Fluorescence-based radiomics analysis improves the identification of head and neck cancer in preclinical studies

Yao Chen; Cheng Wang; Samuel S. Streeter; Sassan Hodge; Brian W. Pogue; Kimberley S. Samkoe

doi:10.1117/12.2608791

4 March 2022 Fluorescence-based radiomics analysis improves the identification of head and neck cancer in preclinical studies

Yao Chen, Cheng Wang, Samuel S. Streeter, Sassan Hodge, Brian W. Pogue, Kimberley S. Samkoe

Author Affiliations +

Proceedings Volume 11943, Molecular-Guided Surgery: Molecules, Devices, and Applications VIII; 119430D (2022) https://doi.org/10.1117/12.2608791
Event: SPIE BiOS, 2022, San Francisco, California, United States

Abstract

Optimal differentiation between tumor and normal tissues using epidermal growth factor receptor targeted fluorescence guided surgery (FGS) of head and neck cancer (HNC) is complicated by the presence of target receptor in the normal surrounding tissues. We propose the use of radiomics feature analysis to increase the accuracy and efficiency of tumor tissue discrimination based on machine-learning algorithms. Radiomics analysis demonstrates that radiomics analysis reaches a higher identification performance than the traditional intensity threshold method in the preclinical mice. This study proposes that a radiomics approach for fluorescence imaging in preclinical studies is a more accurate tissue type identification method requiring less post-agent-administration waiting time than the traditional fluorescence intensity threshold method.

Conference Presentation

Citation Download Citation

Yao Chen, Cheng Wang, Samuel S. Streeter, Sassan Hodge, Brian W. Pogue, and Kimberley S. Samkoe "Fluorescence-based radiomics analysis improves the identification of head and neck cancer in preclinical studies", Proc. SPIE 11943, Molecular-Guided Surgery: Molecules, Devices, and Applications VIII, 119430D (4 March 2022); https://doi.org/10.1117/12.2608791

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