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Digital Pathology Enables Automated and Quantitative Assessment of Inflammatory Activity in Patients with Chronic Liver Disease

Traditional histological evaluation for grading liver disease severity is based on subjective and semi-quantitative scores. We examined the relationship between digital pathology analysis and corresponding scoring systems for the assessment of hepatic necroinflammatory activity. A prospective, multi...

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Detalles Bibliográficos
Autores principales: Marti-Aguado, David, Fernández-Patón, Matías, Alfaro-Cervello, Clara, Mestre-Alagarda, Claudia, Bauza, Mónica, Gallen-Peris, Ana, Merino, Víctor, Benlloch, Salvador, Pérez-Rojas, Judith, Ferrández, Antonio, Puglia, Víctor, Gimeno-Torres, Marta, Aguilera, Victoria, Monton, Cristina, Escudero-García, Desamparados, Alberich-Bayarri, Ángel, Serra, Miguel A., Marti-Bonmati, Luis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8699191/
https://www.ncbi.nlm.nih.gov/pubmed/34944452
http://dx.doi.org/10.3390/biom11121808
Descripción
Sumario:Traditional histological evaluation for grading liver disease severity is based on subjective and semi-quantitative scores. We examined the relationship between digital pathology analysis and corresponding scoring systems for the assessment of hepatic necroinflammatory activity. A prospective, multicenter study including 156 patients with chronic liver disease (74% nonalcoholic fatty liver disease-NAFLD, 26% chronic hepatitis-CH etiologies) was performed. Inflammation was graded according to the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network system and METAVIR score. Whole-slide digital image analysis based on quantitative (I-score: inflammation ratio) and morphometric (C-score: proportionate area of staining intensities clusters) measurements were independently performed. Our data show that I-scores and C-scores increase with inflammation grades (p < 0.001). High correlation was seen for CH (ρ = 0.85–0.88), but only moderate for NAFLD (ρ = 0.5–0.53). I-score (p = 0.008) and C-score (p = 0.002) were higher for CH than NAFLD. Our MATLAB algorithm performed better than QuPath software for the diagnosis of low-moderate inflammation (p < 0.05). C-score AUC for classifying NASH was 0.75 (95%CI, 0.65–0.84) and for moderate/severe CH was 0.99 (95%CI, 0.97–1.00). Digital pathology measurements increased with fibrosis stages (p < 0.001). In conclusion, quantitative and morphometric metrics of inflammatory burden obtained by digital pathology correlate well with pathologists’ scores, showing a higher accuracy for the evaluation of CH than NAFLD.