derived predictions corresponded significantly with histological measures of myelin (ρ = 0.77), pTau (ρ = 0.62), and microglia (ρ = 0.61), with weaker correspondence for Aβ (ρ = 0.45). Regionally, predicted pathology recapitulated known patterns of selective vulnerability, with elevated pTau and microglial signal in hippocampal subfields and dominant myelin-associated signal in white matter (p < 0.0001). Higher predicted hippocampal pTau was strongly associated with worse cognitive performance (ρ = −0.88, p = 0.0014), with a moderate association in white matter (ρ = −0.66, p = 0.036). These findings demonstrate that AD-related pathological processes manifest as distinct, spatially organized diffusion–relaxation signatures, providing mechanistic insight into the microstructural basis of MRI contrasts. As clinically feasible MD-MRI protocols continue to emerge, translation of these signatures to in vivo imaging may enable more biologically informed assessment of neurodegeneration.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above.

pyushkevich/greedy

License: Apache-2.0
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: f5212c50d72f4ce511ec1a6e142c58b169de714e, 3 August 2026
Languages: MATLAB (83), C/C++ (52), Shell (5), C (3), Python (1)
Size: 309 files, 144 scripts
Software Heritage: archived
Found in: the text, “Registration of histological images to MRI”
Holds: README, license file, environment (pyproject.toml), continuous integration, documentation
Not found: CITATION.cff, tests
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
146 files

dan-benjamini/madco

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: d665140a31135349ec280e0a4adfd2f9b86f70f6, 21 May 2025
Languages: MATLAB (618), C (70), JavaScript (13), C/C++ (6)
Size: 1,207 files, 707 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README, documentation
Not found: license file, CITATION.cff, environment file, tests, continuous integration
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
708 files

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 851 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author upon request, subject to applicable data sharing agreements and conditions of reuse. MATLAB source code for preprocessing and MADCO data inversion is freely available at https://github.com/dan-benjamini/madco/.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, pages, dates, 6 authors, 6 keywords, 90 references.

Cite

This paper

Manninen, E., Comrie, C. J., Serrano, G. E., Beach, T. G., Hutchinson, E. B., & Benjamini, D. (2026). Diffusion-relaxation MRI as virtual histology: separable microstructural signatures of AD pathology in ex vivo human brain. Research square, rs.3.rs-9657671.

BibTeX

@article{manninen2026diffusion,
author = {Manninen, Eppu and Comrie, Courtney J and Serrano, Geidy E and Beach, Thomas G and Hutchinson, Elizabeth B and Benjamini, Dan},
title = {{Diffusion-relaxation MRI as virtual histology: separable microstructural signatures of AD pathology in ex vivo human brain}},
journal = {Research square},
year = {2026},
month = may,
pages = {rs.3.rs--9657671},
publisher = {American Journal Experts},
pmcid = {PMC13232456}
}

RIS

TY - JOUR
AU - Manninen, Eppu
AU - Comrie, Courtney J
AU - Serrano, Geidy E
AU - Beach, Thomas G
AU - Hutchinson, Elizabeth B
AU - Benjamini, Dan
TI - Diffusion-relaxation MRI as virtual histology: separable microstructural signatures of AD pathology in ex vivo human brain
T2 - Research square
PY - 2026
DA - 2026/05/25
SP - rs.3.rs
EP - 9657671
PB - American Journal Experts
LA - en
ER -

CSL-JSON

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"title": "Diffusion-relaxation MRI as virtual histology: separable microstructural signatures of AD pathology in ex vivo human brain",
"container-title": "Research square",
"author": [
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"family": "Manninen",
"given": "Eppu"
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{
"family": "Comrie",
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{
"family": "Serrano",
"given": "Geidy E"
},
{
"family": "Beach",
"given": "Thomas G"
},
{
"family": "Hutchinson",
"given": "Elizabeth B"
},
{
"family": "Benjamini",
"given": "Dan"
}
],
"page": "rs.3.rs-9657671",
"PMCID": "PMC13232456",
"publisher": "American Journal Experts",
"language": "en",
"issued": {
"date-parts": [
[
2026,
5,
25
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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