Top

Published in:

Open Access 01-12-2016 | Research

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

Authors: Anthony E. Rizzardi, Xiaotun Zhang, Rachel Isaksson Vogel, Suzanne Kolb, Milan S. Geybels, Yuet-Kin Leung, Jonathan C. Henriksen, Shuk-Mei Ho, Julianna Kwak, Janet L. Stanford, Stephen C. Schmechel

Published in: Diagnostic Pathology | Issue 1/2016

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.

Available only for authorised users

Rimm DL. What brown cannot do for you. Nat Biotechnol. 2006;24(8):914–6. doi:10.1038/nbt0806-914.CrossRefPubMed

Rimm DL, Giltnane JM, Moeder C, Harigopal M, Chung GG, Camp RL, et al. Bimodal population or pathologist artifact? J Clin Oncol Off J Am Soc Clin Oncol. 2007;25(17):2487–8. doi:10.1200/JCO.2006.07.7537.CrossRef

Weaver DL, Krag DN, Manna EA, Ashikaga T, Harlow SP, Bauer KD. Comparison of pathologist-detected and automated computer-assisted image analysis detected sentinel lymph node micrometastases in breast cancer. Mod Pathol. 2003;16(11):1159–63. doi:10.1097/01.MP.0000092952.21794.AD.CrossRefPubMed

Jaraj SJ, Camparo P, Boyle H, Germain F, Nilsson B, Petersson F, et al. Intra- and interobserver reproducibility of interpretation of immunohistochemical stains of prostate cancer. Virchows Arch. 2009;455(4):375–81. doi:10.1007/s00428-009-0833-8.CrossRefPubMed

Bloom K, Harrington D. Enhanced accuracy and reliability of HER-2/neu immunohistochemical scoring using digital microscopy. Am J Clin Pathol. 2004;121(5):620–30. doi:10.1309/Y73U-8X72-B68T-MGH5.CrossRefPubMed

Gavrielides MA, Gallas BD, Lenz P, Badano A, Hewitt SM. Observer variability in the interpretation of HER2/neu immunohistochemical expression with unaided and computer-aided digital microscopy. Arch Pathol Lab Med. 2011;135(2):233–42. doi:10.1043/1543-2165-135.2.233.PubMed

Harigopal M, Barlow WE, Tedeschi G, Porter PL, Yeh IT, Haskell C, et al. Multiplexed assessment of the Southwest Oncology Group-directed Intergroup Breast Cancer Trial S9313 by AQUA shows that both high and low levels of HER2 are associated with poor outcome. Am J Pathol. 2010;176(4):1639–47. doi:10.2353/ajpath.2010.090711.CrossRefPubMedPubMedCentral

Atkinson R, Mollerup J, Laenkholm AV, Verardo M, Hawes D, Commins D, et al. Effects of the change in cutoff values for human epidermal growth factor receptor 2 status by immunohistochemistry and fluorescence in situ hybridization: a study comparing conventional brightfield microscopy, image analysis-assisted microscopy, and interobserver variation. Arch Pathol Lab Med. 2011;135(8):1010–6. doi:10.5858/2010-0462-OAR.CrossRefPubMed

Camp RL, Dolled-Filhart M, King BL, Rimm DL. Quantitative analysis of breast cancer tissue microarrays shows that both high and normal levels of HER2 expression are associated with poor outcome. Cancer Res. 2003;63(7):1445–8.PubMed

10.

Feuchtinger A, Stiehler T, Jutting U, Marjanovic G, Luber B, Langer R, et al. Image analysis of immunohistochemistry is superior to visual scoring as shown for patient outcome of esophageal adenocarcinoma. Histochem Cell Biol. 2014. doi:10.1007/s00418-014-1258-2.

11.

Rizzardi AE, Johnson AT, Vogel RI, Pambuccian SE, Henriksen J, Skubitz AP, et al. Quantitative comparison of immunohistochemical staining measured by digital image analysis versus pathologist visual scoring. Diagn Pathol. 2012;7:42. doi:10.1186/1746-1596-7-42.CrossRefPubMedPubMedCentral

12.

Bolton KL, Garcia-Closas M, Pfeiffer RM, Duggan MA, Howat WJ, Hewitt SM, et al. Assessment of automated image analysis of breast cancer tissue microarrays for epidemiologic studies. Cancer Epidemiol Biomark Prev. 2010;19(4):992–9. doi:10.1158/1055-9965.EPI-09-1023.CrossRef

13.

