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Encoding of electrophysiology and other signals in MR images

Lars G. Hanson, Torben E. Lund, Christian G. Hanson
2007 Journal of Magnetic Resonance Imaging  
Purpose: To develop a gradient insensitive, generic technique for recording of non-MR signals by use of surplus scanner bandwidth. Materials and Methods: Relatively simple battery driven hardware is used to transform one or more signals into radio waves detectable by the MR scanner. Similarly to the "mag stripe" technique used for encoding of soundtracks in motion pictures, the electrical signals are in this way encoded as artifacts appearing in the MR images or spectra outside the region of
more » ... erest. The encoded signals are subsequently reconstructed from the signal recorded by the scanner. Results: Electrophysiological eye and heart muscular recording (EOG and ECG) during fast echoplanar imaging is demonstrated with an expandable, modular 8-channel prototype implementation. The gradient artifacts that would normally be dominating EOG are largely eliminated. Conclusion: The method provides relatively inexpensive sampling with inherent micro-second synchronization and it reduces gradient artifacts in physiological recordings significantly. When oversampling is employed, the method is compatible with all MR reconstruction and post-processing techniques. Keywords: Wireless recording of electrophysiology, MRI, mag stripe signal encoding, RF modulation Recording of electrical signals in an MRI suite is generally problematic as the sampling equipment needs to be MR compatible, meaning safe, well-functioning at high field, insensitive to radio frequency waves (RF) and electromagnetically silent at MR frequencies. Such recordings may for example represent button-press responses to stimuli presented to a patient in the scanner, and they often need to be correlated with MR imaging or spectroscopy thus adding the complexity of synchronization. Recording of electrophysiological (EP) signals during MRI poses extra difficulty as the rapidly changing magnetic fields induce electrode voltages that are often orders of magnitude stronger than the weak electrical signals originating from neural activity. A particularly demanding example is recording of electroencephalography (EEG) during fMRI (1). This combination has great potential ranging from patient supervision, over research in basic neurological processes to improved diagnosis of epilepsy (2). However, EEG recording in an MRI environment suffers extreme degradation due to pulse and imaging artifacts that are often orders of magnitude larger than the EEG signal of interest even after minimizing the presence of current loops. The imaging artifacts are induced by the strong and rapidly changing gradients used for fast imaging. In many studies EEG-recordings were therefore performed in silent periods between image acquisition. However, most methods including functional MRI (fMRI) benefits from imaging with high temporal resolution and unnecessary pauses should normally be avoided. An EEG sampling strategy of particular interest in the present context was introduced by Anami and coworkers (3). This technique coined "stepping stone sampling" reduces imaging artifacts by recording EP signals only in periods where gradient currents are constant. It was demonstrated that EEG can be recorded with limited distortion in short periods between gradient reversals during echoplanar imaging (EPI). The method benefits from synchronization between scanner and EEG clocks (4) which facilitates filtering of residual imaging induced noise (5). Triggered 20 kHz sampling was used by Anami to record the EEG during 400 s silent periods where also the MR signals were measured, i.e., in the periods between changes of directions of ¡ -space-traversal in blipped EPI. This method is highly suited for fMRI. The setup used by Anami and coworkers is fairly complicated, and relies on microsecond synchronization between scanner and EEG equipment obtained by driving the EEG-system with the scanner clock and using high bandwidth sampling and triggered sample-hold. Also, the MR sequences generally have to be edited to provide the needed triggering. After acquisition, the problem remains of MATERIALS AND METHODS The implemented setup is schematically illustrated in Fig. 1 . Electrophysiological and known calibration signals are amplified and encoded onto distinct RF carriers in the frequency range detectable by the scanner. These signals are emitted as radio waves inside the RF enclosure by use of a simple aerial. The signals are thus detected by the scanner during imaging, and are encoded in the imaging or spectroscopy data from