Second-harmonic generation (SHG) microscopy has emerged as a powerful modality for imaging fibrillar collagen in a diverse range of tissues. A preliminary study demonstrated that non-imaging, randomly sampled SHG intensity measurements are likely sufficient to distinguish normal colorectal tissue from tumor/tumor-adjacent tissue with digital simulation of random sampling. While SHG images have been used endoscopically for tumor diagnosis before, the process of taking an SHG image complicates the endoscope and sets lower limits on the size, due to the necessity of scanning mechanisms. The novelty of the proposed non-imaging measurements is the feasibility of a much simpler and smaller endoscope that returns a quantitative value instead of relying on an observer to interpret an image.
Colon cancer is the third most common cancer in the United States, excluding skin cancers, and is the second most common cause of cancer deaths when men and women are combined. Despite the high death and case counts, the case rates and death rates have been decreasing the last few years. This type of cancer has a 65% 5-year survival rate. The reason for these decreases is in part due to better screening. This technology will improve screening and result in a continued decrease in cases and deaths.
Non-imaging SHG measurements will be used in colonoscopies and other endoscopic procedures to identify and differentiate normal versus cancerous tissue and identify surgical margins in real-time. This would replace conventional methods for sampling and identifying suspicious samples as it is much more reliable since it gives a quantitative assessment for whether there is cancerous tissue present. The reason that is better is because it is definitive, and patients don’t need to rely on a doctor interpreting an image correctly. It will be very helpful when there are very small areas of cancerous tissue that may have been difficult to see with the naked eye.
- Identifying tumors
- Colon cancer diagnosis
- Replacement to image sampling
- More reliable
- No need to rely on someone interpreting an image
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