Skin cancer is the most prevalent cancer, and its assessment remains a challenge for physicians. This study reports the application of an optical sensing method, elastic scattering spectroscopy (ESS), coupled with a classifier that was developed with machine learning, to assist in the discrimination of skin lesions that are concerning for malignancy. The method requires no special skin preparation, is non-invasive, easy to administer with minimal training, and allows rapid lesion classification.
View Article and Find Full Text PDFObjectives/hypothesis: To evaluate the usefulness of elastic scattering spectroscopy (ESS) as a diagnostic adjunct to frozen section analysis in patients with diagnosed squamous cell carcinoma of the oral cavity.
Study Design: Prospective analytic study.
Methods: Subjects for this single institution, institutional review board-approved study were recruited from among patients undergoing surgical resection for squamous cell cancer of the oral cavity.
Thyroid nodules are common and often require fine needle aspiration biopsy (FNAB) to determine the presence of malignancy to direct therapy. Unfortunately, approximately 15-30% of thyroid nodules evaluated by FNAB are not clearly benign or malignant by cytology alone. These patients require surgery for the purpose of diagnosis alone; most of these nodules ultimately prove to be benign.
View Article and Find Full Text PDFThe work reported compares elastic scattering spectroscopy (ESS) for diagnosis of pigmented skin lesions in two spectral regions: UV-visible and near infrared (NIR). Given the known strong absorption by melanin in the near-UV to mid-visible range of the spectrum, such a comparison can help determine the optimum wavelength range of ESS for diagnosis of pigmented skin lesions. For this purpose, four South American opossums are treated with dimethylbenz(a)anthracene on multiple dorsal sites to induce both malignant melanomas and benign pigmented lesions.
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