Determination of head conductivity frequency response in vivo with optimized EIT-EEG.

Electroencephalography (EEG) benefits from accurate head models. Dipole source modelling errors can be reduced from over 1cm to a few millimetres by replacing generic head geometry and conductivity with tailored ones. When adequate head geometry is available, electrical impedance tomography (EIT) can be used to infer the conductivities of head tissues. In this study, the boundary element method (BEM) is applied with three-compartment (scalp, skull and brain) subject-specific head models. The optimal injection of small currents to the head with a modular EIT current injector, and voltage measurement by an EEG amplifier is first sought by simulations. The measurement with a 64-electrode EEG layout is studied with respect to three noise sources affecting EIT: background EEG, deviations from the fitting assumption of equal scalp and brain conductivities, and smooth model geometry deviations from the true head geometry. The noise source effects were investigated depending on the positioning of the injection and extraction electrode and the number of their combinations used sequentially. The deviation from equal scalp and brain conductivities produces rather deterministic errors in the three conductivities irrespective of the current injection locations. With a realistic measurement of around 2 min and around 8 distant distinct current injection pairs, the error from the other noise sources is reduced to around 10% or less in the skull conductivity. The analysis of subsequent real measurements, however, suggests that there could be subject-specific local thinnings in the skull, which could amplify the conductivity fitting errors. With proper analysis of multiplexed sinusoidal EIT current injections, the measurements on average yielded conductivities of 340 mS/m (scalp and brain) and 6.6 mS/m (skull) at 2 Hz. From 11 to 127 Hz, the conductivities increased by 1.6% (scalp and brain) and 6.7% (skull) on the average. The proper analysis was ensured by using recombination of the current injections into virtual ones, avoiding problems in location-specific skull morphology variations. The observed large intersubject variations support the need for in vivo measurement of skull conductivity, resulting in calibrated subject-specific head models.

Rotary scanning acquisition in ultra-low-field MRI.

PURPOSE: To develop a method of achieving large field of view (FOV) imaging with a smaller amount of data in ultra-low-field (ULF) MRI. THEORY: In rotary scanning acquisition (RSA), data from the imaging object is acquired at multiple angles by rotating the object or the scanner. RSA is similar to radial-trajectory acquisition but simplifies the measurement and image reconstruction when concomitant fields are nonnegligible. METHODS: RSA was implemented to achieve large FOV with only three localized superconductive quantum interference device (SQUID) sensors at the ULF-MRI field of 50 µT. RESULTS: Simulations suggest benefits of RSA, including reduced concomitant field artifacts, large FOV imaging, and SNR improvement. Experimental data demonstrate the feasibility of reconstructing large FOV images using only three SQUID sensors with 33% of the amount of data collected using a Cartesian trajectory. CONCLUSION: RSA can be useful in low-field, low-weight, or portable MRI to generate large FOV images with only a few sensors. Magn Reson Med 75:2255-2264, 2016. © 2015 Wiley Periodicals, Inc.

Efficient concomitant and remanence field artifact reduction in ultra-low-field MRI using a frequency-space formulation.

PURPOSE: For ultra-low-field MRI, the spatial-encoding magnetic fields generated by gradient coils can have strong concomitant fields leading to prominent image distortion. Additionally, using superconducting magnet to pre-polarize magnetization can improve the signal-to-noise ratio of ultra-low-field MRI. Yet the spatially inhomogeneous remanence field due to the permanently trapped flux inside a superconducting pre-polarizing coil modulates magnetization and causes further image distortion. METHOD: We propose a two-stage frequency-space (f-x) formulation to accurately describe the dynamics of spatially-encoded magnetization under the influence of concomitant and remanence fields, which allows for correcting image distortion due to concomitant and remanence fields. RESULTS: Our method is computationally efficient as it uses a combination of the fast Fourier transform algorithm and a linear equation solver. With sufficiently dense discretization in solving the linear equation, the performance of this f-x method was found to be stable among different choices of the regularization parameter and the regularization matrix. CONCLUSION: We present this method together with numerical simulations and experimental data to demonstrate how concomitant and remanence field artifacts in ultra-low-field MRI can be corrected efficiently.

