Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study

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 correlates 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). Intracranial volume (ICV) correlates with body height (r = 0.46) and the brain volumes and CSA-WM (0.37 ≤ r ≤ 0.77). In comparison, age correlates with cortical GM volume, precentral GM volume, and cortical thickness (-0.21 ≥ r ≥ -0.27). Body weight correlates with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20 ≥ r ≥ -0.23). Body weight further correlates 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 correlates with brain volumes (0.39 ≤ r ≤ 0.64), and 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 age, sex, or sex and age, explained 2 ± 2%, 24 ± 10%, or 26 ± 10%, of data variance in brain volumetry and SC CSA. The amount of explained variance increased to 33 ± 11%, 41 ± 17%, or 46 ± 17%, when body height, ICV, or body height and ICV were added into the mixture model. In females, the explained variances halved suggesting another unidentified biological factor(s) determining females' central nervous system (CNS) morphology. In conclusion, body size and ICV are significant biological variables. 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; and body size and ICV should be considered as covariates in statistical analyses. Normalization of different brain regions with ICV diminishes their correlations with body size, but simultaneously amplifies ICV-related variance (r = 0.72 ± 0.07) and suppresses volume variance of the different brain regions (r = 0.12 ± 0.19) in the normalized measurements.

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Publication Details

Journal
Imaging Neuroscience
Published
2025-01-01
DOI
https://doi.org/10.1162/imag_a_00559
Citations
4
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
5.44

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article

Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study

Sean Mackey, Cornelia Laule, Eva Alonso‐Ortiz, Anna Pichiecchio et al.
4 citations
Imaging Neuroscience
Advanced Neuroimaging Techniques and Applications
5.44
article

Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study

Sean Mackey, Cornelia Laule, Eva Alonso‐Ortiz, Anna Pichiecchio, René Labounek, Dimitri Van De Ville, Jürgen Finsterbusch, Kevin Epperson, Adam Dvorak, Julien Cohen‐Adad, Marek Dostál, Sara Llufriú, Jan Valošek, Shannon Kolind, Akifumi Hagiwara, Nicole Atcheson, Eloy Martínez‐Heras, Virginie Callot, Elisabeth Solana, Joo-won Kim, Yazhuo Kong, Miloš Keřkovský, Masaaki Hori, Benjamin De Leener, Nikolaus Weiskopf, Issei Fukunaga, Nyoman D. Kurniawan, Deborah Pareto, Pierre‐Gilles Henry, Paulo Loureiro de Sousa, Christine Law, Christian Büchel, James M. Joers, George Tackley, Loan Mattera, Junqian Xu, Patrick Freund, Claudia A. M. Gandini Wheeler‐Kingshott, Kenneth A. Weber, Giancarlo Germani, Sandrine Bédard, Francesco Grussu, Marios Yiannakas, Alan C. Seifert, Maxime Descoteaux, Hagen H. Kitzler, Falk Eippert, Yaou Liu, Matthew D. Budde, Zachary A. Smith, Giovanni Savini, Julien Doyon, Karla R. Epperson, Ferrán Prados, Maryam Seif, Federico Giove, Markus Barth, Yuichi Suzuki, Richard G. Wise, Alexandru Foias, Alexandra Tinnermann, Mihael Abramovic, Àlex Rovira, Ali Khatibi, Michela Fratini, Amy Paulson, Paul Kuntke, Anna Combes, Sławomir Kuśmia, Christophe Lenglet, Daniel S. Papp, Patrik O. Wyss, Alex K. Smith, Nico Papinutto, Haleh Karbasforoushan, Igor Nestrašil, Allan R. Martin, Rebecca S. Samson, Todd B. Parrish, Tobias Leutritz, Kristin P. O’Grady, Nawal Kinany, Marco Battiston, Robert Barry, Marc J. Ruitenberg, Maria Marcella Laganà, Guillaume Gilbert, Kouhei Kamiya, Tomáš Horák, Monica T. Bondy, Seth A. Smith, Laura Barlow
article en
4 citations

Abstract

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 correlates 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). Intracranial volume (ICV) correlates with body height (r = 0.46) and the brain volumes and CSA-WM (0.37 ≤ r ≤ 0.77). In comparison, age correlates with cortical GM volume, precentral GM volume, and cortical thickness (-0.21 ≥ r ≥ -0.27). Body weight correlates with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20 ≥ r ≥ -0.23). Body weight further correlates 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 correlates with brain volumes (0.39 ≤ r ≤ 0.64), and 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 age, sex, or sex and age, explained 2 ± 2%, 24 ± 10%, or 26 ± 10%, of data variance in brain volumetry and SC CSA. The amount of explained variance increased to 33 ± 11%, 41 ± 17%, or 46 ± 17%, when body height, ICV, or body height and ICV were added into the mixture model. In females, the explained variances halved suggesting another unidentified biological factor(s) determining females' central nervous system (CNS) morphology. In conclusion, body size and ICV are significant biological variables. 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; and body size and ICV should be considered as covariates in statistical analyses. Normalization of different brain regions with ICV diminishes their correlations with body size, but simultaneously amplifies ICV-related variance (r = 0.72 ± 0.07) and suppresses volume variance of the different brain regions (r = 0.12 ± 0.19) in the normalized measurements.

