Development and evaluation of a virtual microscopy application for automated assessment of Ki-67 expression in breast cancer

BMC Clinical Pathology

Johan Lundin¹  Jorma Isola⁷  Liisa Sailas⁶  Vesa Kataja⁴  Taina Turpeenniemi-Hujanen²  Kaija Holli⁵  Harri Sihto³  Tiina Lehtimäki⁸  Heikki Joensuu³  Mikael Lundin⁸  Juho Konsti⁸ 

[1]Division of Global Health, Karolinska Institutet, Stockholm, Sweden

[2]Department of Oncology and Radiotherapy, Oulu University Central Hospital, Oulu, Finland

[3]Molecular and Cancer Biology Research Program, Biomedicum Helsinki, University of Helsinki, Helsinki, Finland

[4]Department of Oncology, Vaasa Central Hospital, Vaasa, Finland

[5]University of Tampere and Department of Oncology, Tampere University Hospital, Tampere, Finland

[6]Department of Oncology, Kuopio University Hospital, Kuopio, Finland

[7]Institute of Medical Technology, University of Tampere, Tampere, Finland

[8]FIMM - Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland

Others  :  1085642
DOI  :  10.1186/1472-6890-11-3

 received in 2010-07-23, accepted in 2011-01-25,  发布年份 2011

【 摘 要 】

Background

The aim of the study was to develop a virtual microscopy enabled method for assessment of Ki-67 expression and to study the prognostic value of the automated analysis in a comprehensive series of patients with breast cancer.

Methods

Using a previously reported virtual microscopy platform and an open source image processing tool, ImageJ, a method for assessment of immunohistochemically (IHC) stained area and intensity was created. A tissue microarray (TMA) series of breast cancer specimens from 1931 patients was immunostained for Ki-67, digitized with a whole slide scanner and uploaded to an image web server. The extent of Ki-67 staining in the tumour specimens was assessed both visually and with the image analysis algorithm. The prognostic value of the computer vision assessment of Ki-67 was evaluated by comparison of distant disease-free survival in patients with low, moderate or high expression of the protein.

Results

1648 evaluable image files from 1334 patients were analysed in less than two hours. Visual and automated Ki-67 extent of staining assessments showed a percentage agreement of 87% and weighted kappa value of 0.57. The hazard ratio for distant recurrence for patients with a computer determined moderate Ki-67 extent of staining was 1.77 (95% CI 1.31-2.37) and for high extent 2.34 (95% CI 1.76-3.10), compared to patients with a low extent. In multivariate survival analyses, automated assessment of Ki-67 extent of staining was retained as a significant prognostic factor.

Conclusions

Running high-throughput automated IHC algorithms on a virtual microscopy platform is feasible. Comparison of visual and automated assessments of Ki-67 expression shows moderate agreement. In multivariate survival analysis, the automated assessment of Ki-67 extent of staining is a significant and independent predictor of outcome in breast cancer.

