Laryngeal Cancer Screening During Flexible Video Laryngoscopy Using Large Computer Vision Models.
Ann Otol Rhinol Laryngol
; 133(8): 720-728, 2024 Aug.
Article
in En
| MEDLINE
| ID: mdl-38755974
ABSTRACT
OBJECTIVE:
Develop an artificial intelligence assisted computer vision model to screen for laryngeal cancer during flexible laryngoscopy.METHODS:
Using laryngeal images and flexible laryngoscopy video recordings, we developed computer vision models to classify video frames for usability and cancer screening. A separate model segments any identified lesions on the frames. We used these computer vision models to construct a video stream annotation system. This system classifies findings from flexible laryngoscopy as "potentially malignant" or "probably benign" and segments any detected lesions. Additionally, the model provides a confidence level for each classification.RESULTS:
The overall accuracy of the flexible laryngoscopy cancer screening model was 92%. For cancer screening, it achieved a sensitivity of 97.7% and a specificity of 76.9%. The segmentation model attained an average precision at a 0.50 intersection-over-union of 0.595. The confidence level for positive screening results can assist clinicians in counseling patients regarding the findings.CONCLUSION:
Our model is highly sensitive and adequately specific for laryngeal cancer screening. Segmentation helps endoscopists identify and describe potential lesions. Further optimization is required to enable the model's deployment in clinical settings for real-time annotation during flexible laryngoscopy.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Video Recording
/
Artificial Intelligence
/
Laryngeal Neoplasms
/
Early Detection of Cancer
/
Laryngoscopy
Limits:
Humans
Language:
En
Journal:
Ann Otol Rhinol Laryngol
Year:
2024
Document type:
Article
Affiliation country:
United States