Evidence map›Paper›PMID 41415458›Full record

ArticlebioRxiv : the preprint server for biology2025

Cellular deconvolution of the brain with topological magnetic resonance image analysis.

Luis A Vazquez, Michael B Fromandi, Tracy L Hagemann, Ryan D Risgaard, Jose M Guerrero-Gonzalez, Ajay P Singh, Paloma C Frautschi, Samuel A Hurley, André M M Sousa, Doug C Dean and 2 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Luis A VazquezNeuroscience Training Program, Wisconsin Institutes for Medical Research, University of Wisconsin-Madison; Madison, WI, USA.
Michael B FromandiDepartment of Radiology, University of Wisconsin School of Medicine and Public Health; Madison, WI, USA.
Tracy L HagemannWaisman Center, University of Wisconsin-Madison; Madison, WI, USA.
Ryan D RisgaardMedical Scientist Training Program, School of Medicine and Public Health, University of Wisconsin-Madison; Madison, WI, USA.
Jose M Guerrero-GonzalezWaisman Center, University of Wisconsin-Madison; Madison, WI, USA.
Ajay P SinghMedical Scientist Training Program, School of Medicine and Public Health, University of Wisconsin-Madison; Madison, WI, USA.
Paloma C FrautschiDepartment of Radiology, University of Wisconsin School of Medicine and Public Health; Madison, WI, USA.
Samuel A HurleyDepartment of Radiology, University of Wisconsin School of Medicine and Public Health; Madison, WI, USA.
André M M SousaWaisman Center, University of Wisconsin-Madison; Madison, WI, USA.ORCID 0000-0003-1740-5066
Doug C DeanWaisman Center, University of Wisconsin-Madison; Madison, WI, USA.
Tyler K UllandDepartment of Pathology and Laboratory Medicine, University of Wisconsin; Madison, WI, USA.
John-Paul J YuDepartment of Radiology, University of Wisconsin School of Medicine and Public Health; Madison, WI, USA.ORCID 0000-0003-1878-052X

Funding

Research Training for Computation and Informatics in Biology and MedicineT15LM007359 · NLM · UNIVERSITY OF WISCONSIN-MADISON · PI Mark W. Craven, Colin Noel Dewey · 2002 to 2026
$22.6M
Integrated Training For Physician-ScientistsT32GM140935 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Anna Huttenlocher, Jeniel E Nett · 2021 to 2026
$6.5M
ß-hydroxybutyrate inhibition of pathology in Alzheimer's diseaseR01AG083883 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Barbara Brigitta Bendlin, Federico E Rey · 2023 to 2026
$3.8M
Astrocyte-synapse interactions in a rat model of Alexander diseaseR01NS110719 · NINDS · UNIVERSITY OF WISCONSIN-MADISON · PI HAGEMANN, TRACY · 2019 to 2023
$2.1M
Mechanisms underlying the development, evolution, and function of human-specific cortical dopaminergic interneuronsF30MH140382 · NIMH · UNIVERSITY OF WISCONSIN-MADISON · PI Ryan David Risgaard · 2025 to 2026
$78k
NIA NIH HHS R01 AG083883NIGMS NIH HHS T32 GM140935NIMH NIH HHS F30 MH140382NINDS NIH HHS R01 NS110719NLM NIH HHS T15 LM007359
6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) is foundational tool in neuroscience, enabling characterization of neuroanatomical markers of disease, behavior, and cognition. However, the precise cellular processes driving the structural and functional readouts provided by MRI remain opaque. Non-invasively assessing cell type, abundance, and location using MRI has the potential to revolutionize both basic science and clinical practice. To this end, we developed SpaTial Representation and Analysis using Topological Architecture (STRATA), an image-based gradient-boosted machine learning framework, which quantifies cell type proportions of neurons, astrocytes, oligodendrocytes, and microglia from MR images. Here we demonstrate and validate STRATA on diverse disease models, species, and regions of interest that together highlight the generalizability of the STRATA framework.

Indexed as

cellular deconvolutiondiffusion weighted MRIMRINODDItopological data analysis

Identifiers

PMID41415458
PMCPMC12710656

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.