ArticleBMC gastroenterology2022
Nuclear morphometry and chromatin texture changes in hepatocellular carcinoma samples may predict outcomes of liver transplanted patients.
Article in BMC gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- NucVerse3D: generalizable 3D nuclear instance segmentation across heterogeneous microscopy modalities.Scientific reports · 2026Article
- Cracking the Code: Computational Image Analysis Tools for Histopathological and Morphometric Insights.Journal of imaging · 2026Review
- Correlation Between Molecular Genetic Analysis and Nuclear Pleomorphism in Long-Term Recurrent and Metastatic Chordoma.Cancers · 2026Article
- Enhancing frozen histological section images using permanent-section-guided deep learning with nuclei attention.Scientific reports · 2025Article
- Phenothiazine-Based Nanoaggregates: Dual Role in Bioimaging and Stem Cell-Driven Photodynamic Therapy.Nanomaterials (Basel, Switzerland) · 2025Article
- Clinical values of nuclear morphometric analysis in fibroepithelial lesions.Breast cancer research : BCR · 2024Article
- Machine learning approaches to detect hepatocyte chromatin alterations from iron oxide nanoparticle exposure.Scientific reports · 2024Article
- Exploring prognostic values of DNA ploidy, stroma-tumor fraction and nucleotyping in stage II colon cancer patients.Discover oncology · 2024Article
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNuclear changes are typical in the carcinogenesis of hepatocellular carcinoma (HCC). Morphometry and chromatin texture analysis are quantitative methods for their quantification. In this study, we analyzed nuclear morphometry and chromatin texture parameters in samples of hepatocellular carcinoma from liver transplant patients and their associations with clinicopathologic variables.
methodsSamples of HCC and adjacent tissue from 34 individuals were collected in tissue microarray blocks. Stained slides were microphotographed using an optical microscope and nuclear parameters analyzed in ImageJ (FracLac plug-in). ROC curve analysis was used to find accurate cut-offs for differentiation of neoplastic and non-neoplastic cells. The inter-rater agreement was also evaluated.
resultsNuclear morphometric and textural differences were observed between the samples of HCC and adjacent tissue of liver transplant patients. Lower mean gray value (p = 0.034) and Feret diameter (p = 0.024) were associated with higher Model for End-Stage Liver Disease (MELD) scores. Nuclei with larger area (p = 0.014) and larger Feret diameter (p = 0.035) were associated with lower survival. Lower aspect ratio was associated with HCC recurrence after the transplant (p = 0.048). The cut-off of 1.13 μm (p = < 0.001) for aspect ratio and cut-off of 21.15 μm (p = 0.038) for perimeter were established for the differentiation of neoplastic and non-neoplastic cells. The morphometric analysis was reproducible to area, circularity, Feret diameter, mean gray value and aspect ratio between observers (p = < 0.001).
conclusionsNuclear morphometric differences between the HCC and the adjacent tissue samples were associated with prognostic variables (MELD scores, recurrence and survival) and may predict liver transplant patients' outcomes.
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