Evidence map›Paper›PMID 38987827›Full record

ArticleAlzheimer's research & therapy2024

Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population?

Aishwarya Pradeep, Sheelakumari Raghavan, Scott A Przybelski, Gregory M Preboske, Christopher G Schwarz, Val J Lowe, David S Knopman, Ronald C Petersen, Clifford R Jack, Jonathan Graff-Radford and 2 more

Abstract read
In one paragraph

Article in Alzheimer's research & therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
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  7. Risk factors and prediction model of dysphagia in patients with recent small subcortical infarct.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
    Article
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  15. Plasma NfL and GFAP for predicting VCI and related brain changes in community and clinical cohorts.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  16. Article
  17. Article
  18. Review
  19. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Aishwarya PradeepMayo Clinic Alix School of Medicine, Rochester, MN, 55905, USA.
Sheelakumari RaghavanDepartment of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Scott A PrzybelskiDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA.
Gregory M PreboskeDepartment of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Christopher G SchwarzDepartment of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Val J LoweDepartment of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
David S KnopmanDepartment of Neurology, Mayo Clinic, Rochester, MN, 55905, USA.
Ronald C PetersenDepartment of Neurology, Mayo Clinic, Rochester, MN, 55905, USA.
Clifford R JackDepartment of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Jonathan Graff-RadfordDepartment of Neurology, Mayo Clinic, Rochester, MN, 55905, USA.
Petrice M CogswellDepartment of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Prashanthi VemuriDepartment of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. vemuri.prashanthi@mayo.edu.

Funding

SUPPLEMENT TO ALZHEIMERS DISEASE PATIENT REGISTRYU01AG006786 · NIA · MAYO CLINIC ROCHESTER · PI GRAFF-RADFORD, JONATHAN, JACK, CLIFFORD R. · 1986 to 2023
$49.6M
THE PGRN/TDP-43 AXIS IN ALZHEIMER?S DISEASE AND NEURODEGENERATIONP50AG016574 · NIA · MAYO CLINIC ROCHESTER · PI BU, GUOJUN · 1999 to 2018
$36.9M
Investigating Resistance and Resilience Mechanisms in Alzheimer’s DiseaseR01AG056366 · NIA · MAYO CLINIC ROCHESTER · PI PRASHANTHI VEMURI · 2017 to 2026
$7.0M
Disease pathways in the population determined by amyloid, tau, and neurodegeneration imaging biomarkersR37AG011378 · NIA · MAYO CLINIC ROCHESTER · PI CLIFFORD R. JACK · 2018 to 2026
$6.8M
Validating the New Criteria for Preclinical Alzheimer's diseaseR01AG041851 · NIA · MAYO CLINIC ROCHESTER · PI JACK, CLIFFORD R., KNOPMAN, DAVID S · 2012 to 2021
$6.3M
MarkVCID Validation in the General CommunityUF1NS125417 · NINDS · MAYO CLINIC ROCHESTER · PI PETERSEN, RONALD C, VEMURI, PRASHANTHI · 2021 to 2023
$6.1M
Development, Validation, and Application of an Imaging based CVD ScaleR01NS097495 · NINDS · MAYO CLINIC ROCHESTER · PI VEMURI, PRASHANTHI · 2016 to 2020
$2.9M
Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology ProjectR33AG058738 · NIA · MAYO CLINIC ROCHESTER · PI LEBRASSEUR, NATHAN K, OLSON, JANET E · 2020 to 2022
$2.4M
"What is N?" Towards operationalizing neurodegeneration in Alzheimer's and related dementiasRF1AG069052 · NIA · MAYO CLINIC ROCHESTER · PI GRAFF-RADFORD, JONATHAN, MIELKE, MICHELLE M · 2021 to 2021
$2.4M
Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology ProjectR21AG058738 · NIA · MAYO CLINIC ROCHESTER · PI LEBRASSEUR, NATHAN K, OLSON, JANET E · 2018 to 2019
$437k
NIA NIH HHS P50 AG016574NIA NIH HHS R01 AG056366NIA NIH HHS R21 AG058738NIA NIH HHS R33 AG058738NIA NIH HHS R37 AG011378NIA NIH HHS RF1 AG069052NIH HHS R01 AG041851NIH HHS R01 NS097495NIH HHS U01 AG006786NINDS NIH HHS R01 NS097495NINDS NIH HHS UF1 NS125417
6 · The paper itself

Abstract

backgroundWhite matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease (AD) pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, AD imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging.

methodsWe identified 1144 participants from the Mayo Clinic Study of Aging consisting of a population-based sample from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET, and tau-PET standardized uptake value ratio, automated WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC).

resultsPeriventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (p < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (R = 0.07, p = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.82 and 0.74). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97) and showed poor correlation with amyloid and tau PET markers similar to the visual grading.

conclusionOur study investigated risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.

Indexed as

Alzheimer DiseaseMagnetic Resonance ImagingPositron-Emission TomographyWhite MatterAgedAged, 80 and overBrainFemaleHumansMaleMiddle AgedReproducibility of Resultstau Proteinstau ProteinsAlzheimer’s diseaseDeep white matter hyperintensityFazekas scorePeriventricular white matter hyperintensityWhite matter hyperintensities

Identifiers

PMID38987827
PMCPMC11234605

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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.