Keywords: number estimation, morphometry, stereology, stereology software, volume estimation. INTRODUCTION In 1970, Weibel defined stereology as “a body of mathematical methods relating to three dimensional parameters defining the structure from two dimensional measurements obtainable on sections of the structure”.

• Collection of unbiased stereology data currently relies on relatively simple, low throughput technology developed in the mid-1990s. In an effort to improve the accuracy and efficiency of these integrated hardware-software-digital microscopy systems, we have developed an automatic segmentation algorithm (ASA) for automatic stereology counts using the unbiased optical fractionator method.
• The paper describes microcomputer software for point counting stereology. Stereology includes a collection of statistical methods that quantify the images of light and transmission electron microscop.

Dear Editor,

In a recent issue of this journal, combined polarization microscopy, immunohistochemistry and connective tissue reconstruction to study the collagen staining of picrosirius red. Using this approach, the authors definitively clarified a frequent misconception with regard to the use of this stain, showing that picrosirius red does not allow a differentiation of collagen types in polarized microscopy. Nowadays, this stain is widely used for studying fibrosis in many organs and, particularly, in the liver (e.g., ), kidney (e.g., ) and heart (e.g., ). Picrosirius red is considered ideal for collagen staining because it does not fade, is selective and is highly reproducible, more so than Masson’s trichrome or collagen immunohistochemistry (). Notably, the assessment of collagen area with picrosirius red and polarization has been weakly correlated with the area of collagen III detected by immunohistochemistry () or with Masson’s trichrome (). This is well explained by the findings presented by .

In the paper by , the authors state that picrosirius red associated with morphometric image analysis “remains the most powerful method to study and quantify collagen” and we would like to comment on this sentence. Morphometric image analysis is highly influenced by threshold settings, magnification and image resolution (), as it is essentially a two-dimensional procedure (; ). In contrast, stereology uses test-systems that are applied to two-dimensional images (such as histological sections) in order to obtain the three-dimensional information that is inherent to biological tissues (). Because of the objective and independent nature of stereological methods, these methods are used as the gold standard or reference method for comparative image analysis (; ). Image analysis methods are generally viewed as more user-friendly and faster, but they can also be time-consuming, particularly when there is a need for the manual exclusion of regions in images ().

We have used stereological point counting and picrosirius red in the livers from normal male Wistar rats, aged 2 to 18 months (n=5 per age; Fig. 1), and have quantified the distribution and total content of collagen in these specimens (observer was blinded to the age of the animals). In the rat liver, 56% of the collagen was identified as intralobular, whereas 20% and 14% were located in portal tracts and around central venules, respectively; only 10% was found in the Glisson’s capsule. Although no significant aging differences existed in this distribution, aging differences were found for the total amount of collagen (ANOVA, p<0.01): Young rats (2 months old) demonstrated 2.0% ± 0.3% collagen whereas 18-month-old rats had 3.2% ± 0.2% collagen. These data are in accordance with previous studies that have estimated collagen content in the liver by measuring hydroxyproline content (; ).

Liver of an 18-month-old rat stained with picrosirius red. For illustrative purposes, the counting grid (composed of 36 points) is shown. Points hitting collagen fibers are counted and allocated as intralobular or perivascular (around central vein) collagen (arrow and arrowhead, respectively). Scale, 22 µm.

Additionally, we have compared quantification by stereology and image analysis (Fig. 2). A total of 16 images per animal were randomly taken from the same slides used for point counting and analyzed with ImageJ (NIH, Bethesda, MD; observer was blinded to the stereological data and age of the animals). Around 41% of collagen was estimated to be within the lobules. Overall, total collagen varied from 1.59% ± 0.62% to 2.06% ± 0.41% in young and old rats, respectively. Non-significant differences of 0.38% to 0.53% were noted between image analysis and stereology, with a significant correlation noted between the two methods (r² = 0.94). This is consistent with the existing literature, with good correlations (r² > 0.90) and non-significant differences (0.50%) previously reported by others between these two methods for various tissues (heart, lung, kidney, liver) (Besusparis et al. 2014; ; ). Analyzing the different locations of collagen with both methods took about 2 hours.

Automated quantification of liver collagen with ImageJ (version 1.47v; NIH, Bethesda, MD) using the same image from Figure 1. (A) First, the colour deconvolution plugin was used (version v1.8) to enable the automatic detection of collagen fibers, which appear white (B). These fibers were demarcated using the color threshold plugin (C) to create a monochromatic image. Collagen in the capsule and perivascular areas were manually erased (D) and the remaining intralobular collagen determined through the “Analyze particles” function. Scale, 22 µm.

