For the first time, researchers used a powerful microscopy technique in conjunction with automated image analysis algorithms to distinguish between healthy and metastatic cancerous tissue without using invasive biopsies or contrast dye. This novel non-invasive imaging approach could one day assist doctors in detecting cancer metastasis that is otherwise difficult to detect during operations using standard imaging technologies.
Existing techniques are extremely useful but have low spatial resolution and frequently require exogenous contrast agents. The method used in this study identifies cellular and tissue features at the microscopic level in a completely label-free manner, essentially acting as a biopsy without a knife.
The researchers show how to use multiphoton microscopy and automated image and statistical analysis algorithms (non-invasive imaging) to examine freshly excised biopsies from the peritoneal cavity, a part of the abdomen frequently affected by metastatic cancers, particularly in ovarian cancer patients. This is the first time healthy and metastatic human peritoneal tissue has been successfully assessed using this microscopy modality and image texture analysis techniques.
Because the method evaluates cellular and extracellular tissue features at the microscopic level, it can potentially detect cancer metastasis at an earlier stage, when it may be easier to treat. The approach, which uses algorithms to classify tissues, could also help reduce bias in image interpretation and supplement methods that rely on human expertise.
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