School of Dentistry, China Medical University, Taichung, 404, Taiwan.
Department of Biomedical Engineering, China Medical University, Taichung, 404, Taiwan.
BMC Oral Health. 2023 May 25;23(1):324. doi: 10.1186/s12903-023-03039-2.
This study proposed a new classification method of bone quantity and quality at the dental implant site using cone-beam computed tomography (CBCT) image analysis, classifying cortical and cancellous bones separately and using CBCT for quantitative analysis.
Preoperative CBCT images were obtained from 128 implant patients (315 sites). First, measure the crestal cortical bone thickness (in mm) and the cancellous bone density [in grayscale values (GV) and bone mineral density (g/cm)] at the implant sites. The new classification for bone quality at the implant site proposed in this study is a "nine-square division" bone classification system, where the cortical bone thickness is classified into A: > 1.1 mm, B:0.7-1.1 mm, and C: < 0.7 mm, and the cancellous bone density is classified into 1: > 600 GV (= 420 g/cm), 2:300-600 GV (= 160 g/cm-420 g/cm), and 3: < 300 GV (= 160 g/cm).
The results of the nine bone type proportions based on the new jawbone classification were as follows: A1 (8.57%,27/315), A2 (13.02%), A3 (4.13%), B1 (17.78%), B2 (20.63%), B3 (8.57%) C1 (4.44%), C2 (14.29%), and C3 (8.57%).
The proposed classification can complement the parts overlooked in previous bone classification methods (bone types A3 and C1).
The retrospective registration of this study was approved by the Institutional Review Board of China Medical University Hospital, No. CMUH 108-REC2-181.
本研究提出了一种基于锥形束 CT(CBCT)图像分析的新的种植体部位骨量和骨质量分类方法,分别对皮质骨和松质骨进行分类,并使用 CBCT 进行定量分析。
从 128 名种植患者(315 个部位)的术前 CBCT 图像中获取数据。首先,测量种植部位的牙槽嵴皮质骨厚度(以毫米为单位)和松质骨密度[灰度值(GV)和骨矿物质密度(g/cm)]。本研究提出的种植部位骨质量的新分类是一种“九宫格”骨分类系统,其中皮质骨厚度分为 A:>1.1mm、B:0.7-1.1mm 和 C:<0.7mm,松质骨密度分为 1:>600GV(=420g/cm)、2:300-600GV(=160g/cm-420g/cm)和 3:<300GV(=160g/cm)。
基于新的颌骨分类的 9 种骨型比例结果如下:A1(8.57%,27/315)、A2(13.02%)、A3(4.13%)、B1(17.78%)、B2(20.63%)、B3(8.57%)、C1(4.44%)、C2(14.29%)和 C3(8.57%)。
所提出的分类可以补充以往骨分类方法中忽略的部分(骨型 A3 和 C1)。
本研究的回顾性注册获得了中国医科大学附属医院机构审查委员会的批准,注册号为 CMUH 108-REC2-181。