Literature DB >> 28891547

Classification of alveolar bone destruction patterns on maxillary molars by using cone-beam computed tomography.

G Ozcan1, A E Sekerci1.   

Abstract

OBJECTIVE: The defective diagnosis of alveolar structures is one of most serious handicaps when assessing available periodontal treatment options for the prevention of tooth loss. The aim of this research was to classify alveolar bone defects in the maxillary molar region which is a challenging area for dental implant applications. To our knowledge, this is the first study of periodontal bone defect prevalence by using cone-beam computed tomography (CBCT).
MATERIALS AND METHODS: In this study, the remaining alveolar bone patterns of 669 maxillary molars of 243 patients with periodontal bone loss were investigated on four aspects and the furcation areas of teeth, and then they were classified into six main groups. Combined periodontal-endodontic lesions (CPELs) were also reported in another category.
RESULTS: Following exclusion of 39 (5.8%) teeth with CPEL, the most common group was horizontal bone defects (71.4%) and the least seen group was three-walled vertical bone defects (1.9%) in all alveolar bone sides of teeth. Osseous crater was found at the rate of 6.7% on interdental alveolar bone. Dehiscence and fenestration were detected at rates of 2.7% and 3.3%, respectively. In the assessment of furcation areas, there was no furcation involvement in 61.4% of all teeth and the rate of Grade-II involvements was 26.2%.
CONCLUSIONS: The most appropriate treatment option may be decided through accurate imaging of periodontal defect morphology. CBCT can provide comprehensive information about the remaining alveolar bone structures. In this way, the need for dental implant can be prevented in many cases and be replaced with a more conservative approach on the maxillary molar region.

Entities:  

Mesh:

Year:  2017        PMID: 28891547     DOI: 10.4103/1119-3077.180074

Source DB:  PubMed          Journal:  Niger J Clin Pract            Impact factor:   0.968


  2 in total

1.  [Accuracy of cone beam computed tomography in assessing maxillary molar furcation involvement].

Authors:  Hai-Yan Zhao; Nan Wang; Yi Ding; Hai-Ying Zheng; Jun-Rong Qian
Journal:  Hua Xi Kou Qiang Yi Xue Za Zhi       Date:  2020-06-01

2.  Deep Learning Hybrid Method to Automatically Diagnose Periodontal Bone Loss and Stage Periodontitis.

Authors:  Hyuk-Joon Chang; Sang-Jeong Lee; Tae-Hoon Yong; Nan-Young Shin; Bong-Geun Jang; Jo-Eun Kim; Kyung-Hoe Huh; Sam-Sun Lee; Min-Suk Heo; Soon-Chul Choi; Tae-Il Kim; Won-Jin Yi
Journal:  Sci Rep       Date:  2020-05-05       Impact factor: 4.379

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.