Evidence map›Paper›PMID 32931942›Full record

ArticleNeuroImage2020

Nonlinear associations of neurite density and myelin content with age revealed using multicomponent diffusion and relaxometry magnetic resonance imaging.

Wenshu Qian, Nikkita Khattar, Luis E Cortina, Richard G Spencer, Mustapha Bouhrara

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
2.7field-weighted citation impact, top 8% 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

33 citing papers in PubMed, 44 citations in OpenAlex.

  1. Review
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  6. Multi-Omics Validation of Myelin Water Fraction as a Myelin-Specific MRI Biomarker.medRxiv : the preprint server for health sciences · 2025
    Article
  7. Review
  8. Article
  9. Review
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  11. Article
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  14. Diffusion MRI of the Hippocampus.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Review
  15. Article
  16. Article
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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

5 authors at 1 institution in 1 country.

Wenshu QianMagnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA.
Nikkita KhattarMagnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA.
Luis E CortinaMagnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA.
Richard G SpencerMagnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA.
Mustapha BouhraraMagnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA. Electronic address: bouhraram@mail.nih.gov.
National Institutes of Health · US

Funding

Intramural NIH HHS Z99 AG999999
6 · The paper itself

Abstract

Most magnetic resonance imaging (MRI) studies investigating the relationship between regional brain myelination or axonal density and aging have relied upon nonspecific methods to probe myelin and axonal content, including diffusion tensor imaging and relaxation time mapping. While these studies have provided pivotal insights into changes in cerebral architecture with aging and pathology, details of the underlying microstructural alterations have not been fully elucidated. In the current study, we used the BMC-mcDESPOT analysis, a direct and specific multicomponent relaxometry method for imaging of myelin water fraction (MWF), a marker of myelin content, and NODDI, an emerging multicomponent diffusion technique, for neurite density index (NDI) imaging, a proxy of axonal density. We investigated age-related differences in MWF and NDI in several white matter brain regions in a cohort of cognitively unimpaired participants over a wide age range. Our results indicate a quadratic, inverted U-shape, relationship between MWF and age in all brain regions investigated, suggesting that myelination continues until middle age followed by a decrease at older ages, in agreement with previous work. We found a similarly complex regional association between NDI and age, with several cerebral structures also exhibiting a quadratic, inverted U-shape, relationship. This novel observation suggests an increase in axonal density until the fourth decade of age followed by a rapid loss at older ages. We also observed that these age-related differences in MWF and NDI vary across different brain regions, as expected. Finally, our study indicates no significant association between MWF and NDI in most cerebral structures investigated, although this association approached significance in a limited number of brain regions, indicating the complementary nature of their information and encouraging further investigation. Overall, we find evidence of nonlinear associations between age and myelin or axonal density in a sample of well-characterized adults, using direct myelin and axonal content imaging methods.

Indexed as

AdultAgedAged, 80 and overAgingAxonsBrainDiffusion Magnetic Resonance ImagingHumansMiddle AgedMyelin SheathNeuritesWhite MatterYoung AdultAxonal densityBMC-mcDESPOTMyelin water fractionNODDINormal agingQuantitative MRI

Identifiers

PMID32931942
PMCPMC7775614
OpenAlexW3084599580

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.