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01-12-2020 | Computed Tomography | Original Article

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

Authors: Nithin Manohar Rayudu, D. Praveen Anitha, Kai Mei, Florian Zoffl, Felix K. Kopp, Nico Sollmann, Maximilian T. Löffler, Jan S. Kirschke, Peter B. Noël, Karupppasamy Subburaj, Thomas Baum

Published in: Archives of Osteoporosis | Issue 1/2020

Abstract

Summary

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.

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Title: Low-dose and sparse sampling MDCT-based femoral bone strength prediction using finite element analysis
Authors: Nithin Manohar Rayudu
D. Praveen Anitha
Kai Mei
Florian Zoffl
Felix K. Kopp
Nico Sollmann
Maximilian T. Löffler
Jan S. Kirschke
Peter B. Noël
Karupppasamy Subburaj
Thomas Baum
Publication date: 01-12-2020
Publisher: Springer London
Keywords: Computed Tomography
Computed Tomography
Osteoporosis
Osteoporosis
Published in: Archives of Osteoporosis / Issue 1/2020
Print ISSN: 1862-3522
Electronic ISSN: 1862-3514
DOI: https://doi.org/10.1007/s11657-020-0708-9

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

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

Abstract

Summary

Purpose

Methods

Results

Conclusion

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Summary

Purpose

Methods

Results

Conclusion

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