X线头影测量确定无牙颌垂直距离的研究

目的通过X线头影测量对青年正常牙合垂直距离进行研究 ,寻找一个比较客观的确定无牙颌垂直距离的方法 ,进一步提高临床修复质量。方法选择 74例青年正常牙合拍摄X线头影测量片 ,将X线头影测量片描绘后输入计算机 ,用头影测量软件测量相关数据 ,用直线相关分析和直线回归分析对数据进行处理。结果在硬组织标志点中颏下点至眶耳平面的距离 (thedimensionfrommentontoFrankforthorizontalplane,Me FH)与前鼻棘点至眶耳平面的距离 (thedimensionfromanteriornasalspinetoFrankforthorizontalplane ,ANS FH)的相关性最强 (男性 :Y =86 .5 74 0 0 .6 5 39X ,r =0 .4 0 2 1,P <0 .0 5 ;女性 :Y =6 5 .4 4 2 7 1.115 6X ,r =0 .4 2 0 4 ,P <0 .0 1) ;在软组织标志点中Me FH与鼻下点至眶耳平面的距离 (thedimensionfromsubnasaletoFrankforthorizontalplane ,Sn FH)的相关性最强 (男性 :Y =74 .4 6 34 0 .936 8X ,r =0 .5 74 0 ,P <0 .0 1;女性 :Y =6 2 .76 6 0 1.0 6 34X ,r =0 .4 792 ,P <0 .0 1)。结论无牙颌患者的垂直距离可以利用直线回归方程确定。

DETERMINATION OF VERTICAL DIMENSION OF EDENTULOUS JAW WITH CEPHALOMETRIC METHOD

ObjectiveTo study the vertical dimension of adolescents with normal occlusion by cephalometrics and to find a method to determine the vertical dimension of edentulous jaw objectively for improving the level of prosthodontics in clinic.MethodsSeventy-four adolescents with normal occlusion (thirty male, forty-four female, aged from seventeen to twenty-two years old) were selected and everyone was taken a cephalometic roentgenogram.The roentgenogram was put into computer and measured with the software of cephalometrics.The linear correlation and linear regression analysis were used for data analysis.ResultsThe dimension from menton to Frankfort horizontal plane (Me-FH) appeared to be highly correlative with the dimension from anterior nasal spine to Frankfort horizontal plane (ANS-FH) in hard tissue(male:r= 0.4021, P< 0.05, female:r= 0.4204, P< 0.01), and the regression formulas were Y= 86.5740 0.6539X for male, and Y= 65.4427 1.1156X for female. Me-FH appeared to be highly correlative with the dimension from subnasal to Frankfort horizontal plane (Sn-FH) in soft tissue (male:r= 0.5740, P< 0.01, female:r= 0.4792, P< 0.01),and the regression formulas were Y= 74.4634 0.9368X for male, and Y= 62.766 1.0634X for female.ConclusionThe vertical dimension of edentulous jaw can be determined with the linear regression formulas.