Evidence map›Paper›PMID 30128275›Full record

ArticleNeuroImage. Clinical2018

Automatic normative quantification of brain tissue volume to support the diagnosis of dementia: A clinical evaluation of diagnostic accuracy.

Meike W Vernooij, Bas Jasperse, Rebecca Steketee, Marcel Koek, Henri Vrooman, M Arfan Ikram, Janne Papma, Aad van der Lugt, Marion Smits, Wiro J Niessen

Abstract read
In one paragraph

Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Quantification of amyloid PET for future clinical use: a state-of-the-art review.European journal of nuclear medicine and molecular imaging · 2022
    Review
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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

10 authors.

Meike W VernooijRadiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands. Electronic address: m.vernooij@erasmusmc.nl.
Bas JasperseRadiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
Rebecca SteketeeRadiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
Marcel KoekRadiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Medical informatics, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
Henri VroomanRadiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Medical informatics, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
M Arfan IkramRadiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Neurology of Erasmus, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
Janne PapmaNeurology of Erasmus, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
Aad van der LugtRadiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
Marion SmitsRadiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
Wiro J NiessenRadiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Medical informatics, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Faculty of Applied Sciences, Delft University of Technology, Delft, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To assesses whether automated brain image analysis with quantification of structural brain changes improves diagnostic accuracy in a memory clinic setting. Methods: In 42 memory clinic patients, we evaluated whether automated quantification of brain tissue volumes, hippocampal volume and white matter lesion volume improves diagnostic accuracy for Alzheimer's disease (AD) and frontotemporal dementia (FTD), compared to visual interpretation. Reference data were derived from a dementia-free aging population ( Results: Providing radiologists with only quantitative data decreased diagnostic accuracy both for AD and FTD compared to conventional visual rating. The combination of quantitative with visual information, however, led to better diagnostic accuracy compared to only visual ratings for AD. This was not the case for FTD. Conclusion: Quantitative assessment of structural brain MRI combined with a reference standard in addition to standard visual assessment may improve diagnostic accuracy in a memory clinic setting.

Indexed as

AgedBrainDementiaDiagnosis, DifferentialFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedOrgan SizeRetrospective Studies

Identifiers

PMID30128275
PMCPMC6096052

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.