Evidence map›Paper›PMID 35253765›Full record

ArticleJournal of Alzheimer's disease : JAD2022

Quantified Brain Magnetic Resonance Imaging Volumes Differentiate Behavioral Variant Frontotemporal Dementia from Early-Onset Alzheimer's Disease.

Somayeh Meysami, Cyrus A Raji, Mario F Mendez

Open access · greenAbstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  4. Review
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

3 authors at 2 institutions in 1 country.

Somayeh MeysamiDepartment of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Cyrus A RajiMallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University, St. Louis, MO, USA.
Mario F MendezDepartment of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
University of California, Los Angeles · USWashington University in St. Louis · US

Funding

Washington University Institute of Clinical and Translational SciencesKL2TR000450 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$8.8M
Neuroinflammation and Alzheimer's Disease Imaging Biomarkers in Midlife ObesityRF1AG072637 · NIA · WASHINGTON UNIVERSITY · PI RAJI, CYRUS A · 2021 to 2021
$2.3M
Early-Onset Alzheimer's Disease Phenotypes: Neuropsychology and Neural NetworksRF1AG050967 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MENDEZ, MARIO F. · 2016 to 2016
$1.9M
Neuroinflammation and Alzheimer's Disease Imaging Biomarkers in Midlife ObesityR01AG072637 · NIA · WASHINGTON UNIVERSITY · PI RAJI, CYRUS A · 2024 to 2025
$1.4M
NCATS NIH HHS KL2 TR000450NIA NIH HHS R01 AG072637NIA NIH HHS RF1 AG050967NIA NIH HHS RF1 AG072637
6 · The paper itself

Abstract

backgroundThe differentiation of behavioral variant frontotemporal dementia (bvFTD) from early-onset Alzheimer's disease (EOAD) by clinical criteria can be inaccurate. The volumetric quantification of clinically available magnetic resonance (MR) brain scans may facilitate early diagnosis of these neurodegenerative dementias.

objectiveTo determine if volumetric quantification of brain MR imaging can identify persons with bvFTD from EOAD.

methods3D T1 MR brain scans of 20 persons with bvFTD and 45 with EOAD were compared using Neuroreader to measure subcortical, and lobar volumes, and Volbrain for hippocampal subfields. Analyses included: 1) discriminant analysis with leave one out cross-validation; 2) input of predicted probabilities from this process into a receiver operator characteristic (ROC) analysis; and 3) Automated linear regression to identify predictive regions.

resultsBoth groups were comparable in age and sex with no statistically significant differences in symptom duration. bvFTD had lower volume percentiles in frontal lobes, thalamus, and putamen. EOAD had lower parietal lobe volumes. ROC analyses showed 99.3% accuracy with Neuroreader percentiles and 80.2% with subfields. The parietal lobe was the most predictive percentile. Although there were differences in hippocampal (particularly left CA2-CA3) subfields, it did not add to the discriminant analysis.

conclusionPercentiles from an MR based volumetric quantification can help differentiate between bvFTD from EOAD in routine clinical care. Use of hippocampal subfield volumes does not enhance the diagnostic separation of these two early-onset dementias.

Indexed as

Alzheimer DiseaseFrontotemporal DementiaBrainHumansMagnetic Resonance ImagingNeuroimagingBehavioral variant frontal temporal dementiaearly-onset Alzheimer’s diseasevolumetric MRI

Identifiers

PMID35253765
PMCPMC9123600
OpenAlexW4214896293

What OpenQuestion holds

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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.