Automated quantification of Ki-67 index associates with pathologic grade of pulmonary neuroendocrine tumors.
10.1097/CM9.0000000000000109
- Author:
Hai-Yue WANG
1
;
Zhong-Wu LI
;
Wei SUN
;
Xin YANG
;
Li-Xin ZHOU
;
Xiao-Zheng HUANG
;
Ling JIA
;
Dong-Mei LIN
Author Information
1. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
- Publication Type:Journal Article
- MeSH:
Adult;
Aged;
Aged, 80 and over;
Carcinoma, Neuroendocrine;
metabolism;
pathology;
Female;
Humans;
Immunohistochemistry;
Ki-67 Antigen;
metabolism;
Leukemia, Lymphocytic, Chronic, B-Cell;
metabolism;
pathology;
Male;
Middle Aged;
Neuroendocrine Tumors;
metabolism;
pathology;
Prognosis;
World Health Organization
- From:
Chinese Medical Journal
2019;132(5):551-561
- CountryChina
- Language:English
-
Abstract:
BACKGROUND:Classification of the pulmonary neuroendocrine tumor (pNET) categories is a step-wise process identified by the presence of necrosis and number of mitoses per 2 mm. In neuroendocrine tumor pathology, Ki-67 was first described as a prognostic factor in the pancreas and incorporated into the grading system of digestive tract neuroendocrine neoplasms in the 2010 WHO classification. However, the significance of Ki-67 in pNETs was still a controversial issue. This study was to investigate the potentially diagnostic value of Ki-67 in pNETs.
METHODS:We retrieved 159 surgical specimens of pNETs, including 35 typical carcinoids (TCs), 2 atypical carcinoid (ACs), 28 large-cell neuroendocrine carcinomas (LCNECs), 94 small-cell lung cancers (SCLCs). Manual conventional method (MCM) and computer-assisted image analysis method (CIAM) were used to calculate the Ki-67 proliferative index. In CIAM, 6 equivalent fields (500 × 500 μm) at 10× magnification were manually annotated for digital image analysis.
RESULTS:The Ki-67 index among the 4 groups with ranges of 0.38% to 12.66% for TC, 4.34% to 29.48% for AC, 30.67% to 93.74% for LCNEC, and 40.71% to 96.87% for SCLC. The cutoff value of Ki-67 index to distinguish low grade with high grade was 30.07%. For the univariate survival analyses in pNETs, both the overall survival and progression-free survival correlated with Ki-67 index. In addition, the Ki-67 index performed by CIAM was proved to be of great positive correlation with MCM.
CONCLUSIONS:Ki-67 index counted by CIAM is a reliable method and can be a useful adjunct to classify the low- and high-grade NETs.
