ABSTRACT
Objective@#To analyze the correlation between the age and the cone-beam CT (CBCT) images of the third and fourth cervical vertebrae in female skeletal class Ⅰ patients aged between 9 and 17 years, and to establish a quantitative evaluation method for calculating the age.@*Methods@#CBCT images of 108 female skeletal class Ⅰ patients aged between 9 and 17 years were collected from Qingdao Stomatological Hospital from September, 2017 to March, 2019. The two-dimensional linear values (AH: height of anterior edge of vertebral body; H: height of middle part of vertebral body; PH: height of posterior edge of vertebral body; AP: width of vertebral body), the two-dimensional linear ratio values (AH/PH, AH/AP, AH/H, H/AP, H/PH, PH/AP) and the three-dimensional volume values of the third vertical vertebrae (C3) and the fourth vertical vertebrae (C4) were measured. By Exponential transformation of measurements and multiple linear regression analysis, the optimal index for evaluating age were screened, and the fitting degree of multiple linear regression equation (R2) and the accuracy of age estimation (SEE) were compared. CBCT images of 27 female skeletal class Ⅰ patients aged from 9 to 17 years were added from Qingdao Stomatological Hospital between April, 2019 and July, 2019, by which the accuracy of the regression equation was verified.@*Results@#Multiple linear regression equation for age estimation based on two-dimensional linear indexes was as follows: Y=-113.928+33.743×eAH3/100+58.844×ePH4/100+20.590×eAP4/100( "e" was a natural constant, e≈2.718), R2=0.745, SEE=1.31. Multiple linear regression equation for age estimation based on two-dimensional linear ratio indexes was as follows: Y=-0.076-2.284×eAH3/PH3+3.227×eAH3/AP3+2.149×eAH3/H3+1.961×eAH4/H4, R2=0.576, SEE=1.70. Multiple linear regression equation of age estimation by the volume index was as follows: Y=-16.828+22.184×eV3/10 000, R2=0.555, SEE=1.71. The data of 27 new patients were tested. The CBCT measurement index of C3 and C4 vertebral bodies inferred the fitting degree (R2) and accuracy (SEE) of the equation of the age estimation. The two-dimensional linear value was superior to the two-dimensional linear ratio and the latter was superior to the three-dimensional volume value. The standard error of the estimate about them was 1.74, 2.00 and 2.37, respectively.@*Conclusions@#The two-dimensional linear index of CBCT images of C3 and C4 could be used to estimate the age of 9 to 17-year-old female skeletal class Ⅰ patients, and the accuracy of the method was higher than that of two-dimensional ratio index and three-dimensional volume index.
ABSTRACT
Objective@#To investigate the effect of incisor retraction on three-dimensional morphology of upper airway and fluid dynamics in class Ⅰ adult patients with bimaxillary protrusion.@*Methods@#Thirty class Ⅰ patients with bimaxillary protrusion that received fixed orthodontic treatment in Department of Stomatology, The First Affiliated Hospital of Wenzhou Medical University from January 2011 to September 2014 were selected using random number table. All the patients were treated with extraction of four first premolars and retraction of anterior teeth using implant anchorage. Cone-beam CT (CBCT) scans were performed before and after incisor retraction for all patients. The CBCT data of the upper airway were constructed using Mimics 16.0, and the flow field characteristics inside the upper airway were simulated using Ansys 14.0. The changes of volume (V), mean cross-sectional area (mCSA), maximum lateral diameters/maximum anteroposterior diameters (LP/AP) of cross section, the maximum pressure of airflow (Pmax), the minimum pressure of airflow (Pmin) and pressure drop (△P) of nasopharynx, oropharynx and hypopharynx before and after incisor retraction were measured and compared using paired t test. The correlation between the variation of △P in the most significant pharyngeal part and the morphological variables after incisor retraction was analyzed using Pearson correlation test.