Brugmann A, Eld M, Lelkaitis G, Nielsen S, Grunkin M, Hansen JD, et al. Digital image analysis of membrane connectivity is a robust measure of HER2 immunostains. Breast Cancer Res Treat. 2012;132(1):41–9. doi:10.1007/s10549-011-1514-2.CrossRefPubMed

14.

Chosidow O, Bagot M, Vernant JP, Roujeau JC, Cordonnier C, Kuentz M, et al. Sclerodermatous chronic graft-versus-host disease. Analysis of seven cases. J Am Acad Dermatol. 1992;26(1):49–55.CrossRefPubMed

15.

Faratian D, Kay C, Robson T, Campbell FM, Grant M, Rea D, et al. Automated image analysis for high-throughput quantitative detection of ER and PR expression levels in large-scale clinical studies: the TEAM Trial Experience. Histopathology. 2009;55(5):587–93. doi:10.1111/j.1365-2559.2009.03419.x.CrossRefPubMed

16.

Gokhale S, Rosen D, Sneige N, Diaz LK, Resetkova E, Sahin A, et al. Assessment of two automated imaging systems in evaluating estrogen receptor status in breast carcinoma. Appl Immunohistochem Mol Morphol. 2007;15(4):451–5. doi:10.1097/PAI.0b013e31802ee998.CrossRefPubMed

17.

Krecsak L, Micsik T, Kiszler G, Krenacs T, Szabo D, Jonas V, et al. Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer. Diagn Pathol. 2011;6:6. doi:10.1186/1746-1596-6-6.CrossRefPubMedPubMedCentral

18.

Laurinaviciene A, Dasevicius D, Ostapenko V, Jarmalaite S, Lazutka J, Laurinavicius A. Membrane connectivity estimated by digital image analysis of HER2 immunohistochemistry is concordant with visual scoring and fluorescence in situ hybridization results: algorithm evaluation on breast cancer tissue microarrays. Diagn Pathol. 2011;6:87. doi:10.1186/1746-1596-6-87.CrossRefPubMedPubMedCentral

19.

Masmoudi H, Hewitt SM, Petrick N, Myers KJ, Gavrielides MA. Automated quantitative assessment of HER-2/neu immunohistochemical expression in breast cancer. IEEE Trans Med Imaging. 2009;28(6):916–25. doi:10.1109/TMI.2009.2012901.CrossRefPubMed

20.

Skaland I, Ovestad I, Janssen EA, Klos J, Kjellevold KH, Helliesen T, et al. Comparing subjective and digital image analysis HER2/neu expression scores with conventional and modified FISH scores in breast cancer. J Clin Pathol. 2008;61(1):68–71. doi:10.1136/jcp.2007.046763.CrossRefPubMed

21.

Turashvili G, Leung S, Turbin D, Montgomery K, Gilks B, West R, et al. Inter-observer reproducibility of HER2 immunohistochemical assessment and concordance with fluorescent in situ hybridization (FISH): pathologist assessment compared to quantitative image analysis. BMC Cancer. 2009;9:165. doi:10.1186/1471-2407-9-165.CrossRefPubMedPubMedCentral

22.

Turbin DA, Leung S, Cheang MC, Kennecke HA, Montgomery KD, McKinney S, et al. Automated quantitative analysis of estrogen receptor expression in breast carcinoma does not differ from expert pathologist scoring: a tissue microarray study of 3,484 cases. Breast Cancer Res Treat. 2008;110(3):417–26. doi:10.1007/s10549-007-9736-z.CrossRefPubMed

23.

Alexander BM, Wang XZ, Niemierko A, Weaver DT, Mak RH, Roof KS, et al. DNA repair biomarkers predict response to neoadjuvant chemoradiotherapy in esophageal cancer. Int J Radiat Oncol Biol Phys. 2012;83(1):164–71. doi:10.1016/j.ijrobp.2011.05.033.CrossRefPubMed

24.

Messersmith W, Oppenheimer D, Peralba J, Sebastiani V, Amador M, Jimeno A, et al. Assessment of Epidermal Growth Factor Receptor (EGFR) signaling in paired colorectal cancer and normal colon tissue samples using computer-aided immunohistochemical analysis. Cancer Biol Ther. 2005;4(12):1381–6.CrossRefPubMed

25.

