کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4132368 1606657 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparison of the methods for measuring the Ki-67 labeling index in adrenocortical carcinoma: manual versus digital image analysis
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی آسیب‌شناسی و فناوری پزشکی
پیش نمایش صفحه اول مقاله
Comparison of the methods for measuring the Ki-67 labeling index in adrenocortical carcinoma: manual versus digital image analysis
چکیده انگلیسی

SummaryAdrenocortical carcinoma (ACC) is a rare, highly malignant neoplasm harboring marked histologic heterogeneity. The Ki-67 labeling index (LI) is one of the most effective diagnostic and prognostic markers in ACC. However, its assessment has by no means been standardized. Therefore, in this study, we analyzed the Ki-67 LI in 18 ACC cases both by seven pathologists using microscopes (MA; manual analysis) and with digital image analysis (DIA) and also compared the Ki-67 LI obtained by selecting “hot spots” and formulating the “average” reading of the whole tumor specimen. In addition, we performed statistical analysis of the association between Ki-67 LI and the clinical and pathologic features of individual cases. The DIA was significantly correlated with MA in hot spots but not in the average fields. The Ki-67 LI in hot spots was significantly and consistently higher than that in average areas by both MA and DIA, indicating intratumoral heterogeneity. The Ki-67 LI was significantly correlated with the Weiss criteria (eosinophilic cytoplasm, nuclear atypia, atypical mitoses, and sinusoidal invasion) by any mode of evaluation. The clinical outcome was significantly better in the patients with a Ki-67 < 10% than in those with a Ki-67 > 10% by MA in hot spots. The Ki-67 LI in hot spots measured by MA best reflected the clinical and pathologic features of ACC. Employment of DIA to obtain the Ki-67 LI in ACC requires further improvement, including correction of its overestimation of the value by counting non-tumorous cells and nuclear segmentation in areas of high cell density.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Human Pathology - Volume 53, July 2016, Pages 41–50
نویسندگان
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