Imaging Science in Dentistry

Korean Academy of Oral and Maxillofacial Radiology (대한영상치의학회)
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Optimizing the reconstruction filter in cone-beam CT to improve periodontal ligament space visualization: An in vitro study

  • Houno, Yuuki (Graduate School of Medicine, Nagoya University) ;
  • Hishikawa, Toshimitsu (Department of Periodontology, School of Dentistry, Aichi Gakuin University) ;
  • Gotoh, Ken-ichi (Division of Radiology, Dental Hospital, Aichi Gakuin University) ;
  • Naitoh, Munetaka (Department of Oral and Maxillofacial Radiology, School of Dentistry, Aichi Gakuin University) ;
  • Mitani, Akio (Department of Periodontology, School of Dentistry, Aichi Gakuin University) ;
  • Noguchi, Toshihide (Department of Periodontology, School of Dentistry, Aichi Gakuin University) ;
  • Ariji, Eiichiro (Department of Oral and Maxillofacial Radiology, School of Dentistry, Aichi Gakuin University) ;
  • Kodera, Yoshie (Graduate School of Medicine, Nagoya University)
  • Received : 2017.03.22
  • Accepted : 2017.06.07
  • Published : 2017.09.30
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Abstract

Purpose: Evaluation of alveolar bone is important in the diagnosis of dental diseases. The periodontal ligament space is difficult to clearly depict in cone-beam computed tomography images because the reconstruction filter conditions during image processing cause image blurring, resulting in decreased spatial resolution. We examined different reconstruction filters to assess their ability to improve spatial resolution and allow for a clearer visualization of the periodontal ligament space. Materials and Methods: Cone-beam computed tomography projections of 2 skull phantoms were reconstructed using 6 reconstruction conditions and then compared using the Thurstone paired comparison method. Physical evaluations, including the modulation transfer function and the Wiener spectrum, as well as an assessment of space visibility, were undertaken using experimental phantoms. Results: Image reconstruction using a modified Shepp-Logan filter resulted in better sensory, physical, and quantitative evaluations. The reconstruction conditions substantially improved the spatial resolution and visualization of the periodontal ligament space. The difference in sensitivity was obtained by altering the reconstruction filter. Conclusion: Modifying the characteristics of a reconstruction filter can generate significant improvement in assessments of the periodontal ligament space. A high-frequency enhancement filter improves the visualization of thin structures and will be useful when accurate assessment of the periodontal ligament space is necessary.