【 授权许可】

   
2011 Konsti et al; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

【 参考文献 】

• [1]Bloom K, Harrington D: Enhanced accuracy and reliability of HER-2/neu immunohistochemical scoring using digital microscopy. Am J Clin Pathol 2004, 121:620-630.
• [2]Camp RL, Chung GG, Rimm DL: Automated subcellular localization and quantification of protein expression in tissue microarrays. Nat Med 2002, 8:1323-1327.
• [3]Chen W, Reiss M, Foran DJ: A prototype for unsupervised analysis of tissue microarrays for cancer research and diagnostics. IEEE Trans Inf Technol Biomed 2004, 8:89-96.
• [4]Chung GG, Zerkowski MP, Ghosh S, Camp RL, Rimm DL: Quantitative analysis of estrogen receptor heterogeneity in breast cancer. Lab Invest 2007, 87:662-669.
• [5]Corletto V, Verderio P, Giardini R, Cipriani S, Di Palma S, Rilke F: Evaluation of residual cellularity and proliferation on preoperatively treated breast cancer: a comparison between image analysis and light microscopy analysis. Anal Cell Pathol 1998, 16:83-93.
• [6]Kolles H, Forderer W, Bock R, Feiden W: Combined Ki-67 and Feulgen stain for morphometric determination of the Ki-67 labelling index. Histochemistry 1993, 100:293-296.
• [7]Layfield LJ, Saria EA, Conlon DH, Kerns BJ: Estrogen and progesterone receptor status determined by the Ventana ES 320 automated immunohistochemical stainer and the CAS 200 image analyzer in 236 early-stage breast carcinomas: prognostic significance. J Surg Oncol 1996, 61:177-184.
• [8]Lehr HA, Hansen DA, Kussick S, Li M, Hwang H, Krummenauer F, Trouet S, Gown AM: Assessment of proliferative activity in breast cancer: MIB-1 immunohistochemistry versus mitotic figure count. Hum Pathol 1999, 30:1314-1320.
• [9]Pietilainen T, Lipponen P, Aaltomaa S, Eskelinen M, Kosma VM, Syrjanen K: The important prognostic value of Ki-67 expression as determined by image analysis in breast cancer. J Cancer Res Clin 1996, 122:687-692.
• [10]Pinder SE, Wencyk P, Sibbering DM, Bell JA, Elston CW, Nicholson R, Robertson JF, Blamey RW, Ellis IO: Assessment of the new proliferation marker MIB1 in breast carcinoma using image analysis: associations with other prognostic factors and survival. Br J Cancer 1995, 71:146-149.
• [11]Querzoli P, Albonico G, Ferretti S, Rinaldi R, Magri E, Indelli M, Nenci I: MIB-1 proliferative activity in invasive breast cancer measured by image analysis. Journal of Clinical Pathology 1996, 49:926-930.
• [12]Querzoli P, Ferretti S, Albonico G, Magri E, Scapoli D, Indelli M, Nenci I: Application of Quantitative-Analysis to Biologic Profile Evaluation in Breast-Cancer. Cancer 1995, 76:2510-2517.
• [13]Stromberg S, Bjorklund MG, Asplund C, Skollermo A, Persson A, Wester K, Kampf C, Nilsson P, Andersson AC, Uhlen M, et al.: A high-throughput strategy for protein profiling in cell microarrays using automated image analysis. Proteomics 2007, 7:2142-2150.
• [14]Sullivan CA, Ghosh S, Ocal IT, Camp RL, Rimm DL, Chung GG: Microvessel area using automated image analysis is reproducible and is associated with prognosis in breast cancer. Hum Pathol 2009, 40:156-165.
• [15]Turashvili G, Leung S, Turbin D, Montgomery K, Gilks B, West R, Carrier M, Huntsman D, Aparicio S: 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. BioMed Central Full Text
• [16]Turbin DA, Leung S, Cheang MC, Kennecke HA, Montgomery KD, McKinney S, Treaba DO, Boyd N, Goldstein LC, Badve 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, 110:417-426.
• [17]Tuominen VJ, Ruotoistenmaki S, Viitanen A, Jumppanen M, Isola J: ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67. Breast Cancer Res 2010, 12:R56. BioMed Central Full Text
• [18]Kononen J, Bubendorf L, Kallioniemi A, Barlund M, Schraml P, Leighton S, Torhorst J, Mihatsch MJ, Sauter G, Kallioniemi OP: Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat Med 1998, 4:844-847.
• [19]de Azambuja E, Cardoso F, de Castro G Jr, Colozza M, Mano MS, Durbecq V, Sotiriou C, Larsimont D, Piccart-Gebhart MJ, Paesmans M: Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12,155 patients. Br J Cancer 2007, 96:1504-1513.
• [20]Domagala W, Markiewski M, Harezga B, Dukowicz A, Osborn M: Prognostic significance of tumor cell proliferation rate as determined by the MIB-1 antibody in breast carcinoma: its relationship with vimentin and p53 protein. Clin Cancer Res 1996, 2:147-154.
• [21]Rudolph P, Olsson H, Bonatz G, Ratjen V, Bolte H, Baldetorp B, Ferno M, Parwaresch R, Alm P: Correlation between p53, c-erbB-2, and topoisomerase II alpha expression, DNA ploidy, hormonal receptor status and proliferation in 356 node-negative breast carcinomas: Prognostic implications. J Pathol 1999, 187:207-216.
• [22]Stuart-Harris R, Caldas C, Pinder SE, Pharoah P: Proliferation markers and survival in early breast cancer: a systematic review and meta-analysis of 85 studies in 32,825 patients. Breast 2008, 17:323-334.
• [23]Lundin M, Lundin J, Helin H, Isola J: A digital atlas of breast histopathology: an application of web based virtual microscopy. J Clin Pathol 2004, 57:1288-1291.
• [24]Joensuu H, Lehtimaki T, Holli K, Elomaa L, Turpeenniemi-Hujanen T, Kataja V, Anttila A, Lundin M, Isola J, Lundin J: Risk for distant recurrence of breast cancer detected by mammography screening or other methods. JAMA 2004, 292:1064-1073.
• [25]Sihto H, Lundin J, Lehtimaki T, Sarlomo-Rikala M, Butzow R, Holli K, Sailas L, Kataja V, Lundin M, Turpeenniemi-Hujanen T, et al.: Molecular subtypes of breast cancers detected in mammography screening and outside of screening. Clin Cancer Res 2008, 14:4103-4110.
• [26]Konsti J, Lundin J, Jumppanen M, Lundin M, Viitanen A, Isola J: A public-domain image processing tool for automated quantification of fluorescence in situ hybridisation signals. J Clin Pathol 2008, 61:278-282.
• [27]Ruifrok AC, Johnston DA: Quantification of histochemical staining by color deconvolution. Anal Quant Cytol Histol 2001, 23:291-299.
• [28]Cohen J: Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychol Bull 1968, 70:213-220.
• [29]Ahlin C, Aaltonen K, Amini RM, Nevanlinna H, Fjallskog ML, Blomqvist C: Ki67 and cyclin A as prognostic factors in early breast cancer. What are the optimal cut-off values? Histopathology 2007, 51:491-498.
• [30]Fritz P, Wu X, Tuczek H, Multhaupt H, Schwarzmann P: Quantitation in immunohistochemistry. A research method or a diagnostic tool in surgical pathology? Pathologica 1995, 87:300-309.
• [31]Sapino A, Marchio C, Senetta R, Castellano I, Macri L, Cassoni P, Ghisolfl G, Cerrato M, D'Ambrosio E, Bussolati G: Routine assessment of prognostic factors in breast cancer using a multicore tissue microarray procedure. Virchows Arch 2006, 449:288-296.
• [32]Klintman M, Bendahl PO, Grabau D, Lovgren K, Malmstrom P, Ferno M: The prognostic value of Ki67 is dependent on estrogen receptor status and histological grade in premenopausal patients with node-negative breast cancer. Mod Pathol 2010, 23:251-259.
• [33]Faratian D, Munro A, Twelves C, Bartlett JM: Membranous and cytoplasmic staining of Ki67 is associated with HER2 and ER status in invasive breast carcinoma. Histopathology 2009, 54:254-257.