Abstract
The volume of digital image (DI) storage continues to be an important problem in computer-assisted pathology. DI compression enables the size of files to be reduced but with the disadvantage of loss of quality. Previous results indicated that the efficiency of computer-assisted quantification of immunohistochemically stained cell nuclei may be significantly reduced when compressed DIs are used. This study attempts to show, with respect to immunohistochemically stained nuclei, which morphometric parameters may be altered by the different levels of JPEG compression, and the implications of these alterations for automated nuclear counts, and further, develops a method for correcting this discrepancy in the nuclear count. For this purpose, 47 DIs from different tissues were captured in uncompressed TIFF format and converted to 1:3, 1:23 and 1:46 compression JPEG images. Sixty-five positive objects were selected from these images, and six morphological parameters were measured and compared for each object in TIFF images and those of the different compression levels using a set of previously developed and tested macros. Roundness proved to be the only morphological parameter that was significantly affected by image compression. Factors to correct the discrepancy in the roundness estimate were derived from linear regression models for each compression level, thereby eliminating the statistically significant differences between measurements in the equivalent images. These correction factors were incorporated in the automated macros, where they reduced the nuclear quantification differences arising from image compression. Our results demonstrate that it is possible to carry out unbiased automated immunohistochemical nuclear quantification in compressed DIs with a methodology that could be easily incorporated in different systems of digital image analysis.
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Alvaro-Naranjo T, Lejeune M, Salvado-Usach MT, Bosch-Princep R, Reverter-Branchat G, Jaen-Martinez J, Pons-Ferre LE (2005) Tumor-infiltrating cells as a prognostic factor in Hodgkin’s lymphoma: a quantitative tissue microarray study in a large retrospective cohort of 267 patients. Leukemia Lymphoma 46:1581–1591
Alvaro T, Lejeune M, Salvado MT, Bosch R, Garcia JF, Jaen J, Banham AH, Roncador G, Montalban C, Piris MA (2005) Outcome in Hodgkin’s lymphoma can be predicted from the presence of accompanying cytotoxic and regulatory T cells. Clin Cancer Res 11:1467–1473
Alvaro T, Lejeune M, Salvado MT, Lopez C, Jaen J, Bosch R, Pons LE (2006) Immunohistochemical patterns of reactive microenvironment are associated with clinicobiologic behavior in follicular lymphoma patients. J Clin Oncol 24:5350–5357
Appel T, Bierhoff E, Appel K, von Lindern JJ, Berge S, Niederhagen B (2003) Predictive variables for the biological behaviour of basal cell carcinoma of the face: relevance of morphometry of the nuclei. Br J Oral Maxillofac Surg 41:147–150
Atalag K, Sincan M, Celasun B, Karaagaoglu E (2004) Effects of lossy image compression on quantitative image analysis of cell nuclei. Anal Quant Cytol Histol 26:22–27
Babik TM (2007) Morphometric characteristics of epitheliocytes in the choroid plexus of the cerebral ventricles in humans during aging. Neurosci Behav Physiol 37:107–109
Belair ML, Fansi AK, Descovich D, Leblanc AR, Harasymowycz P (2005) The effect of compression on clinical diagnosis of glaucoma based on non-analyzed confocal scanning laser ophthalmoscopy images. Ophthalmic Surg Lasers Imaging 36:323–326
Brey EM, Lalani Z, Johnston C, Wong M, McIntire LV, Duke PJ, Patrick CW Jr (2003) Automated selection of DAB-labeled tissue for immunohistochemical quantification. J Histochem Cytochem 51:575–584
