Evidence map›Paper›PMID 30209854›Full record

ArticleJournal of magnetic resonance imaging : JMRI2019

T2 Relaxometry and Diffusion Tensor Indices of the Hippocampus and Entorhinal Cortex Improve Sensitivity and Specificity of MRI to Detect Amnestic Mild Cognitive Impairment and Alzheimer's Disease Dementia.

Michael J Knight, Alfie Wearn, Elizabeth Coulthard, Risto A Kauppinen

Open access · greenAbstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2019. 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
3.2field-weighted citation impact, top 7% 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

22 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Quantitative MRI of the hippocampus reveals microstructural trajectories of aging and Alzheimer's disease pathology.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  3. Review
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  9. Simultaneous high-resolution TMagnetic resonance in medicine · 2022
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  17. Review
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  19. Article
  20. Fast TMagnetic resonance in medicine · 2020
    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

4 authors at 1 institution in 1 country.

Michael J KnightSchool of Experimental Psychology, University of Bristol, Bristol, United Kingdom.
Alfie WearnBristol Institute of Clinical Neuroscience, North Bristol NHS Trust, Southmead Hospital, Bristol, United Kingdom.
Elizabeth CoulthardBristol Institute of Clinical Neuroscience, North Bristol NHS Trust, Southmead Hospital, Bristol, United Kingdom.
Risto A KauppinenSchool of Experimental Psychology, University of Bristol, Bristol, United Kingdom.
University of Bristol · GB

Funding

BRACE Charity Alzheimer's Research UKThe Dunhill Medical Trust R385/1114The Dunhill Medical Trust R385_1114
6 · The paper itself

Abstract

backgroundQuantitative T2 and diffusion MRI indices inform about tissue state and microstructure, both of which may be affected by pathology before tissue atrophy. PURPOSE: To evaluate the capability of both volumetric and quantitative MRI (qMRI) of the hippocampus and entorhinal cortex (EC) for classification of amnestic mild cognitive impairment (aMCI) and Alzheimer's disease dementia (ADD). STUDY TYPE: Retrospective cross-sectional study. POPULATION: Consecutive cohorts of healthy age-matched controls (n = 62), aMCI patients (n = 25), and ADD patients (n = 14). FIELD STRENGTH/SEQUENCE: 3T using T1-weighted imaging, T2-weighted imaging, T2 relaxometry and diffusion tensor imaging (DTI). ASSESSMENT: Montreal Cognitive Assessment and paired associate learning tests for cognitive state. Hippocampal subfield volumes by the automated segmentation of hippocampal subfields system from structural brain images. T2 relaxation time and DTI indices quantified for hippocampal subfields. The fraction of voxels with high T2 values (>20 ms above subfield median) was calculated and regionalized for hippocampus and EC. STATISTICAL TESTS: Support vector machine and receiver operating characteristic analyses from cognitive and MRI data.

resultsqMRI classified aMCI and ADD with excellent sensitivity (79.0% and 94.5%, respectively) and specificity (85.6% and 86.1%, respectively), superior to volumes alone (70.0% and 84.5% for respective sensitivities; 82.2 and 91.1 for respective specificities) and similar to cognitive tests (61.7% and 87.5% for respective sensitivities; 88.2% and 90.7% for respective specificities). Regions of high T2 are dispersed throughout each hippocampal subfield in aMCI and ADD with higher concentration than controls, and was most pronounced in the EC. No other individual qMRI marker than EC volume can separate aMCI from ADD, however. DATA

conclusionqMRI markers of hippocampal and entorhinal tissue states are sensitive and specific classifiers of aMCI and ADD. They may serve as markers of a neurodegenerative state preceding volume loss. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:445-455.

Indexed as

Magnetic Resonance ImagingAgedAged, 80 and overAlzheimer DiseaseAmnesiaAtrophyBrainCognitionCognitive DysfunctionCross-Sectional StudiesDementiaDiffusion Tensor ImagingEntorhinal CortexFemaleHippocampusHumans

Identifiers

PMID30209854
PMCPMC6330085
OpenAlexW2891900152

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.