BACKGROUND: Optical transfer diagnosis is a novel melanoma detection system that uses morphologic-physiologic mapping. OBJECTIVE: To further evaluate the potential of optical transfer diagnosis for distinguishing benign from malignant pigmented melanocytic neoplasms. METHODS AND MATERIALS: Ninety-four patients with pigmented lesions suggestive of melanoma were referred for optical transfer diagnosis. After lesions were scanned with the camera, they were removed for histopathologic examination by two dermatopathologists each. From the recorded images, morphologic-physiologic maps were created with prediction models of light absorption and scattering by chromophores such as hemoglobin, keratin, and melanin at different epidermal and dermal depths. Entropy and relative entropy values derived from the morphologic-physiologic maps and a set of pure morphologic parameters were analyzed for output prediction of melanoma versus nonmelanoma. Dermoscopic images were reviewed and scored using the color, architecture, symmetry, and homogeneity (CASH) algorithm to assign a value of clinical atypia. RESULTS Of the 118 scanned and biopsied lesions (median CASH score 8), 11 were identified as melanoma or atypical melanocytic hyperplasia consistent with melanoma. For identification of melanomas, optical transfer diagnosis had a sensitivity of 100% and a specificity of 90%. CONCLUSIONS: This technology continues to be a promising adjunct to clinical skin cancer screening.
BACKGROUND: Optical transfer diagnosis is a novel melanoma detection system that uses morphologic-physiologic mapping. OBJECTIVE: To further evaluate the potential of optical transfer diagnosis for distinguishing benign from malignant pigmented melanocytic neoplasms. METHODS AND MATERIALS: Ninety-four patients with pigmented lesions suggestive of melanoma were referred for optical transfer diagnosis. After lesions were scanned with the camera, they were removed for histopathologic examination by two dermatopathologists each. From the recorded images, morphologic-physiologic maps were created with prediction models of light absorption and scattering by chromophores such as hemoglobin, keratin, and melanin at different epidermal and dermal depths. Entropy and relative entropy values derived from the morphologic-physiologic maps and a set of pure morphologic parameters were analyzed for output prediction of melanoma versus nonmelanoma. Dermoscopic images were reviewed and scored using the color, architecture, symmetry, and homogeneity (CASH) algorithm to assign a value of clinical atypia. RESULTS Of the 118 scanned and biopsied lesions (median CASH score 8), 11 were identified as melanoma or atypical melanocytic hyperplasia consistent with melanoma. For identification of melanomas, optical transfer diagnosis had a sensitivity of 100% and a specificity of 90%. CONCLUSIONS: This technology continues to be a promising adjunct to clinical skin cancer screening.
Authors: Milind Rajadhyaksha; Ashfaq Marghoob; Anthony Rossi; Allan C Halpern; Kishwer S Nehal Journal: Lasers Surg Med Date: 2016-10-27 Impact factor: 4.025
Authors: Lavinia Ferrante di Ruffano; Yemisi Takwoingi; Jacqueline Dinnes; Naomi Chuchu; Susan E Bayliss; Clare Davenport; Rubeta N Matin; Kathie Godfrey; Colette O'Sullivan; Abha Gulati; Sue Ann Chan; Alana Durack; Susan O'Connell; Matthew D Gardiner; Jeffrey Bamber; Jonathan J Deeks; Hywel C Williams Journal: Cochrane Database Syst Rev Date: 2018-12-04