How Sex, Age, Adiposity, and Smoking Shape the Human Rib Cage: Evidence from 26,275 Whole-Body MRIs across the German National Cohort (NAKO)
Year: 2026
Type: preprint
Abstract: Rib-cage morphology is a determinant of thoracic biomechanics, ventilation, and injury response, yet statistical shape models (SSMs) of the rib cage have relied on small cohorts (∼100s of individuals) imaged by clinical computed tomography, which over-represents injury and disease. We constructed a surface-based SSM of the complete 24-rib cage from 26,275 standardised whole-body magnetic resonance imaging (MRI) scans of adults aged 19–74 years from the population-based German National Cohort (NAKO). Ribs were segmented with a deep- learning pipeline (a rib-extended SPINEPS model), reconstructed as per-rib surface meshes, and brought into dense vertex-wise correspondence by Gaussian-process morphable registration in Scalismo; the aligned ensemble was summarised by generalised Procrustes analysis and principal component analysis (PCA). Fourteen per-rib geometric descriptors provided a quantitative cross- walk between the abstract PCA modes and named shape features, and associations with sex, age, body size and composition (including body-fat percentage), and smoking exposure were estimated by multivariable regression with Benjamini–Hochberg false-discovery-rate control. Shape variation was strongly concentrated: 28 modes captured 95% of the total variance, and the first three alone accounted for 69.4% (PC1, 42.6%; PC2, 16.3%; PC3, 10.5%) and admitted consistent anatomical readings – a sexually dimorphic axis (PC1), a slender-versus-stout body- habitus contrast (PC2), and a free-rib-size axis at ribs 11–12 (PC3). The sexes were nearly fully separated along PC1 (Cohen’s d = 2.52). Body mass and body-fat percentage were the dominant modifiable correlates of rib-cage shape, whereas the association with cumulative smoking exposure was comparatively small. The model is released as a population-representative geometric reference for benchmarking and morphing donor-derived finite-element human-body models and for further large-cohort shape analysis.
Source: medRxiv
Authors: Anatol Aicher, Robert Graf, Jan Kirschke, Thomas Frauenfelder, Falko Ensle, Bjoern Menze, Josua Decker, Thomas Kröncke, Johannes Haubold, Steffen Ringhof, Fabian Bamberg, Carsten Oliver Schmidt, Mark Wielpütz, Michael Leitzmann, Stefan N. Willich, Thomas Keil, Thoralf Niendorf, Tobias Pischon, Christopher Schlett, Hendrik Möller
Institutions: University Hospital Zurich, TUM Klinikum, Technical University of Munich, University of Zurich, University Hospital Augsburg, Essen University Hospital, University of Freiburg, University Medical Center Freiburg, Universitätsmedizin Greifswald, University of Regensburg, Charité – Universitätsmedizin Berlin, University of Würzburg, Max Delbrück Center, Universitäts-Herzzentrum Freiburg-Bad Krozingen
Language: English
Domain: Life Sciences
Open Access status: green
Funder: Leibniz-Gemeinschaft
Awards: G3987985702, G852547542
OpenAlex ID: W7208791390
