Automated digital image analysis and manual counting of Ki-67 proliferation index in patients with breast cancer

2017 ◽  
Vol 37 (2) ◽  
pp. 228-235
Author(s):  
Mervat M.F. El-Deftar ◽  
Samir S. Amer ◽  
Eman M.O. El-Touny ◽  
Amany Aboubakr ◽  
Heba El-Zawahry ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Proliferation Index ◽  
Ki 67 ◽  
Manual Counting

Reproducibility and Prognostic Potential of Ki-67 Proliferation Index when Comparing Digital-Image Analysis with Standard Semi-Quantitative Evaluation in Breast Cancer

2017 ◽  
Vol 24 (1) ◽  
pp. 115-127 ◽  
Author(s):  
Balázs Ács ◽  
Lilla Madaras ◽  
Kristóf Attila Kovács ◽  
Tamás Micsik ◽  
Anna-Mária Tőkés ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Quantitative Evaluation ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Proliferation Index ◽  
Ki 67

Comparison of Manual and Digital Assessment of KI-67 in Neuroendocrine Tumors

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S125-S125
Author(s):  
B S Raju ◽  
M Quinton ◽  
L Hassell
Keyword(s):  
Image Analysis ◽  
Neuroendocrine Tumors ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Hot Spot ◽  
World Health ◽  
Proliferation Index ◽  
Digital Analysis ◽  
Ki 67 ◽  
Digital Assessment

Abstract Introduction/Objective Proliferative activity is an essential prognostic and treatment indicator for neuroendocrine tumors (NET). Ki-67 proliferation index, if reported by unaided microscopic estimation on hot-spot locations could lead to variability and inconsistencies. This study aims to compare the Ki-67 assessment of NETs by visual estimation versus automated digital image analysis (Roche iCoreo/Virtuoso). Methods 212 patients with Ki-67-graded GI NETs (117 G1; 61 G2; 34 G3) from 2010 to 2019 were reassessed using digital image analysis quantification of hot spot areas of at least 500 cells (average 800 cells). Revised tumor grades were assigned according to the European Neuroendocrine Tumor Society guidelines and the 2010 World Health Organization classification and compared to initially reported grade. Results We found 75% concordance for G1, with 22% of cases upgraded to G2 and 3% of cases upgraded to G3. For G2, there was 70.5% agreement, with 13.1% of cases downgraded to G1 and 16.4% upgraded to G3. For G3, there was 100% agreement, (kappa=0.64, overall). Retrospective review of discordant G3 cases revealed cases with known metastasis, small fragments of tissue, or polyps. Scanning and scoring required approximately 10 minutes per case. Conclusion Our data shows the time/effort difference of visually estimating versus automated digital analysis may lead to significant classification errors in these tumors. Although digital analysis has limitations, including tumor heterogeneity, misidentification of tumor cells, and poor immunostaining which could require manual counting by a pathologist, this rigor should be reinforced and explicitly stated to increase accuracy and reproducibility of grading.

Automated assessment of Ki‐67 in breast cancer: the utility of digital image analysis using virtual triple staining and whole slide imaging

2020 ◽  
Vol 77 (3) ◽  
pp. 471-480
Author(s):  
Akira I Hida ◽  
Dzenita Omanovic ◽  
Lars Pedersen ◽  
Yumi Oshiro ◽  
Takashi Ogura ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Whole Slide Imaging ◽  
Automated Assessment ◽  
Ki 67 ◽  
Triple Staining

Audit of KI-67 digital image analysis for breast cancer at pathwest QEII

Pathology ◽  
2017 ◽  
Vol 49 ◽  
pp. S63
Author(s):  
Morgan Wang ◽  
C. Thomas ◽  
C. Robinson ◽  
J. Harvey ◽  
G. Sterrett ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Ki 67

scholarly journals Digital Image Analysis of Ki-67 Stained Tissue Microarrays and Recurrence in Tamoxifen-Treated Breast Cancer Patients

2020 ◽  
Vol Volume 12 ◽  
pp. 771-781
Author(s):  
Nina Gran Egeland ◽  
Kristin Jonsdottir ◽  
Kristina Lystlund Lauridsen ◽  
Ivar Skaland ◽  
Cathrine F Hjorth ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Cancer Patients ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Tissue Microarrays ◽  
Breast Cancer Patients ◽  
Ki 67 ◽  
Treated Breast ◽  
Treated Breast Cancer

Inter-laboratory comparison of Ki-67 proliferating index detected by visual assessment and automated digital image analysis

2019 ◽  
Vol 38 (2) ◽  
pp. 73-79
Author(s):  
Snježana Tomić ◽  
Ivana Mrklić ◽  
Jasminka Jakić Razumović ◽  
Nives Jonjić ◽  
Božena Šarčević ◽  
...  
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Visual Assessment ◽  
Ki 67

scholarly journals Comparison of digital image analysis and visual scoring of KI-67 in prostate cancer prognosis after prostatectomy

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Patrice Desmeules ◽  
Hélène Hovington ◽  
Molière Nguilé-Makao ◽  
Caroline Léger ◽  
André Caron ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Cancer Prognosis ◽  
Ki 67 ◽  
Visual Scoring ◽  
Prostate Cancer Prognosis

scholarly journals Effects of tissue decalcification on the quantification of breast cancer biomarkers by digital image analysis

2014 ◽  
Vol 9 (1) ◽  
Author(s):  
Arkadiusz Gertych ◽  
Sonia Mohan ◽  
Shawn Maclary ◽  
Sambit Mohanty ◽  
Kolja Wawrowsky ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Cancer Biomarkers ◽  
Breast Cancer Biomarkers
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