Imaging NeuroscienceVol. 3
Northwestern University (US), University of Geneva (CH), Montreal Neurological Institute and Hospital (CA), Centre National de la Recherche Scientifique (FR), Toho University (JP), University of Minnesota (US), Central European Institute of Technology (CZ), Humanitas University (IT), Université de Sherbrooke (CA), Harvard University (US), Universitat Oberta de Catalunya (ES), University of British Columbia (CA), Universität Hamburg (DE), The University of Queensland (AU), Wellcome Centre for Human Neuroimaging (GB), Queen Mary University of London (GB), University of California, San Francisco (US), Baylor College of Medicine (US), Capital Medical University (CN), Vanderbilt University (US), University of Zurich (CH), Medical College of Wisconsin (US), Masaryk University (CZ), Cracow University of Technology (PL), University of Pavia (IT), Oklahoma City University (US), Centre Hospitalier Universitaire Sainte-Justine (CA), Juntendo University (JP), University of Chieti-Pescara (IT), University of Oxford (GB), Beijing Tian Tan Hospital (CN), Massachusetts General Hospital (US), Istituto di Nanotecnologia (IT), Harvard–MIT Division of Health Sciences and Technology (US), Toho University Omori Medical Center (JP), Milwaukee VA Medical Center (US), Wellcome Centre for Integrative Neuroimaging (GB), University Hospital Brno (CZ), CARE Canada (CA), University Medical Center Hamburg-Eppendorf (DE), Centro Ricerche Enrico Fermi (IT), University of Tokyo Hospital (JP), Hospital Clínic de Barcelona (ES), Swiss Paraplegic Center (CH), Philips (Canada) (CA), Athinoula A. Martinos Center for Biomedical Imaging (US), Vall d'Hebron Hospital Universitari (ES), International Collaboration On Repair Discoveries (CA), Max Planck Institute for Human Cognitive and Brain Sciences (DE), Institute of Psychology, Chinese Academy of Sciences (CN), St. Anne's University Hospital Brno (CZ), Centre de Résonance Magnétique Biologique et Médicale (FR), Fondazione Santa Lucia (IT), National Hospital for Neurology and Neurosurgery (GB), Neurological Surgery (US), Fundació Clínic per a la Recerca Biomèdica (ES), Resonance Research (United States) (US), University Hospital Carl Gustav Carus (DE), Hôpital de la Timone (FR), IRCCS Humanitas Research Hospital (IT), Mila - Quebec Artificial Intelligence Institute (CA), University of Chinese Academy of Sciences (CN), Vall d'Hebron Institute of Oncology (ES), University College London (GB), Polytechnique Montréal (CA), McGill University (CA), École Polytechnique Fédérale de Lausanne (CH), Massachusetts Institute of Technology (US), Université de Strasbourg (FR), Palacký University Olomouc (CZ), Université de Montréal (CA), Universitat de Barcelona (ES), Technische Universität Dresden (DE), Cardiff University (GB), University of Birmingham (GB), University of California, Davis (US), University of Oklahoma (US), Vanderbilt University Medical Center (US), Leipzig University (DE), Stanford University (US), Icahn School of Medicine at Mount Sinai (US)
American Heart Association, Bristol-Myers Squibb, Craig H. Neilsen Foundation, University of Pennsylvania, University of Minnesota, “la Caixa” Foundation, Réseau en Bio-Imagerie du Quebec, Wings for Life, NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research, National Imaging Facility, National Institute for Health and Care Research, Ataxia UK, European Commission, Rosetrees Trust, SpinalCure Australia, Deutsche Forschungsgemeinschaft, University of Queensland, Canada Foundation for Innovation, National Natural Science Foundation of China, Ministerstvo Školství, Mládeže a Tělovýchovy, Ministerstvo Zdravotnictví Ceské Republiky, Max-Planck-Gesellschaft, University College London Hospitals NHS Foundation Trust, Agentura Pro Zdravotnický Výzkum České Republiky, Canada First Research Excellence Fund, Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona, Institut de Valorisation des Données, International Collaboration on Repair Discoveries, Courtois Foundation, National Institutes of Health, Center for Neurobehavioral Development, HORIZON EUROPE Framework Programme, Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, Fonds de Recherche du Québec - Santé, Agència de Gestió d'Ajuts Universitaris i de Recerca, Instituto de Salud Carlos III, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering, H2020 European Research Council, H2020 Marie Skłodowska-Curie Actions
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