Skip to main content
Top
Published in: European Radiology 12/2017

Open Access 01-12-2017 | Computed Tomography

Is multidetector CT-based bone mineral density and quantitative bone microstructure assessment at the spine still feasible using ultra-low tube current and sparse sampling?

Authors: Kai Mei, Felix K. Kopp, Rolf Bippus, Thomas Köhler, Benedikt J. Schwaiger, Alexandra S. Gersing, Andreas Fehringer, Andreas Sauter, Daniela Münzel, Franz Pfeiffer, Ernst J. Rummeny, Jan S. Kirschke, Peter B. Noël, Thomas Baum

Published in: European Radiology | Issue 12/2017

Login to get access

Abstract

Objective

Osteoporosis diagnosis using multidetector CT (MDCT) is limited to relatively high radiation exposure. We investigated the effect of simulated ultra-low-dose protocols on in-vivo bone mineral density (BMD) and quantitative trabecular bone assessment.

Materials and methods

Institutional review board approval was obtained. Twelve subjects with osteoporotic vertebral fractures and 12 age- and gender-matched controls undergoing routine thoracic and abdominal MDCT were included (average effective dose: 10 mSv). Ultra-low radiation examinations were achieved by simulating lower tube currents and sparse samplings at 50%, 25% and 10% of the original dose. BMD and trabecular bone parameters were extracted in T10–L5.

Results

Except for BMD measurements in sparse sampling data, absolute values of all parameters derived from ultra-low-dose data were significantly different from those derived from original dose images (p<0.05). BMD, apparent bone fraction and trabecular thickness were still consistently lower in subjects with than in those without fractures (p<0.05).

Conclusion

In ultra-low-dose scans, BMD and microstructure parameters were able to differentiate subjects with and without vertebral fractures, suggesting osteoporosis diagnosis is feasible. However, absolute values differed from original values. BMD from sparse sampling appeared to be more robust. This dose-dependency of parameters should be considered for future clinical use.

