Multiphoton microscopy combined with machine learning shows promise for localizing pancreatic neuroendocrine tumors

Noelle Daigle; Suzann Duan; Juanita L. Merchant; Travis W. Sawyer

doi:10.1117/12.3000595

13 March 2024 Multiphoton microscopy combined with machine learning shows promise for localizing pancreatic neuroendocrine tumors

Noelle Daigle, Suzann Duan, Juanita L. Merchant, Travis W. Sawyer

Author Affiliations +

Proceedings Volume PC12846, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XXII; PC1284607 (2024) https://doi.org/10.1117/12.3000595
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

Pancreatic neuroendocrine tumors (PNETs) are a relatively rare type of cancer whose preferred method of treatment is surgery, however current intraoperative guidance techniques have poor contrast. Multiphoton microscopy (MPM) is an imaging technique capable of capturing many biomarkers indicative of cancer; this project examines whether MPM images may provide a basis for a robust method of PNET localization. 14 fixed frozen and 57 formalin-fixed paraffin-embedded samples were imaged using MPM and classified using linear discriminant analysis. The model performed well across both sample preparations, indicating our approach could be applied to improve surgical localization of PNETs.

Conference Presentation

Citation Download Citation

Noelle Daigle, Suzann Duan, Juanita L. Merchant, and Travis W. Sawyer "Multiphoton microscopy combined with machine learning shows promise for localizing pancreatic neuroendocrine tumors", Proc. SPIE PC12846, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XXII, PC1284607 (13 March 2024); https://doi.org/10.1117/12.3000595

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