Surgery – Diagnostic testing – Detecting nuclear – electromagnetic – or ultrasonic radiation
Patent
1998-05-11
2000-06-06
Smith, Ruth S.
Surgery
Diagnostic testing
Detecting nuclear, electromagnetic, or ultrasonic radiation
600411, 600509, 600534, 324309, A61B 5055
Patent
active
060730412
DESCRIPTION:
BRIEF SUMMARY
TECHNICAL FIELD
This invention relates to improved magnetic resonance imaging techniques.
BACKGROUND
A recent development in magnetic resonance imaging (MRI) is functional magnetic resonance imaging (fMRI). fMRI relies on the detection of localized changes in signal intensity in T2*-weighted (or T2-weighted) images. For example, MRI may non-invasively map human cortical function without the use of exogenous contrast agents by relying on the blood oxygenation level dependent (BOLD) contrast due to the ability of deoxyhemoglobin to act as an endogenous paramagnetic contrast agent. Therefore, changes in the local concentration of deoxyhemoglobin within the brain lead to alterations in the magnetic resonance signal. Regional neuronal activation within the cerebral cortex leads to an increase in blood flow without a commensurate increase in oxygen extraction. Consequently, the capillary and venous deoxyhemoglobin concentrations decrease, leading to a localized increase in T2* and T2. This increase is reflected as an elevation of intensity in T2*-weighted and T2-weighted MR images. With its high contrast, T2*-weighted imaging is the predominant technique currently employed. It was initially applied to delineate the activity in the human visual cortex, motor cortex, and areas in the frontal cortex during speech.
Although application of fMRI in delineating cortical activity in the last few years has been remarkable, ideally, only intensity changes related to neuronal activation should be detected. In practice, many other sources contribute to image-to-image intensity fluctuation, leading to artifacts in the resultant functional maps. Thus, motion artifacts continue to be a major hindrance to the accurate detection of neuronal activity.
Sources of motion artifacts include system instability, subject movement, as well as normal physiological motions. Artifacts due to gross subject motion have been recognized as one possible source of false activation, and spatial registration of images can be beneficial in reducing these artifacts. Gross involuntary subject motion can be minimized by physically constraining the subject. Other physiology related motions, such as brain motion, respiration, and cardiac pulsation, are more difficult to compensate for and cannot be eliminated in a straightforward manner. These types of motion and their effects will be referred to as physiological fluctuation or physiological effect.
SUMMARY OF THE INVENTION
The invention is a technique for removal of signal fluctuation due to physiological factors such as (but not limited to) respiration and cardiac pulsation. The technique comprises simultaneous measurement of physiological motion, such as respiration-related abdominal motion or cardiac pulse or both, during fMRI data acquisition; then, in post processing steps, imaging data are retrospectively ordered into unit physiological cycles (e.g., respiratory and cardiac cycles), after which the physiological effects are estimated and removed from the fMRI data.
A preferred embodiment involves extraction of the physiological profiles directly from the fMRI data; therefore, no external monitoring of physiology is required. The latter approach avoids problems associated with measurement of physiological parameters disturbing the static magnetic field and also the fMRI signal unless proper filtering (through a filter plate) or special fiber connections are utilized. Moreover, direct monitoring of physiological parameters may not be readily achieved for every subject.
BRIEF DESCRIPTION OF THE DRAWING
FIG. 1a shows the time course of the phase of a representative k-space point from a rapid, low flip angle pulsed NMR imaging ("FLASH") data set plotted against time.
FIG. 1b shows the time course of the magnitude of the representative k-space point of FIG. 1a.
FIG. 2a shows the phase of the k-space data of FIG. 1a plotted against the respiratory cycle, including a solid curve obtained from nonlinear fitting of the plotted data.
FIG. 2b shows the magnitude of the k-space data of FIG. 1b plotte
REFERENCES:
Noll et al, Theory, Simulation, and Compensation of Physiological Motion Artifacts in Functional MRI, Proceedings pf the International Conference on Image Processing, IEEE, pp. 40-44, Nov. 1994.
Hu et al "Reduction of Signal Fluctuation in Functional MRI Using Navigator Echoes", Magnetic Resonance in Medicine, vol. 31, No. 5, pp. 495-503, May 1994.
Bandettini, P.A., et al., "Processing Strategies for Time-Course Data Sets in Functional MRI of the Human Brain", Magnetic Resonance in Medicine, No. 2, pp. 161-173, (Aug. 30, 1993).
Hu, X., et al., "Retrospective Estimation and Correction of Physiological Fluctuation in Functional MRI", MRM, No. 34, pp. 201-212, (1995).
Kim, W.S., et al., "Extraction of Cardiac and Respiratory Motion Cycles by Use of Projection Data and Its Applications to NMR Imaging", Magnetic Resonance in Medicine, No. 1, pp. 25-37, (Jan. 13, 1990).
Erhard Peter W.
Hu Xiaoping
Le Tuong Huu
Parrish Todd B.
Regents of the University of Minnesota
Smith Ruth S.
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