The goal of the research is to use a pump-probe microscopy system to find statistically significant variations between melanomas that did and did not develop metastases. This information will be used to develop automated classification algorithms to find robust molecular and structural features with strong predictive power. These insights will enable a retrospective study of melanoma and sentinel node biopsies, that can be used to validate the findings. By the end of the project, it is expected that there will be statistically significant evidence that pump-probe microscopy can substantially improve the diagnostic accuracy of histopathology.
We propose a novel imaging technology which can image specific cancer biomarkers in developing skin lesions. This approach could reduce the number of false negative diagnoses in thin (less than 1mm) melanomas that uncharacteristically metastasize. Additionally, this approach could eliminate thousands of false positive melanoma diagnoses per year, and save many millions of dollars in healthcare costs.
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