Journal Article

Comparison of Whiskbroom and Pushbroom darkfield elastic light scattering spectroscopic imaging for head and neck cancer identification in a mouse model

Wagner, Alexandra, Mandic, Robert, Rebner, Karsten, Ostertag, Edwin, Bartsch, Jörg W, Sequeira, Inês, Lorenz, Anita, Bassler, Miriam C, Brecht, Marc, Roeßler, Marion, Stefanakis, Mona, Reddmann, Eike F

2021

Overview

The early detection of head and neck cancer is a prolonged challenging task. It requires a precise and accurate identification of tissue alterations as well as a distinct discrimination of cancerous from healthy tissue areas. A novel approach for this purpose uses microspectroscopic techniques with special focus on hyperspectral imaging (HSI) methods. Our proof-of-principle study presents the implementation and application of darkfield elastic light scattering spectroscopy (DF ELSS) as a non-destructive, high-resolution, and fast imaging modality to distinguish lingual healthy from altered tissue regions in a mouse model. The main aspect of our study deals with the comparison of two varying HSI detection principles, which are a point-by-point and line scanning imaging, and whether one might be more appropriate in differentiating several tissue types. Statistical models are formed by deploying a principal component analysis (PCA) with the Bayesian discriminant analysis (DA) on the elastic light scattering (ELS) spectra. Overall accuracy, sensitivity, and precision values of 98% are achieved for both models whereas the overall specificity results in 99%. An additional classification of model-unknown ELS spectra is performed. The predictions are verified with histopathological evaluations of identical HE-stained tissue areas to prove the model’s capability of tissue distinction. In the context of our proof-of-principle study, we assess the Pushbroom PCA-DA model to be more suitable for tissue type differentiations and thus tissue classification. In addition to the HE-examination in head and neck cancer diagnosis, the usage of HSI-based statistical models might be conceivable in a daily clinical routine.

• Publisher: Springer Nature B.V
• Subject: Animal models / Bayesian analysis / Cancer / Classification / Discriminant analysis / Elastic scattering / Head & neck cancer / Hyperspectral imaging / Image resolution / Light scattering / Mathematical models / Medical imaging / Principal components analysis / Spectral sensitivity / Spectroscopy / Spectrum analysis / Statistical analysis / Statistical models / Tissues