Literature DB >> 27511992

Comparison of visual assessment and image analysis in the evaluation of Ki-67 expression and their prognostic significance in immunohistochemically defined luminal breast carcinoma.

Koji Arihiro1, Miyo Oda2, Masahiro Ohara3, Takayuki Kadoya4, Akihiko Osaki5, Takashi Nishisaka6, Noriyuki Shiroma2, Yoshie Kobayashi2,4.   

Abstract

OBJECTIVES: To compare the Ki-67 labeling index value obtained through immunohistochemistry analysis by human examiners to that obtained from computer-assisted image analysis, and to establish a cut-off value for Ki-67 labeling index for each method in luminal B breast carcinoma.
METHODS: Immunohistochemistry analysis for Ki-67 was performed on the formalin-fixed, paraffin-embedded tissue samples from 403 patients with primary luminal breast cancers. Whole slide images were obtained using the NanoZoomer (Hamamatsu Photonics, Hamamatsu, Japan) and thoroughly analyzed using the Definiens Tissue Studio version 1.1 (Definiens AG, Munich, Germany) to detect the percentage of positively-stained nuclei of carcinoma cells.
RESULTS: Although a significant correlation was found between the Ki-67 labeling index obtained by manual assessment and computer-assisted image analysis (Spearman rank correlation coefficient, P < 0.01), the Ki-67 labeling index value obtained by manual assessment was significantly higher than that obtained by computer-assisted image analysis (Wilcoxon signed rank test, P < 0.0001). Disease-free survival was significantly lower in 403 patients with tumors having high Ki-67 labeling index values determined by automated analysis (cut-off value: 11.5%; P < 0.00001) and visual counting (cut-off value: 28.5%; P < 0.00001). Disease-free survival was also significantly lower in 288 patients who received adjuvant endocrine therapy alone having high Ki-67 labeling index values determined by automated analysis (cut-off value: 11.5%; P < 0.0001) and visual counting (cut-off value: 19.7%, P < 0. 0001).
CONCLUSIONS: The Ki-67 labeling index values determined by automated analysis and visual counting could equally predict disease-free survival in patients with luminal B breast carcinoma, including those who received endocrine therapy.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  Ki-67; breast cancer; image analysis; immunohistochemistry; whole slide image

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Year:  2016        PMID: 27511992     DOI: 10.1093/jjco/hyw107

Source DB:  PubMed          Journal:  Jpn J Clin Oncol        ISSN: 0368-2811            Impact factor:   3.019


  3 in total

1.  Relationship between the Ki67 index and its area based approximation in breast cancer.

Authors:  Muhammad Khalid Khan Niazi; Caglar Senaras; Michael Pennell; Vidya Arole; Gary Tozbikian; Metin N Gurcan
Journal:  BMC Cancer       Date:  2018-09-03       Impact factor: 4.430

2.  Ki-67 assessment in early breast cancer: SAKK28/12 validation study on the IBCSG VIII and IBCSG IX cohort.

Authors:  Zsuzsanna Varga; Qiyu Li; Wolfram Jochum; Ulrike Perriard; Tilman Rau; Jean-Christoph Tille; Hanne Hawle; Dirk Klingbiel; Beat Thuerlimann; Thomas Ruhstaller
Journal:  Sci Rep       Date:  2019-09-19       Impact factor: 4.379

3.  Using computer assisted image analysis to determine the optimal Ki67 threshold for predicting outcome of invasive breast cancer.

Authors:  Timothy Kwang Yong Tay; Aye Aye Thike; Nirmala Pathmanathan; Ana Richelia Jara-Lazaro; Jabed Iqbal; Adeline Shi Hui Sng; Heng Seow Ye; Jeffrey Chun Tatt Lim; Valerie Cui Yun Koh; Jane Sie Yong Tan; Joe Poh Sheng Yeong; Zi Long Chow; Hui Hua Li; Chee Leong Cheng; Puay Hoon Tan
Journal:  Oncotarget       Date:  2018-02-05
  3 in total

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