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

Area of Science:

• Radiology and Imaging Science
• Biomedical Engineering
• Orthopedic Biomechanics

Background:

• Multi-detector computed tomography (MDCT) is crucial for predicting femoral bone strength using finite element (FE) analysis.
• Reducing radiation dose in MDCT is essential for patient safety, especially in chronic conditions like osteoporosis.

Purpose of the Study:

• To evaluate the impact of dose reduction strategies, specifically sparse sampling and reduced tube current, on the accuracy of MDCT-based femoral bone strength prediction via FE analysis.
• To determine the optimal dose reduction method that maintains the reliability of FE-predicted femoral failure load.

Main Methods:

• MDCT scans of 21 subjects with osteoporosis were analyzed.
• Radiation dose was reduced by 50% and 75% using sparse sampling and virtually reduced tube current.
• Finite element analysis was performed on reconstructed images to calculate femoral failure load.
• Root mean square coefficient of variation (RMSCV) and coefficient of correlation (R² ) were used to assess accuracy against original-dose scans.

Main Results:

• A 50% dose reduction using sparse sampling showed minimal impact on FE-predicted femoral failure load (RMSCV=5.70%, R²=0.96), outperforming reduced tube current (RMSCV=20.78%, R²=0.79).
• Higher dose reductions (75%) using either method led to significant inaccuracies in failure load prediction.
• Sparse sampling demonstrated superior performance in maintaining prediction accuracy at reduced radiation doses.

Conclusions:

• Up to a 50% dose reduction via sparse sampling is feasible for accurate FE-based prediction of femoral failure load.
• Sparse-sampled MDCT offers a potential pathway for fracture risk prediction and treatment monitoring in osteoporosis with reduced radiation exposure.
• This approach could enhance the clinical utility of MDCT in managing osteoporosis patients.