Imaging Sci Dent.  2019 Dec;49(4):273-279. 10.5624/isd.2019.49.4.273.

Effects of energy level, reconstruction kernel, and tube rotation time on Hounsfield units of hydroxyapatite in virtual monochromatic images obtained with dual-energy CT

• Jeong DK
• Lee SS
• Kim JE
• Huh KH
• Yi WJ
• Heo MS
• Choi SC

• KMID: 2466549
• DOI: http://doi.org/10.5624/isd.2019.49.4.273

Abstract

PURPOSE
This study was performed to investigate the effects of energy level, reconstruction kernel, and tube rotation time on Hounsfield unit (HU) values of hydroxyapatite (HA) in virtual monochromatic images (VMIs) obtained with dual-energy computed tomography (DECT) (Siemens Healthineers, Erlangen, Germany).
MATERIALS AND METHODS
A bone density calibration phantom with 3 HA inserts of different densities (CTWATER®; 0, 100, and 200 mg of HA/cm³) was scanned using a twin-beam DECT scanner at 120 kVp with tube rotation times of 0.5 and 1.0 seconds. The VMIs were reconstructed by changing the energy level (with options of 40 keV, 70 keV, and 140 keV). In order to investigate the impact of the reconstruction kernel, virtual monochromatic images were reconstructed after changing the kernel from body regular 40 (Br40) to head regular 40 (Hr40) in the reconstruction phase. The mean HU value was measured by placing a circular region of interests (ROIs) in the middle of each insert obtained from the VMIs. The HU values were compared with regard to energy level, reconstruction kernel, and tube rotation time.
RESULTS
Hydroxyapatite density was strongly correlated with HU values (correlation coefficient=0.678, P<0.05). For the HA 100 and 200 inserts, HU decreased significantly at increased energy levels (correlation coefficient= −0.538, P<0.05) but increased by 70 HU when using Hr40 rather than Br40 (correlation coefficient=0.158, P<0.05). The tube rotation time did not significantly affect the HU (P>0.05).
CONCLUSION
The HU values of hydroxyapatite were strongly correlated with hydroxyapatite density and energy level in VMIs obtained with DECT.

Keyword

Computed Tomography; Hydroxyapatite; Image Reconstruction

MeSH Terms

Bone Density
Calibration
Durapatite*
Head
Image Processing, Computer-Assisted
Durapatite

Figure

• 

  Fig. 1 A bone density calibration phantom (QRM, Moehrendorf, Germany) contained 3 inserts of different densities (0, 100, and 200 mg of hydroxyapatite [HA]/cm3). As a base material for the 3 inserts, CTWATER® (QRM, Moehrendorf, Germany) was used. CTWATER® is a solid water-equivalent plastic offering the same X-ray attenuation properties as water. In this study, CTWATER® represents 0 mg of HA/cm3. HA 100 and HA 200 represent 100 mg and 200 mg, respectively, of HA/cm3.

• 

  Fig. 2 On the cross-sectional image of the phantom, the mean Hounsfield (HU) is measured via placing a circular region of interests (ROIs) in the center of the HA 100 insert. Min: minimum value, Max: maximum value, Avg: average value, SD: standard deviation.

• 

  Fig. 3 Virtual monochromatic images of hydroxyapatite inserts of various densities obtained with dual-energy computed tomography show the differences in the image contrast and image noise depending on energy level, reconstruction kernel, and rotation time (seconds).

• 

  Fig. 4 Hounsfield units (HU) for CTWATER® (0 mg), 100, and 200 mg of hydroxyapatite/cm3 according to energy level (40, 70, or 140 keV) with a body regular 40 kernel and a 0.5 second tube rotation time. Virtually no difference in HU is observed according to the energy level of CTWATER®. The HU value increases with hydroxyapatite density, but decreases markedly with increasing energy levels.

• 

  Fig. 5 Linear attenuation coefficient µ (cm2/g) of CTWATER® (0), 100, and 200 mg of hydroxyapatite/cm3 according to energy level (40, 70, or 140 keV). Virtually no difference is observed in the linear attenuation coefficient according to the energy level of CTWATER®. The linear attenuation coefficient increases with hydroxyapatite density but decreases with increasing energy level.

Reference

1. Forghani R, De Man B, Gupta R. Dual-energy computed tomography: physical principles, approaches to scanning, usage, and implementation: part 1. Neuroimaging Clin N Am. 2017; 27:371–384.

2. Johnson TR. Dual-energy CT: general principles. AJR Am J Roentgenol. 2012; 199:5 Suppl. S3–S8.

3. Lu X, Lu Z, Yin J, Gao Y, Chen X, Guo Q. Effects of radiation dose levels and spectral iterative reconstruction levels on the accuracy of iodine quantification and virtual monochromatic CT numbers in dual-layer spectral detector CT: an iodine phantom study. Quant Imaging Med Surg. 2019; 9:188–200.