Key Points

• BMD and quantitative bone parameters are assessable in ultra-low-dose in vivo MDCT scans.
• Bone mineral density does not change significantly when sparse sampling is applied.
• Quantitative trabecular bone microstructure measurements are sensitive to dose reduction.
• Osteoporosis subjects could be differentiated even at 10% of original dose.
• Radiation exposure should be considered when comparing quantitative bone parameters.
Appendix
Available only for authorised users
Literature
1.
go back to reference Consensus NI (2001) Development panel on osteoporosis: prevention, diagnosis and therapy. Jama 285(6):785–795CrossRef Consensus NI (2001) Development panel on osteoporosis: prevention, diagnosis and therapy. Jama 285(6):785–795CrossRef
2.
go back to reference Ioannidis G, Papaioannou A, Hopman WM et al (2009) Relation between fractures and mortality: results from the Canadian Multicentre Osteoporosis Study. CMAJ 181(5):265–271CrossRefPubMedPubMedCentral Ioannidis G, Papaioannou A, Hopman WM et al (2009) Relation between fractures and mortality: results from the Canadian Multicentre Osteoporosis Study. CMAJ 181(5):265–271CrossRefPubMedPubMedCentral
3.
go back to reference Burge R, Dawson-Hughes B, Solomon DH et al (2007) Incidence and economic burden of osteoporosis‐related fractures in the United States, 2005–2025. J Bone Miner Res 22(3):465–475CrossRefPubMed Burge R, Dawson-Hughes B, Solomon DH et al (2007) Incidence and economic burden of osteoporosis‐related fractures in the United States, 2005–2025. J Bone Miner Res 22(3):465–475CrossRefPubMed
4.
go back to reference Schuit SC, Van der Klift M, Weel AE et al (2004) Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam Study. Bone 34(1):195–202CrossRefPubMed Schuit SC, Van der Klift M, Weel AE et al (2004) Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam Study. Bone 34(1):195–202CrossRefPubMed
5.
go back to reference Siris ES, Chen YT, Abbott TA et al (2004) Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med 164(10):1108–1112CrossRefPubMed Siris ES, Chen YT, Abbott TA et al (2004) Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med 164(10):1108–1112CrossRefPubMed
6.
go back to reference Ito M, Ikeda K, Nishiguchi M et al (2005) Multi‐detector row CT imaging of vertebral microstructure for evaluation of fracture risk. J Bone Miner Res 20(10):1828–1836CrossRefPubMed Ito M, Ikeda K, Nishiguchi M et al (2005) Multi‐detector row CT imaging of vertebral microstructure for evaluation of fracture risk. J Bone Miner Res 20(10):1828–1836CrossRefPubMed
8.
go back to reference Baum T (2013) C Karampinos D, Liebl H, et al. High-resolution bone imaging for osteoporosis diagnostics and therapy monitoring using clinical MDCT and MRI. Curr Med Chem 20(38):4844–4852CrossRefPubMed Baum T (2013) C Karampinos D, Liebl H, et al. High-resolution bone imaging for osteoporosis diagnostics and therapy monitoring using clinical MDCT and MRI. Curr Med Chem 20(38):4844–4852CrossRefPubMed
9.
go back to reference Graeff C, Timm W, Nickelsen TN et al (2007) Monitoring Teriparatide‐Associated Changes in Vertebral Microstructure by High‐Resolution CT In Vivo: Results From the EUROFORS Study. J Bone Miner Res 22(9):1426–1433CrossRefPubMed Graeff C, Timm W, Nickelsen TN et al (2007) Monitoring Teriparatide‐Associated Changes in Vertebral Microstructure by High‐Resolution CT In Vivo: Results From the EUROFORS Study. J Bone Miner Res 22(9):1426–1433CrossRefPubMed
10.
go back to reference Coursey CA, Frush DP (2008) CT and radiation: What radiologists should know. Appl Radiol 37(3):22 Coursey CA, Frush DP (2008) CT and radiation: What radiologists should know. Appl Radiol 37(3):22
11.
go back to reference Noël PB, Fingerle AA, Renger B et al (2011) Initial performance characterization of a clinical noise–suppressing reconstruction algorithm for mdct. Am J Roentgenol 197(6):1404–1409CrossRef Noël PB, Fingerle AA, Renger B et al (2011) Initial performance characterization of a clinical noise–suppressing reconstruction algorithm for mdct. Am J Roentgenol 197(6):1404–1409CrossRef
12.
go back to reference Noël PB, Renger B, Fiebich M et al (2013) Does iterative reconstruction lower CT radiation dose: evaluation of 15,000 examinations. PLoS One 8(11), e81141CrossRefPubMedPubMedCentral Noël PB, Renger B, Fiebich M et al (2013) Does iterative reconstruction lower CT radiation dose: evaluation of 15,000 examinations. PLoS One 8(11), e81141CrossRefPubMedPubMedCentral
13.
14.
go back to reference Marin D, Nelson RC, Schindera ST et al (2009) Low-tube-voltage, high-tube-current multidetector abdominal ct: Improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm—initial clinical experience 1. Radiology 254(1):145–153CrossRef Marin D, Nelson RC, Schindera ST et al (2009) Low-tube-voltage, high-tube-current multidetector abdominal ct: Improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm—initial clinical experience 1. Radiology 254(1):145–153CrossRef
15.
go back to reference Hara AK, Paden RG, Silva AC et al (2009) Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study. Am J Roentgenol 193(3):764–771CrossRef Hara AK, Paden RG, Silva AC et al (2009) Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study. Am J Roentgenol 193(3):764–771CrossRef
16.
go back to reference Sidky EY, Kao CM, Pan X (2006) Accurate image reconstruction from few-views and limited-angle data in divergent-beam CT. J Xray Sci Technol 14(2):119–139 Sidky EY, Kao CM, Pan X (2006) Accurate image reconstruction from few-views and limited-angle data in divergent-beam CT. J Xray Sci Technol 14(2):119–139
17.
go back to reference QCT Pro Bone Mineral Densitometry Software, Phantom Module. Version 4.0, Mindways Software, 2005. QCT Pro Bone Mineral Densitometry Software, Phantom Module. Version 4.0, Mindways Software, 2005.
