吉林大学学报(医学版) ›› 2017, Vol. 43 ›› Issue (04): 800-804.doi: 10.13481/j.1671-587x.20170426

• 临床研究 • 上一篇    下一篇

基于遗传算法的不同类型错(牙合)患者矢状向颅面结构的关联性分析

滕蓉, 杨陆一, 夏小雪, 王守东, 宁磊, 牡琦丽   

  1. 吉林大学口腔医院正畸科, 吉林 长春 130021
  • 收稿日期:2016-12-02 出版日期:2017-07-28 发布日期:2017-08-01
  • 通讯作者: 杨陆一,副教授,硕士研究生导师(Tel:0431-85579423,E-mail:yangluyi1234@sina.com) E-mail:yangluyi1234@sina.com
  • 作者简介:滕蓉(1990-),女,山东省聊城市人,在读医学硕士,主要从事口腔正畸基础和临床方面的研究。
  • 基金资助:
    吉林省科技厅科研基金资助课题(20150312021ZG)

Analysis on correlation of sagittal craniofacial structures with different classes of malocclusion based on genetic algorithms method

TENG Rong, YANG Luyi, XIA Xiaoxue, WANG Shoudong, NING Lei, MU Qili   

  1. Department of Orthodontics, Stomatology Hospital, Jilin University, Changchun 130021, China
  • Received:2016-12-02 Online:2017-07-28 Published:2017-08-01

摘要: 目的:采用遗传算法(GAS)优化不同类型错(牙合)患者矢状向颅面结构关系方程的参数,探讨其是否具有规律性。方法:选取均角型错(牙合)患者240例,年龄8~18岁,分为安氏Ⅰ类组79例,安氏Ⅱ类组76例,安氏Ⅲ类组85例。每组随机选取10例为检验样本,其余为实验样本,实验样本用于获得GAS优化方程,检验样本用于误差分析。对所有患者的头颅侧位片进行头影测量分析,对各组测量参数[全颅底深度(Ba-N)、面中部深度(Ba-A)、颅底深度(Ba-S)、上颌后部深度(S-Ptm)、上颌骨基骨长度(Ptm-A)、下颌关节相对于颅底的距离(Ba-Ar)、下颌升支长度(Ar-Go)、下颌骨体长度(Go-PoG)、下面部深度(Ba-PoG)及颅底角(N-S-Ar)]进行独立样本t检验、单因素方差分析和逐步回归分析,识别颅面结构的相关影响因子;采用GAS优化方程参数获得相关方程,将优化方程预测值和实测值进行比较。结果:安氏Ⅰ类、Ⅱ类和Ⅲ类组内比较,不同性别间各参数差异无统计学意义(P>0.05),将同一类型不同性别组合并进行比较,Ba-A、Ptm-A、Ar-Go和Ba-PoG差异有统计学意义(P<0.05)。相关分析,安氏Ⅰ类组,Ba-A与Ba-N呈正相关关系(r=0.683),Ptm-A与Go-PoG呈正相关关系(r=0.738),Ar-Go与Ba-PoG呈正相关关系(r=0.833)、与Go-PoG呈负相关关系(r=-0.560),Ba-PoG与Go-PoG呈正相关关系(r=0.669);安氏Ⅱ类组,Ba-A与Ba-PoG和Ba-N呈正相关关系(r=0.884,r=0.883),Ptm-A与Ba-A呈正相关关系(r=0.742),Ar-Go与Ba-PoG呈正相关关系(r=0.401)、与Go-PoG呈负相关关系(r=-0.317),Ba-PoG与Ba-A和Go-PoG呈正相关关系(r=0.883,r=0.488);安氏Ⅲ类组,Ba-A与Ba-N和Ba-PoG呈正相关关系(r=0.891,r=0.829),Ptm-A与Ba-A呈正相关关系(r=0.807)、与Ba-S呈负相关关系(r=-0.404),Ar-Go与S-Ptm呈正相关关系(r=0.548),Ba-PoG与Ba-A呈正相关关系(r=0.829)。使用GAS建立了不同错(牙合)类型矢状向颅面结构的关系方程。安氏Ⅰ类,Ba-A(mm)=10.9639+0.8598×Ba-N,Ptm-A(mm)=6.8976+0.5570×Go-PoG,Ar-Go(mm)=-2.5482+0.5118×Ba-PoG-0.5272×Go-PoG,Ba-PoG(mm)=17.515 6+1.021 3×GO-POG;安氏Ⅱ类,Ba-A(mm)=-2.121 3+0.567 6×Ba-PoG+0.513 2×Ba-N,Ptm-A(mm)=13.788 7+0.349 4×Ba-A,Ar-Go(mm)=2.447 7+0.368 8×Ba-POG-0.427 9×Go-PoG,Ba-PoG(mm)=-7.140 2+0.751 3×Ba-A+0.295 4×Go-PoG;安氏Ⅲ类,Ba-A(mm)=3.281 0+0.545 3×Ba-N+0.394 4×Ba-PoG,Ptm-A(mm)=3.535 8+0.631×Ba-A-0.614 2×Ba-S,Ar-Go(mm)=-9.002 1+1.004 3×S-Ptm,Ba-PoG(mm)=-2.091 2+1.057 5×Ba-A。GAS建立的方程预测值与实测数据比较差异无统计学意义(P>0.05)。结论:采用GAS建立了矢状向错(牙合)颅面结构的优化关系方程,且其定量具有规律性。

