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

NCT ID: NCT06037343

Last Updated: 2025-02-19

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

50 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-02-23

Study Completion Date

2023-12-30

Brief Summary

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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.

Detailed Description

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Conditions

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Hepatocellular Carcinoma

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

RETROSPECTIVE

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Central Hospital, Nancy, France

OTHER

Sponsor Role lead

Responsible Party

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Valérie LAURENT

Principal Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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CHRU de Nancy

Nancy, , France

Site Status

Countries

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France

Other Identifiers

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2023PI111

Identifier Type: -

Identifier Source: org_study_id

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