About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
mca 23(1):

Research Article

Evaluation of accuracy for prediction of soft tissue profile changes in non-growing patients undergoing orthodontic treatment using cephalometric android application.

Download244 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eetmca.3686,
        author={Rushabh Shah and Sachin Durkar and Sonali Deshmukh and Jayesh Rahalkar},
        title={Evaluation of accuracy for prediction of soft tissue profile changes in non-growing patients undergoing orthodontic treatment using cephalometric android application.},
        journal={EAI Endorsed Transactions on Mobile Communications and Applications},
        volume={8},
        number={1},
        publisher={EAI},
        journal_a={MCA},
        year={2024},
        month={12},
        keywords={Webceph cephalometric software, soft tissue prediction, VTO prediction, class I malocclusion, class II malocclusion},
        doi={10.4108/eetmca.3686}
    }
    
  • Rushabh Shah
    Sachin Durkar
    Sonali Deshmukh
    Jayesh Rahalkar
    Year: 2024
    Evaluation of accuracy for prediction of soft tissue profile changes in non-growing patients undergoing orthodontic treatment using cephalometric android application.
    MCA
    EAI
    DOI: 10.4108/eetmca.3686
Rushabh Shah1,*, Sachin Durkar1, Sonali Deshmukh1, Jayesh Rahalkar1
  • 1: Dr D Y Patil Dental College & Hospital
*Contact email: shahrushabh97@gmail.com

Abstract

INTRODUCTION: An accurate prediction in soft tissue changes is of great importance for orthodontic treatment planning. Patients find it difficult to imagine how their facial appearance may change after orthodontic treatment without a visual reference. Predicting the postoperative facial appearance may thus be useful for managing expectations, easing communication, and researching different treatment choices. Computer-assisted programs are still relatively expensive and are not portable in comparison to smartphones, and the accuracy of soft tissue profile prediction of these android applications has not been thoroughly assessed. The purpose of the study is to assess how well the Webceph cephalometric Android application predicts changes in soft tissue profile following orthodontic treatment. MATERIALS AND METHOD: A total of 50 patients were screened for eligibility, and 24 young adult patients (8 males, 16 females; mean age 24.8 ±3.9 years) were finally included in the study based on the inclusion and exclusion criteria. The landmarks and parameters of the Legan and Burstone soft tissue analysis were used for the cephalometric analyses. The cephalometric tracings of the actual treatment result and the Webceph predicted treatment outcome was superimposed to calculate the prediction errors. Paired t-test used to compare the statistical differences between the predicted and actual treatment outcomes of the parameters used in the legan and burstone soft tissue analysis. RESULTS: There were significant differences between the predicted and actual values in parameters of legan and burstone soft tissue analysis (P\0.05). It was reported that the prediction in two parameters (i.e., Lower face throat (Sn-Gn-C angle) (Cm-sn-ls) Nasolabial angle) was a significant difference from the actual modifications in class I bimaxillary protrusion group and there were substantial changes in the prediction of two characteristics (facial convexity (G-Sn-Pg angle) and inter labial (Stms-Stmi) in the class II group. CONCLUSIONS: The Webceph VTO prediction in soft tissue changes after the orthodontic treatment in patients with bimaxillary protrusion and class II malocclusion is the most accurate for the nasolabial angle and the least accurate for the mandibular prognathism parameter.

Keywords
Webceph cephalometric software, soft tissue prediction, VTO prediction, class I malocclusion, class II malocclusion
Received
2024-12-04
Accepted
2024-12-04
Published
2024-12-04
Publisher
EAI
http://dx.doi.org/10.4108/eetmca.3686

Copyright © 2024 Rushabh Shah et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL