Feasibility of Gadolinium Contrast Reduced Brain MRI: the Potential of Deep Learning

NCT ID: NCT06462924

Last Updated: 2025-02-05

Basic Information

• Recruitment Status: WITHDRAWN
• Clinical Phase: PHASE1
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-08-30
• Study Completion Date: 2024-09-15

Brief Summary

MRI scans were performed using 3 different 1.5T scanners with an eight-channel head coils. Following a 3D pre-contrast T1w scan, a low-dose contrast-enhanced 3D T1w scan was obtained using 20% (0.02 mmol/kg) of the standard dosage of gadoterate meglumine.

The subjects were immediately administered the remaining 80% (0.08 mmol/kg) of the contrast agent to reach the standard dose of 0.1 mmol/kg, which served as a training ground truth for further quantitative assessment. All three acquisitions were performed during a single imaging session, with no additional gadolinium dose administered above the standard protocol.

Conditions

Artificial Intelligence; Deep Learning

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

DeepGad

The dataset comprises a total of 500 patients, with 300 patients used for model training and 200 patients reserved for model testing. Each patient had approximately 350 2D brain slices of the coregistered 3D volumes excluding the five slices at the base and five slices at the top of the acquired volume due to their low signal-to-noise ratio (SNR). For robustness and to avoid overfitting, standard DL data augmentation techniques consisting of eight types of transformations were applied to each case in the training set.

Group Type: EXPERIMENTAL

DeepGad

Intervention Type: DEVICE

Using the pre-contrast and low-dose Contrast-Enhanced Magnetic Resonance (CE-MRI) images as input and the true full-dose CE-MRI images as the ground truth. the Cycle GAN deep network (DeepGad), was trained to reconstruct the full-dose CE-MRI images from low-dose CE-MRI images.

Interventions

DeepGad

Using the pre-contrast and low-dose Contrast-Enhanced Magnetic Resonance (CE-MRI) images as input and the true full-dose CE-MRI images as the ground truth. the Cycle GAN deep network (DeepGad), was trained to reconstruct the full-dose CE-MRI images from low-dose CE-MRI images.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

1. Clinical indications for imaging with a contrast-enhanced 3D-T1w MRI sequence including tumor suspicion, postoperative tumor follow-up, multiple sclerosis, routine brain imaging, etc.,

2. no plan for dynamic contrast administration or deviation from the standard dose of 0.1 mmol/kg body weight (e.g., sella imaging, magnetic resonance angiography),

3. no clinical contraindications to imaging prolongation (i.e., emergency, poor patient condition).

Exclusion Criteria

1. prominent image artifacts,

2. incomplete study sequences (e.g., early termination)

3. errors related to contrast agent administration.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

DeepMeds

INDUSTRY

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Other Identifiers

DG53024

Identifier Type: -

Identifier Source: org_study_id