Evidence map›Paper›PMID 31682983›Full record

ArticleNeuroImage2020

White matter hyperintensities and their relationship to cognition: Effects of segmentation algorithm.

Meral A Tubi, Franklin W Feingold, Deydeep Kothapalli, Evan T Hare, Kevin S King, Paul M Thompson, Meredith N Braskie, Alzheimer’s Disease Neuroimaging Initiative

Abstract 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 40 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 2 pooled it
–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

40 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  17. Review
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  19. Cerebrovascular markers of WMH and infarcts in ADNI: A historical perspective and future directions.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Review
  20. Article
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

8 authors.

Meral A TubiImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA.
Franklin W FeingoldImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA; Stanford University, Stanford, CA, 94305, USA.
Deydeep KothapalliImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA.
Evan T HareImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA.
Kevin S KingHuntington Medical Research Institute, Imaging Division, Pasadena, CA, 91105, USA.
Paul M ThompsonImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA.
Meredith N BraskieImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA. Electronic address: braskie@usc.edu.
Alzheimer’s Disease Neuroimaging Initiative

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MICHAEL W WEINER · 2016 to 2026
$226.7M
Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
VASCULAR RISK AND COGNITIVE STATUS IN A LATINO POPULATIONP50AG005142 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ARANDA, MARIA P. · 1985 to 2019
$41.0M
USCADRC Diversity Supplement PachicanoP30AG066530 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI HELENA Chang CHUI, ARTHUR W TOGA · 2020 to 2026
$27.8M
TR&D3: Intrinsic Surface MappingP41EB015922 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI VAN HORN, JOHN DARRELL · 2012 to 2022
$14.1M
Health Disparities in Alzheimer's Disease and Mild Cognitive Impairment among Mexican AmericansR01AG054073 · NIA · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI O'BRYANT, SID E, TOGA, ARTHUR W · 2017 to 2021
$12.6M
Revision Supplement: Model-based cerebrovascular markers extracted from hemodynamic data for diagnosing MCI or AD and predicting disease progressionR01AG058162 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BILLINGER, SANDRA A, CHUI, HELENA CHANG · 2018 to 2022
$11.5M
Urban Air Pollution and Pathological Brain Aging: A Nationwide Twin Study in MenP01AG055367 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI FRANZ, CAROL ELAINE · 2018 to 2022
$11.5M
Growth factors, neuroinflammation, exercise, and brain integrityRF1AG041915 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2014 to 2014
$2.9M
VEGF's Relationship to Brain Aging Biomarkers and CognitionF31AG059356 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TUBI, MERAL · 2018 to 2020
$135k
NIA NIH HHS F31 AG059356NIA NIH HHS P01 AG055367NIA NIH HHS P30 AG066530NIA NIH HHS P50 AG005142NIA NIH HHS R01 AG054073NIA NIH HHS R01 AG058162NIA NIH HHS RF1 AG041915NIA NIH HHS U01 AG024904NIA NIH HHS U19 AG024904NIBIB NIH HHS P41 EB015922
6 · The paper itself

Abstract

White matter hyperintensities (WMHs) are brain white matter lesions that are hyperintense on fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) scans. Larger WMH volumes have been associated with Alzheimer's disease (AD) and with cognitive decline. However, the relationship between WMH volumes and cross-sectional cognitive measures has been inconsistent. We hypothesize that this inconsistency may arise from 1) the presence of AD-specific neuropathology that may obscure any WMH effects on cognition, and 2) varying criteria for creating a WMH segmentation. Manual and automated programs are typically used to determine segmentation boundaries, but criteria for those boundaries can differ. It remains unclear whether WMH volumes are associated with cognitive deficits, and which segmentation criteria influence the relationships between WMH volumes and clinical outcomes. In a sample of 260 non-demented participants (ages 55-90, 141 males, 119 females) from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we compared the performance of five WMH segmentation methods, by relating the WMH volumes derived using each method to both clinical diagnosis and composite measures of executive function and memory. To separate WMH effects on cognition from effects related to AD-specific processes, we performed analyses separately in people with and without abnormal cerebrospinal fluid amyloid levels. WMH volume estimates that excluded more diffuse, lower-intensity lesions were more strongly correlated with clinical diagnosis and cognitive performance, and only in those without abnormal amyloid levels. These findings may inform best practices for WMH segmentation, and suggest that AD neuropathology may mask WMH effects on clinical diagnosis and cognition.

Indexed as

CognitionAgedAged, 80 and overAlzheimer DiseaseAmyloid beta-PeptidesBone SubstitutesBrainCognitive DysfunctionFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedWhite MatterAlgiporeAmyloid beta-PeptidesBone SubstitutesAgingAmyloidCognitively normalExecutive functionMild cognitive impairmentMRI

Identifiers

PMID31682983
PMCPMC6981030

What OpenQuestion holds

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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.