Dose Adjustments for Accuracy: Ultralow Dose Radiation 3D CBCT for Dental and Orthodontic Application

  • Maria Therese S. Galang-Boquiren
  • Budi KusnotoEmail author
  • Zhang Zheng
  • Xiaochuan Pan


Cone beam computed tomography (CBCT) is increasingly popular when gathering initial patient imaging records for diagnosis and treatment planning. Although traditional two-dimensional panoramic or cephalometric radiographs can provide sufficient information to perform treatment in most cases, clinicians have become aware of the distortion inherent with these radiographs that can affect angular and linear measurements and, more importantly, tooth location and tooth-bone-jaw relationships.

A problem with CBCT technology is that its routine use poses a health risk as a source of ionizing radiation, especially in orthodontic patients who are mostly growing patients, preadolescent, and adolescent.

But what if there was a way to reduce the radiation dose and still reap the benefits of this technology to better serve our patients? This chapter will discuss dose adjustment methods used in the medical arena and their applications in the dental profession, with special focus on orthodontics.


Cone beam CT Orthodontics Dentistry Radiation dose Medical radiology Reconstruction algorithm Radiation exposure Dose reduction 


  1. 1.
    American Association of Orthodontists. Statement on the role of CBCT in orthodontics. Creve Coeur, MO: American Association of Orthodontists; 2010. p. 26-10H.Google Scholar
  2. 2.
    American Dental Association Council on Scientific Affairs. The use of cone beam computed tomography in dentistry: an advisory statement from the American Dental Association Council on Scientific Affairs. J Am Dent Assoc. 2012;143:899–902.CrossRefGoogle Scholar
  3. 3.
    American Academy of Oral and Maxillofacial Radiology. Clinical recommendations regarding use of cone beam computed tomography in orthodontics. Position statement by the American Academy of Oral and Maxillofacial Radiology. Oral Surg Oral Med Oral Pathol Oral Radiol. 2013;116:238–57. Scholar
  4. 4.
    Ludlow JB. A manufacturer’s role in reducing the dose of cone beam computed tomography examinations: effect of beam filtration. Dentomaxillofac Radiol. 2011;40:115–22. Scholar
  5. 5.
    Qiu W, Pengpan T, Smith ND, Soleimani M. Evaluating iterative algebraic algorithms in terms of convergence and image quality for cone beam CT. Comput Methods Prog Biomed. 2013;109:313–22. Scholar
  6. 6.
    Park JC, Song B, Kim JS, Park SH, Kim HK, Liu Z, et al. Fast compressed sensing-based CBCT reconstruction using Barzilai–Borwein formulation for application to on-line IGRT. Med Phys. 2012;39:1207–17. Scholar
  7. 7.
    Walker L, Enciso R, Mah J. Three-dimensional localization of maxillary canines with cone-beam computed tomography. Am J Orthod Dentofac Orthop. 2005;128:418–23.CrossRefGoogle Scholar
  8. 8.
    Hatcher DC, Miller A, Peck JL, Sameshima GT, Worth P. Mesiodistal root angulation using panoramic and cone beam CT. Angle Orthod. 2007;77:206–13.CrossRefGoogle Scholar
  9. 9.
    Monnerat C, Restle L, Mucha JN. Tomographic mapping of mandibular interradicular spaces for placement of orthodontic mini-implants. Am J Orthod Dentofac Orthop. 2009;135:428–9.CrossRefGoogle Scholar
  10. 10.
    Baik HS, Kim KD, Lee KJ, Park SH, Yu HS. A proposal for a new analysis of craniofacial morphology by 3-dimensional computed tomography. Am J Orthod Dentofac Orthop. 2006;129:600. e23–600. e34.Google Scholar
  11. 11.
    Nakajima A, Arai Y, Dougherty H Sr, Homme Y, Sameshima GT, Shimizu N. Two- and three-dimensional orthodontic imaging using limited cone beam–computed tomography. Angle Orthod. 2005;75:895–903.PubMedGoogle Scholar
  12. 12.
    Larson BE. Cone-beam computed tomography is the imaging technique of choice for comprehensive orthodontic assessment. Am J Orthod Dentofac Orthop. 2012;141:402–4., 406 passim. Scholar
