AI for Automated vBMD and Fragility Assessment of the Proximal Femur in CT Scans KI zur automatisierten vBMD- und Fragilitätsanalyse des proximalen Femurs an CT-Scans
Krekiehn NR, Bartenschlager S, Seidel R, Chaudry O, Sigurdsson S, Gudnason V, Hövener JB, Engelke K, Glüer CC (2025)
Publication Type: Journal article
Publication year: 2025
Journal
Book Volume: 34
Pages Range: 256-264
Journal Issue: 4
DOI: 10.1055/a-2717-5826
Abstract
Background Osteoporotic hip fractures are associated with high morbidity and mortality. Opportunistic screening by incidental analysis of routine clinical CT scans for fracture risk could reveal the need for prevention at an early stage. However, a freely available fully automated method for determining volumetric bone mineral density (vBMD) of the proximal femur is still lacking. Methods The open-source AI tool TotalSegmentator was combined with two in-house AI models to segment both the proximal femur and a calibration phantom, enabling fully automated vBMD calculation. The accuracy of AI vBMD measurements was evaluated in 1070 hip QCT scans from the AGES study by comparison with the semi-automated gold standard MIAF. For an initial assessment of suitability, 289 clinical CT scans (ARTEMIS study) were analyzed regarding prediction of incident hip fractures. Results AI HU vBMD values correlated closely with MIAF vBMD values (r=0.88-0.97). After calibration, correlation was r=0.96 with a bias of 1.6 mg/cm³ (integral) and 21.9 mg/cm³ (trabecular), and RMS errors of 15.1 mg/cm³ (integral) and 9.8 mg/cm³ (trabecular). Predictive performance for hip fractures (AUC 0.771-0.836) was significantly higher (p<0.031) than the baseline model of age and sex (AUC=0.641). Conclusions The developed AI enables fully automated, rapid, and calibrated assessment of proximal femur vBMD directly from clinical CT scans and allows prediction of hip fracture risk. The positive results of this first prognostic study, however, need to be confirmed in independent and larger datasets. This approach offers the potential to identify at-risk patients in opportunistic screening and to initiate preventive measures at an earlier stage.
Authors with CRIS profile
Stefan Bartenschlager
Medizinische Fakultät
Oliver Chaudry
Department of Medicine 3 – Rheumatology and Immunology
Klaus Engelke
Lehrstuhl für Medizinische Physik und Mikrogewebetechnik (IMP)
Involved external institutions
Universitätsklinikum Schleswig-Holstein (UKSH)
Germany (DE)
Icelandic Heart Association (IHA)
Iceland (IS)
Germany (DE)
Icelandic Heart Association (IHA)
Iceland (IS)
How to cite
APA:
Krekiehn, N.R., Bartenschlager, S., Seidel, R., Chaudry, O., Sigurdsson, S., Gudnason, V.,... Glüer, C.C. (2025). AI for Automated vBMD and Fragility Assessment of the Proximal Femur in CT Scans KI zur automatisierten vBMD- und Fragilitätsanalyse des proximalen Femurs an CT-Scans. Osteologie, 34(4), 256-264. https://doi.org/10.1055/a-2717-5826
MLA:
Krekiehn, Nicolai Raphael, et al. "AI for Automated vBMD and Fragility Assessment of the Proximal Femur in CT Scans KI zur automatisierten vBMD- und Fragilitätsanalyse des proximalen Femurs an CT-Scans." Osteologie 34.4 (2025): 256-264.
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