Precision Without Invasion: The Path to Biopsy-Free Cervical Diagnostics

Authors

Samuel Adjei, Dartmouth CollegeFollow
Anya Ramrakhiani, Dartmouth CollegeFollow
Aditi Singh, Dartmouth CollegeFollow
Petros Taxiarchis, Dartmouth CollegeFollow
Rachel Glantzberg, Dartmouth CollegeFollow

Files

Student Class

2028

First Advisor

Dr. Irene Georgakoudi

First Advisor Department

Department of Engineering Sciences—Thayer School of Engineering

Description

This study explores a non-invasive, biopsy-free method for diagnosing cervical cancer using two-photon excitation fluorescence imaging and AI-driven image analysis. Researchers trained a custom Cellpose model to automatically annotate single-cell metabolic data from optical sections of cervical tissue based on redox ratios derived from NADH and FAD autofluorescence. Results showed that the custom model outperformed generalist alternatives in identifying cellular structures and that cancerous and healthy tissues exhibit distinct redox ratio distributions and depth-dependent metabolic trends. These findings underscore the potential of metabolic imaging and automated analysis to reveal intra-lesion heterogeneity and improve diagnostic precision.

Publication Date

2025

Disciplines

Bioimaging and Biomedical Optics | Biomedical Engineering and Bioengineering

Dartmouth Digital Commons Citation

Adjei, Samuel; Ramrakhiani, Anya; Singh, Aditi; Taxiarchis, Petros; and Glantzberg, Rachel, "Precision Without Invasion: The Path to Biopsy-Free Cervical Diagnostics" (2025). Wetterhahn Science Symposium Posters 2025. 3.
https://digitalcommons.dartmouth.edu/wetterhahn_2025/3