Deep learning image reconstruction improves visualization of arterial phase hyperenhancement and washout appearance on dual-energy CT for hepatocellular carcinoma: a non-inferiority study
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The authors aimed to assess the effectiveness of deep learning image reconstruction (DLIR) in enhancing image quality for dual-energy CT (DECT) in the detection of hepatocellular carcinoma (HCC) features, specifically arterial phase hyperenhancement and washout appearance. Their findings indicate that the DLIR-H/50-keV protocol significantly improves image quality and is non-inferior to MRI for identifying key HCC characteristics, suggesting it as a valuable alternative in settings with limited MRI availability.
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