Evidence map›Paper›PMID 37148501›Full record

ArticleHuman brain mapping2023

Young versus older subject diffusion magnetic resonance imaging data for virtual white matter lesion tractography.

Mohammad Taghvaei, Philip Cook, Shokufeh Sadaghiani, Banafsheh Shakibajahromi, William Tackett, Sudipto Dolui, Debarun De, Christopher Brown, Pulkit Khandelwal, Paul Yushkevich and 3 more

Open access · goldAbstract read
In one paragraph

Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Sub-Networks of the Brain RHuman brain mapping · 2026
    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

13 authors at 2 institutions in 1 country.

Mohammad TaghvaeiDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID 0000-0001-9757-1560
Philip CookDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Shokufeh SadaghianiDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Banafsheh ShakibajahromiDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
William TackettDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Sudipto DoluiDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Debarun DeDepartment of Computer Engineering, University of Illinois, Urbana, Illinois, USA.
Christopher BrownDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Pulkit KhandelwalDepartment of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Paul YushkevichDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Sandhitsu DasDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
David A WolkDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
John A DetreDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
University of Pennsylvania · USUniversity of Illinois Urbana-Champaign · US

Funding

Research Education ComponentP30AG072979 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DAVID A WOLK · 2021 to 2026
$24.8M
MAPPING THE HUMAN CONNECTOME DURING TYPICAL AGINGU01AG052564 · NIA · WASHINGTON UNIVERSITY · PI SALAT, DAVID H, TERPSTRA, MELISSA J · 2016 to 2020
$18.9M
Novel Biomarkers of Small Vessel Contributions to Vascular Cognitive Impairment and Dementia (VCID)R01NS111115 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DETRE, JOHN A, WANG, JIANHUA · 2019 to 2023
$3.7M
Impact of white matter hyperintensities on structural connectivity and cognitionR21AG070434 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DETRE, JOHN A · 2020 to 2020
$446k
Cerebral Blood Flow trajectory in the Alzheimer's Disease continuumR03AG063213 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DOLUI, SUDIPTO · 2019 to 2020
$323k
NIA NIH HHS P30 AG072979NIA NIH HHS R03 AG063213NIA NIH HHS R21 AG070434NIA NIH HHS U01 AG052564NINDS NIH HHS R01 NS111115
6 · The paper itself

Abstract

White matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal-appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP-Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age-matched normative data.

Indexed as

LeukoaraiosisWhite MatterAgedAgingBrainDiffusion Magnetic Resonance ImagingHumansMagnetic Resonance Imagingbrain connectivitytractographyvirtual lesionwhite matter hyperintensity

Identifiers

PMID37148501
PMCPMC10258527
OpenAlexW4372327325

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.