AI-Assisted Low-Dose Gadolinium Breast MRI for Breast Cancer

Overseen By Quenteeria Mooney, BS

Age: 18+

Sex: Female

Trial Phase: Phase 1

Sponsor: University of Alabama at Birmingham

Disqualifiers: Non-female, Pregnant, Recurrent cancer, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 2

20 Participants Needed

Trial Summary

What is the purpose of this trial?

The purpose of this study is to evaluate the ability of AI to correctly aid in characterization of benign and malignant lesions even when a low dose of gadolinium is administered. This study is relevant for several reasons, most notably being the reduction of MRI dose and decreased gadolinium deposition in the brain. In addition, use of AI may provide increased sensitivity and specificity for the radiologist evaluating a breast MRI exam. Half of the population will have benign pathologies and the other half will have malignant pathologies.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It is best to discuss this with the trial coordinators or your doctor.

What data supports the effectiveness of the treatment Reduced Dose Gadolinium Breast MRI with AI for breast cancer?

Research shows that using AI in breast MRI can help identify areas of concern that might develop into cancer, potentially allowing for earlier detection and reducing the need for frequent screenings. In one study, AI identified regions that matched future tumors in 52% of cases, and reevaluating these areas could have led to earlier detection in up to 33% of cases. ^{1 2 3 4 5}

How does the AI-Assisted Low-Dose Gadolinium Breast MRI treatment differ from other breast cancer treatments?

This treatment is unique because it uses artificial intelligence to enhance MRI images, allowing for a reduced dose of gadolinium (a contrast agent used in MRI scans) while maintaining image quality. This approach aims to minimize the amount of contrast agent needed, potentially reducing side effects and improving patient safety compared to standard MRI procedures. ^{2 3 5 6 7}

Research Team

Stefanie Woodard, MD

Principal Investigator

University of Alabama at Birmingham

Eligibility Criteria

This trial is for women aged 18-99 who need a breast MRI, either because they're being screened or have known breast lesions. It's open to those with new primary breast cancer but not recurrent cases. Participants must be able to lie still for an hour and can't join if pregnant, breastfeeding, under 18, have had neoadjuvant chemotherapy, or can't undergo MRI.

Inclusion Criteria

I am referred for an MRI for reasons not related to cancer.

You have had a previous exam that showed abnormal growth or changes in your body.

I am willing and able to join the trial.

Exclusion Criteria

I am not female.

I cannot stay still for an hour on an imaging table.

I am currently pregnant or breastfeeding.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Initial MRI Exam

Participants undergo an initial MRI with a regular dose of gadolinium

1 week

1 visit (in-person)

Reduced Dose MRI Exam

Participants undergo a second MRI with a ¼ dose of gadolinium at least 14 days after the initial exam

2 weeks

1 visit (in-person)

Follow-up

Participants are monitored for safety and effectiveness after MRI exams

4 weeks

Treatment Details

Interventions

• Reduced Dose Gadolinium Breast MRI with AI
• Standard of Care Gadolinium Breast MRI

Trial Overview The study compares two types of breast MRIs: one uses a quarter dose of gadolinium contrast with AI assistance; the other is the standard full-dose MRI without AI. The goal is to see if AI can help diagnose benign and malignant lesions accurately even with less contrast agent.

Participant Groups

Group I: Subjects with enhancing breast lesions Experimental Treatment 2 Interventions

Who Is Running the Clinical Trial?

University of Alabama at Birmingham

Lead Sponsor

Trials

1,677

Recruited

2,458,000+

Bracco Corporate

Industry Sponsor

Trials

7

Recruited

580+

Findings from Research

In a study of 45 breast cancer patients and 35 benign tumor patients, key MRI indicators for diagnosing breast cancer were identified, including tumor edge features, time-signal intensity curve (TIC) types, and apparent diffusion coefficient (ADC) values at b=500 s/mm2.

The combination of conventional MRI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI provided the best diagnostic approach, with magnetic resonance spectroscopy (MRS) serving as a useful supplementary tool for challenging cases.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Optimization of diagnosis indicator selection and inspection plan by 3.0T MRI in breast cancer]. Jiang, Z., Wang, Y., He, Z., et al.[2015]

References

1. United States pubmed.ncbi.nlm.nih.gov

Predicting breast cancer with AI for individual risk-adjusted MRI screening and early detection. [2023]

2. China pubmed.ncbi.nlm.nih.gov

[Optimization of diagnosis indicator selection and inspection plan by 3.0T MRI in breast cancer]. [2015]

3. Switzerland pubmed.ncbi.nlm.nih.gov

Development and validation of a deep learning model for breast lesion segmentation and characterization in multiparametric MRI. [2022]

4. Switzerland pubmed.ncbi.nlm.nih.gov

'Earlier than Early' Detection of Breast Cancer in Israeli BRCA Mutation Carriers Applying AI-Based Analysis to Consecutive MRI Scans. [2023]

5. England pubmed.ncbi.nlm.nih.gov

Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging. [2021]

6. United States pubmed.ncbi.nlm.nih.gov

Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images. [2023]

7. England pubmed.ncbi.nlm.nih.gov

A systematic review of the effectiveness of magnetic resonance imaging (MRI) as an addition to mammography and ultrasound in screening young women at high risk of breast cancer. [2022]