ArticleAnnals of biomedical engineering2022
Personalised 3D Assessment of Trochanteric Soft Tissues Improves HIP Fracture Classification Accuracy.
Article in Annals of biomedical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 19 citations in OpenAlex.
- Sex-specific predictive equations for estimating trochanteric soft tissue thickness across body positions and imaging modalities.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026Article
- Improved prediction of hip fracture using multi-faceted biomechanical computed tomography.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2026Article
- Can Multi-Vertebral CT-Based Finite Element Models Accurately Predict Strains? An In Vitro Validation Study.International journal for numerical methods in biomedical engineering · 2025Article
- Development and validation of a semi-automated and unsupervised method for femur segmentation from CT.Scientific reports · 2024Article
- Phantomless calibration of CT scans for hip fracture risk prediction in silico: Comparison with phantom-based calibration.PloS one · 2024Article
- Fatty infiltration of hip muscles and trochanteric soft tissue thickness are associated with hip fractures in the elderly.International orthopaedics · 2022Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
Passive soft tissues surrounding the trochanteric region attenuate fall impact forces and thereby control hip fracture risk. The degree of attenuation is related to Soft Tissue Thickness (STT). STT at the neutral hip impact orientation, estimated using a regression relation in body mass index (BMI), was previously shown to influence the current absolute risk of hip fracture (ARF0) and its fracture classification accuracy. The present study investigates whether fracture classification using ARF0 improves when STT is determined from the subject's Computed-Tomography (CT) scans (i.e. personalised) in an orientation-specific (i.e. 3D) manner. STT is calculated as the shortest distance along any impact orientation between a semi-automatically segmented femur surface and an automatically segmented soft tissue/air boundary. For any subject, STT along any of the 33 impact orientations analysed always exceeds the value estimated using BMI. Accuracy of fracture classification using ARF0 improves when using personalised 3D STT estimates (AUC = 0.87) instead of the BMI-based STT estimate (AUC = 0.85). The improvement is smaller (AUC = 0.86) when orientation-specificity of CT-based STT is suppressed and is nil when personalisation is suppressed instead. Thus, fracture classification using ARF0 improves when CT is used to personalise STT estimates and improves further when, in addition, the estimates are orientation specific.
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Registered trials
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