Development of Computer-assisted Diagnosis Using Digital Radiography for the Evaluation of Dental Implant Osseointegration

DOI 39 References
  • Hayashi Kiyonobu
    Division of Radiology, Department of Maxillofacial Diagnostic Science, Kanagawa Dental College
  • Kaku Yusuke
    Division of Radiology, Department of Maxillofacial Diagnostic Science, Kanagawa Dental College
  • Kawamata Ryota
    Division of Radiology, Department of Maxillofacial Diagnostic Science, Kanagawa Dental College
  • Nakamura Koji
    Division of Radiology, Department of Maxillofacial Diagnostic Science, Kanagawa Dental College
  • Sakurai Takashi
    Division of Radiology, Department of Maxillofacial Diagnostic Science, Kanagawa Dental College
  • Kashima Isamu
    Division of Radiology, Department of Maxillofacial Diagnostic Science, Kanagawa Dental College

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Abstract

To develop an osseointegration analyzing system for dental implants, a new analyzing system which can assess the level of osseointegration between an implant and trabecular bone was constructed using digital radiography with morphological filter and node-strut analysis. For assessment of this system, a grayscale test chart that simulates six levels of an osseointegration was created. In addition, digital implant images were made in which the trabecular pattern around the implant was varied over a total of five levels. Implant osseointegration was evaluated on the basis of seven parameters related to the number of nodes (Nd) and terminuses (Tm) of the skeleton bound to the implant (Im) and the skeletal length. The seven parameters were as follows: the number of struts connecting the Im with the Nd and Tm (N.ImNd, N.ImTm), the total number of N.ImNd and N.ImTm (N.Im), the strut length connecting the Im with the Nd and Tm (ImNd, ImTm), and the ratios of the struts connecting the Im with the Nd and Tm (ImNd/TSL, ImTm/TSL), where TSL is the total strut length.<BR>Strong correlations (R2 = 0.971-1.0) between the theoretical values from the test charts and the measured values were demonstrated. N.ImNd showed the strongest correlation, R2 = 0.948, from the digital implant images, followed by N.Im and ImNd, with correlations of R2 = 0.86 and R2 = 0.84, respectively. This new system for evaluating implant osseointegration by applying morphological processing and node-strut analysis could be useful for computer-assisted diagnosis of digital dental implant images.

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