Low-dose and sparse sampling MDCT-based femoral bone strength prediction using finite element analysis.

This study aims to evaluate the impact of dose reduction through tube current and sparse sampling on multi-detector computed tomography (MDCT)-based femoral bone strength prediction using finite element (FE) analysis. FE-predicted femoral failure load obtained from MDCT scan data was not significantly affected by 50% dose reductions through sparse sampling. Further decrease in dose through sparse sampling (25% of original projections) and virtually reduced tube current (50% and 25% of the original dose) showed significant effects on the FE-predicted failure load results. PURPOSE: To investigate the effect of virtually reduced tube current and sparse sampling on multi-detector computed tomography (MDCT)-based femoral bone strength prediction using finite element (FE) analysis. METHODS: Routine MDCT data covering the proximal femur of 21 subjects (17 males; 4 females; mean age, 71.0 ± 8.8 years) without any bone diseases aside from osteoporosis were included in this study. Fifty percent and 75% dose reductions were achieved by virtually reducing tube current and by applying a sparse sampling strategy from the raw image data. Images were then reconstructed with a statistically iterative reconstruction algorithm. FE analysis was performed on all reconstructed images and the failure load was calculated. The root mean square coefficient of variation (RMSCV) and coefficient of correlation (R2) were calculated to determine the variation in the FE-predicted failure load data for dose reductions, using original-dose MDCT scan as the standard of reference. RESULTS: Fifty percent dose reduction through sparse sampling showed lower RMSCV and higher correlations when compared with virtually reduced tube current method (RMSCV = 5.70%, R2 = 0.96 vs. RMSCV = 20.78%, R2 = 0.79). Seventy-five percent dose reduction achieved through both methods (RMSCV = 22.38%, R2 = 0.80 for sparse sampling; RMSCV = 24.58%, R2 = 0.73 for reduced tube current) could not predict the failure load accurately. CONCLUSION: Our simulations indicate that up to 50% reduction in radiation dose through sparse sampling can be used for FE-based prediction of femoral failure load. Sparse-sampled MDCT may allow fracture risk prediction and treatment monitoring in osteoporosis with less radiation exposure in the future.

Effect of the intervertebral disc on vertebral bone strength prediction: a finite-element study.

BACKGROUND CONTEXT: Osteoporotic vertebral fractures (OVFs) are a prevalent skeletal condition in the elderly but the mechanism behind these fractures remain unclear due to the complex biomechanical interplay between spinal segments such as the vertebra and intervertebral discs (IVDs). PURPOSE: To investigate the biomechanical influence of IVDs by (1) comparing finite element (FE)-predicted failure load with experimentally measured failure load of functional spinal units (FSUs) and (2) comparing this correlation with those of FE-predicted failure load and bone mineral density (BMD) of the single central vertebra with experimentally measured failure load. STUDY DESIGN: A computational biomechanical analysis. PATIENT SAMPLE: Ten thoracic FSUs consisting of a central vertebra, the adjacent IVDs, and the upper and lower halves of the adjacent vertebrae were harvested from formalin-fixed human donors (4 males, 6 females; mean age of 82±9 years). OUTCOME MEASURES: The outcome measures included the prediction of vertebral strength and determination of BMD in FSUs and the single central vertebra and the correlation of both measures with experimentally measured vertebral strength of the FSUs. METHODS: The FSUs underwent clinical multidetector computed tomography (MDCT) (spatial resolution: 250×250×600 µm3). BMD was determined for the FSUs from the MDCT images of the central vertebrae. FE-predicted failure load was calculated in the single central vertebra of the FSUs alone and the entire FSUs. Experimentally measured failure load of the FSUs was determined in a uniaxial biomechanical test. RESULTS: BMD of the central vertebrae correlated significantly with experimentally measured failure load (R2=0.66, p<.02), whereas FE-predicted failure load of the central vertebra showed no significant correlation with experimentally measured failure load (p=.07). However, FE-predicted failure load of FSUs best predicted experimentally measured failure load of FSUs (R2=0.93, p<.0001). CONCLUSIONS: This study demonstrated that routine clinical MDCT images can be an accurate and feasible tool for prediction of OVFs using patient-specific FE analysis of FSU models. CLINICAL SIGNIFICANCE: Improved management of OVFs is essential amidst current clinical challenges. Implementation of a vertebral strength assessment tool could result in more accurate prediction of osteoporotic fracture risk and aid clinicians with better targeted early treatment strategies.