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Comparison of Ki-67 labeling index measurements using digital image analysis and scoring by pathologists
Toru Morioka1, Naoki Niikura2, Nobue Kumaki3
1Department of Breast and Endocrine Surgery, Tokai University School of Medicine, Kanagawa, Japan.
Insights
Digital image analysis for Ki-67 (a cell proliferation marker) shows moderate correlation with pathologist scoring and predicts relapse-free survival in early-stage breast cancer patients.
Area of Science:
- Oncology
- Pathology
- Biomedical Engineering
Background:
- Routine Ki-67 analysis lacks reproducibility, hindering clinical decision-making.
- Manual cell counting for Ki-67 is time-consuming for pathologists.
- The clinical utility of digital image analysis for Ki-67 remains largely unestablished.
Purpose of the Study:
- To evaluate the reproducibility and clinical efficacy of Ki-67 indices derived from digital image analysis.
- To compare Ki-67 scoring by digital image analysis with traditional pathologist scoring.
- To assess the association between digital image analysis-derived Ki-67 indices and patient survival outcomes.
Main Methods:
- Retrospective analysis of breast cancer patients with available Ki-67 immunohistochemistry and survival data.
- Ki-67 scoring by three pathologists and subsequent digital image analysis of scanned slides.
- Comparison of pathologist and image analysis scores using 2x2 analysis.
- Survival analysis using Kaplan-Meier method and log-rank test.
Main Results:
- Image analysis Ki-67 indices demonstrated moderate correlation with pathologist scores (κ=0.41).
- High Ki-67 index, by both methods, was significantly associated with poorer relapse-free survival in specific patient subgroups.
- Digital image analysis showed moderate correlation with pathologist scoring (κ=0.41; sensitivity=0.573; specificity=0.878).
Conclusions:
- Digital image analysis provides a reproducible method for Ki-67 index determination.
- Image analysis-derived Ki-67 indices are clinically relevant, correlating with survival outcomes.
- Digital image analysis is a viable tool for Ki-67 assessment in ER+, HER2-, Stage I/II breast cancer, aiding clinical decisions.
Background:
Routine analysis of Ki-67 is not widely recommended for clinical decision-making because of poor reproducibility. Furthermore, counting numerous cells can be laborious for pathologists. Digital image analysis for immunohistochemical analysis was recently developed; however, the clinical efficacy of the Ki-67 index obtained using image analysis is unknown.
Methods:
We retrospectively identified female patients with breast cancer with immunohistochemical Ki-67 and survival data using the pathology database at the Tokai University, Japan. Ki-67 expression was scored by three pathologists. Slides were scanned and converted to virtual slides; Ki-67-positive cells were counted using image analysis. Ki-67 indices obtained by the pathologist's scoring and image analysis were evaluated by 2 × 2 analysis. Relationships between Ki-67 index and survival outcomes were evaluated using the Kaplan-Meier method and compared using the log-rank test.
Results:
Based on the 2 × 2 analysis, Ki-67 index obtained using image analysis was moderately correlated with the pathologist's scoring for all patients (κ 0.41; sensitivity, 0.573; specificity, 0.878). Poorer relapse-free survival was associated with high Ki-67 index than with low Ki-67 index for estrogen receptor-positive, human epidermal growth factor receptor 2-negative, and stage I or II patients scored by pathologists (p < 0.001) and obtained using image analysis (p = 0.031).
Conclusions:
The Ki-67 indices obtained using image analysis were moderately correlated with those scored by pathologists. Digital image analysis can be effective for measuring Ki-67 values, because they are associated with relapse-free survival in estrogen receptor-positive, human epidermal growth factor receptor 2-negative, and patients at stage I or II.
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