Chapel Hill, North Carolina 27599


Purpose:

Magnetic Resonance Imaging (MRI) has become one of most important medical imaging tools over the past 30 years because it is non-invasive, requires no ionizing radiation, and provides exquisite images of soft tissues and anatomic structures with many tissue/disease specific contrasts. While MRI has served the community well for many years, it is increasingly clear that it also has significant limitations. One of the principle limitations is the lack of quantitative information for tissue/structure characterization. The current paradigm of MRI is to use a set of scanner settings to generate an image "weighted" by a specific MR contrast mechanism (physical parameter), where it is hoped that variations in the parameter will be accentuated. However, without quantitative knowledge of the parameters, the final image contrast may depend on many factors, which complicates image interpretation and diagnostic performance. Quantitative measurement can provide a great deal of information about tissue properties and pathological conditions, since these parameters ultimately determine the contrast that is observed in conventional images.


Study summary:

The purpose of this study is to evaluate novel quantitative MRI techniques in clinical studies to determine whether they can provide better, faster and more useful information for clinical diagnosis. Quantitative MRI has been a continuous interest in the MRI community, but extremely challenging due to long acquisition times and sensitivity to motion. Recently, the investigators have introduced a novel MRI data acquisition approach, namely MR Fingerprinting (MRF), for simultaneous measurement of several important parameters in a single MRI scan. In this study, the investigators propose to apply MR Fingerprinting at UNC and evaluate its performance for different neurological diseases. The investigators hypothesize that the quantitative MR imaging technique will lead to improved tissue characterization and diagnosis.


Criteria:

Inclusion Criteria: - The study will include English-speaking patients that are already scheduled to undergo a clinical neurological MRI for diagnostic purposes. Exclusion Criteria: - Pregnant women will be excluded.


NCT ID:

NCT03800537


Primary Contact:

Principal Investigator
Yueh Z Lee, MD, PhD
University of North Carolina, Chapel Hill

Jasmin Merhout
Phone: 9849748848
Email: jasmin_merhout@med.unc.edu


Backup Contact:

Email: terry_hartman@med.unc.edu
Terry Hartman, MPH, MS, CCRC
Phone: 9199664997


Location Contact:

Chapel Hill, North Carolina 27599
United States

Jasmin Merhout

Site Status: Recruiting


Data Source: ClinicalTrials.gov

Date Processed: October 09, 2019

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