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Accès ouvert déclaré 2024 preprint

Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study

4Citations signalées, ce qui n’est pas une note de qualité
78Institutions déclarées
13Pays d’affiliation déclarés

Rattachement africain : us, ca, ch, au, gb, de, fr, cz, it, jp, es, cn, pl. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study
Date Crossref
01/05/2024
Éditeur
openRxiv
Type
posted-content

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

University of MinnesotaPolytechnique MontréalSwiss Paraplegic CenterCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalThe University of QueenslandUniversity of British ColumbiaHarvard UniversityMassachusetts General HospitalAthinoula A. Martinos Center for Biomedical ImagingMassachusetts Institute of TechnologyQueen Mary University of LondonNational Hospital for Neurology and NeurosurgeryUniversity College LondonUniversität HamburgUniversity Medical Center Hamburg-EppendorfMedical College of WisconsinMilwaukee VA Medical CenterCentre National de la Recherche ScientifiqueCentre de Résonance Magnétique Biologique et MédicaleHôpital de la TimoneUniversité de SherbrookeUniversité de StrasbourgMasaryk UniversityUniversity Hospital BrnoMontreal Neurological Institute and HospitalMcGill UniversityMax Planck Institute for Human Cognitive and Brain SciencesStanford UniversityWellcome Centre for Human NeuroimagingUniversity of ZurichIstituto di NanotecnologiaFondazione Santa LuciaJuntendo UniversityUniversity of PaviaCARE CanadaPhilips (Canada)Centro Ricerche Enrico FermiVall d'Hebron Hospital UniversitariVall d'Hebron Institute of OncologyResonance Research (United States)Central European Institute of TechnologyToho UniversityToho University Omori Medical CenterUniversity of California, San FranciscoUniversity of BirminghamBaylor College of MedicineIcahn School of Medicine at Mount SinaiUniversity of GenevaÉcole Polytechnique Fédérale de LausanneUniversity Hospital Carl Gustav CarusTechnische Universität DresdenInstitute of Psychology, Chinese Academy of SciencesUniversity of Chinese Academy of SciencesSt. Anne's University Hospital BrnoCracow University of TechnologyInternational Collaboration On Repair DiscoveriesCapital Medical UniversityBeijing Tian Tan HospitalUniversitat de BarcelonaNeurological SurgeryUniversity of California, DavisVanderbilt University Medical CenterUniversity of OxfordWellcome Centre for Integrative NeuroimagingNorthwestern UniversityUniversitat Oberta de CatalunyaHumanitas UniversityIRCCS Humanitas Research HospitalVanderbilt UniversityOklahoma City UniversityUniversity of OklahomaUniversity of Tokyo HospitalCardiff UniversityMila - Quebec Artificial Intelligence InstitutePalacký University OlomoucLeipzig UniversityUniversity of Chieti-Pescara

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Advanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and ApplicationsFunctional Brain Connectivity Studies

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