Marked difference in liver fat measured by histology vs. magnetic resonance-proton density fat fraction: A meta-analysis.

Background & Aims: Pathologists quantify liver steatosis as the fraction of lipid droplet-containing hepatocytes out of all hepatocytes, whereas the magnetic resonance-determined proton density fat fraction (PDFF) reflects the tissue triacylglycerol concentration. We investigated the linearity, agreement, and correspondence thresholds between histological steatosis and PDFF across the full clinical spectrum of liver fat content associated with non-alcoholic fatty liver disease. Methods: Using individual patient-level measurements, we conducted a systematic review and meta-analysis of studies comparing histological steatosis with PDFF determined by magnetic resonance spectroscopy or imaging in adults with suspected non-alcoholic fatty liver disease. Linearity was assessed by meta-analysis of correlation coefficients and by linear mixed modelling of pooled data, agreement by Bland-Altman analysis, and thresholds by receiver operating characteristic analysis. To explain observed differences between the methods, we used RNA-seq to determine the fraction of hepatocytes in human liver biopsies. Results: Eligible studies numbered 9 (N = 597). The relationship between PDFF and histology was predominantly linear (r = 0.85 [95% CI, 0.80-0.89]), and their values approximately coincided at 5% steatosis. Above 5% and towards higher levels of steatosis, absolute values of the methods diverged markedly, with histology exceeding PDFF by up to 3.4-fold. On average, 100% histological steatosis corresponded to a PDFF of 33.0% (29.5-36.7%). Targeting at a specificity of 90%, optimal PDFF thresholds to predict histological steatosis grades were ≥5.75% for ≥S1, ≥15.50% for ≥S2, and ≥21.35% for S3. Hepatocytes comprised 58 ± 5% of liver cells, which may partly explain the lower values of PDFF vs. histology. Conclusions: Histological steatosis and PDFF have non-perfect linearity and fundamentally different scales of measurement. Liver fat values obtained using these methods may be rendered comparable by conversion equations or threshold values. Impact and implications: Magnetic resonance-proton density fat fraction (PDFF) is increasingly being used to measure liver fat in place of the invasive liver biopsy. Understanding the relationship between PDFF and histological steatosis fraction is important for preventing misjudgement of clinical status or treatment effects in patient care. Our analysis revealed that histological steatosis fraction is often significantly higher than PDFF, and their association varies across the spectrum of fatty liver severity. These findings are particularly important for physicians and clinical researchers, who may use these data to interpret PDFF measurements in the context of histologically evaluated liver fat content.

Hybrid ultra-low-field MRI and magnetoencephalography system based on a commercial whole-head neuromagnetometer.

Ultra-low-field MRI uses microtesla fields for signal encoding and sensitive superconducting quantum interference devices for signal detection. Similarly, modern magnetoencephalography (MEG) systems use arrays comprising hundreds of superconducting quantum interference device channels to measure the magnetic field generated by neuronal activity. In this article, hybrid MEG-MRI instrumentation based on a commercial whole-head MEG device is described. The combination of ultra-low-field MRI and MEG in a single device is expected to significantly reduce coregistration errors between the two modalities, to simplify MEG analysis, and to improve MEG localization accuracy. The sensor solutions, MRI coils (including a superconducting polarizing coil), an optimized pulse sequence, and a reconstruction method suitable for hybrid MEG-MRI measurements are described. The performance of the device is demonstrated by presenting ultra-low-field-MR images and MEG recordings that are compared with data obtained with a 3T scanner and a commercial MEG device.

Noise amplification in parallel whole-head ultra-low-field magnetic resonance imaging using 306 detectors.

