Implementation of Digital Image Analysis in Assessment of Ki67 Index in Breast Cancer

被引:1
|
作者
Vanderschelden, Rachel K. [1 ,3 ]
Jerome, Jacob A. [1 ]
Gonzalez, Daniel [2 ]
Seigh, Lindsey [2 ]
Carter, Gloria J. [1 ]
Clark, Beth Z. [1 ]
Elishaev, Esther [1 ]
Louis Fine, Jeffrey [1 ]
Harinath, Lakshmi [1 ]
Jones, Mirka W. [1 ]
Villatoro, Tatiana M. [1 ]
Soong, Thing Rinda [1 ]
Yu, Jing [1 ]
Zhao, Chengquan [1 ]
Hartman, Doug [2 ]
Bhargava, Rohit [1 ]
机构
[1] Univ Pittsburgh, UPMC, Magee Womens Hosp, Dept Pathol, Pittsburgh, PA USA
[2] Univ Pittsburgh, Med Ctr, Dept Pathol, Pittsburgh, PA USA
[3] 200 Lothrop St, Pittsburgh 15213, PA USA
关键词
breast cancer; digital image analysis; Ki67;
D O I
10.1097/PAI.0000000000001171
中图分类号
R602 [外科病理学、解剖学]; R32 [人体形态学];
学科分类号
100101 ;
摘要
The clinical utility of the proliferation marker Ki67 in breast cancer treatment and prognosis is an active area of research. Studies have suggested that differences in pre-analytic and analytic factors contribute to low analytical validity of the assay, with scoring methods accounting for a large proportion of this variability. Use of standard scoring methods is limited, in part due to the time intensive nature of such reporting protocols. Therefore, use of digital image analysis tools may help to both standardize reporting and improve workflow. In this study, digital image analysis was utilized to quantify Ki67 indices in 280 breast biopsy and resection specimens during routine clinical practice. The supervised Ki67 indices were then assessed for agreement with a manual count of 500 tumor cells. Agreement was excellent, with an intraclass correlation coefficient of 0.96 for the pathologist-supervised analysis. This study illustrates an example of a rapid, accurate workflow for implementation of digital image analysis in Ki67 scoring in breast cancer.
引用
收藏
页码:17 / 23
页数:7
相关论文
共 50 条
  • [1] Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer
    Stalhammar, Gustav
    Robertson, Stephanie
    Wedlund, Lena
    Lippert, Michael
    Rantalainen, Mattias
    Bergh, Jonas
    Hartman, Johan
    HISTOPATHOLOGY, 2018, 72 (06) : 974 - 989
  • [2] A Comparison of Visual Assessment and Automated Digital Image Analysis of Ki67 Labeling Index in Breast Cancer
    Zhong, Fangfang
    Bi, Rui
    Yu, Baohua
    Yang, Fei
    Yang, Wentao
    Shui, Ruohong
    PLOS ONE, 2016, 11 (02):
  • [3] A simple digital image analysis system for automated Ki67 assessment in primary breast cancer
    Alataki, Anastasia
    Zabaglo, Lila
    Tovey, Holly
    Dodson, Andrew
    Dowsett, Mitch
    HISTOPATHOLOGY, 2021, 79 (02) : 200 - 209
  • [4] Ki67 assessment in breast cancer: an update
    Penault-Llorca, Frederique
    Radosevic-Robin, Nina
    PATHOLOGY, 2017, 49 (02) : 166 - 171
  • [5] Image Analysis in Digital Pathology: Combining Automated Assessment of Ki67 Staining Quality with Calculation of Ki67 Cell Proliferation Index
    Bengtsson, Ewert
    Ranefall, Petter
    CYTOMETRY PART A, 2019, 95A (07) : 714 - 716
  • [6] A novel model for Ki67 assessment in breast cancer
    Quinci Romero
    Pär-Ola Bendahl
    Mårten Fernö
    Dorthe Grabau
    Signe Borgquist
    Diagnostic Pathology, 9
  • [7] A novel model for Ki67 assessment in breast cancer
    Romero, Quinci
    Bendahl, Par-Ola
    Ferno, Marten
    Grabau, Dorthe
    Borgquist, Signe
    DIAGNOSTIC PATHOLOGY, 2014, 9
  • [8] A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissue
    Arvydas Laurinavicius
    Benoit Plancoulaine
    Aida Laurinaviciene
    Paulette Herlin
    Raimundas Meskauskas
    Indra Baltrusaityte
    Justinas Besusparis
    Darius Dasevicius
    Nicolas Elie
    Yasir Iqbal
    Catherine Bor
    Ian O Ellis
    Breast Cancer Research, 16
  • [9] A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissue
    Laurinavicius, Arvydas
    Plancoulaine, Benoit
    Laurinaviciene, Aida
    Herlin, Paulette
    Meskauskas, Raimundas
    Baltrusaityte, Indra
    Besusparis, Justinas
    Dasevicius, Darius
    Elie, Nicolas
    Iqbal, Yasir
    Bor, Catherine
    Ellis, Ian O.
    BREAST CANCER RESEARCH, 2014, 16 (02)
  • [10] Proliferation assessment in breast carcinomas using digital image analysis based on virtual Ki67/cytokeratin double staining
    Roge, Rasmus
    Riber-Hansen, Rikke
    Nielsen, Soren
    Vyberg, Mogens
    BREAST CANCER RESEARCH AND TREATMENT, 2016, 158 (01) : 11 - 19