Cheretis C, Angelidou E, Dietrich F, Politi E, Kiaris H, Koutselini H (2008) Prognostic value of computer-assisted morphological and morphometrical analysis for detecting the recurrence tendency of basal cell carcinoma. Med Sci Monit 14:MT13–19
Cross SS (1994) The application of fractal geometric analysis to microscopic images. Micron 25:101–113
Cross SS (1997) Fractals in pathology. J Pathol 182:1–8
Davis DW, Buchholz TA, Hess KR, Sahin AA, Valero V, McConkey DJ (2003) Automated quantification of apoptosis after neoadjuvant chemotherapy for breast cancer: early assessment predicts clinical response. Clin Cancer Res 9:955–960
Einstein AJ, Wu HS, Sanchez M, Gil J (1998) Fractal characterization of chromatin appearance for diagnosis in breast cytology. J Pathol 185:366–381
Elhafey AS, Papadimitriou JC, El-Hakim MS, El-Said AI, Ghannam BB, Silverberg SG (2001) Computerized image analysis of p53 and proliferating cell nuclear antigen expression in benign, hyperplastic, and malignant endometrium. Arch Pathol Lab Med 125:872–879
Franzen LE, Hahn-Stromberg V, Edvardsson H, Bodin L (2008) Characterization of colon carcinoma growth pattern by computerized morphometry: definition of a complexity index. Int J Mol Med 22:465–472
Gerger A, Bergthaler P, Smolle J (2004) An automated method for the quantification and fractal analysis of immunostaining. Cell Oncol 26:125–134
Gil J, Wu H, Wang BY (2002) Image analysis and morphometry in the diagnosis of breast cancer. Microsc Res Tech 59:109–118
Gurdal P, Hildebolt CF, Akdeniz BG (2001) The effects of different image file formats and image-analysis software programs on dental radiometric digital evaluations. Dentomaxillofac Radiol 30:50–55
Hannen EJ, van der Laak JA, Kerstens HM, Cuijpers VM, Hanselaar AG, Manni JJ, de Wilde PC (2001) Quantification of tumour vascularity in squamous cell carcinoma of the tongue using CARD amplification, a systematic sampling technique, and true colour image analysis. Anal Cell Pathol 22:183–192
Keenan SJ, Diamond J, McCluggage WG, Bharucha H, Thompson D, Bartels PH, Hamilton PW (2000) An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN). J Pathol 192:351–362
Lejeune M, Jaen J, Pons L, Lopez C, Salvado MT, Bosch R, Garcia M, Escriva P, Baucells J, Cugat X, Alvaro T (2008) Quantification of diverse subcellular immunohistochemical markers with clinicobiological relevancies: validation of a new computer-assisted image analysis procedure. J Anat 212:868–878
Leong FJ, Leong AS (2004) Digital imaging in pathology: theoretical and practical considerations, and applications. Pathology 36:234–241
Levine MD (1985) Vision in man and machines. McGraw-Hill, New York
Li F, Sone S, Takashima S, Kiyono K, Yang ZG, Hasegawa M, Kawakami S, Saito A, Hanamura K, Asakura K (2001) Effects of JPEG and wavelet compression of spiral low-dose ct images on detection of small lung cancers. Acta Radiol 42:156–160
Lopez C, Lejeune M, Salvado MT, Escriva P, Bosch R, Pons LE, Alvaro T, Roig J, Cugat X, Baucells J, Jaen J (2008a) Automated quantification of nuclear immunohistochemical markers with different complexity. Histochem Cell Biol 129:379–387
Lopez C, Lejeune M, Escriva P, Bosch R, Salvado MT, Pons LE, Baucells J, Cugat X, Alvaro T, Jaen J (2008b) Effects of image compression on automatic count of immunohistochemically stained nuclei in digital images. J Am Med Inform Assoc 15:794–798
Makarov DV, Marlow C, Epstein JI, Miller MC, Landis P, Partin AW, Carter HB, Veltri RW (2008) Using nuclear morphometry to predict the need for treatment among men with low grade, low stage prostate cancer enrolled in a program of expectant management with curative intent. Prostate 68:183–189
