BACKGROUND: Subjective radiographic classifications of alveolar bone have been proposed and correlated with implant insertion torque (IT). The present diagnostic study aims to identify quantitative bone features influencing IT and to use these findings to develop an objective radiographic classification for predicting IT. METHODS: Demographics, panoramic radiographs (taken at the beginning of dental treatment), and cone-beam computed tomographic scans (taken for implant surgical planning) of 25 patients receiving 31 implants were analyzed. Bone samples retrieved from implant sites were assessed with dual x-ray absorptiometry, microcomputed tomography, and histology. Odds ratio, sensitivity, and specificity of all variables to predict high peak IT were assessed. RESULTS: A ridge cortical thickness >0.75 mm and a normal appearance of the inferior mandibular cortex were the most sensitive variables for predicting high peak IT (87.5% and 75%, respectively). A classification based on the combination of both variables presented high sensitivity (90.9%) and specificity (100%) for predicting IT. CONCLUSIONS: Within the limitations of this study, the results suggest that it is possible to predict IT accurately based on radiographic findings of the patient. This could be useful in the treatment plan of immediate loading cases.
BACKGROUND: Subjective radiographic classifications of alveolar bone have been proposed and correlated with implant insertion torque (IT). The present diagnostic study aims to identify quantitative bone features influencing IT and to use these findings to develop an objective radiographic classification for predicting IT. METHODS: Demographics, panoramic radiographs (taken at the beginning of dental treatment), and cone-beam computed tomographic scans (taken for implant surgical planning) of 25 patients receiving 31 implants were analyzed. Bone samples retrieved from implant sites were assessed with dual x-ray absorptiometry, microcomputed tomography, and histology. Odds ratio, sensitivity, and specificity of all variables to predict high peak IT were assessed. RESULTS: A ridge cortical thickness >0.75 mm and a normal appearance of the inferior mandibular cortex were the most sensitive variables for predicting high peak IT (87.5% and 75%, respectively). A classification based on the combination of both variables presented high sensitivity (90.9%) and specificity (100%) for predicting IT. CONCLUSIONS: Within the limitations of this study, the results suggest that it is possible to predict IT accurately based on radiographic findings of the patient. This could be useful in the treatment plan of immediate loading cases.
Entities:
Keywords:
Bone density; cone-beam computed tomography; dental implants; radiography, panoramic
Authors: Fernando Antonio Reis Laurino; Isabela Goulart Gil Choi; Jun Ho Kim; Ivan Onone Gialain; Renato Ferraço; Rainer Guilherme Haetinger; Otavio Henrique Pinhata-Baptista; Reinaldo Abdala-Junior; Claudio Costa; Arthur Rodriguez Gonzalez Cortes Journal: Imaging Sci Dent Date: 2020-06-18