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000302867 1001_ $$aPalm, Viktoria$$b0
000302867 245__ $$aAI-based CT assessment of 3117 vertebrae reveals significant sex-specific vertebral height differences.
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000302867 520__ $$aPredicting 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.
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000302867 650_7 $$2Other$$aAnthropometry
000302867 650_7 $$2Other$$aArtificial intelligence
000302867 650_7 $$2Other$$aImage interpretation, computer-assisted
000302867 650_7 $$2Other$$aImage processing, computer-assisted
000302867 650_7 $$2Other$$aSex characteristics
000302867 650_7 $$2Other$$aSpine
000302867 650_2 $$2MeSH$$aHumans
000302867 650_2 $$2MeSH$$aAdult
000302867 650_2 $$2MeSH$$aMale
000302867 650_2 $$2MeSH$$aFemale
000302867 650_2 $$2MeSH$$aMiddle Aged
000302867 650_2 $$2MeSH$$aTomography, X-Ray Computed: methods
000302867 650_2 $$2MeSH$$aYoung Adult
000302867 650_2 $$2MeSH$$aSex Characteristics
000302867 650_2 $$2MeSH$$aThoracic Vertebrae: diagnostic imaging
000302867 650_2 $$2MeSH$$aThoracic Vertebrae: anatomy & histology
000302867 650_2 $$2MeSH$$aSex Factors
000302867 650_2 $$2MeSH$$aSpine: diagnostic imaging
000302867 650_2 $$2MeSH$$aSpine: anatomy & histology
000302867 650_2 $$2MeSH$$aNomograms
000302867 650_2 $$2MeSH$$aReproducibility of Results
000302867 7001_ $$aThangamani, Subasini$$b1
000302867 7001_ $$aBudai, Bettina Katalin$$b2
000302867 7001_ $$aSkornitzke, Stephan$$b3
000302867 7001_ $$aEckl, Kira$$b4
000302867 7001_ $$aTong, Elizabeth$$b5
000302867 7001_ $$aSedaghat, Sam$$b6
000302867 7001_ $$aHeußel, Claus Peter$$b7
000302867 7001_ $$avon Stackelberg, Oyunbileg$$b8
000302867 7001_ $$aEngelhardt, Sandy$$b9
000302867 7001_ $$0P:(DE-He78)a38c565ea337ec882cb349a58d90fffb$$aKopytova, Taisiya$$b10
000302867 7001_ $$0P:(DE-He78)a70f21a2bf78bbc1306c3d432ae08dc7$$aNorajitra, Tobias$$b11$$udkfz
000302867 7001_ $$0P:(DE-He78)33c74005e1ce56f7025c4f6be15321b3$$aMaier-Hein, Klaus$$b12$$udkfz
000302867 7001_ $$aKauczor, Hans-Ulrich$$b13
000302867 7001_ $$aWielpütz, Mark Oliver$$b14
000302867 773__ $$0PERI:(DE-600)2615211-3$$a10.1038/s41598-025-05091-0$$gVol. 15, no. 1, p. 20756$$n1$$p20756$$tScientific reports$$v15$$x2045-2322$$y2025
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