Design and Construction of an Affordable Phantom for Electron Density Measurement and Linearity Tests of Computed Tomography Systems

Document Type : Original Paper

Authors

1 Medical Imaging Research Centre, Shiraz University of Medical Sciences, Shiraz, Iran

2 Ongil, 79 D3, Sivaya Nagar, Reddiyur Alagapuram, Salem 636004. India

3 Department of Instrumentation and Applied Physics, Indian Institute of Science, India, Bangalore

Abstract

Introduction: The performance of computed tomography is routinely checked using phantoms, which are known as important diagnostic imaging tools. Depending upon the aim of the study, different phantoms are designed, while trying to satisfy certain levels of diversities in their application.
Material and Methods: The present study describes the construction of an inexpensive phantom designed for simultaneous measurements of 12 different samples. The body of the phantom, test tube holders, and test tubes were made of materials of low attenuation coefficient. Body of the phantom was filled with water. Test tubes filled with solutions of known chemical compositions were mounted on the test tube holders.  The whole phantom was scanned at 80, 100, 120, 140 kVp to evaluate the performance of the CT system. Using Hounsfield Unit (HU) data from these liquid samples of known electron density, the phantom was calibrated for electron density measurements.
Results: The system's accuracy and reproducibility were verified by measuring the HU values for some known materials. According to the results obtained from the experimental datawith liquid samples, the accuracy of the water and noise was within ±3.2 HU and 0.6%, respectively. Moreover, the image uniformity error was less than ±2 HU, and CT system's linearity for calibration was estimated with 99.9% confidence.
Conclusion: The present system gives satisfactory results with known samples and can be used with confidence for characterizing unknown materials.

Keywords

Main Subjects

References

  1.  

     