@*Results@#No statistical differences were observed in the morphology and flow field in nasopharynx before and after incisor retraction (P>0.05). Before incisor retraction, the oropharyngeal volume and mCSA were (7 580±622) mm3 and (217±40) mm2, respectively, and the hypopharyngeal volume and mCSA were (2 564±162) mm3, and (239±43) mm2, respectively. After incisor retraction, the volumes of oropharynx and hypopharynx were (6 885±601) mm3 and (2 535±156) mm3, respectively, and mCSA of oropharynx and hypopharynx were (197±37) mm2 and (236±42) mm2, respectively. The volume and mCSA of oropharynx and hypopharynx were significantly decreased after incisor retraction (P<0.05). The greatest changes in pharyngeal volume and mCSA occurred in the oropharynx. In addition, the LP/AP of oropharynx after incisor retraction was changed from 1.9±0.6 to 2.1±0.7, which was significantly increased compared with the levels before incisor retraction (P<0.05). After simulation of pharyngeal airflow, the oropharyngeal Pmin, hypopharyngeal Pmax and Pmin were (-13.7±4.3), (-8.3±3.8) and (-42.8±9.5) Pa, respectively, whereas the values turned to (-16.4±6.5), (-11.9±3.6) and (-46.0±11.0) Pa, respectively after incisor retraction, which was significantly reduced (P<0.05). △P of oropharynx was significantly increased from (42.7±10.1) Pa to (45.2±13.0) Pa after incisor retraction (P<0.05) and the variation of oropharyngeal △P was negatively correlated with the variation of V and mCSA in oropharynx before and after incisor retraction (r=-0.681, P=0.001; r=-0.844, P=0.000).@*Conclusions@#The oropharynx was constricted and the pharyngeal resistance was increased after incisor retraction in adult class Ⅰ patients with bimaxillary protrusion. A comprehensive and systematic evaluation of the pharyngeal morphology and ventilatory function were very important for making a scientific and rational clinical treatment plan.
ABSTRACT
Objective: To classify the AngleⅠ malocclusion subgroups using lateral radiographic films according to their ordinary coordinates and standardized coordinates converted by general procrusts analysis (GPA), and to compare the two kinds of classifications and their valne in diagnosis of malocclusion. Methods: 946 pretreatment lateral radiographic films of patients with Angle'I malocclusion were chosen and their ordinary coordinates were acquired via soft ware. The ordinary coordinates were then converted into standardized coordinates by GPA. All of the films were classified by cluster analysis and discrimination analysis applying the upper two kinds of coordinates respectively. Results: (1) Twenty one subgroups were identified according to the ordinary coordinates of the chosen films with the total differentiate rate of 92.7% and leave-one-out differentiate rate of 68.4% (Classification A). Correspondingly, 20 subgroups were identified according to the standardized coordinates with the two differentiate rates of 87.8% and 71.9% (Classification B). (2) If the ordinary coordinates were discriminated by Classification B, the total differentiate rate and leave-one-out differentiate rate were 79.8% and 60.2 % respectively. If the standardized coordinates were discriminated by Classification A, the two differentiate rates were 79.8% and 60.2 % respectively. (3) There were some subgroups having the similar form in Classification A and their difference mainly arose from the difference of the patient age, while there were no such subgroups like that in Classification B. (4)The proportion of the largest subgroup in total subjects is 15.9% and there were 8 subgroups having the number of subjects over 40 in Classification A, whilethe corresponding proportion and number of subgroups were 74.7% and 2 in Classification B.(5)Classification A and Classification B were both suitable to classify a new subject, but Classification B was required to standalize all of the subjects onc again, which was very complex, while Classification A was more simplified. Conclusion: Classification A and Classification B are interelated. GPA could concentrate the subjects in cluster analysis, which reduces some influence of the age to the classification, but the process to classify a new subject is very complex. Thus if quick diagnosis is needed in clinics, Classification A should be recommended, but the influence of the age should be noted.