Quantitative histological image analyses of reticulin fibers in a myelofibrotic mouse
Main Article Content
Keywords
reticulin fibrosis, image analysis, ImageJ, Gata-1low mice
Abstract
Bone marrow (BM) reticulin fibrosis (RF), revealed by silver staining of tissue sections, is associated with myeloproliferative neoplasms, while tools for quantitative assessment of reticulin deposition throughout a femur BM are still in need. Here, we present such a method, allowing via analysis of hundreds of composite images to identify a patchy nature of RF throughout the BM during disease progression in a mouse model of myelofibrosis. To this end, initial conversion of silver stained BM color images into binary images identified two limitations: variable color, owing to polychromatic staining of reticulin fibers, and variable background in different sections of the same batch, limiting application of the color deconvolution method, and use of constant threshold, respectively. By blind coding image identities, to allow for threshold input (still within a narrow range), and using shape filtering to further eliminate background we were able to quantitate RF in myelofibrotic Gata-1low (experimental) and wild type (control) mice as a function of animal age. Color images spanning the whole femur BM were batch-analyzed using ImageJ software, aided by our two newly added macros. The results show heterogeneous RF density in different areas of the marrow of Gata-1low mice, with degrees of heterogeneity reduced upon aging. This method can be applied uniformly across laboratories in studies assessing RF remodeling induced by aging or other conditions in animal models.
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References
1. Vardiman, J.W., et al., The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood, 2009. 114(5): p. 937-51.
2. Tefferi, A. and W. Vainchenker, Myeloproliferative neoplasms: molecular pathophysiology, essential clinical understanding, and treatment strategies. J Clin Oncol, 2011. 29(5): p. 573-82.
3. James, C., et al., A unique clonal JAK2 mutation leading to constitutive signalling causes polycythaemia vera. Nature, 2005. 434(7037): p. 1144-8.
4. Kralovics, R., et al., A gain-of-function mutation of JAK2 in myeloproliferative disorders. N Engl J Med, 2005. 352(17): p. 1779-90.
5. Zhao, R., et al., Identification of an acquired JAK2 mutation in polycythemia vera. J Biol Chem, 2005. 280(24): p. 22788-92.
6. Vannucchi, A.M., et al., Abnormalities of GATA-1 in megakaryocytes from patients with idiopathic myelofibrosis. Am J Pathol, 2005. 167(3): p. 849-58.
7. Achison, M., et al., Integrin-independent tyrosine phosphorylation of p125(fak) in human platelets stimulated by collagen. J Biol Chem, 2001. 276(5): p. 3167-74.
8. Mullally, A., et al., Physiological Jak2V617F expression causes a lethal myeloproliferative neoplasm with differential effects on hematopoietic stem and progenitor cells. Cancer Cell, 2010. 17(6): p. 584-96.
9. Hobbs, C.M., et al., JAK2V617F leads to intrinsic changes in platelet formation and reactivity in a knock-in mouse model of essential thrombocythemia. Blood, 2013. 122(23): p. 3787-97.
10. Vannucchi, A.M., et al., Development of myelofibrosis in mice genetically impaired for GATA-1 expression (GATA-1(low) mice). Blood, 2002. 100(4): p. 1123-32.
11. Gomori, G., Silver Impregnation of Reticulum in Paraffin Sections. Am J Pathol, 1937. 13(6): p. 993-1002 5.
12. Kuter, D.J., et al., Bone marrow fibrosis: pathophysiology and clinical significance of increased bone marrow stromal fibres. Br J Haematol, 2007. 139(3): p. 351-62.
13. Vener, C., et al., Prognostic implications of the European consensus for grading of bone marrow fibrosis in chronic idiopathic myelofibrosis. Blood, 2008. 111(4): p. 1862-5.
14. Teman, C.J., et al., Quantification of fibrosis and osteosclerosis in myeloproliferative neoplasms: a computer-assisted image study. Leuk Res, 2010. 34(7): p. 871-6.
