Quantification of myocardial fibrosis by digital image analysis and interactive stereology

Diagnostic Pathology

Arvydas Laurinavicius²  Virginija Grabauskiene⁴  Julius Bogomolovas⁶  Paulette Herlin⁴  Benoit Plancoulaine¹  Sabine Pankuweit³  Daiva Bironaite⁵  Aida Laurinaviciene²  Edvardas Zurauskas²  Justinas Besusparis²  Dainius Daunoravicius⁴ 

[1] Path-Image/BioTiCla, University of Normandy, Unicaen, Caen, France;National Center of Pathology, Affiliate of Vilnius University Hospital Santariskiu Klinikos, Vilnius, Lithuania;Department of Cardiology, University Hospital Giessen & Marburg, Marburg, Germany;Vilnius University Medical faculty, Department of Pathology, Forensic Medicine and Pharmacology, M. K. Ciurlionio 21/27, Vilnius 03101, Lithuania;Department of Stem Cell Biology, Center for Innovative Medicine, State Research Institute, Vilnius, Lithuania;Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany

关键词: Stereology;    Digital;    Quantification;    Fibrosis;    Cardiac;   

Others  :  801420
DOI  :  10.1186/1746-1596-9-114

 received in 2014-03-07, accepted in 2014-06-02,  发布年份 2014

【 摘 要 】

Background

Cardiac fibrosis disrupts the normal myocardial structure and has a direct impact on heart function and survival. Despite already available digital methods, the pathologist’s visual score is still widely considered as ground truth and used as a primary method in histomorphometric evaluations. The aim of this study was to compare the accuracy of digital image analysis tools and the pathologist’s visual scoring for evaluating fibrosis in human myocardial biopsies, based on reference data obtained by point counting performed on the same images.

Methods

Endomyocardial biopsy material from 38 patients diagnosed with inflammatory dilated cardiomyopathy was used. The extent of total cardiac fibrosis was assessed by image analysis on Masson’s trichrome-stained tissue specimens using automated Colocalization and Genie software, by Stereology grid count and manually by Pathologist’s visual score.

Results

A total of 116 slides were analyzed. The mean results obtained by the Colocalization software (13.72 ± 12.24%) were closest to the reference value of stereology (RVS), while the Genie software and Pathologist score gave a slight underestimation. RVS values correlated strongly with values obtained using the Colocalization and Genie (r > 0.9, p < 0.001) software as well as the pathologist visual score. Differences in fibrosis quantification by Colocalization and RVS were statistically insignificant. However, significant bias was found in the results obtained by using Genie versus RVS and pathologist score versus RVS with mean difference values of: -1.61% and 2.24%. Bland-Altman plots showed a bidirectional bias dependent on the magnitude of the measurement: Colocalization software overestimated the area fraction of fibrosis in the lower end, and underestimated in the higher end of the RVS values. Meanwhile, Genie software as well as the pathologist score showed more uniform results throughout the values, with a slight underestimation in the mid-range for both.

Conclusion

Both applied digital image analysis methods revealed almost perfect correlation with the criterion standard obtained by stereology grid count and, in terms of accuracy, outperformed the pathologist’s visual score. Genie algorithm proved to be the method of choice with the only drawback of a slight underestimation bias, which is considered acceptable for both clinical and research evaluations.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9857909611227193 webcite

【 授权许可】

   
2014 Daunoravicius et al.; licensee BioMed Central Ltd.

【 图 表 】

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