In ultra-low-field magnetic resonance imaging, arrays of up to hundreds of highly sensitive superconducting quantum interference devices (SQUIDs) can be used to detect the weak magnetic fields emitted by the precessing magnetization. Here, we investigate the noise amplification in sensitivity-encoded ultra-low-field MRI at various acceleration rates using a SQUID array consisting of 102 magnetometers, 102 gradiometers, or 306 magnetometers and gradiometers, to cover the whole head. Our results suggest that SQUID arrays consisting of 102 magnetometers and 102 gradiometers are similar in g-factor distribution. A SQUID array of 306 sensors (102 magnetometers and 204 gradiometers) only marginally improves the g-factor. Corroborating with previous studies, the g-factor in 2D sensitivity-encoded ultra-low-field MRI with 9 to 16-fold 2D accelerations using the SQUID array studied here may be acceptable.

Relationship of electrocardiographic repolarization measures to echocardiographic left ventricular mass in men with hypertension.

OBJECTIVE: Arterial hypertension often leads to an increase in left ventricular mass (LVM). Marked left ventricular hypertrophy (LVH) is associated with potentially arrhythmogenic ventricular repolarization abnormalities, which may contribute to the increased risk of sudden cardiac death in this disorder. We studied whether electrocardiographic repolarization changes are already detectable in mild LVM increase associated with hypertension. METHODS: In 220 men (mean age 51+/-6 years) attending the GENRES hypertension study, we measured QT intervals (QTend and QTpeak), T-wave peak to T-wave end (TPE) intervals, and novel T-wave morphology parameters (principal component analysis ratio, T-wave morphology dispersion, total cosine R-to-T, and T-wave residuum) from a digital standard 12-lead electrocardiogram, and related them to echocardiographically determined LVM. RESULTS: In this group of moderately hypertensive men, the mean LVM index (LVMI; LVM divided by body surface area) was 99+/-19 g/m2, with only 18% of the subjects showing evidence of echocardiographic LVH (LVMI>116 g/m2). LVMI correlated significantly with QT intervals (r=0.16-0.21, P=0.018-0.002), TPE intervals (r=0.23-0.27, P<0.001), and T-wave morphology parameters (r=0.22-0.39, P<0.001). Except for the QTpeak interval, the relationship between LVMI and electrocardiographic repolarization parameters was independent in multivariate analyses. CONCLUSION: Altered electrocardiographic ventricular repolarization, indicating reduced repolarization reserve and possibly increased repolarization heterogeneity, is already present in hypertensive men with only mild LVM increase. At a population level, this may carry important risk implications for the large group of hypertensive patients.

Detecting millisecond-range coupling delays between brainwaves in terms of power correlations by magnetoencephalography.

BACKGROUND: The spatiotemporal coupling of brainwaves is commonly quantified using the amplitude or phase of signals measured by electro- or magnetoencephalography (EEG/MEG). To enhance the temporal resolution for coupling delays down to millisecond level, a new power correlation (PC) method is proposed and tested. NEW METHOD: The cross-correlations of any two brainwave powers at two locations are calculated sequentially through a measurement using the convolution theorem. For noise suppression, the cross-correlation series is moving-average filtered, preserving the millisecond resolution in the cross-correlations, but with reduced noise. The coupling delays are determined from the delays of the cross-correlation peaks. RESULTS: Simulations showed that the new method detects reliably power cross-correlations with millisecond accuracy. Moreover, in MEG measurements on three healthy volunteers, the method showed average alpha-alpha coupling delays of around 0-20 ms between the occipital areas of two hemispheres. Lower-frequency brainwaves vs. alpha waves tended to have a larger lag; higher-frequency waves vs. alpha waves showed delays with large deviations. COMPARISON WITH EXISTING METHODS: The use of signal power instead of its square root (amplitude) in the cross-correlations improves noise cancellation. Compared to signal phase, the signal power analysis time delays do not have periodic ambiguity. In addition, the novel method allows fast calculation of cross-correlations. CONCLUSIONS: The PC method conveys novel information about brainwave dynamics. The method may be extended from sensor-space to source-space analysis, and can be applied also for electroencephalography (EEG) and local field potentials (LFP).

Temperature dependence of relaxation times and temperature mapping in ultra-low-field MRI.

