Dr. Marion Butler Profile

Dr. Marion Butler

at National Univ of Ireland Maynooth

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Proceedings Article | 15 October 2021 Poster + Paper

Application of modular digital holographic microscopy to clinical pathology samples before histopathological staining

Zhengyuan Tang, Kevin O'Dwyer, Marion Butler, Adam Dignam, Bryan Hennelly

Proceedings Volume 11898, 118981H (2021) https://doi.org/10.1117/12.2601387

KEYWORDS: Image segmentation, Holograms, Microscopes, Digital holography, Microscopy, Ovarian cancer, Beam splitters, 3D image processing, Holography, Pathology

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Digital Holography microscopy is a widely applied technique in biological imaging for retrieving quantitative phase information relating to a samples three-dimensional morphology and has received considerable interest in the investigation of real-time cellular dynamics. However, the traditional off-axis architecture has drawbacks in terms of a requirement for frequent calibration when the sample is changed as a consequence of the optical path length variation. This inconvenience can be overcome using a common-path design microscopy. Here we report on a portable module utilizing an off-axis architecture and an inexpensive laser diode source. The portability of the system enables it to be added to easily to the output port of an existing life-science microscope. An important feature of the module is that it is based on the self-reference principle, whereby the reference wavefield is generated from the image wavefield that is exiting the microscope image port using a suitable beam splitter and filter. This facilitates the source laser to be completely decoupled from the module. We investigate the application of the module to image samples of cells prepared using a common pathology slide preparation method known as ThinPrep, which is often used to prepare ovarian cancer, urine/bladder, and oral cytology samples for diagnostic inspection and to provide quantitative morphological information. In particular, we are interested in imaging samples that are fixed and air dried such that no mounting medium or coverslip is present, with the motivation of recording phase images immediately prior to cell staining and mounting.

Proceedings Article | 9 October 2021 Poster + Paper

Automated raman cytology for the classification of triple negative breast cancer cell lines

Kevin O'Dwyer, Katarina Domijan, Adam Dignam, Zhengyuan Tang, Marion Butler, Bryan Hennelly

Proceedings Volume 11900, 1190023 (2021) https://doi.org/10.1117/12.2601241

KEYWORDS: Raman spectroscopy, Cell biology, Image processing, Fine needle aspiration, Diagnostics, Cancer

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Raman micro-spectroscopy is an optical technique that can provide information on the biochemical composition of biological cells. Raman cytology, whereby Raman spectra are recorded from the nucleus of human epithelial cells is an active area of research. This typically involves the application of multivariate statistical algorithms to classify cell type, or disease group, based on the Raman spectrum. Although this approach has been shown to improve the diagnostic sensitivity of clinical cervical, bladder, and oral cytology for the identification of cancer cells, there has been no clinical adoption to date. The main reasons for this are the slow recording time and lack of reproducibility. In this paper, we review a recently proposed automated Raman cytology system based on image processing that can record several thousands of cell nuclei/day. The automation process is implemented using an open-source microscopy control system called Micro-Manager, which can readily be adapted by those with existing Raman microscopes and is designed to target the unstained nucleus, identified by imaging a plane below the sample, which is the primary target for Raman cytology based cancer diagnostics. In this paper we investigate the application of automated Raman cytology for the classification of two sub-types of Triple Negative Breast Cancer Cell Lines prepared using the ThinPrep protocol and we discuss how this approach could potentially improve the diagnostic sensitivity of Fine Needle Aspiration Cytology for Breast Cancer Diagnosis.

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