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References

  1. Corbet EF, Ho DK, Lai SM. Radiographs in periodontal disease diagnosis and management. Aust Dent J 2009; 54 Suppl 1: S27-43. https://doi.org/10.1111/j.1834-7819.2009.01141.x
  2. Grondhal HG, Huumonen S. Radiographic manifestations of periapical inflammatory lesions: how new radiological techniques may improve endodontic diagnosis and treatment planning. Endod Topics 2004; 8: 55-67. https://doi.org/10.1111/j.1601-1546.2004.00082.x
  3. Andersson L, Blomlof L, Lindskog S, Feiglin B, Hammarstrom L. Tooth ankylosis. Clinical, radiographic and histological assessments. Int J Oral Surg 1984; 13: 423-31. https://doi.org/10.1016/S0300-9785(84)80069-1
  4. de Faria Vasconcelos K, Evangelista KM, Rodrigues CD, Estrela C, de Sousa TO, Silva MA. Detection of periodontal bone loss using cone beam CT and intraoral radiography. Dentomaxillofac Radiol 2012; 41: 64-9. https://doi.org/10.1259/dmfr/13676777
  5. Esmaeli F, Shirmohammadi A, Faramarzie M, Abolfazli N, Rasouli H, Fallahi S. Determination of vertical interproximal bone loss topography: correlation between indirect digital radiographic measurement and clinical measurement. Iran J Radiol 2012; 9: 83-7. https://doi.org/10.5812/iranjradiol.7732
  6. Baksi BG. Measurement accuracy and perceived quality of imaging systems for the evaluation of periodontal structures. Odontology 2008; 96: 55-60. https://doi.org/10.1007/s10266-008-0081-4
  7. Fuhrmann RA, Wehrbein H, Langen HJ, Diedrich PR. Assessment of the dentate alveolar process with high resolution computed tomography. Dentomaxillofac Radiol 1995; 24: 50-4. https://doi.org/10.1259/dmfr.24.1.8593909
  8. Hishikawa T, Izumi M, Naitoh M, Yoshinari N, Kawase H, Matsuoka M, et al. Effects of the vertical projection angle in intraoral radiography on the detection of furcation involvement of the mandibular first molar. Oral Radiol 2011; 27: 102-7. https://doi.org/10.1007/s11282-011-0070-0
  9. Misch KA, Yi ES, Sarment DP. Accuracy of cone beam computed tomography for periodontal defect measurements. J Periodontol 2006; 77: 1261-6. https://doi.org/10.1902/jop.2006.050367
  10. Walter C, Kaner D, Berndt DC, Weiger R, Zitzmann NU. Three-dimensional imaging as a pre-operative tool in decision making for furcation surgery. J Clin Periodontol 2009; 36: 250-7. https://doi.org/10.1111/j.1600-051X.2008.01367.x
  11. Naitoh M, Yamada S, Noguchi T, Ariji E, Nagao J, Mori K, et al. Three-dimensional display with quantitative analysis in alveolar bone resorption using cone-beam computerized tomography for dental use: a preliminary study. Int J Periodontics Restorative Dent 2006; 26: 607-12.
  12. Bayat S, Talaeipour AR, Sarlati F. Detection of simulated periodontal defects using cone-beam CT and digital intraoral radiography. Dentomaxillofac Radiol 2016; 45: 20160030. https://doi.org/10.1259/dmfr.20160030
  13. Nemtoi A, Czink C, Haba D, Gahleitner A. Cone beam CT: a current overview of devices. Dentomaxillofac Radiol 2013; 42: 20120443. https://doi.org/10.1259/dmfr.20120443
  14. Ozmeric N, Kostioutchenko I, Hagler G, Frentzen M, Jervoe-Storm PM. Cone-beam computed tomography in assessment of periodontal ligament space: in vitro study on artificial tooth model. Clin Oral Investig 2008; 12: 233-9. https://doi.org/10.1007/s00784-008-0186-8
  15. Jervoe-Storm PM, Hagner M, Neugebauer J, Ritter L, Zoller JE, Jepsen S, et al. Comparison of cone-beam computerized tomography and intraoral radiographs for determination of the periodontal ligament in a variable phantom. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2010; 109: e95-101.
  16. Bushberg JT, Seibert JA, Leidholdt EM, Boone JM. The essential physics of medical imaging. 2nd ed. Philadelphia: Lippincott Williams & Wilkins; 2002. p. 368-9.
  17. Hsieh J, Nett B, Yu Z, Sauer K, Thibault JB, Bouman CA. Recent advances in CT image reconstruction. Curr Radiol Rep 2013; 1: 39-51. https://doi.org/10.1007/s40134-012-0003-7
  18. Feldkamp LA, Davis LC, Kress JW. Practical cone-beam algorithm. J Opt Soc Am A 1984; 1: 612-9. https://doi.org/10.1364/JOSAA.1.000612
  19. Lee SW, Lee CL, Cho HM, Park HS, Kim DH, Choi YN, et al. Effects of reconstruction parameters on image noise and spatial resolution in cone-beam computed tomography. J Korean Phys Soc 2011; 59: 2825-32. https://doi.org/10.3938/jkps.59.2825
  20. Worthy S. High resolution computed tomography of the lungs. BMJ 1995; 310: 615-6.
  21. Rezvani N, Aruliah D, Jackson K, Moseley D, Siewerdsen J. SU-FF-I-16: OSCaR: an open-source cone-beam CT reconstruction tool for imaging research. Med Phys 2007; 34: 2341.
  22. Ramachandran GN, Lakshminarayanan AV. Three-dimensional reconstruction from radiographs and electron micrographs: application of convolutions instead of Fourier transforms. Proc Natl Acad Sci U S A 1971; 68: 2236-40. https://doi.org/10.1073/pnas.68.9.2236
  23. Shepp LA, Logan BF. The Fourier reconstruction of a head section. IEEE Trans Nucl Sci 1974; 21: 21-43.
  24. Thurstone LL. A law of comparative judgment. Psychol Rev 1927; 34: 273-86. https://doi.org/10.1037/h0070288
  25. Scheffe H. An analysis of variance for paired comparisons. J Am Stat Assoc 2012; 47: 381-400.
  26. Rossmann K. Point spread-function, line spread-function, and modulation transfer function. Tools for the study of imaging systems. Radiology 1969; 93: 257-72. https://doi.org/10.1148/93.2.257
  27. Nickoloff EL. Measurement of the PSF for a CT scanner: appropriate wire diameter and pixel size. Phys Med Biol 1988; 33: 149-55. https://doi.org/10.1088/0031-9155/33/1/014
  28. Boedeker KL, Cooper VN, McNitt-Gray MF. Application of the noise power spectrum in modern diagnostic MDCT: part I. Measurement of noise power spectra and noise equivalent quanta. Phys Med Biol 2007; 52: 4027-46. https://doi.org/10.1088/0031-9155/52/14/002
  29. Boedeker KL, McNitt-Gray MF. Application of the noise power spectrum in modern diagnostic MDCT: part II. Noise power spectra and signal to noise. Phys Med Biol 2007; 52: 4047-61. https://doi.org/10.1088/0031-9155/52/14/003
  30. Barrett J, Keat N. Artifacts in CT: recognition and avoidance. Radiographics 2004; 24: 1679-91. https://doi.org/10.1148/rg.246045065

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