Computer aided diagnosis system for automated label-free early detection of oral epithelial cancer and dysplasia based on autofluorescence lifetime imaging endoscopy (Conference Presentation)

Javier A. Jo; Shuna Cheng; Rodrigo Cuenca; Elvis Duran; Bilal Malik; Kristen Maitland; Beena Ahmed; Lisa Cheng; John Wright

doi:10.1117/12.2293813

14 March 2018 Computer aided diagnosis system for automated label-free early detection of oral epithelial cancer and dysplasia based on autofluorescence lifetime imaging endoscopy (Conference Presentation)

Javier A. Jo, Shuna Cheng, Rodrigo Cuenca, Elvis Duran, Bilal Malik, Kristen Maitland, Beena Ahmed, Lisa Cheng, John Wright

Author Affiliations +

Proceedings Volume 10575, Medical Imaging 2018: Computer-Aided Diagnosis; 105750Y (2018) https://doi.org/10.1117/12.2293813
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

Abstract

Despite the fact that the oral cavity is easily accessible, only ~30% of oral cancers are diagnosed at an early stage, which is the main factor attributed to the low 5-year survival rate (63%) of oral cancer patients. Several screening tools for oral cancer have been commercially available; however, none of them have been demonstrated to have sufficient sensitivity and specificity for early detection of oral cancer and dysplasia. We hypothesized that an array of biochemical and metabolic biomarkers for oral cancer and dysplasia can be quantified by endogenous fluorescence lifetime imaging (FLIM), thus enabling levels of sensitivity and specificity adequate for early detection of oral cancer and dysplasia. Our group has recently developed multispectral FLIM endoscopes to image the oral cavity with unprecedented imaging speed (>2fps). We have also performed an in vivo pilot study, in which endogenous multispectral FLIM images were acquired from clinically suspicious oral lesions of 52 patients undergoing tissue biopsy. The results from this pilot study indicated that mild-dysplasia and early stage oral cancer could be detected from benign lesions using a computed aided diagnosis (CAD) system developed based on biochemical and metabolic biomarkers that could be quantified from endogenous multispectral FLIM images. The diagnostic performance of this novel FLIM clinical tool was estimated using a cross-validation approach, showing levels of sensitivity and specificity >80%, and Area Under the Receiving Operating Curve (RO- AUC) >0.9. Future efforts are focused on developing cost-effective FLIM endoscopes and validating this novel clinical tool in prospective multi-center clinical studies.

Conference Presentation

Citation Download Citation

Javier A. Jo, Shuna Cheng, Rodrigo Cuenca, Elvis Duran, Bilal Malik, Kristen Maitland, Beena Ahmed, Lisa Cheng, and John Wright "Computer aided diagnosis system for automated label-free early detection of oral epithelial cancer and dysplasia based on autofluorescence lifetime imaging endoscopy (Conference Presentation)", Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 105750Y (14 March 2018); https://doi.org/10.1117/12.2293813

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
PRESENTATION

WATCH
PRESENTATION SAVE TO MY LIBRARY

GET CITATION

KEYWORDS

Cancer

Fluorescence lifetime imaging

Computer aided diagnosis and therapy

Multispectral imaging

Computing systems

Endoscopes

Endoscopy

Show All Keywords

Keywords/Phrases

Search In:

Publication Years