4.5 Article

Personalised 3D Assessment of Trochanteric Soft Tissues Improves HIP Fracture Classification Accuracy

期刊

ANNALS OF BIOMEDICAL ENGINEERING
卷 50, 期 3, 页码 303-313

出版社

SPRINGER
DOI: 10.1007/s10439-022-02924-1

关键词

Osteoporosis; Hip fracture risk prediction; Trochanteric soft tissues; Multiscale model

资金

  1. EPSRC [EP/K03877X/1, EP/S032940/1]
  2. European Commission H2020 programme through the CompBioMed2 Centres of Excellence
  3. SANO European Centre for Computational Medicine [H2020-INFRAEDI-2018-1/823712, H2020-WIDESPREAD-2018-01/857533]

向作者/读者索取更多资源

The thickness of passive soft tissues surrounding the trochanteric region is related to hip fracture risk. Personalized measurement of thickness using computed tomography scans can improve the accuracy of fracture classification based on absolute risk values.
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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