4. Rassouli N, Etesami M, Dhanantwari A, Rajiah P. Detector-based spectral CT with a novel dual-layer technology: principles and applications. Insights Imaging. 2017; 8:589–598.

5. Euler A, Parakh A, Falkowski AL, Manneck S, Dashti D, Krauss B, et al. Initial results of a single-source dual-energy computed tomography technique using a split-filter: assessment of image quality, radiation dose, and accuracy of dual-energy applications in an in vitro and in vivo study. Invest Radiol. 2016; 51:491–498.

6. Yu L, Leng S, McCollough CH. Dual-energy CT-based monochromatic imaging. AJR Am J Roentgenol. 2012; 199:5 Suppl. S9–S15.

7. Fulton N, Rajiah P. Abdominal applications of a novel detector-based spectral CT. Curr Probl Diagn Radiol. 2018; 47:110–118.

8. Hamrahian AH, Ioachimescu AG, Remer EM, Motta-Ramirez G, Bogabathina H, Levin HS, et al. Clinical utility of noncontrast computed tomography attenuation value (Hounsfield units) to differentiate adrenal adenomas / hyperplasias from nonadenomas: Cleveland Clinic experience. J Clin Endocrinol Metab. 2005; 90:871–877.

9. Levi C, Gray JE, McCullough EC, Hattery RR. The unreliability of CT numbers as absolute values. AJR Am J Roentgenol. 1982; 139:443–447.

10. Lamba R, McGahan JP, Corwin MT, Li CS, Tran T, Seibert JA, et al. CT Hounsfield numbers of soft tissues on unenhanced abdominal CT scans: variability between two different manufacturers' MDCT scanners. AJR Am J Roentgenol. 2014; 203:1013–1020.

11. Sande EP, Martinsen AC, Hole EO, Olerud HM. Interphantom and interscanner variations for Hounsfield units - establishment of reference values for HU in a commercial QA phantom. Phys Med Biol. 2010; 55:5123–5135.

12. Jacobsen MC, Schellingerhout D, Wood CA, Tamm EP, Godoy MC, SUN J, et al. Intermanufacturer comparison of dual-energy CT iodine quantification and monochromatic attenuation: a phantom study. Radiology. 2018; 287:224–234.

13. Junqueira LC, Carneiro J. Basic histology: text & atlas. 10th ed. New York: McGraw-Hill Companies;2003. p. 144.

14. van Hamersvelt RW, Schilham AM, Engelke K, den Harder AM, de Keizer B, Verhaar HJ, et al. Accuracy of bone mineral density quantification using dual-layer spectral detector CT: a phantom study. Eur Radiol. 2017; 27:4351–4359.

15. Yu L, Leng S. Image reconsgruction techniques [Internet]. Reston: American College of Radiology;2016. cited 2019 Sep 11. Availaboe from: https://www.imagewisely.org/Imaging-Modalities/Computed-Tomography/Image-Reconstruction-Techniques.

16. Achenbach S, Boehmer K, Pflederer T, Ropers D, Seltmann M, Lell M, et al. Influence of slice thickness and reconstruction kernel on the computed tomographic attenuation of coronary atherosclerotic plaque. J Cardiovasc Comput Tomogr. 2010; 4:110–115.

17. NDT Education Resource Center [Internet]. Ames: Iowa State University;2001–2014. cited 2019 Sep 11. Transmitted intensity and linear attenuation coefficient. Available from: https://www.nde-ed.org/EducationResources/CommunityCollege/Radiography/Physics/attenuationCoef.htm.

18. Hubbell JH, Seltzer SM. NIST Standard Reference Database 126. Tables of X-ray mass attenuation coefficients and mass energy-absorption coefficients from 1 keV to 20 MeV for elements Z=1 to 92 and 48 additional substances of dosimetric interest [Internet]. Gaithersburg: National Institute of Standards and Technology;1996. cited 2019 Sep 11. Available from: https://www.nist.gov/pml/x-ray-mass-attenuation-coefficients.

19. Okayama S, Soeda T, Takami Y, Kawakami R, Somekawa S, Uemura S, et al. The Influence of effective energy on computed tomography number depends on tissue characteristics in monoenergetic cardiac imaging. Radiol Res Pract. 2012; 2012:150980.

20. McCollough CH, Leng S, Yu L, Fletcher JG. Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology. 2015; 276:637–653.

21. Fornaro J, Leschka S, Hibbeln D, Butler A, Anderson N, Pache G, et al. Dual- and multi-energy CT: approach to functional imaging. Insights Imaging. 2011; 2:149–159.

22. Birnbaum BA, Hindman N, Lee J, Babb JS. Multi-detector row CT attenuation measurements: assessment of intra- and interscanner variability with an anthropomorphic body CT phantom. Radiology. 2007; 242:109–119.