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Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor β2 immunohistochemistry in prostate cancer.

Rizzardi AE, Zhang X, Vogel RI, Kolb S, Geybels MS, Leung YK, Henriksen JC, Ho SM, Kwak J, Stanford JL, Schmechel SC - Diagn Pathol (2016)

Bottom Line: Two independent analysis runs were performed to evaluate reproducibility.For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99).After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012).

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology, University of Washington, 908 Jefferson Street, Room 2NJB244, Seattle, WA, 98104, USA.

ABSTRACT

Background: Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-β2 (ERβ2).

Methods: Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERβ2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy.

Results: We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERβ2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02-4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20-5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70-15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012).

Conclusions: Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.

No MeSH data available.


Related in: MedlinePlus

Correlation between digital image analysis and pathologist visual scoring of tumor cytoplasm. Scatter plots of cytoplasmic data generated using digital image analysis (AvgCytoOD*%PosCyto) versus pathologist visual scores. Data were averaged across tissue microarray replicates for each patient for Analysis Run A (left) and Analysis Run B (right)
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Fig3: Correlation between digital image analysis and pathologist visual scoring of tumor cytoplasm. Scatter plots of cytoplasmic data generated using digital image analysis (AvgCytoOD*%PosCyto) versus pathologist visual scores. Data were averaged across tissue microarray replicates for each patient for Analysis Run A (left) and Analysis Run B (right)

Mentions: Patients were represented in duplicate on the TMAs. Therefore we first compared the correlation of patient replicates to each other (within an Analysis Run). As shown in Table 1, the correlations between replicates were similar for both Analysis Runs A and B, and were higher for digital IHC measures (0.84 and 0.84 in tumor cytoplasmic areas in Analysis Runs A and B, respectively; and 0.85 and 0.84 in tumor nuclear areas in Analysis Runs A and B, respectively) compared to pathologist scores (0.72 and 0.71 in tumor cytoplasmic areas in Analysis Runs A and B, respectively; and 0.64 and 0.62 in tumor nuclear areas in Analysis Runs A and B, respectively). Both methods had relatively high correlation, indicating that replicates within a patient were similar. Since IHC evaluation is often performed for linking to outcome data on a per-patient level, these high correlations provided a rationale for averaging patient data together when comparing quantification methods. When quantification methods were directly compared (patient replicates averaged together), there was a weak/moderate correlation between digital IHC measures and pathology scores of tumor nuclei (Analysis Run A: 0.42 (0.34–0.49), p < 0.0001; and Analysis Run B: 0.41 (0.34–0.48), p < 0.0001; Fig. 2), and a moderate/strong correlation between digital IHC measures and pathology scores of tumor cytoplasm (Analysis Run A: 0.70 (0.65–0.74), p < 0.0001; and Analysis Run B: 0.69 (0.64–0.74), p < 0.0001; Fig. 3).Table 1


Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor β2 immunohistochemistry in prostate cancer.

Rizzardi AE, Zhang X, Vogel RI, Kolb S, Geybels MS, Leung YK, Henriksen JC, Ho SM, Kwak J, Stanford JL, Schmechel SC - Diagn Pathol (2016)

Correlation between digital image analysis and pathologist visual scoring of tumor cytoplasm. Scatter plots of cytoplasmic data generated using digital image analysis (AvgCytoOD*%PosCyto) versus pathologist visual scores. Data were averaged across tissue microarray replicates for each patient for Analysis Run A (left) and Analysis Run B (right)
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Related In: Results  -  Collection

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Fig3: Correlation between digital image analysis and pathologist visual scoring of tumor cytoplasm. Scatter plots of cytoplasmic data generated using digital image analysis (AvgCytoOD*%PosCyto) versus pathologist visual scores. Data were averaged across tissue microarray replicates for each patient for Analysis Run A (left) and Analysis Run B (right)
Mentions: Patients were represented in duplicate on the TMAs. Therefore we first compared the correlation of patient replicates to each other (within an Analysis Run). As shown in Table 1, the correlations between replicates were similar for both Analysis Runs A and B, and were higher for digital IHC measures (0.84 and 0.84 in tumor cytoplasmic areas in Analysis Runs A and B, respectively; and 0.85 and 0.84 in tumor nuclear areas in Analysis Runs A and B, respectively) compared to pathologist scores (0.72 and 0.71 in tumor cytoplasmic areas in Analysis Runs A and B, respectively; and 0.64 and 0.62 in tumor nuclear areas in Analysis Runs A and B, respectively). Both methods had relatively high correlation, indicating that replicates within a patient were similar. Since IHC evaluation is often performed for linking to outcome data on a per-patient level, these high correlations provided a rationale for averaging patient data together when comparing quantification methods. When quantification methods were directly compared (patient replicates averaged together), there was a weak/moderate correlation between digital IHC measures and pathology scores of tumor nuclei (Analysis Run A: 0.42 (0.34–0.49), p < 0.0001; and Analysis Run B: 0.41 (0.34–0.48), p < 0.0001; Fig. 2), and a moderate/strong correlation between digital IHC measures and pathology scores of tumor cytoplasm (Analysis Run A: 0.70 (0.65–0.74), p < 0.0001; and Analysis Run B: 0.69 (0.64–0.74), p < 0.0001; Fig. 3).Table 1

Bottom Line: Two independent analysis runs were performed to evaluate reproducibility.For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99).After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012).

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology, University of Washington, 908 Jefferson Street, Room 2NJB244, Seattle, WA, 98104, USA.

ABSTRACT

Background: Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-β2 (ERβ2).

Methods: Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERβ2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy.

Results: We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERβ2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02-4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20-5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70-15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012).

Conclusions: Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.

No MeSH data available.


Related in: MedlinePlus