Braun M, Kirsten R, Rupp NJ, Moch H, Fend F, Wernert N, et al. Quantification of protein expression in cells and cellular subcompartments on immunohistochemical sections using a computer supported image analysis system. Histol Histopathol. 2013;28(5):605–10.PubMed

26.

Allred DC, Clark GM, Elledge R, Fuqua SA, Brown RW, Chamness GC, et al. Association of p53 protein expression with tumor cell proliferation rate and clinical outcome in node-negative breast cancer. J Natl Cancer Inst. 1993;85(3):200–6.CrossRefPubMed

27.

FitzGerald LM, Zhang X, Kolb S, Kwon EM, Liew YC, Hurtado-Coll A, et al. Investigation of the relationship between prostate cancer and MSMB and NCOA4 genetic variants and protein expression. Hum Mutat. 2013;34(1):149–56. doi:10.1002/humu.22176.CrossRefPubMed

28.

Rizzardi AE, Rosener NK, Koopmeiners JS, Isaksson Vogel R, Metzger GJ, Forster CL, et al. Evaluation of protein biomarkers of prostate cancer aggressiveness. BMC Cancer. 2014;14:244. doi:10.1186/1471-2407-14-244.CrossRefPubMedPubMedCentral

29.

Leung YK, Lam HM, Wu S, Song D, Levin L, Cheng L, et al. Estrogen receptor beta2 and beta5 are associated with poor prognosis in prostate cancer, and promote cancer cell migration and invasion. Endocr Relat Cancer. 2010;17(3):675–89. doi:10.1677/ERC-09-0294.CrossRefPubMedPubMedCentral

30.

Schade GR, Holt SK, Zhang X, Song D, Wright JL, Zhao S, et al. Prostate cancer expression profiles of cytoplasmic ERbeta1 and nuclear ERbeta2 are associated with poor outcomes following radical prostatectomy. J Urol. 2016. doi:10.1016/j.juro.2015.12.101.

31.

Agalliu I, Salinas CA, Hansten PD, Ostrander EA, Stanford JL. Statin use and risk of prostate cancer: results from a population-based epidemiologic study. Am J Epidemiol. 2008;168(3):250–60. doi:10.1093/aje/kwn141.CrossRefPubMedPubMedCentral

32.

Stanford JL, Wicklund KG, McKnight B, Daling JR, Brawer MK. Vasectomy and risk of prostate cancer. Cancer Epidemiol Biomark Prev. 1999;8(10):881–6.

33.

Rizzardi AE, Vogel RI, Koopmeiners JS, Forster CL, Marston LO, Rosener NK, et al. Elevated hyaluronan and hyaluronan-mediated motility receptor are associated with biochemical failure in patients with intermediate-grade prostate tumors. Cancer. 2014;120(12):1800–9. doi:10.1002/cncr.28646.CrossRefPubMedPubMedCentral

34.

Krajewska M, Smith LH, Rong J, Huang X, Hyer ML, Zeps N, et al. Image analysis algorithms for immunohistochemical assessment of cell death events and fibrosis in tissue sections. J Histochem Cytochem. 2009;57(7):649–63. doi:10.1369/jhc.2009.952812.CrossRefPubMedPubMedCentral

35.

Borlot VF, Biasoli I, Schaffel R, Azambuja D, Milito C, Luiz RR, et al. Evaluation of intra- and interobserver agreement and its clinical significance for scoring bcl-2 immunohistochemical expression in diffuse large B-cell lymphoma. Pathol Int. 2008;58(9):596–600. doi:10.1111/j.1440-1827.2008.02276.x.CrossRefPubMed

36.

Ong CW, Kim LG, Kong HH, Low LY, Wang TT, Supriya S, et al. Computer-assisted pathological immunohistochemistry scoring is more time-effective than conventional scoring, but provides no analytical advantage. Histopathology. 2010;56(4):523–9. doi:10.1111/j.1365-2559.2010.03496.x.CrossRefPubMed

37.

Tzeng CH, Chen PM, Chuang MW, Liu JH, Hsieh RK, Liu CJ, et al. Treatment of severe aplastic anemia: comparison of bone marrow transplantation to immunotherapy. Zhonghua Yi Xue Za Zhi (Taipei). 1989;43(1):21–8.

38.

