Two-Photon Microscopy for Skin Cancer

This trial explores a new method for examining skin cancer biopsies using two-photon microscopy imaging. The goal is to determine if this technique, combined with a machine learning model, can match the results of traditional lab tests. It could make diagnosing skin cancer faster and more accurate in the clinic. Individuals with punch, excisional, or shave biopsy specimens are suitable participants, provided their biopsy is not for melanoma or similar conditions. As an unphased trial, this study offers a unique opportunity to contribute to innovative research that could transform skin cancer diagnosis.

Research has shown that two-photon fluorescence microscopy (TPFM) on human skin is generally safe. In one study, more than 70% of skin cells remained healthy with this imaging method. Clinical studies also showed only slight redness and minimal cell damage, indicating that the treatment does not significantly harm skin cells. Safety is crucial when using this technology on human skin, and these studies suggest that TPFM is well-tolerated.¹²³⁴⁵

Researchers are excited about two-photon microscopy (TPFM) for skin cancer because it offers a non-invasive way to diagnose the disease. Unlike traditional options that often require surgical biopsies, TPFM uses advanced imaging technology to visualize skin tissues at the cellular level. This method could reduce the need for invasive procedures and provide quicker, more accurate diagnoses, enhancing patient comfort and care. Additionally, by integrating machine learning for analysis, TPFM has the potential to improve diagnostic precision, making it a promising tool for early detection and treatment planning.

This trial will evaluate the effectiveness of two-photon fluorescence microscopy (TPFM) for diagnosing skin cancers. Studies have shown that TPFM can be highly effective. One study found that it identified squamous cell carcinoma with 89% sensitivity and 100% specificity. Another study demonstrated that TPFM diagnosed basal cell carcinoma with perfect accuracy, or 100%. These findings suggest that TPFM could enable doctors to make quick and accurate diagnoses. In this trial, TPFM will image specimens, and a machine learning model will diagnose them, potentially providing a reliable alternative to traditional biopsy methods for identifying nonmelanoma skin cancers.¹⁴⁶⁷⁸