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Determination of computed tomography number of high-density materials in 12-bit, 12-bit extended and 16-bit depth for dosimetric calculation in treatment planning system

Published online by Cambridge University Press:  19 February 2019

Jayapramila Jayamani Open the ORCID record for Jayapramila Jayamani [Opens in a new window] ,
Noor Diyana Osman ,
Abdul Aziz Tajuddin ,
Zaker Salehi ,
Mohd Hanafi Ali  and
Mohd Zahri Abdul Aziz
Jayapramila Jayamani
Affiliation:
Oncological and Radiological Sciences Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Pulau Pinang, Malaysia
Noor Diyana Osman
Affiliation:
Oncological and Radiological Sciences Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Pulau Pinang, Malaysia
Abdul Aziz Tajuddin
Affiliation:
Oncological and Radiological Sciences Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Pulau Pinang, Malaysia
Zaker Salehi
Affiliation:
Department of Radiation Sciences, Yasuj University of Medical Sciences, Yasuj, Iran
Mohd Hanafi Ali
Affiliation:
The Discipline of Medical Radiation Sciences, The University of Sydney, Sydney, Australia
Mohd Zahri Abdul Aziz*
Affiliation:
Oncological and Radiological Sciences Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Pulau Pinang, Malaysia
*
Author for correspondence: Mohd Zahri Abdul Aziz, University Lecturer, Oncological and Radiological Sciences Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, 13200 Kepala Batas, Pulau Pinang, Malaysia. Tel: +604-5622356. E-mail: [email protected]
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Abstract

Aim

The main aim was to examine the effect of bit depth on computed tomography (CT) number for high-density materials. Analysis of the CT number for high-density materials using 16-bit scanners will extend the CT scale that currently exists for 12-bit scanners and thus will be beneficial for use in CT–electron density (ED) curve in radiotherapy treatment planning system (TPS). Implementation of this extended CT scale will compensate for tissue heterogeneity during CT–ED conversion in treatment planning.

Materials and methods

An in-house built phantom with 10 different metal samples was scanned using 80, 100 and 120 kVp in two different CT scanners. A region of interest was set at the centre of the material and the mean CT numbers together with data deviation were determined. Dosimetry calculation was performed by applying a direct anterior beam on 12-bit, 12-bit extended and 16-bit.

Results

High-density materials (>4·34 g cm−3) in 16-bit depth provide disparities up to 44% compared to Siemens’ 12-bit extended. Influence of tube voltage showed a significant difference (p<0·05) in both bit depth and CT number of the gold and amalgam saturated in 16-bit depth. A 120 kVp energy illustrated a low variation on CT number for different scanners, but dosimetry calculation showed significant disparities at the metal interface in 12-bit, 12-bit extended and 16-bit.

Findings

High-density materials require 16-bit scanners to obtain CT number to be implemented in treatment planning in radiotherapy. This also suggests that proper tube voltage together with correct CT–ED resulted in accurate TPS algorithm calculation.

Keywords

bit depthCT numberdosimetryhigh-density materialtreatment planning system (TPS)
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 18 , Issue 3 , September 2019 , pp. 285 - 294
Copyright
© Cambridge University Press 2019 

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Footnotes

Cite this article: Jayamani J, Osman ND, Tajuddin AA, Salehi Z, Ali MH, Abdul Aziz MZ. (2019) Determination of computed tomography number of high-density materials in 12-bit, 12-bit extended and 16-bit depth for dosimetric calculation in treatment planning system. Journal of Radiotherapy in Practice18: 285–294. doi: 10.1017/S1460396919000013

