Evidence map›Paper›PMID 41840283›Full record

ReviewRadiologie (Heidelberg, Germany)2026

[Magnetic resonance imaging in dementia].

Umut Yilmaz

Abstract readEnglish AbstractReview
PubMed Publisher
In one paragraph

Review in Radiologie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Umut YilmazKlinik für Diagnostische und Interventionelle Neuroradiologie, Universitätsklinikum des Saarlandes, Kirrberger Straße, 66424, Homburg-Saar, Deutschland. umut.yilmaz@uks.eu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) plays a pivotal role in the diagnostic work-up of dementia. In addition to excluding secondary and potentially treatable causes, MRI enables the identification of characteristic neuroanatomical patterns that support the differentiation between major dementia entities. In daily clinical practice, the diagnostic value of MRI relies primarily on systematic visual assessment and semiquantitative evaluation of regional atrophy patterns and accompanying vascular pathology. In recent years, automated morphometric analyses and artificial intelligence (AI)-based approaches have gained increasing attention. While these techniques promise objective quantification of structural brain changes, their clinical utility on an individual patient level remains limited. High interindividual variability of brain volumes, technical dependencies, and normative database issues restrict their diagnostic accuracy and may lead to overinterpretation of numerical results if used outside the appropriate context. This review provides a clinically oriented overview of MRI in dementia imaging. Emphasis is placed on pattern-based visual assessment, the role of established semiquantitative rating scales and a critical appraisal of automated morphometry. A practical imaging algorithm is proposed that integrates visual analysis, rating scales and quantitative tools in a structured manner. The aim is to highlight the realistic clinical value of MRI and to emphasize its role as an interpretative rather than a purely numerical diagnostic modality.

Indexed as

DementiaMagnetic Resonance ImagingAlgorithmsBrainHumansAlzheimer’s diseaseFrontotemporal dementiaMorphometryPattern recognitionSemiquantitative rating scales

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

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 Socratic graph.