Milord RA, Lecksell K, Epstein JI (2001) An objective morphologic parameter to aid in the diagnosis of flat urothelial carcinoma in situ. Hum Pathol 32:997–1002
Mofidi R, Walsh R, Ridgway PF, Crotty T, McDermott EW, Keaveny TV, Duffy MJ, Hill AD, O’Higgins N (2003) Objective measurement of breast cancer oestrogen receptor status through digital image analysis. Eur J Surg Oncol 29:20–24
Ohgiya Y, Gokan T, Nobusawa H, Hirose M, Seino N, Fujisawa H, Baba M, Nagai K, Tanno K, Takeyama N, Munechika H (2003) Acute cerebral infarction: effect of JPEG compression on detection at CT. Radiology 227:124–127
Oishi T, Sasaki A, Hamada N, Ishiuchi S, Funayama T, Sakashita T, Kobayashi Y, Nakano T, Nakazato Y (2008) Proliferation and cell death of human glioblastoma cells after carbon-ion beam exposure: morphologic and morphometric analyses. Neuropathology 28:408–416
Rubin MA, Zerkowski MP, Camp RL, Kuefer R, Hofer MD, Chinnaiyan AM, Rimm DL (2004) Quantitative determination of expression of the prostate cancer protein alpha-methylacyl-CoA racemase using automated quantitative analysis (AQUA): a novel paradigm for automated and continuous biomarker measurements. Am J Pathol 164:831–840
Singh SS, Kim D, Mohler JL (2005) Java Web Start based software for automated quantitative nuclear analysis of prostate cancer and benign prostate hyperplasia. Biomed Eng Online 4:31
Tambasco M, Magliocco AM (2008) Relationship between tumor grade and computed architectural complexity in breast cancer specimens. Hum Pathol 39:740–746
Trere D, Montanaro L, Ceccarelli C, Barbieri S, Cavrini G, Santini D, Taffurelli M, Derenzini M (2007) Prognostic relevance of a novel semiquantitative classification of Bcl2 immunohistochemical expression in human infiltrating ductal carcinomas of the breast. Ann Oncol 18:1004–1014
Wang S, Saboorian MH, Frenkel EP, Haley BB, Siddiqui MT, Gokaslan S, Wians FH Jr, Hynan L, Ashfaq R (2001) Assessment of HER-2/neu status in breast cancer. Automated Cellular Imaging System (ACIS)-assisted quantitation of immunohistochemical assay achieves high accuracy in comparison with fluorescence in situ hybridization assay as the standard. Am J Clin Pathol 116:495–503
Weaver DL, Krag DN, Manna EA, Ashikaga T, Harlow SP, Bauer KD (2003) Comparison of pathologist-detected and automated computer-assisted image analysis detected sentinel lymph node micrometastases in breast cancer. Mod Pathol 16:1159–1163
Williams SG, Buscarini M, Stein JP (2001) Molecular markers for diagnosis, staging, and prognosis of bladder cancer. Oncology (Huntingt) 15:1461–1470, 1473–1464, 1476; discussion 1476–1484
Zhang K, Prichard JW, Yoder S, De J, Lin F (2007) Utility of SKP2 and MIB-1 in grading follicular lymphoma using quantitative imaging analysis. Hum Pathol 38:878–882
Acknowledgments
We thank María del Mar Barbera, Bárbara Tomás, Vanesa Gestí, Ainhoa Montserrat, Ana Suñé, Verònica Echevarría and Marc Iniesta for their skillful technical assistance, and Anna Carot, Montse Sebastià and Rosa Cabrera for their excellent secretarial work. Grants numbers and sources of support: This work was supported by grants FIS 04/1440, 04/1467 and 05/1527 from the Ministerio de Sanidad y Consumo, Spain and by a grant from the Fundación Mutua Madrileña (FMM Dr. Bosch 2008).
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López, C., Jaén Martinez, J., Lejeune, M. et al. Roundness variation in JPEG images affects the automated process of nuclear immunohistochemical quantification: correction with a linear regression model. Histochem Cell Biol 132, 469–477 (2009). https://doi.org/10.1007/s00418-009-0626-9
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DOI: https://doi.org/10.1007/s00418-009-0626-9