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1.
Cancer Treat Rev ; 99: 102263, 2021 Sep.
Article in English | MEDLINE | ID: mdl-34343892

ABSTRACT

The application of imaging biomarkers in oncology is still in its infancy, but with the expansion of radiomics and radiogenomics a revolution is expected in this field. This may be of special interest in head and neck cancer, since it can promote precision medicine and personalization of treatment by overcoming several intrinsic obstacles in this pathology. Our goal is to provide the medical oncologist with the basis to approach these disciplines and appreciate their main uses in clinical research and clinical practice in the medium term. Aligned with this objective we analyzed the most relevant studies in the field, also highlighting novel opportunities and current challenges.


Subject(s)
Head and Neck Neoplasms/diagnostic imaging , Head and Neck Neoplasms/genetics , Squamous Cell Carcinoma of Head and Neck/diagnostic imaging , Squamous Cell Carcinoma of Head and Neck/genetics , Biomarkers, Tumor , Decision Making , Diagnostic Techniques, Radioisotope , Head and Neck Neoplasms/therapy , Humans , Machine Learning , Precision Medicine , Prognosis , Squamous Cell Carcinoma of Head and Neck/therapy
2.
Biomed Opt Express ; 11(1): 8-26, 2020 Jan 01.
Article in English | MEDLINE | ID: mdl-32010496

ABSTRACT

"How thick is your light sheet?" is a question that has been asked frequently after talks showing impressive renderings of 3D data acquired by a light-sheet microscope. This question is motivated by the fact that most of the time the thickness of the light-sheet is uniquely associated to the axial resolution of the microscope. However, the link between light-sheet thickness and axial resolution has never been systematically assessed and it is still unclear how both are connected. The question is not trivial because commonly employed measures cannot readily be applied or do not lead to easily interpretable results for the many different types of light sheet. Here, we introduce a set of intuitive measures that helps to define the relationship between light sheet thickness and axial resolution by using simulation data. Unexpectedly, our analysis revealed a trade-off between better axial resolution and thinner light-sheet thickness. Our results are surprising because thicker light-sheets that provide lower image contrast have previously not been associated with better axial resolution. We conclude that classical Gaussian illumination beams should be used when image contrast is most important, and more advanced types of illumination represent a way to optimize axial resolution at the expense of image contrast.

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