High Resolution HBA-MRI Using Deep Learning Reconstruction

N/AUnknownNCT05182099

Seoul National University Hospital52 enrolled

Overview

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.

Study Type

INTERVENTIONAL

Allocation

NON_RANDOMIZED

Purpose

DIAGNOSTIC

Masking

SINGLE

Enrollment

Conditions

Liver Diseases Magnetic Resonance Imaging Deep Learning

Interventions

Liver MRIDIAGNOSTIC_TEST

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.

Eligibility

Sex: ALLMin age: 20 Years

Medical Language ↔ Plain English

Inclusion Criteria: * older than 20 years old * scheduled for Gd-EOB-DTPA enhanced liver MRI at a 3T scanner (Premier, GE Healthcare) in our institution * signed informed consent Exclusion Criteria: * younger than 20 years old * any absolute/relative contrast indication of Gd-EOB-DTPA enhanced MRI * history of transient dyspnea after Gd-EOB-DTPA administration

Locations (1)

Seoul National University Hospital

Seoul, South Korea

Outcomes

Primary Outcomes

Overall image quality of arterial phase

qualitative assessment of arterial phase on a five point scale (highest score indicates better image quality)

Time frame: 3 months after enrollment completion

Data from ClinicalTrials.gov

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