References

1. Yagi, M, Ueguchi, T, Koizumi, M et al. Gemstone spectral imaging: Determination of CT to ED conversion curves for radiotherapy treatment planning. J Appl Clin Med Phys 2013; 14 (5): 173–186.10.1120/jacmp.v14i5.4335Google Scholar
2. Van Elmpt, W, Landry, G, Das, M, Verhaegen, F. Dual energy CT in radiotherapy: current applications and future outlook. Radiother Oncol 2016; 119 (1): 137–144.10.1016/j.radonc.2016.02.026Google Scholar
3. Coolens, C, Childs, P J. Calibration of CT Hounsfield units for radiotherapy treatment planning of patients with metallic hip prostheses: the use of the extended CT-scale. Phys Med Biol 2003; 48 (1): 1591–1603.Google Scholar
4. Glide-Hurst, C, Chen, D, Zhong, H, Chetty, I J. Changes realized from extended bit-depth and metal artifact reduction in CT. Med Phys 2013; 40 (6): 061711.10.1118/1.4805102Google Scholar
5. Das, I J, Cheng, C-W, Cao, M, Johnstone, P S. Computed tomography imaging parameters for inhomogeneity correction in radiation treatment planning. J Med Phys 2016; 41 (1): 3–11.10.4103/0971-6203.177277Google Scholar
6. Giantsoudi, D, De Man, B, Verburg, J et al. Metal artifacts in computed tomography for radiation therapy planning: dosimetric effects and impact of metal artifact reduction. Phys Med Biol 2017; 62 (8): R49–R80.10.1088/1361-6560/aa5293Google Scholar
7. Xin-Ye, N, Liugang, G, Mingming, F, Tao, L. Application of metal implant 16-bit imaging: new technique in radiotherapy. Technol Cancer Res Treat 2017; 16 (2): 188–194.10.1177/1533034616649530Google Scholar
8. Papanikolaou, N, Battista, J, Boyer, A. et al. AAPm Report No. 85: Tissue Inhomogeneity Corrections for Megavoltage Photon Beams. Madison, WI: Medical Physics Publishing, 2004.Google Scholar
9. Indrajit, I K, Verma, B S. Digital imaging in radiology practice: an introduction to few fundamental concepts. Indian J. Radiol. Imaging 2007; 17 (4): 230–236.10.4103/0971-3026.36866Google Scholar
10. Mullins, J P, Grams, M P, Herman, M G, Brinkmann, D H, Antolak, J A. Treatment planning for metals using an extended CT number scale. J Appl Clin Med Phys 2016; 17 (6): 179–188.10.1120/jacmp.v17i6.6153Google Scholar
11. Jechel, C A. CT Image Electron Density Quantification in Regions with Metal Implants: Implications for Radiotherapy Treatment Planning. Queen’s University, Kingston, Ontario, Canada, 2016.Google Scholar
12. Hebb, A O, Poliakov, A V. Imaging of deep brain stimulation leads using extended Hounsfield unit CT. Stereotact Funct Neurosurg 2009; 87 (3): 155–160.10.1159/000209296Google Scholar
13. Escott, E J, Rubinstein, D. Free DICOM image viewing and processing software for your desktop computer: what’s available and what it can do for you. RadioGraphics 2003; 23 (5): 1341–1357.10.1148/rg.235035047Google Scholar
14. Allisy-Roberts, P, Williams, J R, Jerry, R, Farr, R F, Reginald, F. Digital radiography. In: Farr’s Physics for Medical Imaging. Saunders, 2008: 80.10.1016/B978-0-7020-2844-1.50009-0Google Scholar
15. Hernandez, Y. Nist Reference Tables. 2017. Available at: https://www.nist.gov/ncnr/sample-environment/sample-mounting/reference-tables. Accessed on 10th July 2018.Google Scholar
16. Shin, H J, Chung, Y E, Lee, Y H et al. Radiation dose reduction via sinogram affirmed iterative reconstruction and automatic tube voltage modulation (CARE kV) in abdominal CT. Korean J Radiol 2013; 14 (6): 886–893.10.3348/kjr.2013.14.6.886Google Scholar
17. Gao, G, Sun, H, Ni, X, Fang, M, Lin, T. Effects of 16-bit CT imaging scanning conditions for metal implants on radiotherapy dose distribution. Oncol Lett 2018; 15 (2): 2373–2379.Google Scholar
18. Mahmoudi, R, Jabbari, N, Aghdasi, M, Khalkhali, HR. Energy dependence of measured CT numbers on substituted materials used for CT number calibration of radiotherapy treatment planning systems. PLoS One 2016; 11: e0158828.10.1371/journal.pone.0158828Google Scholar
19. Ebert, M A, Lambert, J, Greer, P B. CT-ED conversion on a GE lightspeed-RT scanner: influence of scanner settings. Australas Phys Eng Sci Med 2008; 31: 154–159.10.1007/BF03178591Google Scholar
20. Zurl, B, Tiefling, R, Winkler, P, Kindl, P, Kapp, K S. Hounsfield units variations. Strahlentherapie und Onkol 2014; 190 (1): 88–93.10.1007/s00066-013-0464-5Google Scholar
21. Webster, G J, Rowbottom, C G, Mackay, R I, Voet, P, Levendag, P. Evaluation of the impact of dental artefacts on intensity-modulated radiotherapy planning for the head and neck. Radiother Oncol 2009; 93 (3): 553–558.10.1016/j.radonc.2009.10.006Google Scholar