15. Kvasnicka, H.M., et al., Problems and pitfalls in grading of bone marrow fibrosis, collagen deposition and osteosclerosis - a consensus-based study. Histopathology, 2016. 68(6): p. 905-15.
16. Martelli, F., et al., Variegation of the phenotype induced by the Gata1low mutation in mice of different genetic backgrounds. Blood, 2005. 106(13): p. 4102-13.
17. McDevitt, M.A., et al., A "knockdown" mutation created by cis-element gene targeting reveals the dependence of erythroid cell maturation on the level of transcription factor GATA-1. Proc Natl Acad Sci U S A, 1997. 94(13): p. 6781-5.
18. Muntean, A.G., et al., Cyclin D-Cdk4 is regulated by GATA-1 and required for megakaryocyte growth and polyploidization. Blood, 2007. 109(12): p. 5199-207.
19. Eliades, A., et al., Control of megakaryocyte expansion and bone marrow fibrosis by lysyl oxidase. J Biol Chem, 2011. 286(31): p. 27630-8.
20. Schneider, C.A., W.S. Rasband, and K.W. Eliceiri, NIH Image to ImageJ: 25 years of image analysis. Nat Methods, 2012. 9(7): p. 671-5.
21. Hyter, A.J., A Proof of the Conjecture that the Tukey-Kramer Multiple Comparisons Procedure is Conservative. The Annals of Statistics, 1984. 12: p. 61-75.
22. Prasad, K. and G.K. Prabhu, Image analysis tools for evaluation of microscopic views of immunohistochemically stained specimen in medical research-a review. J Med Syst, 2012. 36(4): p. 2621-31.
23. Wagner, T. and H.G. Lipinski, IJBlob: An ImageJ Library for Connected Component Analysis and Shape Analysis. Journal of Open Research Software, 2013. 1: p. e6.
24. Thiele, J., et al., Reticulin fibre content of bone marrow infiltrates of malignant non-Hodgkin's lymphomas (B-cell type, low malignancy)--a morphometric evaluation before and after therapy. Virchows Arch A Pathol Anat Histopathol, 1990. 417(6): p. 485-92.
25. Zingariello, M., et al., Characterization of the TGF-beta1 signaling abnormalities in the Gata1low mouse model of myelofibrosis. Blood, 2013. 121(17): p. 3345-63.
26. Zetterberg, E., et al., Pericyte coverage of abnormal blood vessels in myelofibrotic bone marrows. Haematologica, 2007. 92(5): p. 597-604.
27. Thiele, J., et al., European consensus on grading bone marrow fibrosis and assessment of cellularity. Haematologica, 2005. 90(8): p. 1128-32.
2. Tefferi, A. and W. Vainchenker, Myeloproliferative neoplasms: molecular pathophysiology, essential clinical understanding, and treatment strategies. J Clin Oncol, 2011. 29(5): p. 573-82.
3. James, C., et al., A unique clonal JAK2 mutation leading to constitutive signalling causes polycythaemia vera. Nature, 2005. 434(7037): p. 1144-8.
4. Kralovics, R., et al., A gain-of-function mutation of JAK2 in myeloproliferative disorders. N Engl J Med, 2005. 352(17): p. 1779-90.
5. Zhao, R., et al., Identification of an acquired JAK2 mutation in polycythemia vera. J Biol Chem, 2005. 280(24): p. 22788-92.
6. Vannucchi, A.M., et al., Abnormalities of GATA-1 in megakaryocytes from patients with idiopathic myelofibrosis. Am J Pathol, 2005. 167(3): p. 849-58.
7. Achison, M., et al., Integrin-independent tyrosine phosphorylation of p125(fak) in human platelets stimulated by collagen. J Biol Chem, 2001. 276(5): p. 3167-74.
8. Mullally, A., et al., Physiological Jak2V617F expression causes a lethal myeloproliferative neoplasm with differential effects on hematopoietic stem and progenitor cells. Cancer Cell, 2010. 17(6): p. 584-96.
9. Hobbs, C.M., et al., JAK2V617F leads to intrinsic changes in platelet formation and reactivity in a knock-in mouse model of essential thrombocythemia. Blood, 2013. 122(23): p. 3787-97.
