ReviewAbdominal radiology (New York)2026
Beyond morphology: functional imaging of the liver with gadoxetic acid-enhanced magnetic resonance imaging.
Review in Abdominal radiology (New York), 2026. 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.
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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.
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Authors and funding
10 authors.
Funding
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Abstract
Chronic liver diseases (CLD) are highly prevalent. Early diagnosis and staging of hepatic dysfunction are essential for optimal treatment decisions. While conventional imaging primarily evaluates morphology and focal liver lesions, gadoxetic acid (GA)-enhanced magnetic resonance imaging (MRI) provides additional functional information by assessing hepatocellular uptake and biliary excretion. Hepatocyte uptake depends largely on sinusoidal membrane transporters (OATP1B1/1B3), while excretion into bile canaliculi is mediated by MRP2. In liver dysfunction and cirrhosis, both processes may be impaired, resulting in measurable changes on hepatobiliary phase (HBP). This review summarizes the biological rationale, MRI protocol, and quantitative indices, including RLE, REI, HUI, rHUI, SIR, CUI, LSI, as well as the qualitative Functional Liver Imaging Score (FLIS). It also highlights key clinical applications, including prognostication in advanced CLD, preoperative risk stratification for post-hepatectomy liver failure, evaluation in the setting of embolization and locoregional therapies, and transplant assessment, along with emerging roles in metabolic dysfunction-associated steatotic liver disease. Finally, future directions are discussed, including T1 mapping and AI-based whole-liver quantification.
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Registered trials
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