Multi-detector computed tomography (MDCT) imaging: association of bone texture parameters with finite element
Nico Sollmann1,2,3, Nithin Manohar Rayudu4, John Jie Sheng Lim4
1Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Background:
Osteoporosis is a systemic skeletal disease that is characterized by low bone mass and microarchitectural deterioration, predisposing affected individuals to fragility fractures. Yet, standard measurement of areal bone mineral density (BMD) in dual-energy X-ray absorptiometry (DXA) as the current reference standard has limitations for correctly detecting osteoporosis and fracture risk, with opportunistic osteoporosis screening using computed tomography (CT) showing increasing importance. This study's objective is to compare finite element analysis (FEA)-based vertebral failure load with parameters of texture analysis (TA) derived from multi-detector CT (MDCT).
Methods:
MDCT data of seven subjects (mean age: 71.9±7.4 years) were included for FEA and TA. Manual segmentation was performed for the vertebral bodies T11, T12, L1, and L2 and the intervertebral discs (IVDs) T11/12, T12/L1, L1/2, and L2/3. Correlation analyses between FEA-derived failure loads and parameters of TA for the single vertebrae and two functional spinal units (FSUs) were calculated, defining FSU-1 as T11-IVD-T12-IVD-L1 and FSU-2 as T12-IVD-L1-IVD-L2. Furthermore, multivariate regressions were performed to identify the texture parameters that predicted the failure load best.
Results:
For single vertebrae, the strongest correlations were observed for skewnessglobal, kurtosisglobal, and gray level variance (rho =-0.7668 to -0.7362; P<0.001), while for FSUs, SumAverage, long-run emphasis, long-run low gray-level emphasis, homogeneity, and energy showed the strongest correlations (rho =-0.8187 to 0.8407; P<0.05) to failure loads. SumAverage best predicted the failure load for single vertebrae (R2 adj =0.523, P<0.001). For the two FSUs, kurtosisglobal (FSU-1: R2 adj =0.611, P=0.001) and skewnessglobal (FSU-2: R2 adj =0.579, P=0.002) were the best predictors.
Conclusions:
TA using MDCT data of the spine was significantly associated with FEA-derived failure loads of both, single vertebrae and FSUs. Texture parameters predicted failure loads of FSUs as a more realistic in-vivo scenario equally well as compared to single vertebrae analyses. TA may reflect a less complex and time-consuming approach to accurately and non-invasively evaluate vertebral bone strength.