  13. 13.
    Halazonetis DJ. Cone-beam computed tomography is not the imaging technique of choice for comprehensive orthodontic assessment. Am J Orthod Dentofac Orthop. 2012;141:403–5., 407 passim. Scholar
  14. 14.
    Wiesent K, Barth K, Navab N, Durlak P, Brunner T, Schuetz T, et al. Enhanced 3-D-reconstruction algorithm for C-arm systems suitable for interventional procedures. IEEE Trans Med Imaging. 2000;19:391–403.CrossRefGoogle Scholar
  15. 15.
    Lauritsch G, Boese J, Wigström L, Kemeth H, Fahrig R. Towards cardiac C-arm computed tomography. IEEE Trans Med Imaging. 2006;25:922–34.CrossRefGoogle Scholar
  16. 16.
    Wallace MJ, Kuo MD, Glaiberman C, Binkert CA, Orth RC, Soulez G. Three-dimensional C-arm cone-beam CT: applications in the interventional suite. J Vasc Interv Radiol. 2008;19:799–813. Scholar
  17. 17.
    Orth RC, Wallace MJ, Kuo MD. C-arm cone-beam CT: general principles and technical considerations for use in interventional radiology. J Vasc Interv Radiol. 2008;19:814–20. Scholar
  18. 18.
    Grass M, Koppe R, Klotz E, Proksa R, Kuhn M, Aerts H, et al. Three-dimensional reconstruction of high contrast objects using C-arm image intensifier projection data. Comput Med Imaging Graph. 1999;23:311–21.CrossRefGoogle Scholar
  19. 19.
    Siewerdsen JH, Moseley DJ, Burch S, Bisland SK, Bogaards A, Wilson BC, et al. Volume CT with a flat-panel detector on a mobile, isocentric C-arm: pre-clinical investigation in guidance of minimally invasive surgery. Med Phys. 2005;32:241–54.CrossRefGoogle Scholar
  20. 20.
    Hott JS, Deshmukh VR, Klopfenstein JD, Sonntag VK, Dickman CA, Spetzler RF, et al. Intraoperative Iso-C C-arm navigation in craniospinal surgery: the first 60 cases. Neurosurgery. 2004;54:1131–7.CrossRefGoogle Scholar
  21. 21.
    De Vos W, Casselman J, Swennen G. Cone-beam computerized tomography (CBCT) imaging of the oral and maxillofacial region: a systematic review of the literature. Int J Oral Maxillofac Surg. 2009;38:609–25. Scholar
  22. 22.
    Jaffray DA, Siewerdsen JH, Wong JW, Martinez AA. Flat-panel cone-beam computed tomography for image-guided radiation therapy. Int J Radiat Oncol Biol Phys. 2002;53:1337–49.CrossRefGoogle Scholar
  23. 23.
    Oldham M, Létourneau D, Watt L, Hugo G, Yan D, Lockman D, et al. Cone-beam-CT guided radiation therapy: a model for on-line application. Radiother Oncol. 2005;75:271–8.CrossRefGoogle Scholar
  24. 24.
    Smitsmans MH, De Bois J, Sonke J-J, Betgen A, Zijp LJ, Jaffray DA, et al. Automatic prostate localization on cone-beam CT scans for high precision image-guided radiotherapy. Int J Radiat Oncol Biol Phys. 2005;63:975–84.CrossRefGoogle Scholar
  25. 25.
    Grills IS, Hugo G, Kestin LL, Galerani AP, Chao KK, Wloch J, et al. Image-guided radiotherapy via daily online cone-beam CT substantially reduces margin requirements for stereotactic lung radiotherapy. Int J Radiat Oncol Biol Phys. 2008;70:1045–56.CrossRefGoogle Scholar
  26. 26.
    Sidky EY, Kao C-M, Pan X. Accurate image reconstruction from few-views and limited-angle data in divergent-beam CT. J Xray Sci Technol. 2006;14:119–39.Google Scholar
  27. 27.
    Sidky EY, Pan X. Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization. Phys Med Biol. 2008;53:4777–807. Scholar
  28. 28.
    Bian J, Siewerdsen JH, Han X, Sidky EY, Prince JL, Pelizzari CA, et al. Evaluation of sparse-view reconstruction from flat-panel-detector cone-beam CT. Phys Med Biol. 2010;55:6575–99. Scholar
  29. 29.
    Bian J, Yang K, Boone JM, Han X, Sidky EY, Pan X. Investigation of iterative image reconstruction in low-dose breast CT. Phys Med Biol. 2014;59:2659–85. Scholar
  30. 30.
    Zhang Z, Han X, Pearson E, Pelizzari C, Sidky EY, Pan X. Artifact reduction in short-scan CBCT by use of optimization-based reconstruction. Phys Med Biol. 2016;61:3387–406. Scholar