It should be noted that the point-counting method is a simple, reproducible and accurate procedure, as long as the grid is appropriately applied (). With the stereology software, the procedure is generally fast and particularly valuable for assessing the relative volume of various structures at the same time (e.g., cells and collagen fibers) or for studying their distribution, as shown here. Even with the most recent advances in digital microscopy, the human eye is still the most sophisticated machine for particle recognition ().

In conclusion, stereology and image analysis are powerful methods with which to study and quantify collagen (or other structures) in histological sections. Researchers should choose between these two methodologies, as both have advantages and pitfalls.

Stereology Systems

Footnotes

Declaration of Competing Interests: The authors declared no potential competing interests with respect to the research, authorship, and/or publication of this article.

Author Contributions: RM performed the stereological analysis and drafted the manuscript. BB and APFS performed the image analysis. All authors read and approved the manuscript.

Funding: The authors received no financial support for the research, authorship, and/or publication of this article.

References

Stereology Software Zeiss

• Besusparis J, Jokubauskiene S, Plancoulaine B, Herlin P, Laurinaviciene A, Buivydiene A, Laurinavicius A. (2014). Quantification Accuracy of Liver Fibrosis by In Vivo Elastography and Digital Image Analysis of Liver Biopsy Histochemistry. Anal Cell Pathol (Amst)2014:317635. [Google Scholar]
• Daunoravicius D, Besusparis J, Zurauskas E, Laurinaviciene A, Bironaite D, Pankuweit S, Plancoulaine B, Herlin P, Bogomolovas J, Grabauskiene V, Laurinavicius A. (2014). Quantification of myocardial fibrosis by digital image analysis and interactive stereology. Diagn Pathol. 9:114. [PMC free article] [PubMed] [Google Scholar]
• Farris AB, Adams CD, Brousaides N, Della Pelle PA, Collins AB, Moradi E, Smith RN, Grimm PC, Colvin RB. (2011). Morphometric and visual evaluation of fibrosis in renal biopsies. J Am Soc Nephrol22:176-186. [PMC free article] [PubMed] [Google Scholar]
• Gagliano N, Arosio B, Grizzi F, Masson S, Tagliabue J, Dioguardi N, Vergani C, Annoni G. (2002). Reduced collagenolytic activity of matrix metalloproteinases and development of liver fibrosis in the aging rat. Mech Ageing Dev123:413-425. [PubMed] [Google Scholar]
• Hadi AM, Mouchaers KT, Schalij I, Grunberg K, Meijer GA, Vonk-Noordegraaf A, van der Laarse WJ, Beliën JA. (2011). Rapid quantification of myocardial fibrosis: a new macro-based automated analysis. Cell Oncol34:343-354. [PMC free article] [PubMed] [Google Scholar]
• Huang Y, de Boer WB, Adams LA, MacQuillan G, Rossi E, Rigby P, Raftopoulos SC, Bulsara M, Jeffrey GP. (2013). Image analysis of liver collagen using sirius red is more accurate and correlates better with serum fibrosis markers than trichrome. Liver Int33:1249-1256. [PubMed] [Google Scholar]
• Lattouf R, Younes R, Lutomski D, Naaman N, Godeau G, Senni K, Changotade S. (2014). Picrosirius red staining: a useful tool to appraise collagen networks in normal and pathological tissues. J Histochem Cytochem62:751-758. [PubMed] [Google Scholar]
• Mandarim-de-Lacerda CA. (2003). Stereological tools in biomedical research. Anais da Academia Brasileira de Ciências75:469-486. [PubMed] [Google Scholar]
• Marcos R, Monteiro RAF, Rocha E. (2012). The use of design based stereology to evaluate volumes and numbers in the liver: a review with practical guidelines. J Anat220:303-317. [PMC free article] [PubMed] [Google Scholar]
• Porta E, Keopuhiwa L, Joun N, Nitta R. (1981). Effects of the type on dietary fat at two levels of vitamin E in Wistar male rats during development and aging. III. Biochemical and morphometric parameters of the liver. Mech Ageing Dev15:297-335. [PubMed] [Google Scholar]
• Schmitz C, Eastwood BS, Tappan SJ, Glaser JR, Peterson DA, Hof PR. (2014). Current automated 3D cell detection methods are not a suitable replacement for manual stereologic counting. Front Neuroanat8:27. [PMC free article] [PubMed] [Google Scholar]
• Street JM, Souza AC, Alvarez-Prats A, Horino T, Hu X, Yuen PS, Star RA. (2014). Automated quantification of renal fibrosis with Sirius Red and polarization contrast microscopy. Physiol Rep2:e12088. [PMC free article] [PubMed] [Google Scholar]

Stereology Software Zeiss