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5.
J Cutan Pathol ; 42(12): 1000-1011, 2015 Dec.
Article in English | MEDLINE | ID: mdl-26269423

ABSTRACT

We present an extremely rare case of low-grade cylindromatous adnexal carcinoma (CAC) on the right chest wall of a 77-year-old man. Histopathologically, the neoplasm was initially diagnosed as a cylindroma that developed over the course of 13 years. A diagnosis of low-grade CAC was rendered after the documentation of a local recurrence and histopathology of the recurrent tumor. To further assess the evolution of low-grade CAC over time, we compared the morphology, mitotic account, proliferative markers and adhesion molecule immunoreactivity among paired primary and recurrent tumors. Unlike those earlier reported, our case showed the maintenance of tumor morphology after a recurrence without areas of obvious malignant transformation or metaplastic change. We showed here for the first time the expression of adhesion molecules of CAC/spiradenoma and a comparison of proliferation indices between a primary tumor and its local recurrence. This peculiar tumor differs from previously reported cases and harbors a malignant potential although the histopathological features of malignancy are subtle. Our meta-analysis of the literature provided background information regarding this rare entity. Alterations of E-cadherin and GCDFP-15 expression may provide additional helpful clues in differential diagnosis and determining the clinical behavior of this unusual neoplasm. Further studies are warranted to confirm the potential discriminative role of these markers.

17.
Article in English | MEDLINE | ID: mdl-19163608

ABSTRACT

In acne treatment, it is important to accurately evaluate the severity of Acne. The acne should be classified into several skin lesions including comedo, reddish papule, pustule, and scar. However, in some cases, a visual detection from RGB image maybe difficult for the proper evaluation of acne skin lesions. This paper proposes an extraction method using the spectral information of the various type of acne skin lesions calculated from the multispectral images (MSI) of the lesions. In the experiment, we showed the possibility of classifying acne lesion types by applying a combination of several linear discriminant functions (LDF's).


Subject(s)
Acne Vulgaris/diagnosis , Diagnosis, Computer-Assisted/methods , Image Processing, Computer-Assisted/methods , Skin/pathology , Acne Vulgaris/physiopathology , Algorithms , Dermatology/methods , Equipment Design , Face , Humans , Reproducibility of Results , Sensitivity and Specificity , Signal Processing, Computer-Assisted , Spectrophotometry/methods
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