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Comparative Study
. 2017 Apr 1;147(4):364-369.
doi: 10.1093/ajcp/aqx011.

Interobserver Variability in Histologic Evaluation of Liver Fibrosis Using Categorical and Quantitative Scores

Michael Pavlides  1   2 , Jacqueline Birks  3 , Eve Fryer  4 , David Delaney  4 , Nikita Sarania  5 , Rajarshi Banerjee  6 , Stefan Neubauer  2 , Eleanor Barnes  1   7 , Kenneth A Fleming  5   4 , Lai Mun Wang  4
Affiliations
Comparative Study

Interobserver Variability in Histologic Evaluation of Liver Fibrosis Using Categorical and Quantitative Scores

Michael Pavlides et al. Am J Clin Pathol. .

Abstract

Objectives: The aim of the study was to investigate the interobserver agreement for categorical and quantitative scores of liver fibrosis.

Methods: Sixty-five consecutive biopsy specimens from patients with mixed liver disease etiologies were assessed by three pathologists using the Ishak and nonalcoholic steatohepatitis Clinical Research Network (NASH CRN) scoring systems, and the fibrosis area (collagen proportionate area [CPA]) was estimated by visual inspection (visual-CPA). A subset of 20 biopsy specimens was analyzed using digital imaging analysis (DIA) for the measurement of CPA (DIA-CPA).

Results: The bivariate weighted κ between any two pathologists ranged from 0.57 to 0.67 for Ishak staging and from 0.47 to 0.57 for the NASH CRN staging. Bland-Altman analysis showed poor agreement between all possible pathologist pairings for visual-CPA but good agreement between all pathologist pairings for DIA-CPA. There was good agreement between the two pathologists who assessed biopsy specimens by visual-CPA and DIA-CPA. The intraclass correlation coefficient, which is equivalent to the κ statistic for continuous variables, was 0.78 for visual-CPA and 0.97 for DIA-CPA.

Conclusions: These results suggest that DIA-CPA is the most robust method for assessing liver fibrosis followed by visual-CPA. Categorical scores perform less well than both the quantitative CPA scores assessed here.

Keywords: Bland-Altman plot; Collagen proportionate area; Digital imaging analysis; statistic; κ.

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Figures

Image 1
Image 1
Digital imaging analysis for estimation collagen proportionate area. A, Liver biopsy image produced using a high- definition slide scanner. B, Manual editing step to crop out artifacts in the background and any nonliver tissue. The image is then split into the red, green, and blue components, and the green channel (C) is selected for further analysis. Manual thresholding is used to select the collagen in the slide (D), and the number of pixels in this selection is then automatically counted by the software. A further step allows the collagen selection (yellow outline) to be superimposed onto the original image (E and magnified section in F), which allows the reporting pathologist to validate the collagen selection. The total area of the biopsy slide can also be estimated using this technique, and collagen proportionate area is calculated as (number of pixels in the collagen area/number of pixels in the whole biopsy specimen) ×100.
See this image and copyright information in PMC

References

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