Academic Journal
Comparison of Whiskbroom and Pushbroom darkfield elastic light scattering spectroscopic imaging for head and neck cancer identification in a mouse model
| العنوان: | Comparison of Whiskbroom and Pushbroom darkfield elastic light scattering spectroscopic imaging for head and neck cancer identification in a mouse model |
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| المؤلفون: | Bassler, MC, Stefanakis, M, Sequeira, I, Ostertag, E, Wagner, A, Bartsch, JW, Roeßler, M, Mandic, R, Reddmann, EF, Lorenz, A, Rebner, K, Brecht, M |
| بيانات النشر: | Springer |
| سنة النشر: | 2021 |
| المجموعة: | Queen Mary University of London: Queen Mary Research Online (QMRO) |
| مصطلحات موضوعية: | Chemometrics/statistics, Clinical/biomedical analysis, Head and neck cancer, Microspectroscopy, Mie elastic light scattering spectroscopy, Mouse tumor model, Animals, Disease Models, Animal, Female, Light, Male, Mice, Inbred C57BL, Principal Component Analysis, Reproducibility of Results, Scattering, Radiation, Squamous Cell Carcinoma of Head and Neck, Tongue Neoplasms |
| الوصف: | 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. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | 7363 - 7383 |
| اللغة: | English |
| Relation: | Anal Bioanal Chem; https://qmro.qmul.ac.uk/xmlui/handle/123456789/93313 |
| DOI: | 10.1007/s00216-021-03726-5 |
| الاتاحة: | https://qmro.qmul.ac.uk/xmlui/handle/123456789/93313 https://doi.org/10.1007/s00216-021-03726-5 |
| Rights: | Attribution 3.0 United States ; http://creativecommons.org/licenses/by/3.0/us/ |
| رقم الانضمام: | edsbas.282A9A92 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1007/s00216-021-03726-5 |
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