AI Recognition of Important Structures in Otolaryngological Surgery
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 1,000
- 试验地点
- 1
- 主要终点
- otolaryngological diseases requiring mastoidectomy
研究概览
简要总结
Developing a system for artificial intelligence to recognize anatomical landmarks in otolaryngological surgery, enabling real-time tracking of critical temporal bone structures during surgery.
详细描述
Take the example of the Al recognition and prediction of the incus, external semicircular canal, facial nerve, and facial nerve recess. Within the defined surgical area, annotated data points are utilized to identify and segment the incus and the lateral semicircular canal based on their relative positions and angles concerning the posterior wall of the external auditory canal and the surrounding tissues. Detailed descriptions of the incus and lateral semicircular canal within the surgical area include: Incus: The incus is a small anvil-shaped bone located in the middle ear. It connects to the malleus laterally and the stapes medially. Identifying the incus accurately is crucial due to its proximity to the facial nerve and its involvement in the ossicular chain that transmits sound vibrations. Lateral Semicircular Canal: This is one of the three semicircular canals in the inner ear, oriented horizontally. It is involved in detecting rotational movements of the head. Proper identification is necessary to avoid damaging the canal, which could result in vertigo or balance issues. Input features include further contrast adjustment and localized magnification of images. The enhanced images are classified and localized using the trained model, and the consistency of multiple frames is utilized to determine the final positions of the facial nerve and the facial recess. Statistical analysis is conducted to predict the positions of the facial recess relative to the incus and lateral semicircular canal, providing reference information for surgeons. The system continuously monitors changes in the surgical area, offering dynamic feedback and optimizing the model's accuracy and robustness through incremental training.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Other
入排标准
- 年龄范围
- 6 Months 至 100 Years(Child, Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Performing otolaryngological surgeries such as cochlear implantation, endolymphatic sac decompression, semicircular canal plugging, and acoustic neuroma surgery using a microscope.
- •Microscopic exposure provides a comprehensive and clear view of the surgical area within the temporal bone.
排除标准
- •No surgical video recording available.
- •Unclear visualization of the surgical area during microscopic otolaryngological procedures.
- •Incomplete visualization of the entire surgical process.
- •Patients who did not undergo high-resolution temporal bone CT at our hospital or Shenzhen Deep Bay Hospital.
结局指标
主要结局
otolaryngological diseases requiring mastoidectomy
时间窗: 1 week from admission to discharge
1. Performing otolaryngological surgeries such as cochlear implantation, endolymphatic sac decompression, semicircular canal plugging, and acoustic neuroma surgery using a microscope. 2. Microscopic exposure provides a comprehensive and clear view of the surgical area within the temporal bone.
Relevant indicators to evaluate the accuracy of the model
时间窗: From enrollment to the end of the study
1. The F1 score is the harmonic mean of accuracy and recall, which is used to measure the balance between accuracy and recall of the model. The higher the F1 score, the better the model performance. 2. Kappa value (Cohen's Kappa) is a statistical indicator used to measure classification consistency. It is mainly used to evaluate the degree of consistency between two or more classifiers (including manual classification and model classification), or the classification consistency of the same classifier at different times or under different conditions.
次要结局
- Relevant indicators of other evaluation models(From enrollment to the end of the study)
