Infiltration of Gadolinium Injection in Brain MR Scans Using Artificial Intelligence

April 8, 2022 updated by: James G. Pipe, Mayo Clinic

Detection of the Occurrence of Infiltration of Gadolinium Injection in Brain MR Scans Using Artificial Intelligence

The purpose of this research is to develop machine learning algorithms to analyze images from brain MRI to confirm that contrast agent has been correctly administered.

Study Overview

Status

Completed

Study Type

Observational

Enrollment (Actual)

40

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

    • Minnesota
      • Rochester, Minnesota, United States, 55905
        • Mayo Clinic Rochester

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

18 years and older (ADULT, OLDER_ADULT)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Adults undergoing MR brain without and with IV contrast examination as part of their care plan.

Description

Inclusion Criteria:

  • Patients undergoing a MR brain without and with contrast examination on any GE or Siemens 1.5T and 3T MRI system within Mayo Clinic, Rochester, as part of their care plan.

Exclusion Criteria:

  • None

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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Detection of Infiltration of Gadolinium contrast agent into tissue and muscle using artificial intelligence model
Time Frame: 2 months
Correct detection of the presence of infiltration of Gadolinium contrast agent into tissue and muscleusing an artificial intelligence model. This outcome will be determined by measuring the difference in signal enhancement in the nasal mucosa or the lack of signal enhancement within the nasal mucosa.
2 months

Collaborators and Investigators

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

Sponsor

Investigators

  • Principal Investigator: James Pipe, PhD, Mayo Clinic

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

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)

March 14, 2022

Primary Completion (ACTUAL)

April 5, 2022

Study Completion (ACTUAL)

April 5, 2022

Study Registration Dates

First Submitted

January 19, 2022

First Submitted That Met QC Criteria

February 8, 2022

First Posted (ACTUAL)

February 11, 2022

Study Record Updates

Last Update Posted (ACTUAL)

April 11, 2022

Last Update Submitted That Met QC Criteria

April 8, 2022

Last Verified

April 1, 2022

More Information

Terms related to this study

Other Study ID Numbers

  • 21-010301

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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