ArticleScientific reports2015
Automated biphasic morphological assessment of hepatitis B-related liver fibrosis using second harmonic generation microscopy.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed.
- Long-Term Follow-Up of Patients After Autologous Bone Marrow Cell Infusion for Decompensated Liver Cirrhosis.Cell transplantation · 2017Trial
- Label-free multiphoton microscopy and machine learning for recognition of hepatocellular carcinoma.Scientific reports · 2026Article
- A machine learning based algorithm accurately stages liver disease by quantification of arteries.Scientific reports · 2025Article
- Machine learning for automated classification of lung collagen in a urethane-induced lung injury mouse model.Biomedical optics express · 2024Article
- Liver fibrosis analysis using digital pathology.Medical molecular morphology · 2024Review
- Digital pathology for nonalcoholic steatohepatitis assessment.Nature reviews. Gastroenterology & hepatology · 2024Review
- Artificial Intelligence-Based Opportunities in Liver Pathology-A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- Quantitative image-based collagen structural features predict the reversibility of hepatitis C virus-induced liver fibrosis post antiviral therapies.Scientific reports · 2023Article
- Label-free multiphoton microscopy enables histopathological assessment of colorectal liver metastases and supports automated classification of neoplastic tissue.Scientific reports · 2023Article
- Automated quantitative assay of fibrosis characteristics in tuberculosis granulomas.Frontiers in microbiology · 2023Article
- Registered Trials of Artificial Intelligence Conducted on Chronic Liver Disease: A Cross-Sectional Study on ClinicalTrials.gov.Disease markers · 2022Article
- Artificial intelligence in gastroenterology and hepatology: Status and challenges.World journal of gastroenterology · 2021Review
- Improved second harmonic generation and two-photon excitation fluorescence microscopy-based quantitative assessments of liver fibrosis through auto-correction and optimal sampling.Quantitative imaging in medicine and surgery · 2021Article
- Clinical and Molecular Prediction of Hepatocellular Carcinoma Risk.Journal of clinical medicine · 2020Review
- Deep learning enables automated scoring of liver fibrosis stages.Scientific reports · 2018Article
- Risk factors and prevention of hepatocellular carcinoma in the era of precision medicine.Journal of hepatology · 2018Review
- Quantitative assessment of liver fibrosis (qFibrosis) reveals precise outcomes in Ishak "stable" patients on anti-HBV therapy.Scientific reports · 2018Article
- Tissue Intrinsic Fluorescence Spectra-Based Digital Pathology of Liver Fibrosis by Marker-Controlled Segmentation.Frontiers in medicine · 2018Article
- Discovering Macrophage Functions UsingFrontiers in immunology · 2018Review
- Dual-photon microscopy-based quantitation of fibrosis-related parameters (q-FP) to model disease progression in steatohepatitis.Hepatology (Baltimore, Md.) · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liver fibrosis assessment by biopsy and conventional staining scores is based on histopathological criteria. Variations in sample preparation and the use of semi-quantitative histopathological methods commonly result in discrepancies between medical centers. Thus, minor changes in liver fibrosis might be overlooked in multi-center clinical trials, leading to statistically non-significant data. Here, we developed a computer-assisted, fully automated, staining-free method for hepatitis B-related liver fibrosis assessment. In total, 175 liver biopsies were divided into training (n = 105) and verification (n = 70) cohorts. Collagen was observed using second harmonic generation (SHG) microscopy without prior staining, and hepatocyte morphology was recorded using two-photon excitation fluorescence (TPEF) microscopy. The training cohort was utilized to establish a quantification algorithm. Eleven of 19 computer-recognizable SHG/TPEF microscopic morphological features were significantly correlated with the ISHAK fibrosis stages (P < 0.001). A biphasic scoring method was applied, combining support vector machine and multivariate generalized linear models to assess the early and late stages of fibrosis, respectively, based on these parameters. The verification cohort was used to verify the scoring method, and the area under the receiver operating characteristic curve was >0.82 for liver cirrhosis detection. Since no subjective gradings are needed, interobserver discrepancies could be avoided using this fully automated method.
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