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Quantitative assessment of flow between cerebrospinal and interstitial fluid compartments in humans.

Code ↔ Paper

2 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 2 matches
  1. [1] § Results › Intrathecal Injections for Quantification of CSF-to-ISF Flow. ↔ ITexperiments.m, lines 14–68 · score 0.53 · tissue classes, ISF volume fraction, flow rates, subcortical, model
  2. [2] § Materials and Methods › A Model for CSF-to-ISF Inflow. ↔ ITexperiments.m, lines 14–68 · score 0.53 · tissue class, glymphatic flow, subcortical, modeling, ISF

Paper

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The authors' code

MATLAB · 127 lines · 4 KB · no license · 2 matches

  1. %% Code for the paper "Quantitative assessment of flow between cerebrospinal and interstitial fluid compartments in humans".
  2. %
  3. % Code-authors: Anders Wåhlin, Viktor Vigren Näslund, Anders Eklund
  4. %
  5. % gFlow is the function for estimating k1 and k2 from which CSF-to-ISF flow
  6. % rate and ISF volume fraction can be calculated.
  8. % getEstCt is a support function that calculates brain tissue concentrations given
  9. % a matrix of CSF concentrations (Nrois X time), as well as a given k1 and
  10. % k2 (or just as a function of k1 if extracellular volume fraction is fixed, using function suffix "_constantVe").
  11. %
  12. % Implementation below is all intrathecal Gd flow calculations from the paper.
  14. %% Main section
  15. clear all
  16. load dataset1.mat
  18. for pat = 1:14; %loop cases
  19. for tissueClass = 1:3 %loop tissue classes
  22. if tissueClass ==1 %Cortex, estimate ve
  23. it = dataset1(pat).it;
  24. concCSF = dataset1(pat).concCsf_Ctx;
  25. concTissue = dataset1(pat).concCtx;
  26. dt = dataset1(pat).dt;
  27. points=dataset1(pat).points;
  28. tissueVolume = dataset1(pat).volCtx
  29. k0 = zeros(1,2)
  30. fun1=@(k)ITmodel(k,it,concCSF,concTissue,dt,points); %fit the model
  31. [kest,fval,exitflag,output] = fminunc(fun1,k0);
  32. q(pat,tissueClass) = kest(1)*tissueVolume %Glymphatic flow rate
  33. ve(pat,tissueClass) = kest(1)/kest(2) %ISF volume fraction
  35. end
  37. if tissueClass ==2 %White matter, keep ve constant
  38. it = dataset1(pat).it;
  39. concCSF = dataset1(pat).concCsf_Wm;
  40. concTissue = dataset1(pat).concWm;
  41. dt = dataset1(pat).dt;
  42. points=dataset1(pat).points;
  43. tissueVolume = dataset1(pat).volWm
  44. k0 = zeros(1)
  45. fun1=@(k)ITmodel(k,it,concCSF,concTissue,dt,points,ve(pat,1)); %fit the model
  46. [kest,fval,exitflag,output] = fminunc(fun1,k0);
  47. q(pat,tissueClass) = kest(1)*tissueVolume %Glymphatic flow rate
  48. ve(pat,tissueClass) = ve(pat,1) %ISF volume fraction
  49. end
  51. if tissueClass ==3 %Subcortical, keep ve constant
  52. it = dataset1(pat).it;
  53. concCSF = dataset1(pat).concCsf_Subcor;
  54. concTissue = dataset1(pat).concSubcor;
  55. dt = dataset1(pat).dt;
  56. points=dataset1(pat).points;
  57. tissueVolume = dataset1(pat).volSubcor
  58. k0 = zeros(1)
  59. fun1=@(k)ITmodel(k,it,concCSF,concTissue,dt,points,ve(pat,1)); %fit the model
  60. [kest,fval,exitflag,output] = fminunc(fun1,k0);
  61. q(pat,tissueClass) = kest(1)*tissueVolume %Glymphatic flow rate
  62. ve(pat,tissueClass) = ve(pat,1) %ISF volume fraction
  63. end
  65. end
  68. end
  71. %% Support functions
  73. %%
  74. function estCt = getEstCt(k,it,ccsf,dt)
  76. % Estimates brain tissue concentrations provided a CSF concentrations
  77. % (Nrois X time), k1 and k2.
  78. % dt is the temporal resolution in hrs
  80. for i = 1:size(ccsf,1) %loop over ROIs
  81. estCt(i,:) = k(1)*convolution(ccsf(i,:)',exp(-k(2).*it'))*dt ;
  82. end
  84. end
  85. %%
  86. function estCt = getEstCt_constantVe(k,it,ccsf,dt,ve)
  88. % Estimates brain tissue concentrations provided a CSF concentrations
  89. % (Nrois X time), k1 and k2.
  90. % dt is the temporal resolution in hrs
  92. for i = 1:size(ccsf,1) %loop over ROIs
  93. estCt(i,:) = k(1)*convolution(ccsf(i,:)',exp(-k(1)/ve.*it'))*dt ;
  94. end
  96. end
  98. %%
  99. function sse = ITmodel(k,it,ccsf,ct,dt,points,ve)
  100. % Calculates the difference between measured (ct) and estimated brain tissue
  101. % concentrations provided CSF concentrations (ccsf), k1 and k2 (stored as a
  102. % vector k).
  103. % The vector points specifies time points where the difference is calculated, and dt is the temporal resolution in hrs
  104. switch nargin
  106. case 6 %ve estimated
  108. estCt = getEstCt(k,it,ccsf,dt);
  109. sse = sum(sum(((ct(:,points)-estCt(:,points)).^2)));
  111. case 7 %ve supplied
  113. estCt = getEstCt_constantVe(k,it,ccsf,dt,ve);
  114. sse = sum(sum(((ct(:,points)-estCt(:,points)).^2)));
  115. end
  117. end
  119. %%
  120. function c = convolution(a, b)
  121. c = conv2(a(:), b(:), 'full');
  122. c = c(1:size(a, 1));
  124. if isrow(a)
  125. c = c.';
  126. end
  127. end

