ArticlePancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]2023
Artificial intelligence assisted whole organ pancreatic fat estimation on magnetic resonance imaging and correlation with pancreas attenuation on computed tomography.
Article in Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.], 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence-based models for quantification of intra-pancreatic fat deposition and their clinical relevance: a systematic review of imaging studies.European radiology · 2026Pooled it
- Intrapancreatic Fat and Risk of Pancreatic Ductal Adenocarcinoma-Pathophysiology, Clinical Implications, and Future Directions.International journal of molecular sciences · 2026Review
- Emerging Issue - Fatty Pancreas in Pancreatic Cystic Neoplasms: Results of a Matched Case-Control Study.Digestive diseases and sciences · 2026Article
- Pancreatic Steatosis and Survival Outcomes in Pancreatic Ductal Adenocarcinoma: A Systematic Review of the Current Evidence.Diagnostics (Basel, Switzerland) · 2026Review
- Development and validation of a fully automated transformer-based 3D framework for pancreatic fat quantification in pancreatic steatosis.European journal of radiology open · 2026Article
- Prevalence and Association of Liver Steatosis and Non-Alcoholic Pancreatic Steatosis in Very High Cardiovascular Risk.Diseases (Basel, Switzerland) · 2026Article
- The Fatty Pancreas: Current Evidence, Treatment Implications, and Future Directions.Gastro hep advances · 2026Review
- A dual self-attentive transformer U-Net model for precise pancreatic segmentation and fat fraction estimation.BMC medical imaging · 2025Article
- Significance of Pancreatic Steatosis as a Predictor of New-Onset Diabetes Mellitus Following Pancreatectomy.Pancreas · 2025Article
- The exposome as a target for primary prevention and a tool for early detection of pancreatic cancer.Best practice & research. Clinical gastroenterology · 2025Review
- Association between intra-pancreatic fat deposition and diseases of the exocrine pancreas: A narrative review.World journal of gastroenterology · 2025Review
- Changes in pancreatic steatosis by computed tomography 24 months after sleeve gastrectomy in youth with severe obesity.Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery · 2025Article
- Multiparametric quantitative MRI of healthy adult pancreas: correlations with gender and age.Frontiers in gastroenterology (Lausanne, Switzerland) · 2024Article
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Abstract
backgroundFatty pancreas is associated with inflammatory and neoplastic pancreatic diseases. Magnetic resonance imaging (MRI) is the diagnostic modality of choice for measuring pancreatic fat. Measurements typically use regions of interest limited by sampling and variability. We have previously described an artificial intelligence (AI)-aided approach for whole pancreas fat estimation on computed tomography (CT). In this study, we aimed to assess the correlation between whole pancreas MRI proton-density fat fraction (MR-PDFF) and CT attenuation.
methodsWe identified patients without pancreatic disease who underwent both MRI and CT between January 1, 2015 and June 1, 2020. 158 paired MRI and CT scans were available for pancreas segmentation using an iteratively trained convolutional neural network (CNN) with manual correction. Boxplots were generated to visualize slice-by-slice variability in 2D-axial slice MR-PDFF. Correlation between whole pancreas MR-PDFF and age, BMI, hepatic fat and pancreas CT-Hounsfield Unit (CT-HU) was assessed.
resultsMean pancreatic MR-PDFF showed a strong inverse correlation (Spearman -0.755) with mean CT-HU. MR-PDFF was higher in males (25.22 vs 20.87; p = 0.0015) and in subjects with diabetes mellitus (25.95 vs 22.17; p = 0.0324), and was positively correlated with age and BMI. The pancreatic 2D-axial slice-to-slice MR-PDFF variability increased with increasing mean whole pancreas MR-PDFF (Spearman 0.51; p < 0.0001).
conclusionOur study demonstrates a strong inverse correlation between whole pancreas MR-PDFF and CT-HU, indicating that both imaging modalities can be used to assess pancreatic fat. 2D-axial pancreas MR-PDFF is variable across slices, underscoring the need for AI-aided whole-organ measurements for objective and reproducible estimation of pancreatic fat.
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