where, it can be extracted during data processing. In order to reduce bandwidth requirements and to avoid gradient and RF induced transients in the measured EP-signals, gradient activity triggered gating is implemented with a sensor coil placed near the opening of the scanner. The details of the various components are described below. ¢ 1600-14600 allowing input ranges of 300 V to 3 mV, full scale), the signal was offset and scaled to ensure an always positive sign for the dynamic range of interest. This resolves sign ambiguity in subsequent demodulation steps. RF ENCODING The RF signal encoding was performed using a specially designed multi-frequency amplitude modulator, consisting of a common reference oscillator and eight oscillators providing different frequency offsets for each of eight channels. The reference oscillator was made with a voltage controlled crystal oscillator and a low jitter programmable phase locked loop (PLL). The clock for each channel was obtained by another low jitter programmable PLL. This gives the advantage of easy adjustment to the MR frequency range and frequency drifts well below levels of significance. The drift between channels is negligible whereas used for repeated echo planar imaging of three axial slices through the eye region of a healthy volunteer for 28 seconds. The standard quadrature head coil was used. In the middle third of the period, the subject paused with open eyes, whereas the remaining time was spent alternately looking right and left self-paced. This activity would normally be visible on both MR images (6) and EOG, and the correlation between the two can therefore be used to probe the validity of the approach. Electrophysiological signals were measured during MRI with MR compatible electrodes positioned near the heart and eye musculature to record ECG and EOG simultaneously. The experiments were performed after approval was granted by the local ethics committee and after informed consent was given by the subject. The MRI parameters were as follows: Slice thickness 5 mm with 1 mm inter-slice gap. The echo and repetition times, TE/TR=41 ms/235 ms, were chosen minimal for the used 128x128 image matrix and 400 mm quadratic FOV (3 mm is a typical fMRI in-plane resolution). Each EPI gradient lobe involved ramping up for 130 s, a 300 s plateau, and 130 s ramping down. Sampling was performed in the middle 512 s period, thus including 212 s ramp-sampling, being unproblematic only due to the used gradient-activity triggering. The used parameters are representative of studies where emphasis is put on fMRI performance, i.e., the gradient artifacts in EP-recordings were not minimized by sacrificing temporal or spatial resolution. ELECTROPHYSIOLOGICAL SIGNAL CHARACTERISTICS AND FILTERING The EPI echo spacing was 0.56 ms which is therefore also the time resolution of the EP signals measured during single-image acquisition when reconstructed as described above. Between image acquisitions, however, there are periods of excitation, spoiling and other acquisition pauses. With the used imaging parameters, there are 5 ms periods between EPI of neighboring slices, where the EP-signal was not measured. For a time domain-analysis, this would normally not require attention, but it must be considered if, e.g., the alpha-power of an EEG is to be estimated (discussed later). In addition to the 128 readouts used for reconstruction of each EPI image, the used sequence acquires 3 reference lines for the purpose of ghost-correction. These are not phase-encoded. They contain encoded EP-signals but were discarded from the EP-signal reconstruction to avoid potential transients in the beginning of the EPI echo-train. The non-sampled interval therefore increased from 5 to 6.6 ms corresponding to EP-signals being measured in roughly 90% of the available time. Due to eddy-currents and other differences between sampling on positive and negative gradient lobes (sources of normal EPI-ghosting), modulation of every second EP-sample is expected, but easily removed by filtering or by sacrificing half the bandwidth. The latter approach was chosen here as the resulting Nyquist frequency, 446 Hz, is still sufficient for sampling of all EP signals. Neighboring samples were simply averaged giving a time resolution of ¦ § ¢ © ¤ ms ¦ ms except in the above-mentioned pauses between slices. There may be additional signal variation with the EPI line number, e.g., from transient eddy currents from phase-encoding or slice selection gradients. This non-random noise can be estimated and filtered relatively easily (4, 7) but this was not necessary for the present application. It is likely to
doi:10.1002/jmri.20906 pmid:17457795 fatcat:7w3nknii5rhz3kfp3q56ueieti

