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@ARTICLE{Palm:302867,
      author       = {V. Palm and S. Thangamani and B. K. Budai and S. Skornitzke
                      and K. Eckl and E. Tong and S. Sedaghat and C. P. Heußel
                      and O. von Stackelberg and S. Engelhardt and T. Kopytova$^*$
                      and T. Norajitra$^*$ and K. Maier-Hein$^*$ and H.-U. Kauczor
                      and M. O. Wielpütz},
      title        = {{AI}-based {CT} assessment of 3117 vertebrae reveals
                      significant sex-specific vertebral height differences.},
      journal      = {Scientific reports},
      volume       = {15},
      number       = {1},
      issn         = {2045-2322},
      address      = {[London]},
      publisher    = {Springer Nature},
      reportid     = {DKFZ-2025-01407},
      pages        = {20756},
      year         = {2025},
      abstract     = {Predicting vertebral height is complex due to individual
                      factors. AI-based medical imaging analysis offers new
                      opportunities for vertebral assessment. Thereby, these novel
                      methods may contribute to sex-adapted nomograms and
                      vertebral height prediction models, aiding in diagnosing
                      spinal conditions like compression fractures and supporting
                      individualized, sex-specific medicine. In this study an
                      AI-based CT-imaging spine analysis of 262 subjects (mean age
                      32.36 years, range 20-54 years) was conducted, including a
                      total of 3117 vertebrae, to assess sex-associated anatomical
                      variations. Automated segmentations provided anterior,
                      central, and posterior vertebral heights. Regression
                      analysis with a cubic spline linear mixed-effects model was
                      adapted to age, sex, and spinal segments. Measurement
                      reliability was confirmed by two readers with an intraclass
                      correlation coefficient (ICC) of 0.94-0.98. Female vertebral
                      heights were consistently smaller than males (p < 0.05). The
                      largest differences were found in the upper thoracic spine
                      (T1-T6), with mean differences of $7.9-9.0\%.$ Specifically,
                      T1 and T2 showed differences of $8.6\%$ and $9.0\%,$
                      respectively. The strongest height increase between
                      consecutive vertebrae was observed from T9 to L1 (mean slope
                      of 1.46; $6.63\%$ for females and 1.53; $6.48\%$ for males).
                      This study highlights significant sex-based differences in
                      vertebral heights, resulting in sex-adapted nomograms that
                      can enhance diagnostic accuracy and support individualized
                      patient assessments.},
      keywords     = {Humans / Adult / Male / Female / Middle Aged / Tomography,
                      X-Ray Computed: methods / Young Adult / Sex Characteristics
                      / Thoracic Vertebrae: diagnostic imaging / Thoracic
                      Vertebrae: anatomy $\&$ histology / Sex Factors / Spine:
                      diagnostic imaging / Spine: anatomy $\&$ histology /
                      Nomograms / Reproducibility of Results / Anthropometry
                      (Other) / Artificial intelligence (Other) / Image
                      interpretation, computer-assisted (Other) / Image
                      processing, computer-assisted (Other) / Sex characteristics
                      (Other) / Spine (Other)},
      cin          = {E230},
      ddc          = {600},
      cid          = {I:(DE-He78)E230-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40595983},
      pmc          = {pmc:PMC12218285},
      doi          = {10.1038/s41598-025-05091-0},
      url          = {https://inrepo02.dkfz.de/record/302867},
}