Ultra-low-field MRI is an emerging technology that allows MRI and NMR measurements in microtesla-range fields. In this work, the possibilities of relaxation-based temperature measurements with ultra-low-field MRI were investigated by measuring T1 and T2 relaxation times of agarose gel at 50 µT-52 mT and at temperatures 5-45°C. Measurements with a 3T scanner were made for comparison. The Bloembergen-Purcell-Pound relaxation theory was combined with a two-state model to explain the field-strength and temperature dependence of the data. The results show that the temperature dependencies of agarose gel T1 and T2 in the microtesla range differ drastically from those at 3T; the effect of temperature on T1 is reversed at approximately 5 mT. The obtained results were used to reconstruct temperature maps from ultra-low-field scans. These time-dependent temperature maps measured from an agarose gel phantom at 50 µT reproduced the temperature gradient with good contrast.

Suppressing multi-channel ultra-low-field MRI measurement noise using data consistency and image sparsity.

Ultra-low-field (ULF) MRI (B 0 = 10-100 µT) typically suffers from a low signal-to-noise ratio (SNR). While SNR can be improved by pre-polarization and signal detection using highly sensitive superconducting quantum interference device (SQUID) sensors, we propose to use the inter-dependency of the k-space data from highly parallel detection with up to tens of sensors readily available in the ULF MRI in order to suppress the noise. Furthermore, the prior information that an image can be sparsely represented can be integrated with this data consistency constraint to further improve the SNR. Simulations and experimental data using 47 SQUID sensors demonstrate the effectiveness of this data consistency constraint and sparsity prior in ULF-MRI reconstruction.

Gradient-excitation encoding combined with frequency and phase encodings for three-dimensional ultra-low-field MRI.

Ultra-low-field magnetic resonance imaging (ULF MRI) in microtesla fields is a new technology with features unseen in tesla-range MRI. Instead of induction coils as sensors, superconducting quantum interference device (SQUID) sensors are used, providing a frequency-independent signal-to-noise ratio (SNR). Owing to its tolerance for large relative imaging-field inhomogeneities, electromagnet shimming is not necessary. ULF MRI can also be combined with magnetoencephalography (MEG) to image the brain with close to millimetre-millisecond resolution. In this paper, the hybrid MEG-MRI device developed at Aalto University will be presented, as well as a 3D imaging scheme combining gradient-excitation encoding with frequency and phase and encodings. It is noteworthy that, regarding the presented gradient-excitation encoding in ULF MRI, the kilohertz-range Larmor frequencies allow MR signals to propagate unattenuated through tissue, which is not the case in tesla-range MRI with Larmor frequencies even above 100 MHz. Thus, the presented encoding method is especially compatible with ULF MRI, where the use of three different encoding mechanisms for three-dimensional imaging is possible. The feasibility of image reconstruction with the gradient-excitation-encoding method is demonstrated by simulations.

SQUID-sensor-based ultra-low-field MRI calibration with phantom images: towards quantitative imaging.

In ultra-low-field magnetic resonance imaging (ULF MRI), measured resonance signals oscillate at Larmor frequencies around 1 kHz compared to even above 100 MHz in high-field MRI. Thus, detection by induction coils in ULF MRI is not feasible, whereas superconducting quantum interference device (SQUID) sensors can measure these femtotesla-level signals. The signal-to-noise ratio is enhanced by prepolarization in a field that is typically 100-1000 times higher than the field during acquisition. Based on both measurements and simulations, a procedure for calibrating a SQUID-sensor-based MRI system with MR images is presented in this article. Magnetoencephalography (MEG) can be integrated with ULF MRI, and may also benefit from such a calibration procedure. Conventionally, electromagnet probe signals have been used for the SQUID-sensor calibration in MEG; the presented ULF-MRI-based approach using an imaging phantom could replace this procedure in hybrid MEG-MRI or ULF MRI alone. The necessary theory is provided here with experimental verification. The calibration procedure opens the possibility of performing quantitative ULF MRI without sample-specific reference scans.

Avoiding eddy-current problems in ultra-low-field MRI with self-shielded polarizing coils.

