ReviewWorld journal of radiology2025
Diffusion-weighted magnetic resonance imaging of the pancreas: A narrative review.
Review in World journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diffusion-weighted magnetic resonance imaging (DWI) has become an essential tool in the field of pancreatic magnetic resonance imaging, enabling the detection, characterization, prediction, and evaluation of pancreatic diseases. In this article, we review the acquisition parameters, postprocessing techniques, and quantitative methods utilized in pancreatic DWI. Various postprocessing models, including monoexponential, biexponential, stretched exponential and non-Gaussian kurtosis models, as well as deep learning networks, have been used to assess the clinical utility of these models in diagnosing pancreatic diseases. The single-shot echo-planar imaging sequence is the most commonly used sequence for DWI data acquisition in clinical settings, and the apparent diffusion coefficient (ADC) calculated using the monoexponential model is the most widely used quantitative parameter in clinical practice. The repeatability threshold for the ADC of a normal pancreas is 37% for test-retest scans, but the repeatability threshold for pancreatic tumors needs to be further investigated. Complex postprocessing models exploring novel DWI-based biomarkers beyond ADC to assess histological features, and artificial intelligence in DWI postprocessing and data analyses hold promise in the diagnosis of pancreatic diseases. Future work should focus on standardizing protocols, conducting multicentre studies, and exploring variety of methods to improve the accuracy of quantitative DWI results to increase the clinical effectiveness of DWI in patients with pancreatic diseases.
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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 Socratic graph.