Practical Guide to Fibrosis Assessment Methods: From Tissue Staining to Quantitative Analysis

Introduction: Data Quality Depends on "Assessment Methods"

In fibrosis research, the most basic and important step is "Quantitative Assessment of Fibrosis." However, incorrect choice of staining methods or bias (subjectivity) in quantitative analysis can significantly impair the reproducibility of research data. This article explains the principles and pitfalls of representative histological staining methods (Sirius Red, Masson's Trichrome) and biochemical quantification methods (Hydroxyproline Assay), as well as the latest automated quantification technologies.

1. Histological Assessment

Sirius Red Staining (Picrosirius Red Staining)

"The Gold Standard for Fibrosis Quantification"

• Principle: The strong acidic dye Sirius Red specifically binds to basic amino acids of collagen molecules.
• Characteristics:
  • High Specificity: Selectively stains collagen fibers (especially Type I and III) red.
  • Observation under Polarized Light: Under polarized light, thick Type I collagen shows yellow-red birefringence, while thin Type III collagen shows green birefringence, allowing evaluation of fiber "quality."
• Merits: Ideal for automated quantification with image analysis software (easy extraction of red areas).
• Points to Note: pH control of the staining solution is crucial. Saturated picric acid solution must be used to prevent non-specific binding to non-collagen proteins.

Masson's Trichrome Staining

"Grasping the Overall Picture of Tissue Architecture"

• Principle: Uses three dyes with different molecular weights to stain tissues differentially based on density.
• Characteristics:
  • Collagen Fibers: Blue (or Green)
  • Cytoplasm/Muscle Fibers: Red
  • Nuclei: Black
• Merits: Easy to grasp the overall picture of the lesion, including inflammatory cell infiltration and tissue necrosis, not just fibrosis.
• Points to Note: Many staining steps lead to variability depending on technique. Automated quantification in image analysis can be more difficult for blue extraction compared to red extraction in Sirius Red.

Ashcroft Score

"Semi-quantitative Assessment of Pulmonary Fibrosis"

• Usage: Evaluation of Idiopathic Pulmonary Fibrosis (IPF) models (e.g., Bleomycin lung injury).
• Method: Observe the entire lung tissue at low magnification and score each field on a grade of 0 (normal) to 8 (total fibrosis).
• Challenges: Subjective bias by the examiner (Inter-observer variability) is unavoidable.
• Countermeasures: It is recommended to have multiple skilled examiners evaluate in a blinded manner, or use the Modified Ashcroft Scale (revised version with more detailed definitions).

2. Biochemical Quantification

Hydroxyproline Assay

"Absolute Quantification of Total Collagen"

• Principle: Chemically quantifies "Hydroxyproline," an amino acid specifically abundant in collagen.
• Procedure:
  1. Hydrolyze tissue with hydrochloric acid (Acid Hydrolysis).
  2. Oxidize with Chloramine T.
  3. React with Ehrlich's reagent and measure absorbance.
• Merits: Calculates total collagen amount in the tissue as an objective value (µg/mg tissue), making it ideal for inter-group comparison.
• Points to Note:
  • Unknown Localization: Cannot tell "where" the fibrosis is (perivascular or parenchymal).
  • Complexity of Operation: Acid hydrolysis takes time and generates toxic gas, requiring work in a fume hood.
• Latest Technology: In addition to traditional colorimetric methods, high-sensitivity and high-precision quantification using LC-MS/MS is also becoming widespread.

3. Digital Pathology and AI Analysis

Traditional manual scoring and area ratio calculation by simple thresholding have limitations. Recently, analysis combining Whole Slide Imaging (WSI) and AI (Artificial Intelligence) is becoming mainstream.

• Whole Tissue Analysis: Instead of selecting "5 representative fields" as before, analyzing fibrosis areas across the entire slide eliminates sampling bias.
• Exclusion of Vessels/Bronchi: AI automatically recognizes and excludes collagen around normal blood vessels and bronchi from the analysis, allowing accurate quantification of "Pathological Fibrosis" only.

Conclusion

For fibrosis assessment, it is important not to rely on a single method but to combine "Histological Staining (Distribution/Localization)" and "Biochemical Quantification (Total Amount)." Furthermore, incorporating objective image analysis using AI dramatically improves data reliability.

In our contract fibrosis model studies, we provide quantitative and objective data using the latest image analysis software in addition to evaluation by skilled pathologists.

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References

1. Hadi AM, et al. Rapid quantification of myocardial fibrosis: a new macro-based automated analysis. Int J Exp Pathol. 2011;92(6):434-444.
2. Ashcroft T, et al. Simple method of estimating severity of pulmonary fibrosis on a numerical scale. J Clin Pathol. 1988;41(4):467-470.
3. Karsdal MA, et al. Novel insights into the function and dynamics of extracellular matrix in liver fibrosis. Am J Physiol Gastrointest Liver Physiol. 2015;308(10):G807-830.