Interactive web site and APP for early magnetic resonance education

Lars G. Hanson
2016 Physica medica (Testo stampato)  
doi:10.1016/j.ejmp.2016.07.556 fatcat:ynihvhzz5zeg5mk5ilvu76juhq

General purpose electronics for real-time processing and encoding of non-MR data in MR acquisitions

Jan Ole Pedersen, Christian G. Hanson, Rong Xue, Lars G. Hanson
2018 Concepts in Magnetic Resonance Part B Magnetic Resonance Engineering  
ORCID Jan Ole Pedersen http://orcid.org/0000-0002-3099-2106 Lars G.  ...  Hanson http://orcid.org/0000-0002-8204-6912 ( Larmor frequency of 1 H at 1.5 T), 127.74 MHz ( 1 H at 3 T), 32.13 MHz ( 13 C at 3 T) and 74.97 MHz ( 13 C at 7 T).  ... 
doi:10.1002/cmr.b.21385 fatcat:lcyogu3rs5glpn7kl5mn2ftbwu

Human in-vivo brain magnetic resonance current density imaging (MRCDI)

Cihan Göksu, Lars G. Hanson, Hartwig R. Siebner, Philipp Ehses, Klaus Scheffler, Axel Thielscher
2018 NeuroImage  
r ) or multi-gradient-echo readouts with fly-back (multi 609 G r ) are used.  ...  Either single-gradient-echo readouts (single G r ) or multi-gradient-echo readouts with 615 fly-back (multi G r ) are used. 616 Experiment 1: Comparison of single-vs. multi-gradient-echo acquisition in  ... 
doi:10.1016/j.neuroimage.2017.12.075 pmid:29288869 fatcat:eqernm2rcff5fhp3ah6hbhv7pu

Motion correction of single-voxel spectroscopy by independent component analysis applied to spectra from nonanesthetized pediatric subjects

Robin de Nijs, Maria J. Miranda, Lars Kai Hansen, Lars G. Hanson
2009 Magnetic Resonance in Medicine  
For Single Voxel Spectroscopy (SVS), the acquisition of the spectrum is typically repeated n times and then combined with a factor n in order to improve the Signal-to-Noise Ratio (SNR). In practice the acquisitions are not only affected by random noise, but also by physiological motion and subject movements. Since the influence of physiological motion such as cardiac and respiratory motion on the data is limited, it can be compensated for without data-loss. Individual acquisitions hampered by
more » ... bject movements on the other hand need to be rejected, if no correction or compensation is possible. If the individual acquisitions are stored, it is possible to identify and reject the motion-disturbed acquisitions before averaging. Several automatic algorithms were investigated using a dataset of spectra from non-anesthetized infants with a gestational age of 40 weeks. Median filtering removed most subject movement artifacts, but at the cost of increased sensitivity to random noise. Neither Independent Component Analysis (ICA) nor outlier identification with multiple comparisons has this problem. These two algorithms are novel in this context. The peak height values of the metabolites were increased compared to the mean of all acquisitions for both methods, although primarily for the ICA method.
doi:10.1002/mrm.22129 pmid:19780157 fatcat:nrslbuhb3bbi5guumwhac72fc4

Is quantum mechanics necessary for understanding magnetic resonance?

Lars G. Hanson
2008 Concepts in magnetic resonance. Part A, Bridging education and research  
Educational material introducing magnetic resonance typically contains sections on the underlying principles. Unfortunately the explanations given are often unnecessarily complicated or even wrong. Magnetic resonance is often presented as a phenomenon that necessitates a quantum mechanical explanation whereas it really is a classical effect, i.e. a consequence of the common sense expressed in classical mechanics. This insight is not new, but there have been few attempts to challenge common
more » ... ading explanations, so authors and educators are inadvertently keeping myths alive. As a result, new students' first encounters with magnetic resonance are often obscured by explanations that make the subject difficult to understand. Typical problems are addressed and alternative intuitive explanations are provided.
doi:10.1002/cmr.a.20123 fatcat:al47ri44tbaenaozrpuk3vqhp4

A virtual scanner for teaching fundamental magnetic resonance in biomedical engineering

Jens E. Wilhjelm, Jonas Duun-Henriksen, Lars G. Hanson
2018 Computer Applications in Engineering Education  
A virtual scanner for introductory teaching in magnetic resonance imaging in biomedical engineering is presented and evaluated in a randomized trial of ultra-short and short-term learning. The results show similar performance, but indicate higher motivation, when compared with a classical approach, when class duration was identical. K E Y W O R D S biomedical engineering, magnetic resonance, matlab gui, signal analysis, virtual scanner Comput Appl Eng Educ. 2018;1-13. wileyonlinelibrary.com/cae
doi:10.1002/cae.22028 fatcat:nzk2x2etobhohgbidp3b3z6vom

Reconstruction strategy for echo planar spectroscopy and its application to partially undersampled imaging

