ArticleJournal of toxicologic pathology2017
Quantitative analysis of histopathological findings using image processing software.
Article in Journal of toxicologic pathology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed, 69 citations in OpenAlex.
- Histopathological and Transcriptomic Alterations in Metabolic Organs: A Case Study from a Spontaneously Diabetic Rhesus Macaque.International journal of molecular sciences · 2026Article
- Temporal plasticity of thermal tolerance and cellular responses in Atlantic salmon (Salmo salar) during warm acclimation and subsequent cold acclimation to baseline temperature.Fish physiology and biochemistry · 2026Article
- Gastrodin mitigates cisplatin-induced cardiotoxicity in Swiss albino mice by restoring redox homeostasis and modulating the p62-Keap1-Nrf2 Axis.Molecular biology reports · 2026Article
- Article
- Correlation Between Molecular Genetic Analysis and Nuclear Pleomorphism in Long-Term Recurrent and Metastatic Chordoma.Cancers · 2026Article
- A multi-omics molecular landscape of 30 tissues in aging female rhesus macaques.Nature methods · 2025Article
- Report of the AI Pathology Task Force, Non-clinical Evaluation Expert Committee, Japan Pharmaceutical Manufacturers Association: an overview of recent publications about AI pathology.Journal of toxicologic pathology · 2025Review
- Identifying a gene signature for age-related hearing loss through machine learning and revealing the effect of the CTSS on the mice cochlea.Biogerontology · 2025Article
- eIF6 modulates skin wound healing by upregulating keratin 6B.Stem cells translational medicine · 2024Article
- Improvement of functional dyspepsia with Suaeda salsa (L.) Pall via regulating brain-gut peptide and gut microbiota structure.European journal of nutrition · 2024Article
- Combination of pathological, biochemical and behavioral evaluations for peripheral neurotoxicity assessment in isoniazid-treated rats.Journal of toxicologic pathology · 2024Article
- Ultrastructural, Antioxidant, and Metabolic Responses of Male Genetically Improved Farmed Tilapia (GIFT,Antioxidants (Basel, Switzerland) · 2024Article
- Qingfei Formula Protects against Human Respiratory Syn cytial Virus-induced Lung Inflammatory Injury by Regulating the M APK Signaling Pathway.Combinatorial chemistry & high throughput screening · 2024Article
- Article
- A comparative study on the implementation of deep learning algorithms for detection of hepatic necrosis in toxicity studies.Toxicological research · 2023Article
- Irisin ameliorates age-associated sarcopenia and metabolic dysfunction.Journal of cachexia, sarcopenia and muscle · 2023Article
- Comprehensive genomic profiling reveals prognostic signatures and insights into the molecular landscape of colorectal cancer.Frontiers in oncology · 2023Article
- HOXC6 impacts epithelial-mesenchymal transition and the immune microenvironment through gene transcription in gliomas.Cancer cell international · 2022Article
- Automated recognition of glomerular lesions in the kidneys of mice by using deep learning.Journal of pathology informatics · 2022Article
- Spectroscopic and deep learning-based approaches to identify and quantify cerebral microhemorrhages.Scientific reports · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In evaluating pathological changes in drug efficacy and toxicity studies, morphometric analysis can be quite robust. In this experiment, we examined whether morphometric changes of major pathological findings in various tissue specimens stained with hematoxylin and eosin could be recognized and quantified using image processing software. Using Tissue Studio, hypertrophy of hepatocytes and adrenocortical cells could be quantified based on the method of a previous report, but the regions of red pulp, white pulp, and marginal zones in the spleen could not be recognized when using one setting condition. Using Image-Pro Plus, lipid-derived vacuoles in the liver and mucin-derived vacuoles in the intestinal mucosa could be quantified using two criteria (area and/or roundness). Vacuoles derived from phospholipid could not be quantified when small lipid deposition coexisted in the liver and adrenal cortex. Mononuclear inflammatory cell infiltration in the liver could be quantified to some extent, except for specimens with many clustered infiltrating cells. Adipocyte size and the mean linear intercept could be quantified easily and efficiently using morphological processing and the macro tool equipped in Image-Pro Plus. These methodologies are expected to form a base system that can recognize morphometric features and analyze quantitatively pathological findings through the use of information technology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.