High Resolution HBA-MRI Using Deep Learning Reconstruction

May 15, 2023 updated by: Jeong Min Lee, Seoul National University Hospital

AIRTM Deep Learning Reconstruction of Abdominal High Resolution Gd-EOB-DTPA Enhanced MRI in Patients With Suspicious Focal Liver Lesions: Image Quality Assessment

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 Overview

Status

Active, not recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Actual)

52

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

20 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Non-Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Other: Conventional image reconstruction
Gd-EOB-DTPA enhanced liver MRI images are reconstructed using a conventional image reconstruction algorithm. It is automatically generated from a MRI console after the examination.
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.
Active Comparator: Deep learning image reconstruction

Gd-EOB-DTPA enhanced liver MRI images are reconstructed using a deep learning based image reconstruction algorithm (AIRTM). It is additionally generated aside from the conventional images.

For obtaining the images, we will use the same MRI raw data which is used for conventional image reconstruction.
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Overall image quality of arterial phase
Time Frame: 3 months after enrollment completion
qualitative assessment of arterial phase on a five point scale (highest score indicates better image quality)
3 months after enrollment completion

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Seoul National University Hospital

Collaborators

GE Healthcare

Investigators

  • Principal Investigator: Jeong Min Lee, MD, Seoul National University Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 10, 2022

Primary Completion (Actual)

March 30, 2022

Study Completion (Anticipated)

September 30, 2023

Study Registration Dates

First Submitted

December 16, 2021

First Submitted That Met QC Criteria

January 6, 2022

First Posted (Actual)

January 10, 2022

Study Record Updates

Last Update Posted (Actual)

May 16, 2023

Last Update Submitted That Met QC Criteria

May 15, 2023

Last Verified

May 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2021-3044

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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