Artificial Intelligence (AI) based assessment and prediction for outcomes of Twin Block appliance therapy in growing patients having Class II malocclusion
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 50
- 试验地点
- 1
- 主要终点
- 1)This study will provide insight into the prediction of treatment outcomes with TBA.
研究概览
简要总结
The development of a model which can efficiently evaluate the status of treatment, taking multiple associated factors into account, will be time saving and aid in clinical decision making. Any discrepancy between expected outcome obtained from the algorithm and actual result would also assist in evaluating patient compliance. AI would eliminate the inherent subjectivity in planning and possibly obtain more favorable aesthetic and customized outcomes. Using the capabilities and potentials of machine learning and computer vision, data derived precision orthodontic approaches can be facilitated and enhanced.
To the best of our knowledge, there is no available AI model in literature that assesses and predicts the outcome of Class II malocclusion correction with TBA. Thus, the purpose of this study is to apply artificial intelligence to build a model that can assess and predict the treatment outcome with Twin Block appliance for correction of Class II malocclusion.
Since the treatment success is highly dependent on the timing of treatment, there is immense potential for the algorithm to be incorporated with the radiographic machine software so that timely referral of the patient can be made by the general dentist/ primary health care centres to the orthodontists/ higher specialized centres. Thus, the developed system may be evaluated on data from multiple centres and finally a software (standalone as well as web-based application) can be developed for wide-spread utility.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 盲法
- None
入排标准
- 年龄范围
- 9.00 Year(s) 至 14.00 Year(s)（—）
- 性别
- All
入选标准
- •Growing patients diagnosed with skeletal Class II malocclusion due to retrognathic mandible (indicated for TBA)
- •Age group: 9-14 years
- •CVMI stage: 2,3,4
- •Positive visual treatment objective (VTO)
- •Positive informed consent/assent for treatment and use of dental records.
排除标准
- •Patients with signs and symptoms of neuromuscular disorders or temporomandibular disorders
- •Patients with history of previous or current orthodontic treatment
- •Compromised physical or mental health.
结局指标
主要结局
1)This study will provide insight into the prediction of treatment outcomes with TBA.
时间窗: 1. Pre-treatment (T0)-Before insertion of Twin block appliance | 2. Mid-treatment or Post myofunctional therapy (T1)-At the end of 9-12 months of TB therapy (completion of Active phase) | 3. Post-treatment (T2)-At the end of treatment period (24 months)
2)This study will help in the development of a model which can efficiently and effectively reduce the prolonged hours spent in diagnosis/treatment planning and aid in clinical decision making. Prognostic factors to be considered during the development of treatment plans and clinical protocols for growing Class II patients will largely help in reducing the burden of orthodontic care.
时间窗: 1. Pre-treatment (T0)-Before insertion of Twin block appliance | 2. Mid-treatment or Post myofunctional therapy (T1)-At the end of 9-12 months of TB therapy (completion of Active phase) | 3. Post-treatment (T2)-At the end of treatment period (24 months)
次要结局
- 1)It will help the clinicians to understand the pitfalls in rendering treatment & achieving patient compliance since discrepancy in the actual results & predicted outcome can be noted.
研究者
Isha Duggal
Maulana Azad Institute of Dental Sciences