Case Western Reserve University

Anagha Deshmane

Mark A Griswold

Jeffrey L Sunshine

Vikas Gulani

Dan Ma

Yun Jiang

Chaitra Badve

Nicole Seiberlich

Example embodiments associated with characterizing a sample using NMR fingerprinting are described. One example NMR apparatus includes an NMR logic that repetitively and variably samples a (k, t, E) space associated with an object to acquire a set of NMR signals that are associated with different points in the (k, t, E) space. Sampling is performed with t and/or E varying in a non-constant way. The NMR apparatus may also include a signal logic that produces an NMR signal evolution from the NMR signals and a characterization logic that characterizes a tissue in the object as a result of comparing acquired signals to reference signals. Example embodiments facilitate distinguishing diseased tissue from healthy tissue based on tissue component fractions identified using the NMR fingerprinting.

Distinguishing diseased tissue from healthy tissue based on tissue component fractions using magnetic resonance fingerprinting (MRF)

A system and method is provided for correcting receiver bias during quantitative proton density mapping with magnetic resonance fingerprinting (MRF). The method comprises acquiring MRF data from a region of interest in a subject by performing a pulse sequence using a series of varied sequence blocks to elicit a series of signal evolutions. The method further comprises comparing the MRF data to a MRF dictionary to simultaneously map proton density and another tissue property from the region of interest, the proton density map having a proton density signal and a receiver sensitivity profile signal. The method also includes quantifying the proton density signal and the receiver sensitivity profile signal using parameters provided by the proton density map and the tissue property map, and generating a quantitative map from the region of interest based on the proton density signal.

System and method for proton density mapping and receiver bias correction using magnetic resonance fingerprinting (MRF)

Apparatus, methods, and other embodiments associated with NMR fingerprinting are described. One example NMR apparatus includes an NMR logic that repetitively and variably samples a (k, t, E) space associated with an object to acquire a set of NMR signals that are associated with different points in the (k, t, E) space. Sampling is performed with t and/or E varying in a non-constant way. The NMR apparatus may also include a signal logic that produces an NMR signal evolution from the NMR signals, and a characterization logic that characterizes a resonant species in the object as a result of comparing acquired signals to reference signals. The NMR signal evolution may be assigned to a cluster based on the characterization of the resonant species. Cluster overlay maps may be produced simultaneously based, at least in part, on the clustering. The clusters may be associated with different tissue types.

Nuclear magnetic resonance (NMR) fingerprinting tissue classification and image segmentation

Apparatus, methods, and other embodiments associated with magnetic resonance (MR) trajectory correcting using GRAPPA operator gridding (GROG) are described. One example method includes identifying an on angle or regular portion of a projection in an MR trajectory and then computing base GROG weights for that portion. The example method includes identifying a shift direction and a shift amount for the projection. The shift direction is configured to shift the projection towards a desired point in k-space and the shift amount is configured to shift the projection by a desired amount in the shift direction. With a shift direction and amount available, the example method corrects for a gradient delay by manipulating the MR source signal data using the shift direction and the shift amount. In one embodiment, a gradient delay can be determined and used to calibrate an MRI apparatus.

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Cleveland Heights, OH, United States of America

Anagha Deshmane