Deep Learning Image Reconstruction for Abdominal CT of Hepatocellular Carcinoma Compared With 3-TESLA MRI

Brief summary (registry, in English)

New algorithms for processing CT acquisitions, based on artificial intelligence, have been reported to improve acquisition quality. Thats' why it's possible to imagine that new scan post-processing algorithms enable better detection and characterization of hepatocellular carcinoma lesions than with standard reconstructions. DLIR reconstructions could even match with MRI detection. The aim of the study is to compare the detection and characterization of hepatic lesions according to the LI-RADS classification in CT with DLIR artificial intelligence reconstruction, compared with ASIR-V reconstruction and the gold standard of MRI.

What you commit to

• Study type: Observational
• Participants enrolled: 50
• From 23 Feb 2023 to the primary completion date, 23 Jun 2023
• 1 site in 1 country
• Visits and tests: ask the trial team, the registry does not list them

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Who the study is looking for

Age in the registry: 18 years to - · Sex: All

Full criteria on ClinicalTrials.gov

Sites (1)

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