ArticleThe American journal of pathology2021
Image-Based Machine Learning Algorithms for Disease Characterization in the Human Type 1 Diabetes Pancreas.
Article in The American journal of pathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 31 citations in OpenAlex.
- MRI T1 signal intensity ratios correlate with fibrosis in recurrent acute and chronic pancreatitis.Abdominal radiology (New York) · 2026Article
- Deep learning-powered quantification of endocrine cells and CD3Diabetologia · 2026Article
- AI-guided analysis of human pancreatic islet sociology reveals distinct cell compositional changes in type 1 diabetes.bioRxiv : the preprint server for biology · 2026Article
- Integrated histopathology of the human pancreas throughout stages of type 1 diabetes progression.Nature communications · 2026Article
- Loss of Insulin-Positive Cell Clusters Precedes the Decrease in Islet Frequency and β-Cell Area in Type 1 Diabetes.Diabetes · 2025Article
- Quantitative temporal analysis of pancreatic islet T lymphocyte and macrophage infiltration heralded by serum IgE in congenic BioBreeding (BB) Gimap5Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025Article
- Integrated histopathology of the human pancreas throughout stages of type 1 diabetes progression.bioRxiv : the preprint server for biology · 2025Article
- Leveraging pre-trained machine learning models for islet quantification in type 1 diabetes.Journal of pathology informatics · 2025Article
- Advances in MRI of Chronic Pancreatitis.Advances in clinical radiology · 2024Article
- Impaired islet function and normal exocrine enzyme secretion occur with low inter-regional variation in type 1 diabetes.Cell reports · 2024Article
- Activation of ductal progenitor-like cells from adult human pancreas requires extracellular matrix protein signaling.iScience · 2024Article
- Diagnosis of chronic pancreatitis using semi-quantitative MRI features of the pancreatic parenchyma: results from the multi-institutional MINIMAP study.Abdominal radiology (New York) · 2023Article
- Longitudinal MRI Shows Progressive Decline in Pancreas Size and Altered Pancreas Shape in Type 1 Diabetes.The Journal of clinical endocrinology and metabolism · 2023Article
- The pathogenic "symphony" in type 1 diabetes: A disorder of the immune system, β cells, and exocrine pancreas.Cell metabolism · 2023Review
- Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases: Workshop Proceedings.Diabetes · 2023Review
- Precision medicine in type 1 diabetes.Diabetologia · 2022Review
- Quantitative MRI of chronic pancreatitis: results from a multi-institutional prospective study, magnetic resonance imaging as a non-invasive method for assessment of pancreatic fibrosis (MINIMAP).Abdominal radiology (New York) · 2022Article
- T1 signal intensity ratio of the pancreas as an imaging biomarker for the staging of chronic pancreatitis.Abdominal radiology (New York) · 2022Article
- Histopathologic correlation of pancreatic fibrosis with pancreatic magnetic resonance imaging quantitative metrics and Cambridge classification.Abdominal radiology (New York) · 2022Article
- State-of-the-art microscopy to understand islets of Langerhans: what to expect next?Immunology and cell biology · 2021Review
Corrections and comments
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Authors and funding
12 authors at 4 institutions in 3 countries.
Funding
Abstract
Emerging data suggest that type 1 diabetes affects not only the β-cell-containing islets of Langerhans, but also the surrounding exocrine compartment. Using digital pathology, machine learning algorithms were applied to high-resolution, whole-slide images of human pancreata to determine whether the tissue composition in individuals with or at risk for type 1 diabetes differs from those without diabetes. Transplant-grade pancreata from organ donors were evaluated from 16 nondiabetic autoantibody-negative controls, 8 nondiabetic autoantibody-positive subjects with increased type 1 diabetes risk, and 19 persons with type 1 diabetes (0 to 12 years' duration). HALO image analysis algorithms were implemented to compare architecture of the main pancreatic duct as well as cell size, density, and area of acinar, endocrine, ductal, and other nonendocrine, nonexocrine tissues. Type 1 diabetes was found to affect exocrine area, acinar cell density, and size, whereas the type of difference correlated with the presence or absence of insulin-positive cells remaining in the pancreas. These changes were not observed before disease onset, as indicated by modeling cross-sectional data from pancreata of autoantibody-positive subjects and those diagnosed with type 1 diabetes. These data provide novel insights into anatomic differences in type 1 diabetes pancreata and demonstrate that machine learning can be adapted for the evaluation of disease processes from cross-sectional data sets.
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