Evidence map›Paper›PMID 30451343›Full record

ArticleHuman brain mapping2019

Discriminating Alzheimer's disease progression using a new hippocampal marker from T1-weighted MRI: The local surface roughness.

Carlos Platero, María Eugenia López, María Del Carmen Tobar, Miguel Yus, Fernando Maestu

Abstract read
In one paragraph

Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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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

5 authors.

Carlos PlateroHealth Science Technology Group, Universidad Politécnica de Madrid, Madrid, Spain.ORCID 0000-0003-3712-8297
María Eugenia LópezLaboratory of Cognitive and Computational Neuroscience UCM-UPM Centre for Biomedical Technology; Department of Experimental Psychology, Psychological Processes and Speech Therapy, Universidad Complutense de Madrid and Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.ORCID 0000-0002-3928-2629
María Del Carmen TobarHealth Science Technology Group, Universidad Politécnica de Madrid, Madrid, Spain.ORCID 0000-0002-7370-6835
Miguel YusRadiology Department, San Carlos Clinical Hospital, Madrid, Spain.
Fernando MaestuLaboratory of Cognitive and Computational Neuroscience UCM-UPM Centre for Biomedical Technology; Department of Experimental Psychology, Psychological Processes and Speech Therapy, Universidad Complutense de Madrid and Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.ORCID 0000-0002-3195-0071

Funding

Spanish Ministry of Economy and Competitiveness IJCI-2016-30662Spanish Ministry of Economy and Competitiveness PSI2009-14415-C03-01Spanish Ministry of Economy and Competitiveness PSI2012-38375-C03-01
6 · The paper itself

Abstract

Hippocampal atrophy is one of the main hallmarks of Alzheimer's disease (AD). However, there is still controversy about whether this sign is a robust finding during the early stages of the disease, such as in mild cognitive impairment (MCI) and subjective cognitive decline (SCD). Considering this background, we proposed a new marker for assessing hippocampal atrophy: the local surface roughness (LSR). We tested this marker in a sample of 307 subjects (normal control (NC) = 70, SCD = 87, MCI = 137, AD = 13). In addition, 97 patients with MCI were followed-up over a 3-year period and classified as stable MCI (sMCI) (n = 61) or progressive MCI (pMCI) (n = 36). We did not find significant differences using traditional markers, such as normalized hippocampal volumes (NHV), between the NC and SCD groups or between the sMCI and pMCI groups. However, with LSR we found significant differences between the sMCI and pMCI groups and a better ability to discriminate between NC and SCD. The classification accuracy of the LSR for NC and SCD was 68.2%, while NHV had a 57.2% accuracy. In addition, the classification accuracy of the LSR for sMCI and pMCI was 74.3%, and NHV had a 68.3% accuracy. Cox proportional hazards models adjusted for age, sex, and education were used to estimate the relative hazard of progression from MCI to AD based on hippocampal markers and conversion times. The LSR marker showed better prediction of conversion to AD than NHV. These results suggest the relevance of considering the LSR as a new hippocampal marker for the AD continuum.

Indexed as

Disease ProgressionAgedAged, 80 and overAgingAlgorithmsAlzheimer DiseaseBiomarkersCognitive DysfunctionEducational StatusFemaleFollow-Up StudiesHippocampusHumansLongitudinal StudiesMagnetic Resonance ImagingMaleBiomarkersAlzheimer's disease continuumhippocampal biomarkershippocampal segmentationlocal surface roughnessprogression to AD

Identifiers

PMID30451343
PMCPMC6865478

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Registered trials

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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.