MR Fingerprinting: A Novel Sequence Applied to Neuroimaging
| Status: | Recruiting |
|---|---|
| Conditions: | Neurology |
| Therapuetic Areas: | Neurology |
| Healthy: | No |
| Age Range: | 18 - 99 |
| Updated: | 2/8/2019 |
| Start Date: | March 2019 |
| End Date: | March 2023 |
| Contact: | Jasmin Merhout |
| Email: | jasmin_merhout@med.unc.edu |
| Phone: | 9849748848 |
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.
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.
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.
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.
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.
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