In ultra-low-field magnetic resonance imaging (ULF MRI), superconductive sensors are used to detect MRI signals typically in fields on the order of 10-100 µT. Despite the highly sensitive detectors, it is necessary to prepolarize the sample in a stronger magnetic field on the order of 10-100 mT, which has to be switched off rapidly in a few milliseconds before signal acquisition. In addition, external magnetic interference is commonly reduced by situating the ULF-MRI system inside a magnetically shielded room (MSR). With typical dipolar polarizing coil designs, the stray field induces strong eddy currents in the conductive layers of the MSR. These eddy currents cause significant secondary magnetic fields that may distort the spin dynamics of the sample, exceed the dynamic range of the sensors, and prevent simultaneous magnetoencephalography and MRI acquisitions. In this paper, we describe a method to design self-shielded polarizing coils for ULF MRI. The experimental results show that with a simple self-shielded polarizing coil, the magnetic fields caused by the eddy currents are largely reduced. With the presented shielding technique, ULF-MRI devices can utilize stronger and spatially broader polarizing fields than achievable with unshielded polarizing coils.

Improved determination of FID signal parameters in low-field NMR.

In this work, novel methods are suggested for assessing signal parameters of the free induction decay (FID) in nuclear magnetic resonance (NMR) experiments. The FID signal was recorded in a microtesla field and analysed to determine its relaxation time, amplitude, Larmor frequency and phase. The challenge was posed by the narrow line width, whose related effects were investigated through simulations, also. The developed methods give a new view on FID signal estimation in microtesla as well as lower and higher fields. It is shown that the transverse relaxation time of a sample can be accurately determined in the frequency domain by other means than the Lorentz peak half width. Also, with some realistic approximations, a simple functional form for the power spectrum Lorentz peak shape is proposed. As shown in this work, the inspection of the power spectrum instead of the absorption and dispersion Lorentzians is advantageous in the sense that the waveform is independent of the FID phase. The automatic and efficient methods presented in this work incorporate an integral exponential fit, the fit of the power spectrum Lorentz peak and two ways to determine the FID phase. When there are sufficiently many data points in the Lorentz peak, the power spectrum Lorentz peak shape fit provides a quick, simple and accurate way of determining the amplitude, relaxation time and Larmor frequency of the FID. In the measurements of this work, however, the narrow line width led to establishing a more applicable method which is based on the exponential decay of the Lorentz peak with a temporally moving power spectrum window.

Short-term electrophysiological effects of losartan, bisoprolol, amlodipine, and hydrochlorothiazide in hypertensive men.

BACKGROUND AND AIM: Hypertension-induced left ventricular structural remodelling associates with repolarization abnormalities. We investigated if antihypertensive drugs can modulate ventricular repolarization. METHODS: A total of 183 hypertensive men received for 4 weeks drugs (losartan 50 mg, bisoprolol 5 mg, amlodipine 5 mg, hydrochlorothiazide (HCTZ) 25 mg) in a randomized order, separated by 4-week placebo periods. Electrocardiograms (ECG) were recorded at the end of placebo and drug periods. Measurements of repolarization duration (QT intervals), repolarization heterogeneity (T-wave peak to T-wave end (TPE) intervals), and T-wave morphology (T-wave principal component analysis (PCA) ratio, T-wave morphology dispersion (TMD), and total cosine R-to-T (TCRT)) during each drug were compared to placebo measurements. RESULTS: Losartan and bisoprolol shortened maximum and mean rate-adjusted QT intervals as well as mean TPE interval, decreased TMD, and increased TCRT. Losartan also shortened precordial maximum TPE interval and decreased PCA ratio. Amlodipine had no repolarization effects, whereas HCTZ prolonged precordial maximum TPE interval and mean TPE interval. CONCLUSION: Losartan and bisoprolol have beneficial short-term ECG repolarization effects. Amlodipine seems to have no repolarization effects. HCTZ seems to prolong the ECG TPE interval, potentially reflecting increased repolarization heterogeneity. These findings show that antihypertensive drugs may relatively rapidly and treatment-specifically modulate ECG markers of ventricular repolarization.