关键词: 错(牙合)类型, 矢状向颅面结构, 遗传算法, 相关关系分析

Abstract: Objective: To optimize the parameters of the equation of sagittal craniofacial structures with different classes of malocclusion using genetic algorithms(GAS), and to explore the rules.Methods: Atotal of 240 patients with average angle malocclusion aged 8-18 years old were divided into three groups:Angle Class Ⅰ(n=79), Angle Class Ⅱ(n=76)and Angle Class Ⅲ(n=85) groups.In each group 10 cases were randomly selected as the test samples, the rest as the experimental samples.The cephalometric analysis was performed on all the patients' cephalograms, and the results of Ba-N,Ba-A,Ba-S,S-Ptm,Ptm-A,Ba-Ar,Ar-Go,Go-PoG,Ba-PoG and N-S-Ar were analyzed by two independent samples t-test and One-Way ANOVA. The relevant influencing factors of craniofacial structures were found.The parameters of the equation was optimized to obtain the relevant equations using GAS.The predicted values of the optimized equation were compared with the measured values.Results: There were no significant differences in sex between Angle Class Ⅰ, Class Ⅱ and Class Ⅲ groups(P> 0.05);when the men and women with the same type were combined,the Ba-A,Ptm-A,Ar-Go,and Ba-PoG had statistically significant differences between Angle Class Ⅰ, Class Ⅱ, and Class Ⅲ groups (P<0.05).The correlation analysis results showed that in Angle Class Ⅰgroup:Ba-A was positively correlated with Ba-N (r=0.683),Ptm-A was positively correlated with Go-PoG (r=0.738), Ar-Go was positively correlated with Ba-PoG (r=0.833), and negatively correlated with Go-PoG (r=-0.560) and Ba-PoG was positively correlated with Go-PoG (r=0.669); in Angle class Ⅱ group,Ba-A was positively correlated with Ba-PoG and Ba-N(r=0.884,r=0.883), Ptm-A was positively correlated with Ba-A (r=0.742),Ar-Go was positively correlated with Ba-PoG (r=0.401)and negatively correlated with Go-PoG (r=-0.317) and Ba-PoG was positively correlated with Ba-A and Go-PoG(r=0.883,r=0.488);in Angle Class Ⅲ group,Ba-A was positively correlated with Ba-N and Ba-PoG(r=0.891,r=0.829),Ptm-A was positively correlated with Ba-A (r=0.807)and negatively correlated with Ba-S (r=-0.404),Ar-Go was positively correlated with S-Ptm (r=0.548) and Ba-PoG was positively correlated with Ba-A (r=0.829).The equation of sagittal craniofacial structure with different occlusal classes was established by GAS.In Angle Class Ⅰgroup:Ba-A(mm)=10.963 9+0.859 8×Ba-N,Ptm-A(mm)=6.897 6+0.557 0×Go-PoG,Ar-Go(mm)=-2.548 2+ 0.511 8×Ba-PoG-0.5272×Go-PoG,Ba-PoG(mm)=17.515 6+1.021 3×GO-POG;in Angle Class Ⅱ group:Ba-A(mm)=-2.121 3+0.567 6×Ba-PoG+0.513 2×Ba-N,Ptm-A(mm)=13.788 7+0.349 4×Ba-A,Ar-Go(mm)=2.447 7+0.368 8×Ba-PoG-0.427 9×Go-PoG,Ba-PoG(mm)=-7.140 2+0.751 3×Ba-A+0.295 4×Go-PoG;in Angle Class Ⅲgroup:Ba-A(mm)=3.281 0+0.545 3×Ba-N+0.394 4×Ba-PoG,Ptm-A(mm)=3.535 8+0.63 1×Ba-A-0.614 2×Ba-S,Ar-Go(mm)=-9.002 1+1.004 3×S-Ptm,Ba-PoG(mm)=-2.091 2+1.057 5×Ba-A.There were no significant differences between the predicted values of GAS and the measured data (P> 0.05), and the error was small.Conclusion: The optimal relation equation of craniofacial structure of sagittal malocclusion is established by GAS with the quantitative regularity.

Key words: genetic algorithms, classes of malocclusion, sagittal craniofacial structure, correlation analysis

中图分类号: 

  • R783.5