    1. Yoon YE, KooNon BK. Non-invasive functional assessment using computed tomography: when will they be ready for clinical use?. Cardiovasc Diagn Ther. 2012; 2: 106-12.
    2. Mollet NR, Cademartiri F, Van Mieghem CAG, Runza G, McFadden EP, Baks T, et al. High-Resolution Spiral Computed Tomography Coronary Angiography in Patients Referred for Diagnostic Conventional Coronary Angiography. Circulation. 2005; 112: 2318-23.
    3. Bazalova M, Carrier J-F, Beaulieu L, Verhagen F , Dual-energy CT-based material extraction for tissue segmentation in Monte Carlo dose calculations. Phys. Med.Biol. 2008  53: 2439-56.
    4. Heismann B, Balda M, Quantitative image-based spectral reconstruction for computed tomography. Med. Phys. 2009 36: 4471-4485.  
    5. Govind AS, Sukumar S, Dkhar W, Grading of cerebral infraction using CT-Hounsfield unit to report the Hounsfield unit in acute, subacute and chronic stroke. International Journal of Current Research 2015 7:17874-78.  Available from : http://www.journalcra.com
    6. Cody DD, Pfeiffer D, McNitt-Gray MF, Ruckdeschel TG, Strauss KJ. Computed Tomography Quality Control Manual, American College of Radiology. available from: http://www.acr.org/~/media/ACR%20No%20Index/Documents/QC%20Manual/2012CTQCManual1a Year: 2012.
    7. International Atomic Energy Agency. HUMAN HEALTH SERIES NO.19 Quality. Assurance Program for Computed Tomography: Diagnostic and Therapy Applications. Austria Year: 2012.
    8. AAPM Diagnostic X-Ray Committee. Specification and acceptance testing of computed tomography scanners. American Association of Physicists in Medicine; 1993.
    9. Euclid S. Computed Tomography, physical principles, clinical applications, and quality control.  Second edition, W.B. SAUNDERS COMPANY, A Harcourt Health Sciences Company, New York, United States of America. 2001.
    10. Kalender WA. Computed Tomography, Fundamentals, System Technology, Image Quality, Publics Corporate Publishing.2005.
    11. Cropp RJ, Seslija P, Tso D, Thakur Y. Scanner and kVp dependence of measured CT numbers in the ACR CT phantom. J Appl Clin Med Phys. 2013; 14: 338-49. 
    12. Akpochafor MO, Adeneye SO, Kehinde O, Omojola AD, Oluwafemi A, Nusirat A, et al. Development of Computed Tomography Head and Body Phantom for Organ Dosimetry. Iran J Med Phys. 2019; 16: 8-14.
    13. Amini I, Akhlaghi P, Sarbakhsh P. Construction and verification of a physical chest phantom from suitable tissue equivalent materials for computed tomography examinations. Radiation Physics and Chemistry. 2018;150:51-7.
    14. Haghighi RR, Chatterjee S, Tabin M, Sharma S, Jagia P, Ray R, et al. DECT evaluation of non-calcified coronary artery plaque. Med Phys. 2015; 42: 5945-54.
    15. Sunga R. Solutions for Technicians. Available from: http://www.handymath.com/mission.html . 
    16. Lide DR. CRC Handbook of Chemistry and Physics. CRC Press, New York. 1997.
    17. Blumensath T, Boardman R.Non-convexly constrained image reconstructions from non-linear tomographic X-ray measurements. Phil. Transactions of the Royal Society A. 2015; 373. DOI:10.1098/esra.2014.0393.
    18. Haghighi RR, Chatterjee S, Vyas A, Kumar P, Thulkar S. X-ray attenuation coefficient of mixtures: Inputs for dual-energy CT.  Med Phys. 2011; 38:5270-9.
    19. Haghighi RR. Evaluation of the coronary artery plaque. All India Institute of Medical Sciences. New Delhi, India. 2013.
    20. Schneider W, Bortfeld T, Schlegel W. Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose. Phys Med Biol. 2000; 45:459-78.
    21. Schneider U, Pedroni E, Lomax A. The calibration of CT Hounsfield units for radiotherapy treatment planning. Phys Med Biol. 1996; 41 :111-24.
    22. Shih CT, Wu J.Converting computed tomography images into photon interactions by using stoichiometric calibration and parametric fit models. Med Phys. 2017; 44:510-21.
    23. Vanderstraeten B, Chin PW, Fix M, Leal A, Mora G, Reynaert N, Seco J, Soukup M, Spezi E, De Neve W, Thierens H. Conversion of CT numbers into tissue parameters for Monte Carlo dose calculations: a multi-centre study. Physics in Medicine & Biology. 2007 Jan 5;52(3):539.
    24. Kalender WA, AAPM Report on Computed Tomograhy Scanners.. American Association of Physicists in Medicine; 1977
    25. Pan X, Siewerdsen J, La Riviere PJ, Kalender WA, Radiation dose and image-quality assessment in Computed Tomography Radiology. Med Phys  2008 35:3728-39.
    26. Judy PF. Phantoms for performance evaluation and quality assurance of CT scanners. American Association of Physicists in Medicine Report. 1977.
    27.  27. Glover GH, Pelc NJ. Nonlinear partial volume artifacts in x‐ray computed tomography. Medical physics. 1980;7(3):238-48..
    28.  28. Park HS, Gao H, Lee SM, Seo JK. TOWARDS BEAM HARDENING CORRECTION FOR POLYCHROMATIC X-RAY CT. Journal of Computational Mathematics. 2016;34(6): 671-82.
    29. Thomas SJ. Relative electron density calibration of CT scanners for radiotherapy treatment planning.  Br J Radiol. 1999; 72: 781-6.
    30. Thomas SJ. Relative electron density calibration of CT scanners for radiotherapy treatment planning.  Br J Radiol. 1999; 72: 781-6.
    31. Mandal SR, Bharati A, Haghighi RR, Arava S, Ray R, Jagia P, et al. Non-invasive characterization of coronary artery atherosclerotic plaque using dual energy CT: Explanation in ex-vivo samples. Phys Med. 2018; 45: 52-8.
Iranian Journal of Medical Physics
Volume 17, Issue 1 - Serial Number 1
January and February 2020
Pages 38-47

Files

History

  • Receive Date: 14 March 2019
  • Revise Date: 12 May 2019
  • Accept Date: 20 May 2019

Share

How to cite

Statistics