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High Resolution HBA-MRI Using Deep Learning Reconstruction

NCT05182099 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 52

Last updated 2023-05-16

No results posted yet for this study

Summary

This study aims to compare image qualities between conventionally reconstructed MRI sequences and deep-learning reconstructed MRI sequences from the same data in patients who undergo Gd-EOB-DTPA enhanced liver MRI. The AIRTM deep learning sequence is applicable for various MRI sequences including T2-weighted image (T2WI), T1-weighted image and diffusion-weighted image (DWI). We plan to perform intra-individual comparisons of the image qualities between two reconstructed image datasets.

Conditions

Interventions

DIAGNOSTIC_TEST

Liver MRI

Gd-EOB-DTPA enhanced MRI consists of T2-weighted image (T2WI), diffusion weighted image (DWI) and precontrast T1-weighted image (T1WI), dynamic T1WI (arterial, portal and transitional phases), and hepatobiliary phase.

Sponsors & Collaborators

  • GE Healthcare

    collaborator INDUSTRY

  • Seoul National University Hospital

    lead OTHER

Principal Investigators

  • Jeong Min Lee, MD · Seoul National University Hospital

Study Design

Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-01-10
Primary Completion
2022-03-30
Completion
2023-09-30

Countries

  • South Korea

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05182099 on ClinicalTrials.gov