ITexperiments.m at commit 12049d0, no license · at the source

Overview

Authors: Anders Wåhlin1,2,3, Sofia Behndig2,4, Johan Eriksson De Ryst5, Viktor Vigren Näslund2, Daniel Dahlgren Lindström2, Jan Axelsson2,3, Cecilia Björnfot2,3, Mikael Bylund2,3, Anders Garpebring2, Petter Holmlund1, Afroditi Lalou2, Klara Mogensen2, Daniel P. G. Nilsson6, Sara Qvarlander2, Pontus Söderström1, Tomas Vikner2,7, Krister Wiklund6, Magnus Andersson6,8, Katrine Riklund3,4, Jan Malm5, Anders Eklund2,3
ORCID iDs: Anders Wåhlin, Sofia Behndig, Viktor Vigren Näslund, Daniel Dahlgren Lindström, Jan Axelsson, Klara Mogensen, Daniel P. G. Nilsson, Sara Qvarlander, Pontus Söderström, Krister Wiklund, Magnus Andersson, Katrine Riklund, Anders Eklund
  1. Department of Applied Physics and Electronics, Umeå University, Umeå S-90187, Sweden
  2. Department of Diagnostics and Intervention, Biomedical Engineering and Radiation Physics, Umeå University, Umeå S-90187, Sweden
  3. Umeå Center for Functional Brain Imaging, Umeå University, Umeå S-90187, Sweden
  4. Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, Umeå S-90187, Sweden
  5. Department of Clinical Science, Neurosciences, Umeå University, Umeå S-90187, Sweden
  6. Department of Physics, Umeå University, Umeå S-90187, Sweden
  7. Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705-2275
  8. Umeå Centre for Microbial Research Umeå University, Umeå S-90187, Sweden
Institutions: Umeå University (Sweden); University of Wisconsin–Madison (United States); Umeå Centre for Microbial Research (Sweden)
Journal: Proceedings of the National Academy of Sciences of the United States of America, volume 123, issue 18, article e2526239123
Dates: received 22 September 2025; accepted 30 March 2026; published online 29 April 2026; in print 5 May 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1073/pnas.2526239123 · PMID 42054362 · PMCID PMC13142984 · OpenAlex W7158741967
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: structural MRI / diffusion (modality), human (organism), other condition (population)
Methods: Connectivity, Statistics, fMRI & imaging
Keywords: cerebrospinal fluid, interstitial fluid, brain clearance, glymphatic system, flow
MeSH: Cerebrospinal Fluid*, Extracellular Fluid*, Hydrocephalus, Normal Pressure*, Aged, Brain, Female, Gadolinium, Glymphatic System, Humans, Magnetic Resonance Imaging, Male, Subarachnoid Space (* major topic)
Journal subjects: Biological Sciences, Neuroscience
Topic: Cerebrospinal fluid and hydrocephalus (Cellular and Molecular Neuroscience, Neuroscience), according to OpenAlex
Funding: Stiftelsen för Strategisk Forskning (SSF) (RMX18-0152); Vetenskapsrådet (2021-00711, 2022-04263); Hjärt-Lungfonden (20210653)
Citations: cited by 2 papers (Europe PMC); 64 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above, with 2 matches between paragraphs and lines of code.

