Evidence map›Paper›PMID 35689933›Full record

ArticleJournal of stroke and cerebrovascular diseases : the official journal of National Stroke Association2022

Population-Based Prevalence of Infarctions on 3D Fluid-Attenuated Inversion Recovery (FLAIR) Imaging.

Petrice M Cogswell, Jeremiah A Aakre, Anna M Castillo, David S Knopman, Kejal Kantarci, Alejandro A Rabinstein, Ronald C Petersen, Clifford R Jack, Michelle M Mielke, Prashanthi Vemuri and 1 more

Open access · greenAbstract read
In one paragraph

Article in Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

9 citing papers in PubMed, 8 citations in OpenAlex.

  1. Eligibility for donanemab trial in a population-based study of cognitive aging.The journal of prevention of Alzheimer's disease · 2025
    Trial
  2. Observational
  3. Structure-preserving Image-quality Enhancement for 3D Synthetic FLAIR Using a 3D U-Net with Content and Style Losses.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026
    Article
  4. Ultra-fast MRI for dementia diagnosis and treatment eligibility: A prospective study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    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

11 authors at 2 institutions in 1 country.

Petrice M CogswellDepartment of Radiology, Mayo Clinic. Electronic address: Cogswell.petrice@mayo.edu.
Jeremiah A AakreDepartment of Quantitative Health Sciences, Mayo Clinic.
Anna M CastilloDepartment of Quantitative Health Sciences, Mayo Clinic.
David S KnopmanDepartment of Neurology, Mayo Clinic.
Kejal KantarciDepartment of Radiology, Mayo Clinic.
Alejandro A RabinsteinDepartment of Neurology, Mayo Clinic.
Ronald C PetersenDepartment of Neurology, Mayo Clinic.
Clifford R JackDepartment of Radiology, Mayo Clinic.
Michelle M MielkeDepartment of Quantitative Health Sciences, Mayo Clinic.
Prashanthi VemuriDepartment of Neurology, Mayo Clinic.
Jonathan Graff-RadfordDepartment of Neurology, Mayo Clinic.
Mayo Clinic in Arizona · USWinnMed · US

Funding

SUPPLEMENT TO ALZHEIMERS DISEASE PATIENT REGISTRYU01AG006786 · NIA · MAYO CLINIC ROCHESTER · PI GRAFF-RADFORD, JONATHAN, JACK, CLIFFORD R. · 1986 to 2023
$49.6M
Research Education ComponentP30AG062677 · NIA · MAYO CLINIC ROCHESTER · PI DAVID S KNOPMAN · 2019 to 2026
$33.5M
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
Development, Validation, and Application of an Imaging based CVD ScaleR01NS097495 · NINDS · MAYO CLINIC ROCHESTER · PI VEMURI, PRASHANTHI · 2016 to 2020
$2.9M
Cerebral Microbleeds in the Aging PopulationK76AG057015 · NIA · MAYO CLINIC ROCHESTER · PI GRAFF-RADFORD, JONATHAN · 2017 to 2021
$1.2M
NIA NIH HHS K76 AG057015NIA NIH HHS P30 AG062677NIA NIH HHS R01 AG041851NIA NIH HHS R01 AG056366NIA NIH HHS R37 AG011378NIA NIH HHS U01 AG006786NINDS NIH HHS R01 NS097495
6 · The paper itself

Abstract

objectivesTo report population-based, age-specific prevalence of infarctions as identified via 3D fluid-attenuated inversion recovery (FLAIR) imaging. MATERIALS AND

methodsParticipants without dementia in the Mayo Clinic Study of Aging (MCSA), a population-based study in Olmsted County, MN, age 50-89 who underwent 3D FLAIR imaging between 2017 and 2020 were included. Infarctions per participant were determined via visual interpretation. Inter- and intra-reader reliability were calculated. Infarction prevalence on 3D FLAIR was derived by standardization to the Olmsted County population and was compared to that previously reported on 2D FLAIR imaging.

resultsAmong 580 participants (mean age 71 years, 46% female) the prevalence (95% confidence interval) of any infarction was 5.0% (0.0%-9.9%) at age 50-59 years and 38.8% (28.6%-49.0%) at 80-89 years. In addition to increasing with age, the prevalence varied by sex and type of infarction. Prevalence estimates of cortical infarcts were 0.9% (0.0%-2.7%) at age 50-59 years and 20.2% (10.7%-29.7%) at 80-89 years and lacunar infarcts 4.1% (0.0%-8.8%) at age 50-59 years and 31.2% (21.5%-41.0%) at 80-89 years. Prevalence estimates of any infarction by sex were: men, 8.7% (0.0%-18.7%) at 50-59 years and 54.9% (41.0%-68.8%) at 80-89 years and women, 2.4% (0.0%-7.3%) at age 50-59 years and 27.3% (12.9%-41.7%) at 80-89 years. Intra- and inter- reader reliability were very good (kappa = 0.85 and 0.82, respectively). After adjusting for age, sex and education, individuals imaged with 3D FLAIR were 1.5 times (95% CI 1.2-1.8, p<0.001) more likely to be identified as positive for infarction compared to those imaged with 2D FLAIR.

conclusionsInfarction prevalence increases with age and is greater in men than women. Infarction prevalence on 3D FLAIR imaging, which has become more widely implemented as an alternative to 2D FLAIR over the past several years, will be a useful reference in future work.

Indexed as

AgingMagnetic Resonance ImagingAgedAged, 80 and overFemaleHumansImaging, Three-DimensionalInfarctionMaleMiddle AgedPrevalenceReproducibility of ResultsCerebrovascular diseaseInfarction prevalenceMagnetic resonance imaging (MRI)Population studies

Identifiers

PMID35689933
PMCPMC9329259
OpenAlexW4282929709

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.