DXA-equivalent quantification of bone mineral density using dual-layer spectral CT scout scans
To develop and evaluate a method for areal bone mineral density (aBMD) measurement based on dual-layer spectral CT scout scans.
A post-processing algorithm using a pair of 2D virtual mono-energetic scout images (VMSIs) was established in order to semi-automatically compute the aBMD at the spine similarly to DXA, using manual soft tissue segmentation, semi-automatic segmentation for the vertebrae, and automatic segmentation for the background. The method was assessed based on repetitive measurements of the standardized European Spine Phantom (ESP) using the standard scout scan tube current (30 mA) and other tube currents (10 to 200 mA), as well as using fat-equivalent extension rings simulating different patient habitus, and was compared to dual-energy X-ray absorptiometry (DXA). Moreover, the feasibility of the method was assessed in vivo in female patients.
Derived from standard scout scans, aBMD values measured with the proposed method significantly correlated with DXA measurements (r = 0.9925, p < 0.001), and mean accuracy (DXA, 4.12%; scout, 1.60%) and precision (DXA, 2.64%; scout, 2.03%) were comparable between the two methods. Moreover, aBMD values assessed at different tube currents did not differ significantly (p ≥ 0.20 for all), suggesting that the presented method could be applied to scout scans with different settings. Finally, data derived from sample patients were concordant with BMD values from a reference age-matched population.
Based on dual-layer spectral scout scans, aBMD measurements were fast and reliable and significantly correlated with the according DXA measurements in phantoms. Considering the number of CT acquisitions performed worldwide, this method could allow truly opportunistic osteoporosis screening.
• 2D scout scans (localizer radiographs) from a dual-layer spectral CT scanner, which are mandatory parts of a CT examination, can be used to automatically determine areal bone mineral density (aBMD) at the spine.
• The presented method allowed fast (< 25 s/patient), semi-automatic, and reliable DXA-equivalent aBMD measurements for state-of-the-art DXA phantoms at different tube settings and for various patient habitus, as well as for sample patients.
• Considering the number of CT scout scan acquisitions performed worldwide on a daily basis, the presented technique could enable truly opportunistic osteoporosis screening with DXA-equivalent metrics, without involving higher radiation exposure since it only processes existing data that is acquired during each CT scan.
KeywordsMultidetector computed tomography Dual-energy X-ray absorptiometry Bone density Osteoporosis Spine
Analysis of covariance (a statistical analysis technique)
Bone mineral content (g)
Bone mineral density (mg/mL), sometimes also used for areal bone mineral density (aBMD, g/cm2)
Coefficient of variation
- DXA, DEXA
Dual-energy X-ray absorptiometry
European Spine Phantom
Calcium-hydroxyapatite, the main mineral component of bone
Intravenous (contrast agent)
Quantitative computed tomography
Virtual mono-energetic scout image
We acknowledge support through QRM for providing the ESP phantom, the German Department of Education and Research (BMBF) under grant IMEDO (13GW0072C), the German Research Foundation (DFG - Gottfried Wilhelm Leibniz program), and the DFG within the Research Training Group GRK 2274.
K.B, L.C.F., and R.P. are employees of Philips. The remaining authors have no financial disclosures and had complete, unrestricted access to the study data at all stages of the study.
Compliance with ethical standards
The scientific guarantor of this publication is PD Dr. Peter B. Noël.
Conflict of interest
The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
Statistics and biometry
One of the authors has significant statistical expertise. No complex statistical methods were necessary for this paper.
Written informed consent was waived by the Institutional Review Board.
Institutional Review Board approval was obtained.
• diagnostic study/experimental
• performed at one institution
- 1.Hernlund E, Svedbom A, Ivergård M et al (2013) Osteoporosis in the European Union: medical management, epidemiology and economic burden: a report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos 8:136CrossRefGoogle Scholar
- 8.Schwaiger BJ, Kopperdahl DL, Nardo L et al (2017) Vertebral and femoral bone mineral density and bone strength in prostate cancer patients assessed in phantomless PET/CT examinations. Bone 101:62–69. https://doi.org/10.1016/j.bone.2017.04.008
- 9.Patel AA, Maver DW, Siegel EL (2010) The CT scout exam: a survey of radiation dose, utilization, and opportunity for substantial dose reduction. In: Radiological Society of North America 2010 Scientific Assembly and Annual Meeting. ChicagoGoogle Scholar
- 10.Bohrer E, Schäfer S, Mäder U, Noël PB, Krombach GA, Fiebich M (2017) Optimizing radiation exposure for CT localizer radiographs. Z Med Phys 27(2):145–158. https://doi.org/10.1016/j.zemedi.2016.09.004
- 12.Alvarez RE, Macovski A (1976) Energy-selective reconstructions in X-ray computerised tomography. Phys Med Biol 21(5):2 Available from: http://stacks.iop.org/0031-9155/21/i=5/a=002?key=crossref.9250d07732e8ba4c630ab8afe8ccd214 CrossRefGoogle Scholar
- 16.Vlassenbroek A (2011) Dual layer CT. In: Johnson T, Fink C, Schönberg S, Reiser M (eds) Dual Energy CT in Clinical Practice. Medical Radiology. Springer, Berlin, Heidelberg, pp 21–34Google Scholar
- 18.Carmi R, Naveh G, Altman A (2005) Material separation with dual-layer CT. IEEE Nucl Sci Symp Conf Rec 4:1876–1878Google Scholar
- 22.Bonnick SL (2008) Monitoring changes in bone density. Womens Health (Lond) 4(1):89–97. https://doi.org/10.2217/17455057.4.1.89
- 23.Aubert B, Vazquez C, Cresson T, Parent S, De Guise J (2016) Automatic spine and pelvis detection in frontal X-rays using deep neural networks for patch displacement learning. Proc - Int Symp Biomed Imaging; 2016–June:1426–9Google Scholar
- 26.Muenzel D, Bar-Ness D, Roessl E et al (2016) Spectral photon-counting CT: initial experience with dual–contrast agent K-edge colonography. Radiology 283(3):723–728Google Scholar
- 28.Willemink MJ, Persson M, Pourmorteza A, Pelc NJ, Fleischmann D (2018) Photon-counting CT: technical principles and clinical prospects. Radiology 172656. https://doi.org/10.1148/radiol.2018172656
- 29.Dangelmaier J, Bar-Ness D, Daerr H et al (2018) Experimental feasibility of spectral photon-counting computed tomography with two contrast agents for the detection of endoleaks following endovascular aortic repair. Eur Radiol 28(8):3318–3325Google Scholar