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High Resolution HBA-MRI Using Deep Learning Reconstruction

Primary Purpose

Liver Diseases, Magnetic Resonance Imaging, Deep Learning

Status
Active
Phase
Not Applicable
Locations
Korea, Republic of
Study Type
Interventional
Intervention
Liver MRI
Sponsored by
Seoul National University Hospital
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Liver Diseases

Eligibility Criteria

20 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

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

Sites / Locations

  • Seoul National University Hospital

Arms of the Study

Arm 1

Arm 2

Arm Type

Other

Active Comparator

Arm Label

Conventional image reconstruction

Deep learning image reconstruction

Arm Description

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.

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.

Outcomes

Primary Outcome Measures

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

Secondary Outcome Measures

Full Information

First Posted
December 16, 2021
Last Updated
May 15, 2023
Sponsor
Seoul National University Hospital
Collaborators
GE Healthcare
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1. Study Identification

Unique Protocol Identification Number
NCT05182099
Brief Title
High Resolution HBA-MRI Using Deep Learning Reconstruction
Official Title
AIRTM Deep Learning Reconstruction of Abdominal High Resolution Gd-EOB-DTPA Enhanced MRI in Patients With Suspicious Focal Liver Lesions: Image Quality Assessment
Study Type
Interventional

2. Study Status

Record Verification Date
May 2023
Overall Recruitment Status
Active, not recruiting
Study Start Date
January 10, 2022 (Actual)
Primary Completion Date
March 30, 2022 (Actual)
Study Completion Date
September 30, 2023 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Seoul National University Hospital
Collaborators
GE Healthcare

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes

5. Study Description

Brief 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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Liver Diseases, Magnetic Resonance Imaging, Deep Learning

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
Outcomes Assessor
Masking Description
blinded to the reconstruction types
Allocation
Non-Randomized
Enrollment
52 (Actual)

8. Arms, Groups, and Interventions

Arm Title
Conventional image reconstruction
Arm Type
Other
Arm Description
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.
Arm Title
Deep learning image reconstruction
Arm Type
Active Comparator
Arm Description
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.
Intervention Type
Diagnostic Test
Intervention Name(s)
Liver MRI
Intervention Description
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.
Primary Outcome Measure Information:
Title
Overall image quality of arterial phase
Description
qualitative assessment of arterial phase on a five point scale (highest score indicates better image quality)
Time Frame
3 months after enrollment completion

10. Eligibility

Sex
All
Minimum Age & Unit of Time
20 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
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
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Jeong Min Lee, MD
Organizational Affiliation
Seoul National University Hospital
Official's Role
Principal Investigator
Facility Information:
Facility Name
Seoul National University Hospital
City
Seoul
Country
Korea, Republic of

12. IPD Sharing Statement

Plan to Share IPD
No

Learn more about this trial

High Resolution HBA-MRI Using Deep Learning Reconstruction

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