Evidence map›Paper›PMID 41996765›Full record

ArticleNeuroImage. Clinical2026

Mapping the multiscale neuroanatomy of GRN-related frontotemporal dementia using mode-based morphometry.

Enrico Premi, Giada Bianchetti, Valeria Bracca, Giulia Campana, Elena Gatti, Trang Cao, Alex Fornito, Valentina Cantoni, Sonia Bellini, Daniele Corbo and 5 more

Abstract read
In one paragraph

Article in NeuroImage. Clinical, 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

15 authors.

Enrico PremiStroke Unit, ASST Spedali Civili, Brescia, Italy. Electronic address: zedtower@gmail.com.
Giada BianchettiLaboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. Electronic address: gbianchetti@fatebenefratelli.eu.
Valeria BraccaDepartment of Molecular and Translational Medicine, University of Brescia, Brescia, Italy; Department of Clinical and Experimental Sciences, University of Brescia, Italy. Electronic address: valeria.bracca@gmail.com.
Giulia CampanaDepartment of Molecular and Translational Medicine, University of Brescia, Brescia, Italy. Electronic address: campanagiulia95@gmail.com.
Elena GattiLaboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. Electronic address: egatti@fatebenefratelli.eu.
Trang CaoThe Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia. Electronic address: Trang.Cao@monash.edu.
Alex FornitoThe Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia. Electronic address: Alex.Fornito@monash.edu.
Valentina CantoniDepartment of Clinical and Experimental Sciences, University of Brescia, Italy. Electronic address: valentina.cantoni90@gmail.com.
Sonia BelliniMolecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. Electronic address: sbellini@fatebenefratelli.eu.
Daniele CorboDepartment of Medical Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy. Electronic address: daniele.corbo@unibs.it.
Mauro MagoniStroke Unit, ASST Spedali Civili, Brescia, Italy. Electronic address: mauro.magoni@asst-spedalicivili.it.
Roberto GasparottiDepartment of Medical Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy. Electronic address: roberto.gasparotti@gmail.com.
Roberta GhidoniMolecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. Electronic address: rghidoni@fatebenefratelli.eu.
Michela PievaniLaboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. Electronic address: mpievani@fatebenefratelli.eu.
Barbara BorroniDepartment of Clinical and Experimental Sciences, University of Brescia, Italy; Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. Electronic address: bborroni@inwind.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndividuals carrying Progranulin (GRN) mutations show asymmetrical grey matter atrophy, which could be used for early detection in the long asymptomatic phase. To capture these alterations, we employed both conventional Surface-Based Morphometry (SBM) and Mode-Based Morphometry (MBM). While the former provides high-resolution, location-specific estimates of cortical thickness (CT) differences, the latter has recently been introduced as a novel framework that decomposes CT maps into geometric eigenmodes, allowing a multiscale characterization of brain structural variability. Using both approaches enables the detection of complementary aspects of GRN-related neurodegeneration across spatial scales.

methodsSBM and MBM were applied to CT maps to quantify structural alterations in individuals, 15 presymptomatic and 27 symptomatic, compared to 19 healthy controls (HC). SBM was used to assess vertex-wise CT differences, whereas MBM was used to decompose individual CT maps into geometric eigenmodes and quantify alterations across spatial scales. From both pipelines asymmetry indices (SBM-AI and MBM-AI) were computed. Associations between SBM/MBM-derived measures and domain-specific cognitive performance as well as global disease severity scores were then assessed.

resultsCompared with HC, symptomatic GRN showed significant alterations in seven eigenmodes in the left hemisphere, while only two modes contributed to CT differences in the right hemisphere. For MBM-AI and SBM-AI symptomatic GRN exhibited significantly different values compared to HC and presymptomatic GRN (p < 0.001). Although both asymmetry indices showed significant differences across disease stages (p = 1.3 × 10

conclusionsMBM revealed multiscale cortical alterations in symptomatic GRN mutation carriers, capturing both large-scale hemispheric differences and more localized regional variations in CT that are less apparent with conventional SBM. These findings indicate that GRN-related neurodegeneration involves complex spatial pattern across multiple anatomical scales. Brain asymmetry remains a core hallmark of GRN-related pathology, supporting the use of asymmetry indices (derived from both SBM and MBM) as potential markers of disease progression at the symptomatic stage.

Indexed as

BrainBrain MappingFrontotemporal DementiaProgranulinsAdultAgedAtrophyFemaleGray MatterHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedGRN protein, humanProgranulinsAsymmetryFrontotemporal dementiaGRNMode-based morphometrySurface-based morphometry

Identifiers

PMID41996765
PMCPMC13101774

What Socratic holds

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LicenceCC BY
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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 Socratic graph.