Meet the clusters: a deep learning approach for label-free detection of circulating tumor cell clusters using flow cytometry

Nilay Vora; Prashant Shekhar; Jasmine Kwan; Michael Esmail; Abani Patra; Irene Georgakoudi

doi:10.1117/12.2649335

17 March 2023 Meet the clusters: a deep learning approach for label-free detection of circulating tumor cell clusters using flow cytometry

Nilay Vora, Prashant Shekhar, Jasmine Kwan, Michael Esmail, Abani Patra, Irene Georgakoudi

Author Affiliations +

Proceedings Volume PC12363, Multiscale Imaging and Spectroscopy IV; PC123630A (2023) https://doi.org/10.1117/12.2649335
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

Circulating tumor cell clusters (CTCCs) are extremely rare events (<4 events per 7.5 mL of blood) found in the bloodstream of metastatic cancer patients. Despite their scarcity, they represent an increased risk for metastasis. Detection and isolation of CTCCs remain a priority for oncologists to improve cancer patients' diagnosis, stratification, and treatment. This study aims to demonstrate that confocal backscatter and fluorescence flow cytometry (BSFC) with deep learning-based signal analysis can enable sensitive detection of CTCCs in whole blood in vitro and in vivo without using exogenous labeling.

Conference Presentation

Citation Download Citation

Nilay Vora, Prashant Shekhar, Jasmine Kwan, Michael Esmail, Abani Patra, and Irene Georgakoudi "Meet the clusters: a deep learning approach for label-free detection of circulating tumor cell clusters using flow cytometry", Proc. SPIE PC12363, Multiscale Imaging and Spectroscopy IV, PC123630A (17 March 2023); https://doi.org/10.1117/12.2649335

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