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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Massachusetts Lowell |
| Country | United States |
| Start Date | Jan 01, 2025 |
| End Date | Dec 31, 2025 |
| Duration | 364 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2437649 |
The broader impact of this I-Corps project is based on the development of a new technology using Optical Polarization Imaging (OPI), a technique that uses the light to study and create images of collagen tissue. This technology could be useful in dermatology, especially in skin cancer surgeries. Currently, surgeons often struggle to clearly identify where cancer cells end and healthy tissue begins because they rely on visual inspection alone.
This limitation can lead to incomplete removal of the cancer, causing the cancer to return, which increases patient anxiety, procedure time, and costs. With OPI technology, surgeons will be able to pinpoint cancer boundaries more precisely before surgery and potentially enable complete removal of tumors in a single surgery at least 90% of the time. This OPI technology can make procedures faster, less stressful, and more effective for patients, and could eventually become the standard of care for skin cancer surgeries.
This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of an Optical Polarization Imaging (OPI) device and methods for the rapid, non-invasive, quantitative assessment of collagen. By employing polarization filtering, the device rejects light reflected from the tissue surface, enabling visualization of superficial collagen.
Spectral encoding is conducted by illuminating the imaged field with narrowband target wavelengths to account for chromophores such as melanin and hemoglobin. Validation studies have demonstrated the device's sensitivity (100%) and specificity (98%) in detecting positive cancer margins non-invasively. An algorithm provides high accuracy margin calculations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of Massachusetts Lowell
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