CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume PC12816 > Article
Presentation
13 March 2024 A new biomarker for metastatic melanoma based on femtosecond pump-probe microscopy and supervised learning
David Grass, Angelica M. Selim, Georgia M. Beasley, Martin C. Fischer, Warren S. Warren
Author Affiliations +
Proceedings Volume PC12816, Photonics in Dermatology and Plastic Surgery 2024; PC128160K (2024) https://doi.org/10.1117/12.2691938
Event: SPIE BiOS, 2024, San Francisco, California, United States
Abstract
Melanoma is responsible for around 10,000 deaths annually in the US. While simple excision can cure most melanomas, some progress into metastatic cancer, necessitating advanced treatment options. However, the current clinical diagnosis methods are insufficient in accurately identifying metastasis. There is a need for better biomarkers for patients at risk of developing metastases to enable timely intervention and appropriate treatment. We present a biomarker based on femtosecond pump-probe microscopy and supervised learning techniques to diagnose metastatic melanoma. Pump-probe microscopy images of primary melanomas reveal the chemical and physical structure of melanin, a naturally occurring pigment in most melanoma tumors. Leveraging supervised learning models, we classify melanin features and utilize them to guide the diagnosis of metastatic disease. Our proposed biomarker is compatible with the current clinical protocol, as it only requires a slice of the primary tumor, which is routinely excised following clinical guidelines. In our preliminary dataset of approximately 50 patients, the biomarker demonstrates encouraging sensitivity and specificity, exceeding 80%.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
David Grass, Angelica M. Selim, Georgia M. Beasley, Martin C. Fischer, and Warren S. Warren "A new biomarker for metastatic melanoma based on femtosecond pump-probe microscopy and supervised learning", Proc. SPIE PC12816, Photonics in Dermatology and Plastic Surgery 2024, PC128160K (13 March 2024); https://doi.org/10.1117/12.2691938
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
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
Advertisement
Advertisement
KEYWORDS
Melanoma
Machine learning
Microscopy
Femtosecond phenomena
Tumors
Skin cancer
Gold
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top