New Microscope Technique Improves Metastasis Detection in Ovarian Cancer Patients

New Microscope Technique Improves Metastasis Detection in Ovarian Cancer Patients
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A newly developed imaging approach that combines laser microscopy with computational analysis may make it easier to spot ovarian cancer cells that have spread to other organs, called metastasis, a study found.

The new technique was described in a paper, titled “Two-photon images reveal unique texture features for label-free identification of ovarian cancer peritoneal metastases,” which was published in Biomedical Optics Express.

Cancer cells that have spread to distant organs are called metastases, and detecting these cells accurately and early on is critical for treatment. One way to find these cells is to look at tissue biopsies under a microscope — but this may miss small metastases.

Now, researchers developed a method to better identify these cells. The method uses two-photon microscopy, which involves firing short bursts of light at a sample. Then, based on how the light reflects and refracts off parts of the sample that have different shapes and textures, computer programs can make inferences about the biology of the cells. In this use, they can determine if the cells are normal tissue or cancerous metastases.

Importantly, unlike many other microscopy techniques, this method doesn’t require much sample preparation before a slide is put under a microscope. There are no added chemicals used to label different cell types. Instead, the data is derived purely from how light reflects off the sample.

This is important because it means the technique could feasibly be used in an operating room. That would allow biopsies to be analyzed during a surgery to remove the primary tumor. Additional metastases then could be removed in one surgery, rather than having to wait for lab results and doing a second surgery.

The researchers tested this technique on biopsies of peritoneum — the membrane that covers organs in the abdomen — from eight women who had undergone surgery for primary ovarian cancer.

The overall accuracy of the technique was 97.5%, with 40 out of 41 images correctly classified. The sensitivity — percentage of correctly identified true positives — was 100%, with 11/11 metastases identified as such. The specificity, or percentage of correctly identified true negatives, was 96.6%, with 29/30 healthy tissue samples identified as such.

The researchers noted that this is a relatively small sample, which makes it premature to suppose that these numbers would be reflective of this technique if employed in practice. But this study serves as a proof-of-concept for using this method to identify metastases.

“This is extremely high impact work,” Behrouz Shabestari, PhD, director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) program in Optical Imaging and Spectroscopy, said in a press release. The NIBIB, part of the National Institutes of Health, helped fund the study, along with the Hellenic Medical Society of New York and the Society of American Gastrointestinal and Endoscopic Surgeons.

“The ultimate aim of using this technology during surgery — to detect and remove routinely missed metastases — promises to significantly improve surgical outcomes for women being treated for ovarian cancer. Plus, the technology will also be applicable to other types of cancer,” he added.

Marisa holds an MS in Cellular and Molecular Pathology from the University of Pittsburgh, where she studied novel genetic drivers of ovarian cancer. She specializes in cancer biology, immunology, and genetics. Marisa began working with BioNews in 2018, and has written about science and health for SelfHacked and the Genetics Society of America. She also writes/composes musicals and coaches the University of Pittsburgh fencing club.
Total Posts: 129
Inês holds a PhD in Biomedical Sciences from the University of Lisbon, Portugal, where she specialized in blood vessel biology, blood stem cells, and cancer. Before that, she studied Cell and Molecular Biology at Universidade Nova de Lisboa and worked as a research fellow at Faculdade de Ciências e Tecnologias and Instituto Gulbenkian de Ciência. Inês currently works as a Managing Science Editor, striving to deliver the latest scientific advances to patient communities in a clear and accurate manner.
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Marisa holds an MS in Cellular and Molecular Pathology from the University of Pittsburgh, where she studied novel genetic drivers of ovarian cancer. She specializes in cancer biology, immunology, and genetics. Marisa began working with BioNews in 2018, and has written about science and health for SelfHacked and the Genetics Society of America. She also writes/composes musicals and coaches the University of Pittsburgh fencing club.
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