Transcript
Document archive. Additional information can be found on the MRIware Homepage Last revision: December 30, 2006. Changes are listed at bottom.
Contents 1
Introduction
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The prototype implementation
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Applications
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Graphs
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ISMRM and HBM abstracts
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Publications
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Patent
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Links
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Example data sets 9.1 Double EOG with calibration signal, 18/9-2006 . . . . . . . . . . . . . . . . . . . .
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10 Archive history
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1 Introduction Non-MR signals can be encoded in MR raw data outside the region that becomes visible after image reconstruction. The technique resembles the widely known magstripe technique used for encoding soundtracks in movies outside the visible region. Charachteristics of the method: Surplus bandwidth of the scanner is used for high-quality recording of any signal (half the scanner bandwidth is not intended for anything but oversampling). 60 channels channels with kHz bandwidth can, for example, be recorded, on an 8-channel Siemens Trio system. Non-MR signals recorded in the scanner room becomes available to the image reconstruction computer real-time, thus allowing for feedback of e.g., joystick signals, motion sensor signals, physiologic recordings and EEG. Microsecond precision is readily available for demanding applications such as EEG-fMRI.
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Wireless interface to the scanner makes the method highly generic. Wiring provides additional bandwidth, if needed. When used for recording of electrophysiology, the method provides signals almost free of gradient switching artifacts. Residual artifacts from, e.g., eddy currents are easily filtered due to perfect syncronization of scanner and recorded EEG. The technique does not interfere with image reconstruction (linear or not) when oversampling is employed. In particular, it is compatible with parallel and spiral imaging, as well as RF intensive imaging. Storage of images and non-MR signals together, e.g. in PACS, is facilitated. So is analysis and storage of correlation maps.
2 The prototype implementation 8 amplitude modulated channels at individually selectable frequencies. Digital synthesis. 0-130 MHz, 0.1 Hz resolution. Parameter control and data previewing/surveillance via serial optical fiber PC interface. A gradient activity sensor (coil positioned near opening of scanner) interfaced to a samplehold circuit, provides sampling almost free of gradient artifacts even when ramp-sampling is performed. This saves bandwidth compared to non-triggered sampling, and allows for realtime viewing of nearly gradient-artifact free EEG. Residual artifacts are easily removed from the data recorded by the scanner (see HBM ’06 abstract). If the gradient activity trigger is not used, and ramp-sampling is employed, severe gradient artifacts occur, but they can be filtered very effectively due to the precise timing. This situation occurs in sequences where gradient activity is present almost continuously, e.g., for spiral EPI. Graphical user interface (GUI). Runs on Windows and Linux. Filters, frequencies and trigger timings are controlable via GUI. Data quality can be monitored real-time during scanning. Internally generated amplitude calibration and test signals. Design by Christian G. Hanson. Rights are independent of patent. Diagram of electronics The multi-frequency amplitude modulator Screendumps of GUI controlling modulator and providing real-time preview of aquired data: Frequency selection and filter/gain/trigger control..
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3 Applications The principle is generic and can be used for making the MR system aware of any signal recorded in the RF cabin, e.g., signals from pushbuttons, joysticks, temperature/motion sensors or physiologic monitoring equipment. It provides a simple way of implementing feedback to the MR acquisition system real-time. For the special case of making recordings that are compromised by gradient or RF activity, there are added benefits as described above. The most demanding of these examples is EEG/fMRI that is widely believed to gain importance in clinical practice and research, e.g., for the following reasons: The majority of patients where pre-surgical fMRI is relevant will have epileptic activity in their EEG potentially originating from the epileptogenic zone itself. Together with other MR modalities, simultaneous EEG/fMRI may improve risk assessment ahead of surgery. During the increasingly popular resting state experiments, EEG/fMRI provides monitoring of the subject state (sleep, closed eyes, eye-movement etc.) and useful modelling constraints. EEG can provide better modelling of activity in normal fMRI designs, e.g., by facilitating inclusion in the analysis of degree of attention and response characteristics. EEG/fMRI can be used for improved haemodynamic modelling, since EEG is not a vascular phenomenon, and has more temporal information.
4 Graphs Simple diagram of scanner and modulator. Fiber optical connection to PC is not shown (controls modulator and provides real-time signal viewing). Image reconstruction and signal extraction diagram Normal EPI sequence diagram Movie with eye movement and extracted EEG, EOG and calibration signals as well as corresponding correlation maps. Less illustrative, but more recent high quality movie with 2 EOG and 2 EEG channels and correponding correlation maps (full view).
