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

Central Hospital, Nancy, France

Status: Completed

Conditions: Hepatocellular Carcinoma

Study type: Observational

Funder types: Other

Identifiers

NCT06037343

2023PI111

Details and patient eligibility

About

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.

Enrollment: 50 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

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