Evidence map›Paper›PMID 25193518›Full record

ReviewNeuroscience bulletin2014

Neurostatistical imaging for diagnosing dementia: translational approach from laboratory neuroscience to clinical routine.

Etsuko Imabayashi, Tomio Inoue

Abstract readReview
In one paragraph

Review in Neuroscience bulletin, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Neuro-molecular imaging.Neuroscience bulletin · 2014
    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

2 authors.

Etsuko ImabayashiIntegrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo, 187-8551, Japan, embysh@ncnp.go.jp.
Tomio Inoue

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Statistical analysis in neuroimaging (referred to as "neurostatistical imaging") is important in clinical neurology. Here, neurostatistical imaging and its superiority for diagnosing dementia are reviewed. In neurodegenerative dementia, the proportional distribution of brain perfusion, metabolism, or atrophy is important for understanding the symptoms and status of patients and for identifying regions of pathological damage. Although absolute quantitative changes are important in vascular disease, they are less important than relative values in neurodegenerative dementia. Even under resting conditions in healthy individuals, the distribution of brain perfusion and metabolism is asymmetrical and differs among areas. To detect small changes, statistical analysis such as the Z-score--the number of standard deviations by which a patient's voxel value differs from the normal mean value--comparing normal controls is useful and also facilitates clinical assessment. Our recent finding of a longitudinal one-year reduction of glucose metabolism around the olfactory tract in Alzheimer's disease using the recently-developed DARTEL normalization procedure is also presented. Furthermore, a newly-developed procedure to assess brain atrophy with CT-based voxel-based morphometry is illustrated. The promising possibilities of CT in neurostatistical imaging are also presented.

Indexed as

Statistics as TopicAlzheimer DiseaseBrainDementiaHumansMagnetic Resonance ImagingNeuroimagingPositron-Emission TomographyTomography, Emission-Computed, Single-PhotonTranslational Research, Biomedical

Identifiers

PMID25193518
PMCPMC5562589

What OpenQuestion 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 OpenQuestion graph.