5 ISMRM and HBM abstracts HBM ’05: Introduction of method ISMRM ’06: Hardware description ISMRM ’06: Image quality HBM ’06: EEG recording. Extracted data: EEG recorded at head positions F3-F4 HBM ’06: Poster. Summarises the EEG-setup.
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6 Publications JMRI manuscript in press. Proof of concept paper. The data are not acquired with the currently used version of the hardware. Corresponding figures.
7 Patent Version published after 18 months. Revised patent is pending.
8 Links MRIware – home of Magstripe MRI The place to look for updated information regarding the technique. Danish Research Centre for Magnetic Resonance (DRCMR) DRCMR publication list DRCMR annual reports Recent electrophysiology-MRI review. H:S innovation Tech transfer unit of the Copenhagen Hospital Corporation.
9 Example data sets 9.1 Double EOG with calibration signal, 18/9-2006 Redundant recording of physiological signals with opposite polarity provides a way to differentiate system noise common between channels from physiological noise (quality control). In the present case, the signal from one pair of pads positioned for EOG recording was redundantly measured in two channels. To do this, each pad was equipped with two carbon electrodes. Electrodes from both pads were twisted pairwise and connected to different channels, so that wire-loops were small and similar. A third pad was used for the reference electrode (ground) which was placed on the forehead. The position of this is not critical. A known 30 Hz calibration signal generated internally in the modulator were transmitted through a third channel. The subject was instructed to move the eyes between left and right self-paced interleaved with periods of rest. The periods of rest and eye movement were typically 5-10 seconds. Full speed EPI at 3 tesla was performed meanwhile. Movie showing one of the measured EOGs and the corresponding EPI time series. The imaging parameters can be found in the parameter file. Corresponding unfiltered DICOM images exported from the scanner. Series 8 and 9 are aquired with the modulator on and off, respectively (gzipped files in tar-archive). Extracted, unfiltered signals: EOG1, EOG2 and calibration signal.
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Same signals, EOG1, EOG2 and calibration signal, filtered with a simple algorithm removing noise that is common between images (typically from gradients that go undetected by the gradient trigger, e.g. slice selection gradients). The sampling bandwidth is approximately 500 Hz, but the physiological signals were lowpass filtered to 180 Hz in the modulator (adjustable. For other parameters, see modulator config file). Same filtered signals saved in a format that can easily be read using the provided Matlab function: Filtered signals and corresponding vector of sample times. Signals shown real-time on the PC controlling the modulator. A period with no scanning is followed by a period of scanning. Even though filtering is not employed for this real-time view, the EPI gradient artifacts are small compared to the EOG (left/right eye movement at all times). The reason is the gradient activity triggered sample-hold that very effectively prevents gradient induced noise from affecting the measurements. Without the trigger, the gradient noise would be orders of magnitude larger (but still easy to filter with this method). Raw data in k-space showing that the carrier signals have amplitude approximately equal to the peak MR signal in this demonstration. As seen in the signal spectrogram, this ensures that the reconstructed EOGs have a much higher signal to thermal noise ratio compared to the the MR images (approximately two orders of magnitude: The MR signal is barely visible in the spectrogram, even though it is still strongly peaked at times where the center of k-space is traversed). Such excessively strong carrier signals are not needed, but they illustrate well that 1. despite this there is little (if any) contamination of the MR images, 2. the receiver gain need not be changed due to the presence of the modulator, as weak carriers are sufficient due to the advantageous difference in distribution of signals: The carriers are localised in frequency whereas the MR signal is localised in time. Correlation maps showing that the EOG signals and eye region image intensities are correlated: normal FOV and double FOV images. The latter are reconstructed from the raw data without discarding the oversampled outer image regions. No fine tuning of the center frequency was performed. As the images are nevertheless free of signal contamination outside the intended regions, the frequency is probably near optimal anyway (there should preferably be an integer number of carrier oscillations within each readout period).
10 Archive history $Log: page.tex,v $ Revision 1.8 2006/12/30 22:34:02 larsh Major update to make the page fit in the MRIware framework. JMRI article added. Password Revision 1.7 2006/09/29 10:54:02 larsh Added example data: Double recorded EOG, mfam180906 Additional information can be found on the MRIware Homepage.
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