Evidence map›Paper›PMID 33385546›Full record

ArticleNeuroImage2021

Comparison of diffusion MRI and CLARITY fiber orientation estimates in both gray and white matter regions of human and primate brain.

C Leuze, M Goubran, M Barakovic, M Aswendt, Q Tian, B Hsueh, A Crow, E M M Weber, G K Steinberg, M Zeineh and 6 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.3field-weighted citation impact, top 9% of its field
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

21 citing papers in PubMed, 39 citations in OpenAlex.

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  15. Brain tract structure predicts relapse to stimulant drug use.Proceedings of the National Academy of Sciences of the United States of America · 2022
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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

16 authors at 7 institutions in 4 countries.

C LeuzeDepartment of Radiology, Stanford University, Stanford, CA, USA. Electronic address: cleuze@stanford.edu.
M GoubranDepartment of Radiology, Stanford University, Stanford, CA, USA.
M BarakovicDepartment of Radiology, Stanford University, Stanford, CA, USA; Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.
M AswendtDepartment of Neurosurgery, Stanford University, Stanford, CA, USA.
Q TianDepartment of Radiology, Stanford University, Stanford, CA, USA.
B HsuehDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
A CrowDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
E M M WeberDepartment of Radiology, Stanford University, Stanford, CA, USA.
G K SteinbergDepartment of Neurosurgery, Stanford University, Stanford, CA, USA.
M ZeinehDepartment of Radiology, Stanford University, Stanford, CA, USA.
E D PloweyDepartment of Pathology, Stanford University, Stanford, CA, USA.
A DaducciDepartment of Computer Science, University of Verona, Verona, Italy.
G InnocentiSignal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden; Brain and Mind Institute, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.
J-P ThiranSignal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland.
K DeisserothDepartment of Bioengineering, Stanford University, Stanford, CA, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
J A McNabDepartment of Radiology, Stanford University, Stanford, CA, USA.
Stanford University · USHoward Hughes Medical Institute · USKarolinska Institutet · SEStanford Medicine · USUniversity Hospital of Lausanne · CHUniversity of Basel · CHUniversity of Verona · IT

Funding

Training CoreP50DA042012 · NIDA · STANFORD UNIVERSITY · PI Karl A. Deisseroth, Lisa Giocomo · 2017 to 2026
$27.1M
Training and DisseminationP41EB015891 · NIBIB · STANFORD UNIVERSITY · PI GLOVER, GARY H · 2012 to 2019
$10.7M
Structural and molecular identification of circuitry underlying joint processing of motivation and aversionR37DA035377 · NIDA · STANFORD UNIVERSITY · PI DEISSEROTH, KARL A. · 2013 to 2022
$6.2M
Foundations of MRI Corticography for mesoscale organization and neuronal circuitryR01MH111444 · NIMH · UNIVERSITY OF CALIFORNIA BERKELEY · PI FEINBERG, DAVID ALAN · 2016 to 2020
$5.1M
Integration of Diffusion MRI Fiber Tracking and CLARITY 3D Histology for Improved Neurosurgical TargetingR01NS095985 · NINDS · STANFORD UNIVERSITY · PI Jennifer A McNab · 2016 to 2026
$3.8M
Iron as an Imaging Biomarker for Inflammation in ADR01AG061120 · NIA · STANFORD UNIVERSITY · PI ZEINEH, MICHAEL M · 2019 to 2023
$3.5M
Next Generation 7T MRI Platform Upgrade with Parallel Transmit CapabilitiesS10RR026351 · NCRR · STANFORD UNIVERSITY · PI RUTT, BRIAN KEITH · 2011 to 2011
$600k
Mixed-Reality Neuronavigation for Transcranial Magnetic Stimulation Treatment of DepressionR21MH116484 · NIMH · STANFORD UNIVERSITY · PI MCNAB, JENNIFER A · 2018 to 2019
$449k
Lightsheet Microscope for Large-Scale Imaging of Cleared Tissue SamplesS10OD025091 · OD · STANFORD UNIVERSITY · PI DEISSEROTH, KARL A. · 2018 to 2018
$337k
Howard Hughes Medical InstituteNCRR NIH HHS S10 RR026351NIA NIH HHS R01 AG061120NIBIB NIH HHS P41 EB015891NIDA NIH HHS P50 DA042012NIDA NIH HHS R37 DA035377NIH HHS S10 OD025091NIMH NIH HHS R01 MH111444NIMH NIH HHS R21 MH116484NINDS NIH HHS R01 NS095985
6 · The paper itself

Abstract

Diffusion MRI (dMRI) represents one of the few methods for mapping brain fiber orientations non-invasively. Unfortunately, dMRI fiber mapping is an indirect method that relies on inference from measured diffusion patterns. Comparing dMRI results with other modalities is a way to improve the interpretation of dMRI data and help advance dMRI technologies. Here, we present methods for comparing dMRI fiber orientation estimates with optical imaging of fluorescently labeled neurofilaments and vasculature in 3D human and primate brain tissue cuboids cleared using CLARITY. The recent advancements in tissue clearing provide a new opportunity to histologically map fibers projecting in 3D, which represents a captivating complement to dMRI measurements. In this work, we demonstrate the capability to directly compare dMRI and CLARITY in the same human brain tissue and assess multiple approaches for extracting fiber orientation estimates from CLARITY data. We estimate the three-dimensional neuronal fiber and vasculature orientations from neurofilament and vasculature stained CLARITY images by calculating the tertiary eigenvector of structure tensors. We then extend CLARITY orientation estimates to an orientation distribution function (ODF) formalism by summing multiple sub-voxel structure tensor orientation estimates. In a sample containing part of the human thalamus, there is a mean angular difference of 19

Indexed as

AnimalsBrainDiffusion Magnetic Resonance ImagingGray MatterHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMacacaMultimodal ImagingNeuroimagingOptical ImagingWhite Matter

Identifiers

PMID33385546
PMCPMC7953593
OpenAlexW3113943319

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.