AI Recognition of Important Structures in Otolaryngological Surgery

Developing a system for artificial intelligence to recognize anatomical landmarks in otolaryngological surgery, enabling real-time tracking of critical temporal bone structures during surgery.

Study Overview

• Status: Recruiting
• Conditions: Otolaryngological Diseases Requiring Mastoidectomy; Middle Ear Surgery, Endolymphatic Sac Surgery, Cochlear Implant, Labyrinthectomy, Petrous Apex Lesions, Facial Nerve Surgery, and Lateral Skull Base Tumors

Detailed Description

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.

• Study Type: Observational
• Enrollment (Estimated): 1000

Contacts and Locations

• Study Contact: Name: Haidi Doctor Yang; Phone Number: +86-131 7882 1663; Email: yanghd@mail.sysu.edu.cn
• Study Contact Backup: Name: Jiaqi Doctor Pang; Phone Number: +86-135 1272 2134; Email: pangjq3@mail.sysu.edu.cn

Study Locations

• China
  • Guangdong
    • Guangzhou, Guangdong, China, 510120
      • Recruiting
      • Sun Yat-sen Memorial Hospital
      • Contact: Liushan Ou; Phone Number: +86 20 8133 2587; Email: oulsh@mail.sysu.edu.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

otolaryngological diseases requiring mastoidectomy

Description

Inclusion Criteria:

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.

Exclusion Criteria:

1. No surgical video recording available.
2. Unclear visualization of the surgical area during microscopic otolaryngological procedures.
3. Incomplete visualization of the entire surgical process.
4. Patients who did not undergo high-resolution temporal bone CT at our hospital or Shenzhen Deep Bay Hospital.

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
otolaryngological diseases requiring mastoidectomy	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.	1 week from admission to discharge
Relevant indicators to evaluate the accuracy of the model	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.; 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.	From enrollment to the end of the study

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Relevant indicators of other evaluation models	mIOU:mIOU (Mean Intersection-over-Union), that is, mean intersection over union, is an important evaluation index in semantic segmentation tasks. The purpose of semantic segmentation is to classify each pixel in an image into different categories.In medical images, different tissue categories are divided.; Precision: The precision rate represents the proportion of all samples predicted by the model to be positive that are actually positive.; Recall:The recall rate represents the percentage of all samples that are actually positive that are correctly predicted to be positive; Oacc:Overall accuracy refers to the proportion of correctly classified samples in a classification task It is a basic and intuitive indicator for measuring the accuracy of a model or classification method.; Loss:The Loss value is an indicator used in the training process of machine learning models to measure the degree of difference between the model's prediction results and the true labels.	From enrollment to the end of the study

Collaborators and Investigators

• Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Study record dates

Study Major Dates

• Study Start (Actual): January 1, 2020
• Primary Completion (Estimated): August 30, 2026
• Study Completion (Estimated): August 30, 2026

Study Registration Dates

• First Submitted: November 27, 2024
• First Submitted That Met QC Criteria: December 5, 2024
• First Posted (Estimated): December 10, 2024

Study Record Updates

• Last Update Posted (Estimated): December 10, 2024
• Last Update Submitted That Met QC Criteria: December 5, 2024
• Last Verified: December 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Bone Diseases; Musculoskeletal Diseases; Neoplasms by Site; Neoplasms; Bone Neoplasms; Skull Neoplasms; Skull Base Neoplasms; Otorhinolaryngologic Diseases
• Other Study ID Numbers: SYSKY-2024-529-01

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: The data cannot be made publicly available because they contain sensitive patient information and involved the current trade secrets and intellectual property rights of Guangzhou Hansi Medical Technology Co.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No