  31. 31.
    Xia D, Langan DA, Solomon SB, Zhang Z, Chen B, Lai H, et al. Optimization-based image reconstruction with artifact reduction in C-arm CBCT. Phys Med Biol. 2016;61:7300–33.CrossRefGoogle Scholar
  32. 32.
    Delaney A, Bresler Y, Sunnyvale C. Globally convergent edge-preserving regularized reconstruction: an application to limited-angle tomography. IEEE Trans Image Process. 1998;7:204–21. Scholar
  33. 33.
    Elbakri I, Fessler J. Statistical image reconstruction for polyenergetic X-ray computed tomography. IEEE Trans Med Imaging. 2002;21:89–99.CrossRefGoogle Scholar
  34. 34.
    Pan X, Sidky EY, Vannier M. Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction? Inverse Probl. 2009;25:123009. Scholar
  35. 35.
    Tang J, Nett BE, Chen G-H. Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms. Phys Med Biol. 2009;54:5781–804. Scholar
  36. 36.
    Stsepankou D, Arns A, Ng S, Zygmanski P, Hesser J. Evaluation of robustness of maximum likelihood cone-beam CT reconstruction with total variation regularization. Phys Med Biol. 2012;57:5955–70. Scholar
  37. 37.
    Sidky EY, Jørgensen JH, Pan X. Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm. Phys Med Biol. 2012;57:3065–91. Scholar
  38. 38.
    Wang AS, Stayman JW, Otake Y, Kleinszig G, Vogt S, Gallia GL, et al. Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction. Phys Med Biol. 2014;59:1005–26. Scholar
  39. 39.
    Nien H, Fessler JA. Fast splitting-based ordered-subsets X-ray CT Image reconstruction. Proceedings of the third international conference on image form Xray computed tomography. 2014. pp. 291–294. Accessed 16 Jul 2017.
  40. 40.
    Han X, Bian J, Eaker DR, Kline TL, Sidky EY, Ritman EL, et al. Algorithm-enabled low-dose micro-CT imaging. IEEE Trans Med Imaging. 2011;30:606–20. Scholar
  41. 41.
    Bian J, Wang J, Han X, Sidky EY, Shao L, Pan X. Optimization-based image reconstruction from sparse-view data in offset-detector CBCT. Phys Med Biol. 2012;58:205–30. Scholar
  42. 42.
    Zhang Z, Han X, Kusnoto B, Sidky EY, Pan X. Preliminary evaluation of dental cone-beam CT image reconstruction from reduced projection data by constrained TV-minimization. Proceedings of the third international conference on image form Xray computed tomography. 2014. pp. 299–302. Accessed 16 Jul 2017.
  43. 43.
    Kusnoto B, Kaur P, Salem A, Zhang Z, Galang-Boquiren MT, Viana G, et al. Implementation of ultra-low-dose CBCT for routine 2D orthodontic diagnostic radiographs: cephalometric landmark identification and image quality assessment. Semin Orthod. 2015;21:233–47. Scholar
  44. 44.
    Chambolle A, Pock T. A first-order primal-dual algorithm for convex problems with applications to imaging. J Math Imaging Vis. 2011;40:120–45. Scholar
  45. 45.
    Sidky EY, Kraemer DN, Roth EG, Ullberg C, Reiser IS, Pan X. Analysis of iterative region-of interest image reconstruction for x-ray computed tomography. J Med Imaging (Bellingham). 2014;1:031007. Scholar
  46. 46.
    Sidky EY, Chartrand R, Boone JM, Pan X. Constrained TpV minimization for enhanced exploitation of gradient sparsity: application to CT image reconstruction. IEEE J Trans Eng Health Med. 2014;2:1–18.CrossRefGoogle Scholar
  47. 47.
    Zhang Z, Ye J, Chen B, Perkins AE, Rose S, Sidky EY, et al. Investigation of optimization-based reconstruction with an image-total-variation constraint in PET. Phys Med Biol. 2016;61:6055–84. Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Maria Therese S. Galang-Boquiren
    • 1
  • Budi Kusnoto
    • 1
    Email author
  • Zhang Zheng
    • 2
  • Xiaochuan Pan
    • 2
    • 3
  1. 1.Department of OrthodonticsUniversity of Illinois at Chicago College of DentistryChicagoUSA
  2. 2.Department of RadiologyThe University of ChicagoChicagoUSA
  3. 3.Department of Radiation and Cellular OncologyThe University of ChicagoChicagoUSA

Personalised recommendations