Evidence map›Paper›PMID 28365421›Full record

ArticleNeuroImage2017

Quantitative validation of a nonlinear histology-MRI coregistration method using generalized Q-sampling imaging in complex human cortical white matter.

Mihika Gangolli, Laurena Holleran, Joong Hee Kim, Thor D Stein, Victor Alvarez, Ann C McKee, David L Brody

Abstract read
In one paragraph

Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

7 authors.

Mihika GangolliDepartment of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA.
Laurena HolleranDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
Joong Hee KimDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
Thor D SteinBoston University Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA.
Victor AlvarezBoston University Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA.
Ann C McKeeBoston University Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA.
David L BrodyDepartment of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA. Electronic address: brodyd@neuro.wustl.edu.

Funding

Washington University Center for Translational NeuroscienceP30NS057105 · NINDS · WASHINGTON UNIVERSITY · PI HOLTZMAN, DAVID M. · 2006 to 2011
$8.7M
CTE and Posttraumatic Neurodegeneration: Neuropathology and Ex Vivo ImagingU01NS086659 · NINDS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI MCKEE, ANN C. · 2014 to 2017
$6.1M
NINDS NIH HHS P30 NS057105NINDS NIH HHS U01 NS086659
6 · The paper itself

Abstract

Advanced diffusion MRI methods have recently been proposed for detection of pathologies such as traumatic axonal injury and chronic traumatic encephalopathy which commonly affect complex cortical brain regions. However, radiological-pathological correlations in human brain tissue that detail the relationship between the multi-component diffusion signal and underlying pathology are lacking. We present a nonlinear voxel based two dimensional coregistration method that is useful for matching diffusion signals to quantitative metrics of high resolution histological images. When validated in ex vivo human cortical tissue at a 250×250×500 μm spatial resolution, the method proved robust in correlations between generalized q-sampling imaging and histologically based white matter fiber orientations, with r=0.94 for the primary fiber direction and r=0.88 for secondary fiber direction in each voxel. Importantly, however, the correlation was substantially worse with reduced spatial resolution or with fiber orientations derived using a diffusion tensor model. Furthermore, we have detailed a quantitative histological metric of white matter fiber integrity termed power coherence capable of distinguishing architecturally complex but intact white matter from disrupted white matter regions. These methods may allow for more sensitive and specific radiological-pathological correlations of neurodegenerative diseases affecting complex gray and white matter.

Indexed as

Diffusion Magnetic Resonance ImagingAnimalsAxonsBrainBrain Injuries, TraumaticBrain MappingDiffusion Tensor ImagingFrontal LobeHumansImage Processing, Computer-AssistedMaleMiceWhite MatterChronic Traumatic EncephalopathyDiffusion MRIGeneralized Q-sampling ImagingRadiological-Pathological CorrelationsWhite Matter Injury

Identifiers

PMID28365421
PMCPMC5497585

What OpenQuestion holds

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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.