口腔医学 ›› 2026, Vol. 46 ›› Issue (9): 652-657.doi: 10.13591/j.cnki.kqyx.2026.09.002

• 基础与临床研究 • 上一篇    下一篇

上颌第一磨牙与后牙牙列磨耗特征的相关性研究

季中倩1, 王涵2, 丁涛1, 谢理哲1, 胡建1()   

  1. 1 南京医科大学附属口腔医院修复科, 南京医科大学口腔疾病研究江苏省重点实验室,江苏省口腔转化医学工程研究中心, 江苏南京 (210029)
    2 徐州市口腔医院修复科, 江苏徐州 (221002)
  • 收稿日期:2025-09-01 出版日期:2026-09-28 发布日期:2026-09-20
  • 通讯作者: 胡 建 E-mail:hujianmjc@sohu.com
  • 基金资助:
    国家自然科学基金青年科学基金项目(82571165);江苏省科教能力提升工程——江苏省研究型医院(YJXYYJSDW4);江苏省医学创新中心(CXZX202227)

Study on the correlation between the wear characteristics of maxillary first molars and posterior dentition

JI Zhongqian1, WANG Han2, DING Tao1, XIE Lizhe1, HU Jian1()   

  1. Department of Prosthodontics, The Affiliated Stomatological Hospital of Nanjing Medical University, Jiangsu Province Key Laboratory of Oral Diseases, Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing 210029, China
  • Received:2025-09-01 Online:2026-09-28 Published:2026-09-20

摘要:

目的 探究上颌第一磨牙4个牙尖磨耗面积与上颌后牙牙列(包括上颌第一磨牙)功能尖/非功能尖牙尖高度、牙尖斜度、磨耗面积、接触面积的相关性,为人工智能预测上颌第一磨牙磨耗面特征提供科学依据。方法 纳入196例患者,共计784个上颌后牙(不包括第三磨牙)牙面,根据口扫数据,运用Geomagic Qualify软件测量其功能尖/非功能尖牙尖高度、牙尖斜度、磨耗面积和接触面积。采用独立样本t检验比较不同性别上颌第一磨牙总磨耗面积的组间差异,运用Pearson相关分析研究各变量间的相关性,并通过一元线性回归分析年龄与上颌第一磨牙总磨耗面积的关联。在此基础上,以单因素分析中有统计学意义的指标为自变量,分别以上颌第一磨牙近中颊尖、远中颊尖、近中腭尖、远中腭尖磨耗面积及总磨耗面积为因变量开展多元线性回归分析,并构建相应的磨耗面积预测模型。结果 牙齿磨耗随着年龄增长不断加重,不同性别牙齿磨耗程度无明显差异;上颌第一磨牙4个牙尖之间的磨耗面积显著相关(P<0.05);上颌第一磨牙总磨耗面积与上颌第一前磨牙、上颌第二前磨牙、上颌第二磨牙的各牙尖磨耗面积均显著相关(P<0.05),与上颌第二磨牙近中颊尖磨耗面积相关性最强(P<0.05);上颌第一前磨牙颊尖牙尖斜度与上颌第一磨牙总磨耗面积显著负相关(P<0.05);上颌第一磨牙4个牙尖磨耗面积与上颌第一前磨牙、上颌第二前磨牙、上颌第二磨牙咬合接触面积正相关(P<0.05),但相关性较弱。结论 上颌后牙牙列的磨耗面积与上颌第一磨牙磨耗面积具有一定的相关性,根据已知余留牙的磨耗数据,可以得出上颌第一磨牙各牙尖的磨耗数据,构建相应的数学模型,指导缺损牙全冠修复前的咬合分析与重建。

关键词: 牙齿磨耗, 相关性分析, 咬合接触, 口腔修复, 数字化印模

Abstract:

Objective To explore the correlation between the wear area of the four cusps of maxillary first molars and the height of functional/non-functional cusps of maxillary posterior dentition cusp, cusp inclination, wear area and contact area (including the maxillary first molar), in order to provide a scientific basis for artificial intelligence to predict the wear surface characteristics of maxillary first molars. Methods A total of 196 patients were included, with 784 upper posterior teeth (excluding third molars) analyzed. Based on intraoral scan data, the functional cusp/non-functional cusp height, cusp slope, wear area, and total tooth contact area were measured using Geomagic Qualify software. Independent sample t-tests were used to compare the differences in total wear area of the maxillary first molars between different genders. Pearson correlation analysis was applied to study the relationships between variables, and simple linear regression was used to examine the association between age and total wear area of the maxillary first molars. Based on this, variables that showed statistical significance in univariate analysis were used as independent variables, while the wear areas of the mesio-buccal cusp, disto-buccal cusp, mesio-lingual cusp, disto-lingual cusp, and total wear area of the maxillary first molar were used as dependent variables in multiple linear regression analyses. This allowed analysis of the effects of each influencing factor on the wear of individual cusps and the total wear area, and to build corresponding predictive models for wear area. Results Tooth wear increases with age, and there is no significant difference in wear between genders. The wear areas among the four cusps of the upper first molar are significantly related (P<0.05). The total wear area of the upper first molar is significantly related to the wear areas of the cusps of the upper first premolar, upper second premolar, and upper second molar (P<0.05), with the strongest correlation seen with the mesio-buccal cusp of the upper second molar (P<0.05). The buccal cusp slope of the upper first premolar is significantly negatively correlated with the total wear area of the upper first molar (P<0.05). The wear areas of the four cusps of the upper first molar are positively correlated with the occlusal contact areas of the upper first premolar, upper second premolar, and upper second molar (P<0.05), but the correlation is relatively weak. Conclusion According to the known wear data of the remaining teeth, the wear data of each cusp of the maxillary first molars can be obtained, and the corresponding mathematical model can be constructed to guide the occlusal analysis and reconstruction of the missing teeth before full crown restoration.

Key words: tooth wear, correlation analysis, occlusal contact, oral prosthetics, digital impression

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