Moeder CB, Giltnane JM, Harigopal M, Molinaro A, Robinson A, Gelmon K, et al. Quantitative justification of the change from 10 to 30% for human epidermal growth factor receptor 2 scoring in the American Society of Clinical Oncology/College of American Pathologists guidelines: tumor heterogeneity in breast cancer and its implications for tissue microarray based assessment of outcome. J Clin Oncol. 2007;25(34):5418–25. doi:10.1200/JCO.2007.12.8033.CrossRefPubMed

39.

Shipitsin M, Small C, Choudhury S, Giladi E, Friedlander S, Nardone J, et al. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. Br J Cancer. 2014;111(6):1201–12. doi:10.1038/bjc.2014.396.CrossRefPubMedPubMedCentral

40.

Shipitsin M, Small C, Giladi E, Siddiqui S, Choudhury S, Hussain S, et al. Automated quantitative multiplex immunofluorescence in situ imaging identifies phospho-S6 and phospho-PRAS40 as predictive protein biomarkers for prostate cancer lethality. Proteome Sci. 2014;12:40. doi:10.1186/1477-5956-12-40.CrossRefPubMedPubMedCentral

41.

Widmer DS, Hoek KS, Cheng PF, Eichhoff OM, Biedermann T, Raaijmakers MI, et al. Hypoxia contributes to melanoma heterogeneity by triggering HIF1alpha-dependent phenotype switching. J Invest Dermatol. 2013;133(10):2436–43. doi:10.1038/jid.2013.115.CrossRefPubMed

42.

Avoranta ST, Korkeila EA, Syrjanen KJ, Pyrhonen SO, Sundstrom JT. Lack of CD44 variant 6 expression in rectal cancer invasive front associates with early recurrence. World J Gastroenterol. 2012;18(33):4549–56. doi:10.3748/wjg.v18.i33.4549.CrossRefPubMedPubMedCentral

43.

Chung GG, Zerkowski MP, Ghosh S, Camp RL, Rimm DL. Quantitative analysis of estrogen receptor heterogeneity in breast cancer. Lab Invest. 2007;87(7):662–9. doi:10.1038/labinvest.3700543.CrossRefPubMed

44.

McCabe A, Dolled-Filhart M, Camp RL, Rimm DL. Automated quantitative analysis (AQUA) of in situ protein expression, antibody concentration, and prognosis. J Natl Cancer Inst. 2005;97(24):1808–15. doi:10.1093/jnci/dji427.CrossRefPubMed

45.

Desmeules P, Hovington H, Nguile-Makao M, Leger C, Caron A, Lacombe L, et al. Comparison of digital image analysis and visual scoring of KI-67 in prostate cancer prognosis after prostatectomy. Diagn Pathol. 2015;10:67. doi:10.1186/s13000-015-0294-0.CrossRefPubMedPubMedCentral

46.

Parker AS, Lohse CM, Leibovich BC, Cheville JC, Sheinin YM, Kwon ED. Comparison of digital image analysis versus visual assessment to assess survivin expression as an independent predictor of survival for patients with clear cell renal cell carcinoma. Hum Pathol. 2008;39(8):1176–84. doi:10.1016/j.humpath.2007.12.009.CrossRefPubMedPubMedCentral

Title: Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor β2 immunohistochemistry in prostate cancer
Authors: Anthony E. Rizzardi
Xiaotun Zhang
Rachel Isaksson Vogel
Suzanne Kolb
Milan S. Geybels
Yuet-Kin Leung
Jonathan C. Henriksen
Shuk-Mei Ho
Julianna Kwak
Janet L. Stanford
Stephen C. Schmechel
Publication date: 01-12-2016
Publisher: BioMed Central
Published in: Diagnostic Pathology / Issue 1/2016
Electronic ISSN: 1746-1596
DOI: https://doi.org/10.1186/s13000-016-0511-5

Keynote webinar | Spotlight on medication adherence

Springer Medicine

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

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 1/2016

Primary alveolar rhabdomyosarcoma of the bone: two cases and review of the literature

Retraction Note: Down-regulated microRNA-124 expression as predictive biomarker and its prognostic significance with clinicopathological features in breast cancer patients

Limited independent prognostic value of MMP-14 and MMP-2 expression in ovarian cancer

Case Report: Next generation sequencing identifies a NAB2-STAT6 fusion in Glioblastoma

EZH2 overexpression in different immunophenotypes of breast carcinoma and association with clinicopathologic features

Primary mucinous carcinoma with rhabdoid cells of the thyroid gland: a case report