ArticleScientific reports2019
Quantification of hepatic steatosis in chronic liver disease using novel automated method of second harmonic generation and two-photon excited fluorescence.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 30 citations in OpenAlex.
- Real-World Insights in Designing SteatoStat: An End-to-End Deep Learning Pipeline for Hepatic Steatosis Quantification.Diagnostics (Basel, Switzerland) · 2026Article
- Artificial intelligence in small tissue biopsies: diagnostic applications, histochemical integration, and methodological challenges in surgical pathology.Histochemistry and cell biology · 2026Review
- Label-free multiphoton microscopy and machine learning for recognition of hepatocellular carcinoma.Scientific reports · 2026Article
- Liver biopsy in the modern era: from traditional techniques to artificial intelligence and multi-omics integration.Frontiers in medicine · 2025Review
- Hepatic Steatosis Analysis in Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2024Article
- Machine learning for automated classification of lung collagen in a urethane-induced lung injury mouse model.Biomedical optics express · 2024Article
- Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy.Light, science & applications · 2024Review
- Artificial intelligence-assisted digital pathology for non-alcoholic steatohepatitis: current status and future directions.Journal of hepatology · 2024Review
- Modernizing metabolic dysfunction-associated steatotic liver disease diagnostics: the progressive shift from liver biopsy to noninvasive techniques.Therapeutic advances in gastroenterology · 2024Review
- Article
- Label-free multiphoton microscopy enables histopathological assessment of colorectal liver metastases and supports automated classification of neoplastic tissue.Scientific reports · 2023Article
- Surveillance of the progression and assessment of treatment endpoints for nonalcoholic steatohepatitis.Clinical and molecular hepatology · 2023Review
- Label-free optical metabolic imaging of adipose tissues for prediabetes diagnosis.Theranostics · 2023Article
- Article
- Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future?Healthcare (Basel, Switzerland) · 2022Review
- Assessment of Ultra-Early-Stage Liver Fibrosis in Human Non-Alcoholic Fatty Liver Disease by Second-Harmonic Generation Microscopy.International journal of molecular sciences · 2022Article
- Bimodal fibrosis in a novel mouse model of bleomycin-induced usual interstitial pneumonia.Life science alliance · 2022Article
- Beyond brightfield: a possible future of slide scanners.BioTechniques · 2021Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The presence of hepatic steatosis (HS) is an important histological feature in a variety of liver disease. It is critical to assess HS accurately, particularly where it plays an integral part in defining the disease. Conventional methods of quantifying HS remain semi-quantitative, with potential limitations in precision, accuracy and subjectivity. Second Harmonic Generation (SHG) microscopy is a novel technology using multiphoton imaging techniques with applicability in histological tissue assessment. Using an automated algorithm based on signature SHG parameters, we explored the utility and application of SHG for the diagnosis and quantification of HS. SHG microscopy analysis using GENESIS (HistoIndex, Singapore) was applied on 86 archived liver biopsy samples. Reliability was correlated with 3 liver histopathologists. Data analysis was performed using SPSS. There was minimal inter-observer variability between the 3 liver histopathologists, with an intraclass correlation of 0.92 (95% CI 0.89-0.95; p < 0.001). Good correlation was observed between the histopathologists and automated SHG microscopy assessment of HS with Pearson correlation of 0.93: p < 0.001. SHG microscopy provides a valuable tool for objective, more precise measure of HS using an automated approach. Our study reflects proof of concept evidence for potential future refinement to current conventional histological assessment.
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