Objective This study quantitatively analyzed the initial displacement and stress distribution of maxillary teeth and periodontal ligaments(PDLs)under different traction positions of Class Ⅱ elastics in the anterior region of fixed multibracket appliances,aiming to provide references for the optimal application of Class Ⅱ elastics.Methods A finite element model of the maxilla with Class Ⅱ elastics was established.Based on whether tooth extraction was performed and the traction positions of Class Ⅱ elastics in the maxillary anterior region,the models were divided into 4 groups and 8 working conditions.A 1.2 N load was applied between the maxillary anterior region and the tube of the mandibular first molar.The initial displacement of maxillary teeth and the von Mises stress of maxillary PDLs were analyzed.Results The finite element model of the maxilla with Class Ⅱelastics was successfully constructed.Class Ⅱ elastics induced lingual inclination,eruption,and retraction of maxillary anterior teeth.Variations in the traction positions of Class Ⅱ elastics resulted in differences in the initial displacement of maxillary teeth and the von Mises stress of PDLs.The maximum von Mises stress of PDLs ranged from 5.8 to 12.2 kPa across all working conditions.Conclusions Different traction positions of Class Ⅱelastics alter the torque,induce distinct deformation trends in the archwire,and thus affect tooth movement.Compared with attaching Class Ⅱ elastics to the maxillary canine bracket,attaching them to the hooks increases the tendency toward deep overbite,and this tendency is more pronounced in extraction models.For patients with Class Ⅱ,Division 1 malocclusion,anterior tooth protrusion,and a tendency toward open bite,applying Class Ⅱelastics on the occlusal side of the hooks may be more beneficial in alleviating open bite and enhancing the smile arc.However,the actual efficacy requires clinical verification.

Objective This study quantitatively analyzed the initial displacement and stress distribution of maxillary teeth and periodontal ligaments(PDLs)under different traction positions of Class Ⅱ elastics in the anterior region of fixed multibracket appliances,aiming to provide references for the optimal application of Class Ⅱ elastics.Methods A finite element model of the maxilla with Class Ⅱ elastics was established.Based on whether tooth extraction was performed and the traction positions of Class Ⅱ elastics in the maxillary anterior region,the models were divided into 4 groups and 8 working conditions.A 1.2 N load was applied between the maxillary anterior region and the tube of the mandibular first molar.The initial displacement of maxillary teeth and the von Mises stress of maxillary PDLs were analyzed.Results The finite element model of the maxilla with Class Ⅱelastics was successfully constructed.Class Ⅱ elastics induced lingual inclination,eruption,and retraction of maxillary anterior teeth.Variations in the traction positions of Class Ⅱ elastics resulted in differences in the initial displacement of maxillary teeth and the von Mises stress of PDLs.The maximum von Mises stress of PDLs ranged from 5.8 to 12.2 kPa across all working conditions.Conclusions Different traction positions of Class Ⅱelastics alter the torque,induce distinct deformation trends in the archwire,and thus affect tooth movement.Compared with attaching Class Ⅱ elastics to the maxillary canine bracket,attaching them to the hooks increases the tendency toward deep overbite,and this tendency is more pronounced in extraction models.For patients with Class Ⅱ,Division 1 malocclusion,anterior tooth protrusion,and a tendency toward open bite,applying Class Ⅱelastics on the occlusal side of the hooks may be more beneficial in alleviating open bite and enhancing the smile arc.However,the actual efficacy requires clinical verification.

Objective To investigate the feasibility of the automatic cystocele severity grading software for quantitative evaluation of prolapse of bladder posterior wall by transperineal ultrasound . Methods One hundred and seventy transperineal ultrasound video clips were recorded when the female patients performing the Valsalva maneuver and those clips were divided into training group ( 85 cases) and test group ( 85 cases) randomly ,then the ralated structures of the images from the training group offline were marked . Through machine learning algorithm ,the computer had learned and was able to analyzed the marking information ,then the automatic cystocele severity grading software was obtained . And later the software was ran to mark the structures and get the cystocele severity grading in the images from the test group . Meanwhile , the same structures of the same images manually were marked and after an interval of more than two weeks the process were repeated by 3 doctors . Finally the grading results obtained from the software and the measurers of the 3 doctors were compared . Results The intelligent identification and automatic measurement software obtained from the machine learning algorithm was able to identify the related structures . The grading results of each measurer were of good consistency ( κ :0 .72 －0 .78 ;ICC :0 .980－0 .990) . The grading results between different measurers were of good consistency ( κ :0 .65－0 .75 ;ICC :0 .985－0 .992) . The grading results between automatic software and three different measurers were of good consistency ( κ :0 .63－0 .67 ;ICC :0 .967－0 .969 ; r ＝0 .936 ,0 .943 ,0 .936 ,all P ＜0 .01) . Conclusions The automatic cystocele severity grading software is able to identify the related structures in the images and reliable to apply the software in pelvic floor ultrasound .