Lars G. Hanson, Kjeld Schaumburg, Olaf B. Paulson
2000 Magnetic Resonance in Medicine  
This is illustrated in Fig. 2 and is expressed by the equation H I ¦ ' § 7 © 4 6 c B y d f h g i ¦ X p q W § 6 4 9 G F I Q P b R S P T ¦ § © 4 6 3 d f h g i ¦ b q ( A 4 ) a d f h g 3 ¦ 2 q s § 6 4 9  ...  Corrected signal matrices [1] H I Q U W V X V ¦ § © 4 6 c B u d f h g i ¦ b q W § 6 4 9 G F I Q U ' V S V ¦ ' § 7 © 4 6 [2] Two applications of these equations are of interest: Water reference reconstruction  ... 
doi:10.1002/1522-2594(200009)44:3<412::aid-mrm11>3.0.co;2-p pmid:10975893 fatcat:axatjgb7s5h4tk252gsdexgu7m

Safety Evaluation of a New Setup for Transcranial Electric Stimulation during Magnetic Resonance Imaging

Fróði Gregersen, Cihan Göksu, Gregor Schaefers, Rong Xue, Axel Thielscher, Lars G. Hanson
2021 Brain Stimulation  
G€ oksu, G. Schaefers et al. Brain Stimulation 14 (2021) 488e497  ...  Lars G. Hanson: Conceptualization, Methodology, Investigation, Writing e review & editing, Supervision, Funding acquisition.  ...  The two relevant limitations for head MRI are head SAR (SAR averaged over the mass of the head) and local head SAR given as the peak spatial average SAR over 1 g or 10 g of tissue.  ... 
doi:10.1016/j.brs.2021.02.019 pmid:33706007 fatcat:j6fukd2h4zgydphickv6dmmxhy

Sensitivity analysis of magnetic field measurements for magnetic resonance electrical impedance tomography (MREIT)

Cihan Göksu, Klaus Scheffler, Philipp Ehses, Lars G. Hanson, Axel Thielscher
2017 Magnetic Resonance in Medicine  
G x is the readout gradient strength, N x the readout matrix size, T s the readout period, and Dk x the spatial frequency resolution.  ...  For SSFP-FID, the following experiments were performed: 375 mm 2 , image matrix ¼ 256 Â 256, Dz ¼ 3 mm, a ¼ 60 , N G€ oksu et al.  ... 
doi:10.1002/mrm.26727 pmid:28560836 fatcat:7mxt4nrmjjhz3lsfgg5lwc7tdq

Visualizing the enteric nervous system using genetically engineered double reporter mice: Comparison with immunofluorescence

Yanfen Jiang, Hui Dong, Lars Eckmann, Elaine M. Hanson, Katherine C. Ihn, Ravinder K. Mittal, Juri G. Gelovani
2017 PLoS ONE  
and aims The enteric nervous system (ENS) plays a crucial role in the control of gastrointestinal motility, secretion and absorption functions. Immunohistochemistry has been widely used to visualize neurons of the ENS for more than two decades. Genetically engineered mice that report specific proteins can also be used to visualize neurons of the ENS. The goal of our study was to develop a mouse that expresses fluorescent neuronal nitric oxide synthase (nNOS) and choline acetyltransferase
more » ... the two proteins expressed in 95% of the ENS neurons. We compared ENS neurons visualized in the reporter mouse with the wild type mouse stained using classical immunostaining techniques. Methods Mice hemizygous for ChAT-ChR2-YFP BAC transgene with expression of the mhChR2: YFP fusion protein directed by ChAT promoter/enhancer regions on the BAC transgene were purchased commercially. The Cre/LoxP technique of somatic recombination was used to construct mice with nNOS positive neurons. The two mice were crossbred and tissues were harvested and examined using fluorescent microscopy. Immunostaining was performed in the wild type mice, using antibodies to nNOS, ChAT, Hu and PGP 9.5. Results Greater than 95% of the ENS neurons were positive for either nNOS or ChAT or both. The nNOS and ChAT neurons and their processes in the ENS were well visualized in all the regions of the GI tract, i.e., esophagus, small intestine and colon. The number of nNOS and ChAT neurons was approximately same in the reporter mouse and immunostaining method in the wild type mouse. The nNOS fluorescence in the reporter mouse was seen in both cytoplasm as well as nucleus but in the immunostained specimens it was seen only in the cytoplasm.
doi:10.1371/journal.pone.0171239 pmid:28158225 pmcid:PMC5291392 fatcat:jgqgxhvclfe6pdyyilwpioqvkm

Correlation of Global N-Acetyl Aspartate With Cognitive Impairment in Multiple Sclerosis

