ArticleHealthcare (Basel, Switzerland)2022
Quantitative MRI of Pancreatic Cystic Lesions: A New Diagnostic Approach.
Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed, 6 citations in OpenAlex.
- Radiomics and artificial intelligence in pancreatic cyst characterization: future or fiction?Abdominal radiology (New York) · 2026Review
- The Role of Magnetic Resonance Imaging (MRI) in the Diagnosis of Pancreatic Cystic Lesions (PCLs).Diagnostics (Basel, Switzerland) · 2023Review
- Pancreatic Cyst Management: A Multimodal and Interdisciplinary Approach.Journal of radiological scienceArticle
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The commonly used magnetic resonance (MRI) criteria can be insufficient for discriminating mucinous from non-mucinous pancreatic cystic lesions (PCLs). The histological differences between PCLs' fluid composition may be reflected in MRI images, but cannot be assessed by visual evaluation alone. We investigate whether additional MRI quantitative parameters such as signal intensity measurements (SIMs) and radiomics texture analysis (TA) can aid the differentiation between mucinous and non-mucinous PCLs. Fifty-nine PCLs (mucinous,
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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 OpenQuestion graph.