Analysis On Correlation Of Sagittal Craniofacial Structures With Different Classes Of Malocclusion Based On Genetic Algorithms Method

Objective:To optimize the parameters of the equation of sagittal craniofacial structures with different classes of malocclusion using genetic algorithms,and to explore the rules and provide reference for clinical and scientific research.Method:240 patients with aged:8~18 years old were divided into three groups:Angle Class ?(n = 79),Angle Class?(n = 76)and Angle Class?(n =85).Each group randomly selected 10 cases for the test sample,the rest for the experimental sample.The cephalometric analysis was performed on all the patients' cephalograms,and the results were analyzed by two independent samples t-test and one-way ANOVA.The relevant influencing factors of craniofacial structure were found;Using genetic algorithms to optimize the parameters of the equation to obtain the relevant equations.The error of the optimized equation is compared with the measured value.Results:1 There was no significant difference between sex in class ?,class ?and class ?(P> 0.05),combined of men and women of the same type, most of the indicators was statistically significant among class ?,class ?and class ?(P <0.05).2 Correlation analysis showed in Angle class ?group: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 orrelated with Ba-Pog(r =0.833),and negatively correlated with Go-Pog(r =-0.560),Ba-Pog was positively correlated with Go-Pog(r =0.669);Angle class ? 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),Ba-Pog was positively correlated with Ba-A and Go-Pog(r=0.883,r=0.488);Angle class ? 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),Ba-Pog was positively correlated with Ba-A(r=0.829).3 The equation of sagittal craniofacial structure with different occlusal classes was established by GAS.Angle class ?group: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)=17.5156+1.0213×GO-Pog;Angle class ?group:Ba-A(mm)=-2.1213+0.5676×Ba-Pog+0.5132×Ba-N,Ptm-A(mm)=13.7887+0.3494×Ba-A,Ar-Go(mm)=2.4477+0.3688×Ba-Pog-0.4279×GO-Pog,Ba-Pog(mm)=-7.1402+0.7513×Ba-A+0.2954×GO-Pog;Angle class ? group:Ba-A(mm)=3.2810+0.5453×Ba-N+0.3944×Ba-Pog,Ptm-A(mm)=3.5358+0.631×Ba-A-0.6142×Ba-S,Ar-Go(mm)=-9.0021+1.0043×S-Ptm,Ba-Pog(mm)=-2.0912+1.0575×Ba-A.4 There was no significant difference between the values of GAS and the measured data(P> 0.05),and the error was small.Conclusions:1 There was no significant difference in sagittal craniofacial structure between different sexes.2 The mechanism of different classes of malocclusion is different in the craniofacial internal structure.3 The relationship between the parts inside craniofacial close correlation is high.4 The genetic algorithm optimized the relational equation to reveal the quantitative regularity of the craniofacial structure of sagittal malocclusion, which has directive significance for clinical and scientific research.