anderswahlin/CSF-TISSUE-EXCHANGE

License: none: the authors keep all their rights
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: 12049d02acd037bf167a9bb4cefa447802bcb52c, 5 April 2026
Languages: MATLAB (3)
Size: 8 files, 3 scripts
Software Heritage: not archived
Found in: “Data, Materials, and Software Availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Optimization Toolbox (3 files)
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
4 files
At the source: github.com/anderswahlin/CSF-TISSUE-EXCHANGE

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

Tracing map

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  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 3 scripts, each with its path and the digest of its content;
  • 2 matches between paragraphs of the paper and lines of the code (method lexical-v1);
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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.

Code and data availability statement

The paper has a code and data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1073/pnas.2526239123.

Versions

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 21 authors, 5 keywords, 12 MeSH terms, 3 funders, 64 references.

Cite

This paper

Wåhlin, A., Behndig, S., Eriksson De Ryst, J., Vigren Näslund, V., Dahlgren Lindström, D., Axelsson, J., Björnfot, C., Bylund, M., Garpebring, A., Holmlund, P., Lalou, A., Mogensen, K., Nilsson, D. P. G., Qvarlander, S., Söderström, P., Vikner, T., Wiklund, K., Andersson, M., Riklund, K., . . . Eklund, A. (2026). Quantitative assessment of flow between cerebrospinal and interstitial fluid compartments in humans. Proceedings of the National Academy of Sciences of the United States of America, 123(18), e2526239123. https://doi.org/10.1073/pnas.2526239123

BibTeX

@article{wahlin2026quantitative,
author = {Wåhlin, Anders and Behndig, Sofia and Eriksson De Ryst, Johan and Vigren Näslund, Viktor and Dahlgren Lindström, Daniel and Axelsson, Jan and Björnfot, Cecilia and Bylund, Mikael and Garpebring, Anders and Holmlund, Petter and Lalou, Afroditi and Mogensen, Klara and Nilsson, Daniel P. G. and Qvarlander, Sara and Söderström, Pontus and Vikner, Tomas and Wiklund, Krister and Andersson, Magnus and Riklund, Katrine and Malm, Jan and Eklund, Anders},
title = {{Quantitative assessment of flow between cerebrospinal and interstitial fluid compartments in humans}},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
year = {2026},
month = apr,
volume = {123},
number = {18},
pages = {e2526239123},
publisher = {National Academy of Sciences},
issn = {0027-8424},
doi = {10.1073/pnas.2526239123},
url = {https://doi.org/10.1073/pnas.2526239123},
pmid = {42054362},
pmcid = {PMC13142984}
}

RIS

TY - JOUR
AU - Wåhlin, Anders
AU - Behndig, Sofia
AU - Eriksson De Ryst, Johan
AU - Vigren Näslund, Viktor
AU - Dahlgren Lindström, Daniel
AU - Axelsson, Jan
AU - Björnfot, Cecilia
AU - Bylund, Mikael
AU - Garpebring, Anders
AU - Holmlund, Petter
AU - Lalou, Afroditi
AU - Mogensen, Klara
AU - Nilsson, Daniel P. G.
AU - Qvarlander, Sara
AU - Söderström, Pontus
AU - Vikner, Tomas
AU - Wiklund, Krister
AU - Andersson, Magnus
AU - Riklund, Katrine
AU - Malm, Jan
AU - Eklund, Anders
TI - Quantitative assessment of flow between cerebrospinal and interstitial fluid compartments in humans
T2 - Proceedings of the National Academy of Sciences of the United States of America
J2 - Proc Natl Acad Sci U S A
PY - 2026
DA - 2026/04/29
VL - 123
IS - 18
SP - e2526239123
SN - 0027-8424
PB - National Academy of Sciences
DO - 10.1073/pnas.2526239123
UR - https://doi.org/10.1073/pnas.2526239123
LA - en
ER -

CSL-JSON

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