Evidence map›Paper›PMID 25781983›Full record

ArticlePloS one2015

Head-to-head comparison of two popular cortical thickness extraction algorithms: a cross-sectional and longitudinal study.

Alberto Redolfi, David Manset, Frederik Barkhof, Lars-Olof Wahlund, Tristan Glatard, Jean-François Mangin, Giovanni B Frisoni, neuGRID Consortium, for the Alzheimer’s Disease Neuroimaging Initiative

Registry-linked trialAbstract readComparative Study
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07731191 (Development of Digital Solutions for the Prediction of the Biological Mechanisms of Alzheimer's Disease Through the Analysis of Risk Factors), which is not on this map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing 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.

NCT07731191 narecruitingnot on this mapstarted 2026, after this paper: background citation

Development of Digital Solutions for the Prediction of the Biological Mechanisms of Alzheimer's Disease Through the Analysis of Risk Factors (PrevAI)

TypeinterventionalSponsorIRCCS Centro San Giovanni di Dio FatebenefratelliRan2026 to 2026Enrolled240ConditionsMild Cognitive Impairment (MCI), Subjective Cognitive Decline (SCD)ArmsDigital solution for the prediction of the biological mechanisms of Alzheimer's disease through the analysis of risk factors
3 · Its place in the literature

Who cites it

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

  1. Pooled it
  2. Pooled it
  3. Article
  4. Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2022
    Review
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  7. Decreased Cortical Thickness and Local Gyrification in Individuals with Subjective Cognitive Impairment.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2021
    Article
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  18. Kernel Methods for Riemannian Analysis of Robust Descriptors of the Cerebral Cortex.Information processing in medical imaging : proceedings of the ... conference · 2017
    Article
  19. Article
  20. Riemannian Statistical Analysis of Cortical Geometry with Robustness to Partial Homology and Misalignment.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2016
    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

8 authors.

Alberto RedolfiLaboratory of Epidemiology & Neuroimaging, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
David MansetGnúbila France, Imp Pres d'en Bas, Argonay, France.
Frederik BarkhofDepartment of Radiology, VU University Medical Center, Amsterdam, The Netherlands.
Lars-Olof WahlundDepartment of Neurobiology, Caring Sciences & Society, Division of Clinical Geriatrics Novum, Karolinska Institutet, Stockholm, Stockholm, Sweden.
Tristan GlatardCREATIS, CNRS, INSERM, University of Lyon, Lyon, France; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.
Jean-François ManginCATI, Neurospin, CEA, GIF/YVETTE, France.
Giovanni B FrisoniLaboratory of Epidemiology & Neuroimaging, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Laboratory of Neuroimaging of Aging, Memory Clinic and LANVIE, University Hospitals and University of Geneva, Geneva, Switzerland.
neuGRID Consortium, for the Alzheimer’s Disease Neuroimaging Initiative

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
UC Davis Alzheimer's Disease Core CenterP30AG010129 · NIA · UNIVERSITY OF CALIFORNIA DAVIS · PI DECARLI, CHARLES · 1991 to 2020
$28.3M
"MR Morphometrics and Cognitive Decline Rate in Large-Scale Aging Studies"K01AG030514 · NIA · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CARMICHAEL, OWEN T. · 2008 to 2012
$495k
NIA NIH HHS K01 AG030514NIA NIH HHS P30 AG010129NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

background and purposeThe measurement of cortical shrinkage is a candidate marker of disease progression in Alzheimer's. This study evaluated the performance of two pipelines: Civet-CLASP (v1.1.9) and Freesurfer (v5.3.0).

methodsImages from 185 ADNI1 cases (69 elderly controls (CTR), 37 stable MCI (sMCI), 27 progressive MCI (pMCI), and 52 Alzheimer (AD) patients) scanned at baseline, month 12, and month 24 were processed using the two pipelines and two interconnected e-infrastructures: neuGRID (https://neugrid4you.eu) and VIP (http://vip.creatis.insa-lyon.fr). The vertex-by-vertex cross-algorithm comparison was made possible applying the 3D gradient vector flow (GVF) and closest point search (CPS) techniques.

resultsThe cortical thickness measured with Freesurfer was systematically lower by one third if compared to Civet's. Cross-sectionally, Freesurfer's effect size was significantly different in the posterior division of the temporal fusiform cortex. Both pipelines were weakly or mildly correlated with the Mini Mental State Examination score (MMSE) and the hippocampal volumetry. Civet differed significantly from Freesurfer in large frontal, parietal, temporal and occipital regions (p<0.05). In a discriminant analysis with cortical ROIs having effect size larger than 0.8, both pipelines gave no significant differences in area under the curve (AUC). Longitudinally, effect sizes were not significantly different in any of the 28 ROIs tested. Both pipelines weakly correlated with MMSE decay, showing no significant differences. Freesurfer mildly correlated with hippocampal thinning rate and differed in the supramarginal gyrus, temporal gyrus, and in the lateral occipital cortex compared to Civet (p<0.05). In a discriminant analysis with ROIs having effect size larger than 0.6, both pipelines yielded no significant differences in the AUC.

conclusionsCivet appears slightly more sensitive to the typical AD atrophic pattern at the MCI stage, but both pipelines can accurately characterize the topography of cortical thinning at the dementia stage.

Indexed as

AlgorithmsMagnetic Resonance ImagingAgedAlzheimer DiseaseBrainCognitive DysfunctionCross-Sectional StudiesFemaleHippocampusHumansImage Processing, Computer-AssistedLongitudinal StudiesMaleROC CurveSensitivity and Specificity

Identifiers

PMID25781983
PMCPMC4364123

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Registered trials

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.