Hepatocellular Carcinoma
Conditions
Keywords
Hepatocellular carcinoma, DLIR CT, ASIR reconstruction
Brief summary
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.
Interventions
None listed
Sponsors
Central Hospital, Nancy, France
Study design
Observational model
CASE_ONLY
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Inclusion criteria
* undergoing CT and MRI scans in the same week, with protocols dedicated to the detection of HCC lesions
Exclusion criteria
* imaging with radiological artefact
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Lesion size in mm | Through study completion, an average of 1 year | — |
| Hypervascular appearance of lesion | Through study completion an average of 1 year | Qualitative measurement: presence or absence of hypervascular lesion |
| Hypervascular capsule | Through study completion an average of 1 year | Qualitative measurement : presence or absence of hypervascular capsule |
Secondary
| Measure | Time frame |
|---|---|
| Infiltrative nature Classification of the hepatic lesion by LI-RADS in MRI | Through study completion an average of 1 year |
Countries
France
Outcome results
None listed