Accurate and timely intraoperative classification of vocal cord leukoplakia by machine learning assisted handheld OCT.

ABSTRACT: Precise and timely intraoperative classification of vocal cord leukoplakia is vital for early staging and detection of laryngeal cancer. Current endoscopic imaging, such as narrow-band imaging (NBI) and white-light laryngoscopy (WLI), has the capability to evaluate the malignancy, but has low sensitivity (<70%) for grading the low-risk dysplasia. For the vocal fold lesions, optical coherence tomography (OCT), a non-invasive imaging technology, has been widely used to show the texture and pixel change of lesions caused by squamous epithelial cell hyperplasia and atypical hyperplasia. Here, a handheld OCT probe (OD = 3 mm, length = 25 cm) was designed and fabricated, and a swept-source OCT system was built for vocal lesion monitoring during the surgery. Home-built OCT probe has both a small

SUBMITTER: Li X 

PROVIDER: S-EPMC12532304 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature