J Korean Assoc Maxillofac Plast Reconstr Surg.  2013 May;35(3):167-173.

Marginal Bone Resorption Analysis of Dental Implant Patients by Applying Pattern Recognition Algorithm

Affiliations
  • 1Department of Oral and Maxillofacial Surgery, School of Dentistry, Seoul National University, Korea. myungkim@snu.ac.kr
  • 2Department of Prosthodontics, School of Dentistry, Seoul National University, Korea.
  • 3Dental Research Institute, School of Dentistry, Seoul National University, Korea.

Abstract

PURPOSE
The aim of this study is to analyze the series of panoramic radiograph of implant patients using the system to measure peri-implant crestal bone loss according to the elapsed time from fixture installation time to more than three years.
METHODS
Choose 10 patients having 45 implant fixtures installed, which have series of panoramic radiograph in the period to be analyzed by the system. Then, calculated the crestal bone depth and statistics and selected the implant in concerned by clicking the implant of image shown on the monitor by the implemented pattern recognition system. Then, the system recognized the x, y coordination of the implant and peri-implant alveolar crest, and calculated the distance between the approximated line of implant fixture and alveolar crest. By applying pattern recognition to periodic panoramic radiographs, we attained the results and made a comparison with the results of preceded articles concerning peri-implant marginal bone loss. Analyzing peri-implant crestal bone loss in a regression analysis periodic filmed panoramic radiograph, logarithmic approximation had highest R2 value, and the equation is as shown below. y=0.245Logx+/-0.42, R2=0.53, unit: month (x), mm (y)
RESULTS
Panoramic radiograph is a more wide-scoped view compared with the periapical radiograph in the same resolution. Therefore, there was not enough information in the radiograph in local area. Anterior portion of many radiographs was out of the focal trough and blurred precluding the accurate recognition by the system, and many implants were overlapped with the adjacent structures, in which the alveolar crest was impossible to find.
CONCLUSION
Considering the earlier objective and error, we expect better results from an analysis of periapical radiograph than panoramic radiograph. Implementing additional function, we expect high extensibility of pattern recognition system as a diagnostic tool to evaluate implant-bone integration, calculate length from fixture to inferior alveolar nerve, and from fixture to base of the maxillary sinus.

Keyword

Dental implants; Marginal bone loss; Pattern recognition algorithm; Segmentation process

MeSH Terms

Bone Resorption
Dental Implants
Humans
Mandibular Nerve
Maxillary Sinus
Organothiophosphorus Compounds
Pattern Recognition, Automated
Dental Implants
Organothiophosphorus Compounds
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