Henrik Kahr Mathiesen, Agnete Jonsson, Thomas Tscherning, Lars G. Hanson, Jente Andresen, Morten Blinkenberg, Olaf B. Paulson, Per Soelberg Sorensen
2006 Archives of Neurology  
Whole-brain N-acetyl aspartate (NAA), a measure of neuronal function, can be assessed by multislice echo-planar spectroscopic imaging. Objective: To test the hypothesis that the global brain NAA/creatine (Cr) ratio is a better predictor of cognitive dysfunction in multiple sclerosis than conventional magnetic resonance imaging measures. Design: Survey.
doi:10.1001/archneur.63.4.533 pmid:16606765 fatcat:gofcipzg6regtiy7quefjwkr3m

Sensitivity and resolution improvement for in-vivo magnetic resonance current density imaging (MRCDI) of the human brain [article]

Cihan Goksu, Klaus Scheffler, Frodi Gregersen, Hasan H Eroglu, Rahel Heule, Hartwig R Siebner, Lars G Hanson, Axel Thielscher
2021 bioRxiv   pre-print
Purpose: Magnetic resonance current density imaging (MRCDI) combines MR brain imaging with the injection of time-varying weak currents (1-2 mA) to assess the current flow pattern in the brain. However, the utility of MRCDI is still hampered by low measurement sensitivity and poor image quality. Methods: We recently introduced a multi-gradient-echo-based MRCDI approach that has the hitherto best documented efficiency. We now advanced our MRCDI approach in three directions and performed phantom
more » ... d in-vivo human brain experiments for validation: First, we verified the importance of enhanced spoiling and optimize it for imaging of the human brain. Second, we improved the sensitivity and spatial resolution by using acquisition weighting. Third, we added navigators as a quality control measure for tracking physiological noise. Combining these advancements, we tested our optimized MRCDI method by using 1 mA transcranial electrical stimulation (TES) currents injected via two different electrode montages in five subjects. Results: For a session duration of 4:20 min, the new MRCDI method was able to detect magnetic field changes caused by the TES current flow at a sensitivity level of 84 pT, representing in a twofold increase relative to our original method. Comparing both methods to current flow simulations based on personalized head models demonstrated a consistent increase in the coefficient of determination of ∆R2=0.12 for the current-induced magnetic fields and ∆R2=0.22 for the current flow reconstructions. Interestingly, some of the simulations still clearly deviated from the measurements despite of the strongly improved measurement quality. This suggests that MRCDI can reveal useful information for the improvement of head models used for current flow simulations. Conclusion: The advanced method strongly improves the sensitivity and robustness of MRCDI and is an important step from proof-of-concept studies towards a broader application of MRCDI in clinical and basic neuroscience research.
doi:10.1101/2021.03.23.436558 fatcat:erqd4mhi4jalzhse7busomem5q

Gamma-aminobutyric acid edited echo-planar spectroscopic imaging (EPSI) with MEGA-sLASER at 7T

Peter O. Magnusson, Vincent O. Boer, Anouk Marsman, Olaf B. Paulson, Lars G. Hanson, Esben T. Petersen
2018 Magnetic Resonance in Medicine  
How to cite this article: Magnusson PO, Boer VO, Marsman A, Paulson OB, Hanson LG, Petersen ET. Gamma-aminobutyric acid edited echo-planar spectroscopic imaging (EPSI) with MEGA-sLASER at 7T.  ...  + signal after editing efficiency correction and choline peak frequency and phase alignment (row C) F I G U R E 2 Simulated B 1 field strength dependence of the signal amplitude of the MEGA edited GABA  ... 
doi:10.1002/mrm.27450 pmid:30159924 fatcat:u5mpeayy5zcb5omv6un5mskhwa

Optimal voxel size for measuring global gray and white matter proton metabolite concentrations using chemical shift imaging

Lars G. Hanson, Elfar Adalsteinsson, Adolf Pfefferbaum, Daniel M. Spielman
2000 Magnetic Resonance in Medicine  
The constants and " provide pure white and gray matter metabolite concentration estimates, WM E F ) # E % 4 G and GM E H ) # I 4 G P " , given by the two endpoints  ...  Direct volume effect When line shapes are dominated by irreversible T2-processes, e h R § 0 g f § C h C h i § 0 j Y ) f § U C 4 p k ) v C 4 9 [8] C is defined as the number of voxels and f is the total  ... 
doi:10.1002/1522-2594(200007)44:1<10::aid-mrm3>3.0.co;2-8 pmid:10893515 fatcat:gelzbo4ahfb2fpklhmq3hdwmla
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