ArticleEuropean radiology2019
Diabetes risk assessment with imaging: a radiomics study of abdominal CT.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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15 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- Pancreas image mining: a systematic review of radiomics.European radiology · 2021Pooled it
- Multiparametric Magnetic Resonance Imaging Findings of the Pancreas: A Comparison in Patients with Type 1 and 2 Diabetes.Tomography (Ann Arbor, Mich.) · 2025Article
- Accurate screening of patients with diabetes based on physical examination: pancreas imaging features from chest CT and laboratory data.Frontiers in endocrinology · 2025Article
- Deep learning to estimate impaired glucose metabolism from Magnetic Resonance Imaging of the liver: An opportunistic population screening approach.PLOS digital health · 2024Article
- Radiomics-Based Assessment of OCT Angiography Images for Diabetic Retinopathy Diagnosis.Ophthalmology science · 2023Article
- Clinical parameters correlated with the psoas muscle index in Japanese individuals with type 2 diabetes mellitus.Diabetology international · 2023Article
- Radiomics-based machine learning (ML) classifier for detection of type 2 diabetes on standard-of-care abdomen CTs: a proof-of-concept study.Abdominal radiology (New York) · 2022Article
- Effect of Gray Value Discretization and Image Filtration on Texture Features of the Pancreas Derived from Magnetic Resonance Imaging at 3T.Journal of imaging · 2022Article
- Quantitative analysis of the risk of type 2 diabetes and fatty liver in non-obese individuals by computed tomography.Abdominal radiology (New York) · 2022Article
- Imaging evaluation of the pancreas in diabetic patients.Abdominal radiology (New York) · 2022Review
- New risk score model for identifying individuals at risk for diabetes in southwest China.Preventive medicine reports · 2021Article
- A Case Control Study of the Seroprevalence ofJournal of pancreatic cancer · 2021Article
- Development of a volumetric pancreas segmentation CT dataset for AI applications through trained technologists: a study during the COVID 19 containment phase.Abdominal radiology (New York) · 2020Article
- Development and validation of a prediction model estimating the 10-year risk for type 2 diabetes in China.PloS one · 2020Article
- Volumetric Pancreas Segmentation on Computed Tomography: Accuracy and Efficiency of a Convolutional Neural Network Versus Manual Segmentation in 3D Slicer in the Context of Interreader Variability of Expert Radiologists.Journal of computer assisted tomographyArticle
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesTo identify CT markers for screening of early type 2 diabetes and assessment of the risk of incident diabetes using a radiomics method.
methodsThe medical records of 26,947 inpatients were reviewed. A total of 690 patients were selected and allocated to a primary cohort, a validation cohort, and a prediction cohort and used to build prediction models for diabetes. Three radiomics signatures were constructed using CT image features extracted from three regions of interest, i.e., in the pancreas, liver, and psoas major muscle. By incorporating radiomics signatures and other markers, we built a radiomics nomogram that could be used to screen for early diabetes and predict future diabetes.
resultsOf the three abdominal organs for which radiomics signature were constructed, that of the pancreas showed the best discriminatory power for early diabetes screening and prediction (C-statistics of 0.833, 0.846, and 0.899 for the primary cohort, validation cohort, and prediction cohort, respectively). The sensitivity and specificity of the nomogram for prediction of 3-year incident diabetes were 0.827 and 0.807, respectively.
conclusionsThis study presents alternative radiomics markers that have potential for use in screening for undiagnosed type 2 diabetes and prediction of 3-year incident diabetes. KEY POINTS: • CT images may provide useful information to evaluate the risk of developing diabetes. • Radiomics score for diabetes prediction is based on subtle changes of abdominal organs detected by CT. • The radiomics signature of pancreas, a combination of five features of CT images, is efficient for early diabetes screening and prediction of future diabetes (AUC > 0.8).
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