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.
Study Type
OBSERVATIONAL
Enrollment
50
CHRU de Nancy
Nancy, France
Lesion size in mm
Time frame: Through study completion, an average of 1 year
Hypervascular appearance of lesion
Qualitative measurement: presence or absence of hypervascular lesion
Time frame: Through study completion an average of 1 year
Hypervascular capsule
Qualitative measurement : presence or absence of hypervascular capsule
Time frame: Through study completion an average of 1 year
Infiltrative nature Classification of the hepatic lesion by LI-RADS in MRI
Time frame: Through study completion an average of 1 year
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