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Digital pathology: accurate technique for quantitative assessment of histological features in metabolic‐associated fatty liver disease
Author(s) -
MartiAguado David,
RodríguezOrtega Alejandro,
MestreAlagarda Claudia,
Bauza Mónica,
ValeroPérez Elena,
AlfaroCervello Clara,
Benlloch Salvador,
PérezRojas Judith,
Ferrández Antonio,
AlemanyMonraval Pilar,
EscuderoGarcía Desamparados,
Monton Cristina,
Aguilera Victoria,
AlberichBayarri Ángel,
Serra Miguel Ángel,
MartiBonmati Luis
Publication year - 2021
Publication title -
alimentary pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.308
H-Index - 177
eISSN - 1365-2036
pISSN - 0269-2813
DOI - 10.1111/apt.16100
Subject(s) - steatosis , medicine , fatty liver , grading (engineering) , fibrosis , steatohepatitis , liver biopsy , biopsy , intraclass correlation , pathology , repeatability , gastroenterology , disease , biology , ecology , clinical psychology , chemistry , chromatography , psychometrics
Summary Background Histological evaluation of metabolic‐associated fatty liver disease (MAFLD) biopsies is subjective, descriptive and with interobserver variability. Aims To examine the relationship between different histological features (fibrosis, steatosis, inflammation and iron) measured with automated whole‐slide quantitative digital pathology and corresponding semiquantitative scoring systems, and the distribution of digital pathology measurements across Fatty Liver Inhibition of Progression (FLIP) algorithm and Steatosis, Activity and Fibrosis (SAF) scoring system Methods We prospectively included 136 consecutive patients who underwent liver biopsy for MAFLD at three Spanish centres (January 2017‐January 2020). Biopsies were scored by two blinded pathologists according to the Non‐alcoholic Steatohepatitis (NASH) Clinical Research Network system for fibrosis staging, the FLIP/SAF classification for steatosis and inflammation grading and Deugnier score for iron grading. Proportionate areas of collagen, fat, inflammatory cells and iron deposits were measured with computer‐assisted digital image analysis. A test‐retest experiment was performed for precision repeatability evaluation. Results Digital pathology showed strong correlation with fibrosis (r = 0.79; P < 0.001), steatosis (r = 0.85; P < 0.001) and iron (r = 0.70; P < 0.001). Performance was lower when assessing the degree of inflammation (r = 0.35; P < 0.001). NASH cases had a higher proportion of collagen and fat compared to non‐NASH cases ( P < 0.005), whereas inflammation and iron quantification did not show significant differences between categories. Repeatability evaluation showed that all the coefficients of variation were ≤1.1% and all intraclass correlation coefficient values were ≥0.99, except those of collagen. Conclusion Digital pathology allows an automated, precise, objective and quantitative assessment of MAFLD histological features. Digital analysis measurements show good concordance with pathologists´ scores.