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牙周表型的新分类,结合硬和软组织参数,使用数据驱动的集群

Abeer A Al-Sosowa^1,2, Ehab A Abdulghani^3,4, Anna Dai¹

¹Stomatology Hospital, School of Stomatology, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Zhejiang University School of Medicine, Cancer Center of Zhejiang University, Hangzhou, China.

Clinical oral investigations

|January 10, 2026

概括

一种新的牙周表型分类结合了牙厚度,角质化组织宽度和骨厚度. 这种数据驱动的系统完善了诊断和治疗计划,以获得更好的患者结果.

科学领域:

牙周病学牙周病学
牙科成像牙科成像牙科成像
生物统计学生物统计学

背景情况:

牙周表型的分类对于诊断和治疗规划至关重要.
传统的分类往往缺乏定量精确度.
结合软和硬组织参数,可以提供更全面的评估.

研究的目的:

开发一种新的牙周表型分类系统.
量化结合牙厚度 (GT),角质化组织宽度 (KTW) 和膜口腔骨厚度 (ABT).
在数字成像数据上利用聚类分析来对表型进行分类.

主要方法:

一项涉及180名受试者和1080个大前牙的横截面研究.
使用叠加的圆束计算机断层扫描 (CBCT) 和口内扫描进行GT和ABT的定量评估.
从带有校正因子的口内图像进行KTW测量;层次集群分析 (HCA) 用于分类.

主要成果:

集群分析确定了四个统计学上显著的牙周表型组 (p < 0.001).
传统的薄/厚表型仅占48.9%;51.1%显示混合特征.
已建立的切割值 (GT=0.85mm,KTW=3.0mm,ABT=1.0mm) 允许用于表型分类的0-3分数系统.

结论:

开发了一种新的,数据驱动的牙周表型分类,集成GT,KTW和ABT.
拟议的评分系统为临床医生提供了一个实用,定量工具.
这种分类支持改进基于表型的诊断,风险评估和个性化治疗规划.

关键词:

膜骨的厚度膜骨的厚度 CBCT-口腔内扫描叠加叠加.数据驱动的集群是指数据驱动的集群.牙的厚度牙的厚度角质化组织的宽度牙周表现型牙周表现型

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