10. Vannucchi, A.M., et al., Development of myelofibrosis in mice genetically impaired for GATA-1 expression (GATA-1(low) mice). Blood, 2002. 100(4): p. 1123-32.
11. Gomori, G., Silver Impregnation of Reticulum in Paraffin Sections. Am J Pathol, 1937. 13(6): p. 993-1002 5.
12. Kuter, D.J., et al., Bone marrow fibrosis: pathophysiology and clinical significance of increased bone marrow stromal fibres. Br J Haematol, 2007. 139(3): p. 351-62.
13. Vener, C., et al., Prognostic implications of the European consensus for grading of bone marrow fibrosis in chronic idiopathic myelofibrosis. Blood, 2008. 111(4): p. 1862-5.
14. Teman, C.J., et al., Quantification of fibrosis and osteosclerosis in myeloproliferative neoplasms: a computer-assisted image study. Leuk Res, 2010. 34(7): p. 871-6.
15. Kvasnicka, H.M., et al., Problems and pitfalls in grading of bone marrow fibrosis, collagen deposition and osteosclerosis - a consensus-based study. Histopathology, 2016. 68(6): p. 905-15.
16. Martelli, F., et al., Variegation of the phenotype induced by the Gata1low mutation in mice of different genetic backgrounds. Blood, 2005. 106(13): p. 4102-13.
17. McDevitt, M.A., et al., A "knockdown" mutation created by cis-element gene targeting reveals the dependence of erythroid cell maturation on the level of transcription factor GATA-1. Proc Natl Acad Sci U S A, 1997. 94(13): p. 6781-5.
18. Muntean, A.G., et al., Cyclin D-Cdk4 is regulated by GATA-1 and required for megakaryocyte growth and polyploidization. Blood, 2007. 109(12): p. 5199-207.
19. Eliades, A., et al., Control of megakaryocyte expansion and bone marrow fibrosis by lysyl oxidase. J Biol Chem, 2011. 286(31): p. 27630-8.
20. Schneider, C.A., W.S. Rasband, and K.W. Eliceiri, NIH Image to ImageJ: 25 years of image analysis. Nat Methods, 2012. 9(7): p. 671-5.
21. Hyter, A.J., A Proof of the Conjecture that the Tukey-Kramer Multiple Comparisons Procedure is Conservative. The Annals of Statistics, 1984. 12: p. 61-75.
22. Prasad, K. and G.K. Prabhu, Image analysis tools for evaluation of microscopic views of immunohistochemically stained specimen in medical research-a review. J Med Syst, 2012. 36(4): p. 2621-31.
23. Wagner, T. and H.G. Lipinski, IJBlob: An ImageJ Library for Connected Component Analysis and Shape Analysis. Journal of Open Research Software, 2013. 1: p. e6.
24. Thiele, J., et al., Reticulin fibre content of bone marrow infiltrates of malignant non-Hodgkin's lymphomas (B-cell type, low malignancy)--a morphometric evaluation before and after therapy. Virchows Arch A Pathol Anat Histopathol, 1990. 417(6): p. 485-92.
25. Zingariello, M., et al., Characterization of the TGF-beta1 signaling abnormalities in the Gata1low mouse model of myelofibrosis. Blood, 2013. 121(17): p. 3345-63.
26. Zetterberg, E., et al., Pericyte coverage of abnormal blood vessels in myelofibrotic bone marrows. Haematologica, 2007. 92(5): p. 597-604.
27. Thiele, J., et al., European consensus on grading bone marrow fibrosis and assessment of cellularity. Haematologica, 2005. 90(8): p. 1128-32.
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Published
Nov 22, 2016
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Lucero HA, Patterson S, Matsuura S, Ravid K. Quantitative histological image analyses of reticulin fibers in a myelofibrotic mouse. J Biol Methods [Internet]. 2016 Nov. 22 [cited 2024 Apr. 20];3(4):e60. Available from: https://jbmethods.org/index.php/jbm/article/view/152
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