Special Section on Optical Diagnostic and Biophotonic Methods from Bench to Bedside

Automated detection of malignant features in confocal microscopy on superficial spreading melanoma versus nevi

[+] Author Affiliations
Dan Gareau

Oregon Health and Science University, Department of Dermatology and Department of Biomedical Engineering, 3303 Southwest Bond Avenue Portland, Oregon 97239 and Memorial Sloan-Kettering Cancer Center, Dermatology Service, 160 East 53rd Street, New York, New York 10022

Ricky Hennessy

Oregon Health and Science University, Department of Biomedical Engineering, 3303 Southwest Bond Avenue, Portland, Oregon 97239

Eric Wan

Oregon Health and Science University, Department of Biomedical Engineering, 3303 Southwest Bond Avenue, Portland, Oregon 97239

Giovanni Pellacani

University of Modena and Reggio Emilia, Department of Dermatology, Via del Pozzo 71, Modena 41100, Italy

Steven L. Jacques

Oregon Health and Science University, Department of Dermatology and Department of Biomedical Engineering, 3303 Southwest Bond Avenue, Portland, Oregon 97239

J. Biomed. Opt. 15(6), 061713 (December 28, 2010). doi:10.1117/1.3524301
History: Received February 24, 2010; Revised October 18, 2010; Accepted October 21, 2010; Published December 28, 2010
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In-vivo reflectance confocal microscopy (RCM) shows promise for the early detection of superficial spreading melanoma (SSM). RCM of SSM shows pagetoid melanocytes (PMs) in the epidermis and disarray at the dermal-epidermal junction (DEJ), which are automatically quantified with a computer algorithm that locates depth of the most superficial pigmented surface [DSPS(x,y)] containing PMs in the epidermis and pigmented basal cells near the DEJ. The algorithm uses 200 noninvasive confocal optical sections that image the superficial 200 μm of ten skin sites: five unequivocal SSMs and five nevi. The pattern recognition algorithm automatically identifies PMs in all five SSMs and finds none in the nevi. A large mean gradient ψ (roughness) between laterally adjacent points on DSPS(x,y) identifies DEJ disruption in SSM ψ = 11.7 ± 3.7 [−] for n = 5 SSMs versus a small ψ = 5.5 ± 1.0 [−] for n = 5 nevi (significance, p = 0.0035). Quantitative endpoint metrics for malignant characteristics make digital RCM data an attractive diagnostic asset for pathologists, augmenting studies thus far, which have relied largely on visual assessment.

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© 2010 Society of Photo-Optical Instrumentation Engineers

Citation

Dan Gareau ; Ricky Hennessy ; Eric Wan ; Giovanni Pellacani and Steven L. Jacques
"Automated detection of malignant features in confocal microscopy on superficial spreading melanoma versus nevi", J. Biomed. Opt. 15(6), 061713 (December 28, 2010). ; http://dx.doi.org/10.1117/1.3524301


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