18.
go back to reference Žabić S, Wang Q, Morton T, et al. A low dose simulation tool for CT systems with energy integrating detectors. Med Phys. 2013;40(3). Žabić S, Wang Q, Morton T, et al. A low dose simulation tool for CT systems with energy integrating detectors. Med Phys. 2013;40(3).
19.
20.
go back to reference Fessler JA (2000) Statistical image reconstruction methods for transmission tomography. Handb Med Imaging 2:1–70 Fessler JA (2000) Statistical image reconstruction methods for transmission tomography. Handb Med Imaging 2:1–70
21.
go back to reference Kim D, Ramani S, Fessler JA (2015) Combining ordered subsets and momentum for accelerated X-ray CT image reconstruction. IEEE Trans Med Imaging 34(1):167–178CrossRefPubMed Kim D, Ramani S, Fessler JA (2015) Combining ordered subsets and momentum for accelerated X-ray CT image reconstruction. IEEE Trans Med Imaging 34(1):167–178CrossRefPubMed
22.
go back to reference Fehringer A, Lasser T, Zanette I, et al. A versatile tomographic forward- and back-projection approach on multi-GPUs. SPIE Medical Imaging 2014. International Society for Optics and Photonics. Fehringer A, Lasser T, Zanette I, et al. A versatile tomographic forward- and back-projection approach on multi-GPUs. SPIE Medical Imaging 2014. International Society for Optics and Photonics.
23.
go back to reference Kopp FK, Holzapfel K, Baum T et al (2016) Effect of low-dose MDCT and iterative reconstruction on trabecular bone microstructure assessment. PLoS One 11(7), e0159903CrossRefPubMedPubMedCentral Kopp FK, Holzapfel K, Baum T et al (2016) Effect of low-dose MDCT and iterative reconstruction on trabecular bone microstructure assessment. PLoS One 11(7), e0159903CrossRefPubMedPubMedCentral
24.
go back to reference Baum T, Müller D, Dobritz M et al (2011) BMD measurements of the spine derived from sagittal reformations of contrast-enhanced MDCT without dedicated software. EJR 80(2):e140–e145CrossRef Baum T, Müller D, Dobritz M et al (2011) BMD measurements of the spine derived from sagittal reformations of contrast-enhanced MDCT without dedicated software. EJR 80(2):e140–e145CrossRef
25.
go back to reference Baum T, Gräbeldinger M, Räth C et al (2014) Trabecular bone structure analysis of the spine using clinical MDCT: can it predict vertebral bone strength? J Bone Miner Metab 32(1):56–64CrossRefPubMed Baum T, Gräbeldinger M, Räth C et al (2014) Trabecular bone structure analysis of the spine using clinical MDCT: can it predict vertebral bone strength? J Bone Miner Metab 32(1):56–64CrossRefPubMed
26.
go back to reference Baum T, Carballido-Gamio J, Huber MB et al (2010) Automated 3D trabecular bone structure analysis of the proximal femur—prediction of biomechanical strength by CT and DXA. Osteoporos Int 21(9):1553–1564CrossRefPubMed Baum T, Carballido-Gamio J, Huber MB et al (2010) Automated 3D trabecular bone structure analysis of the proximal femur—prediction of biomechanical strength by CT and DXA. Osteoporos Int 21(9):1553–1564CrossRefPubMed
27.
go back to reference Majumdar S, Genant HK, Grampp S et al (1997) Correlation of trabecular bone structure with age, bone mineral density, and osteoporotic status: in vivo studies in the distal radius using high resolution magnetic resonance imaging. J Bone Miner Res 12(1):111–118CrossRefPubMed Majumdar S, Genant HK, Grampp S et al (1997) Correlation of trabecular bone structure with age, bone mineral density, and osteoporotic status: in vivo studies in the distal radius using high resolution magnetic resonance imaging. J Bone Miner Res 12(1):111–118CrossRefPubMed
28.
go back to reference Stamm G, Nagel HD (2002) CT-expo--a novel program for dose evaluation in CT. RoFo. Fortschr Geb Rontgenstr Nuklearmed 174(12):1570–1576CrossRef Stamm G, Nagel HD (2002) CT-expo--a novel program for dose evaluation in CT. RoFo. Fortschr Geb Rontgenstr Nuklearmed 174(12):1570–1576CrossRef
29.
go back to reference Damilakis J, Adams JE, Guglielmi G et al (2010) Radiation exposure in X-ray-based imaging techniques used in osteoporosis. Euro Radiol 20(11):2707–2714CrossRef Damilakis J, Adams JE, Guglielmi G et al (2010) Radiation exposure in X-ray-based imaging techniques used in osteoporosis. Euro Radiol 20(11):2707–2714CrossRef
30.
go back to reference Beister M, Kolditz D, Kalender WA (2012) Iterative reconstruction methods in X-ray CT. Phys Med 28(2):94–108CrossRefPubMed Beister M, Kolditz D, Kalender WA (2012) Iterative reconstruction methods in X-ray CT. Phys Med 28(2):94–108CrossRefPubMed
31.
go back to reference Pan X, Sidky EY, Vannier M (2009) Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction? Inverse Prob 25(12):123009CrossRef Pan X, Sidky EY, Vannier M (2009) Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction? Inverse Prob 25(12):123009CrossRef
32.
go back to reference Eklund A, Dufort P, Forsberg D et al (2013) Medical image processing on the GPU–Past, present and future. Med Image Anal 17(8):1073–1094CrossRefPubMed Eklund A, Dufort P, Forsberg D et al (2013) Medical image processing on the GPU–Past, present and future. Med Image Anal 17(8):1073–1094CrossRefPubMed
Metadata
Title
Is multidetector CT-based bone mineral density and quantitative bone microstructure assessment at the spine still feasible using ultra-low tube current and sparse sampling?
Authors
Kai Mei
Felix K. Kopp
Rolf Bippus
Thomas Köhler
Benedikt J. Schwaiger
Alexandra S. Gersing
Andreas Fehringer
Andreas Sauter
Daniela Münzel
Franz Pfeiffer
Ernst J. Rummeny
Jan S. Kirschke
Peter B. Noël
Thomas Baum
Publication date
01-12-2017
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 12/2017
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-017-4904-y

Other articles of this Issue 12/2017

European Radiology 12/2017 Go to the issue