Evidence map›Paper›PMID 38640154›Full record

ArticleJournal of Alzheimer's disease : JAD2024

Sulcal Morphometry Predicts Mild Cognitive Impairment Conversion to Alzheimer's Disease.

Giovanni Sighinolfi, Micaela Mitolo, Fabrizio Pizzagalli, Michelangelo Stanzani-Maserati, Daniel Remondini, Magali Jane Rochat, Elena Cantoni, Greta Venturi, Gianfranco Vornetti, Fiorina Bartiromo and 5 more

Open access · greenAbstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

5 citing papers in PubMed, 5 citations in OpenAlex.

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  5. Review
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

15 authors at 5 institutions in 1 country.

Giovanni SighinolfiIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Micaela MitoloIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Fabrizio PizzagalliDepartment of Neurosciences, University of Turin, Turin, Italy.
Michelangelo Stanzani-MaseratiIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Daniel RemondiniDepartment of Physics and Astronomy, University of Bologna, Bologna, Italy.
Magali Jane RochatIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Elena CantoniIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Greta VenturiIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Gianfranco VornettiIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Fiorina BartiromoIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Sabina CapellariIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Rocco LiguoriIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Caterina TononIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Claudia TestaDepartment of Physics and Astronomy, University of Bologna, Bologna, Italy.
Raffaele LodiIRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Istituti di Ricovero e Cura a Carattere Scientifico · ITIstituto delle Scienze Neurologiche di Bologna · ITUniversity of Bologna · ITUniversity of Parma · ITUniversity of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Being able to differentiate mild cognitive impairment (MCI) patients who would eventually convert (MCIc) to Alzheimer's disease (AD) from those who would not (MCInc) is a key challenge for prognosis. Objective: This study aimed to investigate the ability of sulcal morphometry to predict MCI progression to AD, dedicating special attention to an accurate identification of sulci. Methods: Twenty-five AD patients, thirty-seven MCI and twenty-five healthy controls (HC) underwent a brain-MR protocol (1.5T scanner) including a high-resolution T1-weighted sequence. MCI patients underwent a neuropsychological assessment at baseline and were clinically re-evaluated after a mean of 2.3 years. At follow-up, 12 MCI were classified as MCInc and 25 as MCIc. Sulcal morphometry was investigated using the BrainVISA framework. Consistency of sulci across subjects was ensured by visual inspection and manual correction of the automatic labelling in each subject. Sulcal surface, depth, length, and width were retrieved from 106 sulci. Features were compared across groups and their classification accuracy in predicting MCI conversion was tested. Potential relationships between sulcal features and cognitive scores were explored using Spearman's correlation. Results: The width of sulci in the temporo-occipital region strongly differentiated between each pair of groups. Comparing MCIc and MCInc, the width of several sulci in the bilateral temporo-occipital and left frontal areas was significantly altered. Higher width of frontal sulci was associated with worse performances in short-term verbal memory and phonemic fluency. Conclusions: Sulcal morphometry emerged as a strong tool for differentiating HC, MCI, and AD, demonstrating its potential prognostic value for the MCI population.

Indexed as

Alzheimer DiseaseCognitive DysfunctionDisease ProgressionMagnetic Resonance ImagingNeuropsychological TestsAgedAged, 80 and overBrainFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedAlzheimer’s diseasebrain sulcicortical thicknessMCI conversionmild cognitive impairmentsulcalmorphometry

Identifiers

PMID38640154
PMCPMC11191431
OpenAlexW4394951773

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.