Reduce Signal Loss Research Articles

Sodium MRI of the skin using a surface coil to investigate and reduce signal loss and bias.

The purpose was to improve sodium MRI of human skin using a surface coil and twisted projection imaging with smaller, reshaped voxels. Calf skin sodium images were acquired in 14 healthy adults using twisted projection imaging with short TE ˜ 0.1 ms, first with a volume coil and voxels (1.5 × 1.5 × 15 = 34 mm3) reflecting the widely adopted skin imaging protocol (VolPencil). A 5-cm-diameter surface coil then facilitated 5× smaller (0.8 × 0.8 × 10 = 6.4 mm3) voxels with similar signal to noise ratio (SNR) in the same 12-min scan time (SurfPencil). "Pencil-shaped" voxels were then replaced with "pancake-shaped" (0.4 × 4 × 4 = 6.4 mm3) voxels, matching the anatomy of pressed flat skin (SurfPancake). Surface coil B1 was investigated with the novel use of spin-3/2 simulation. Protocol modifications were tested for signal increase (reduced loss) and correlation with (bias by) skin thickness. Higher resolution SurfPencil yielded 44% ± 16% greater skin sodium image intensity than VolPencil, whereas SurfPancake yielded an additional 20% ± 9% (p < 1e-8), reflecting reduced signal loss. Over the 1.0 to 1.8 mm skin thickness across participants, sodium intensity significantly increased 56% ± 19% and 44% ± 12% for VolPencil and SurfPencil, respectively (p < 0.003), but not for SurfPancake, reflecting reduced bias. Imaging yielded skin sodium concentration of 34 ± 5 mM for SurfPancake. This is greater than the ˜20 mM measures from the widely adopted protocol, but simulation (matching experimental trends) identified a remaining 64% signal loss; compensation yields 95 ± 15 mM. Surface coil imaging and "pancake" voxel reshaping increased skin sodium intensity and reduced bias by skin thickness. Simulated loss compensation yields skin sodium concentration similar to that measured by atomic absorption spectroscopy.

Design and Performance Analysis of Strip Photonic Waveguide with Coating Layer for Multimode Propagation

Introduction: Photonic devices play a pivotal role in the realm of high-speed data communication due to their inherent capability to expedite the transfer of information. Historically, research efforts in this domain have predominantly concentrated on investigating the fundamental mode propagation within photonic waveguides. Methods: This study diverges from the conventional approach by delving into the untapped potential of higher-order modes in addition to the fundamental mode of propagation. The exploration of these higher-order modes opens up new possibilities for optimizing and enhancing the performance of photonic devices in high-speed data communication scenarios. As a distinctive aspect of this study, various coating materials were scrutinized for their impact on both fundamental and higher-order mode propagation. The materials under examination included AlN (aluminum nitride), Germanium, and Silicon. These materials were chosen based on their unique optical properties and suitability for influencing different modes of light propagation. The findings from the study reveal that applying a coating of germanium demonstrates advantageous characteristics, particularly in terms of reduced signal loss, even when considering higher-order modes of propagation within photonic devices. Results: In this context, the results indicate that germanium-coated waveguides exhibit notably low propagation losses, with measurements as minimal as 0.25 dB/cm. This low level of loss is particularly noteworthy, especially when the waveguide has a width of 550 nm and is coated with a thickness of 50 nm. The dimensions and coating specifications play a crucial role in determining the efficiency of light transmission within the waveguide. Conclusion: The fact that the propagation loss is substantially low under these conditions suggests that the germanium-coated waveguide, even when considering higher-order modes of light propagation, can effectively maintain the integrity of the optical signal.

Swift and precise detection of unlabeled pathogens using a nanogap electrode impedimetric sensor facilitated by electrokinetics

For the protection of human health and environment, there is a growing demand for high-performance, user-friendly biosensors for the prompt detection of pathogenic bacteria in samples containing various substances. We present a nanogap electrode-based purely electrical impedimetric sensor that utilizes the dielectrophoresis (DEP) mechanism. Our nanogap sensor can directly and sensitively detect pathogens present at concentrations as low as 1–10 cells/assay in buffers and drinking milk without the need for separation, purification, or specific ligand binding. This is achieved by minimizing the electrical double-layer effect and electrode polarization in nanogap impedance sensors, reducing signal loss. In addition, even at low DEP voltages, nanogap sensors can quickly establish strong DEP forces between the nanogap electrodes to control the spatial concentration of pathogens around the electrodes. This activates and stabilizes inter-electrode signal transmission along the nanogap-aligned pathogens, increasing sensitivity and reducing errors during repeated measurements. The DEP-enabled nanogap impedance sensor developed in this study is valuable for a variety of pathogen detection and monitoring systems including point-of-care testing (POCT) as it can detect pathogens in diverse samples containing multiple substances quickly and with high sensitivity, is compatible with complex solutions such as food and beverages, and provides highly reproducible results without the need for separate binding and separation processes.

Vertical Interconnections by Electroless Pd Atoms on Immersion Au Surface for Heterogeneous Integration

Electroless Pd atoms were employed to bond vertical interconnection for chip-stacking applications without pressure and at a temperature below 100 °C. Vertical interconnections were created by channeling an electroless Pd plating solution through microchannels, enabling the reduced Pd atoms to assemble naturally within the gaps between two opposing Cu pillars. Notably, the Pd deposition resulted in epitaxial growth along the orientation of the Cu pillar surface, suggesting improved electrical properties for future high-frequency applications. In this study, highly uniform electroless Pd-bonded Cu pillar joints were fabricated using a patterned microfluidic system. The required bonding time was significantly correlated with the plating temperature. Furthermore, the electroless Pd-bonded joints exhibit a robust strength of approximately 55 MPa. Pd exhibits greater skin depth than other plating materials, which helps reduce signal loss and latency during high-frequency signal transmission. This innovative approach offers promise as a potential candidate for future 5G applications requiring low bonding stress and minimal thermal budget.

Model-based reconstruction for looping-star MRI.

The aim of this study was to develop a reconstruction method that more fully models the signals and reconstructs gradient echo (GRE) images without sacrificing the signal to noise ratio and spatial resolution, compared to conventional gridding and model-based image reconstruction method. By modeling the trajectories for every spoke and simplifying the scenario to only echo-in and echo-out mixture, the approach explicitly models the overlapping echoes. After modeling the overlapping echoes with two system matrices, we use the conjugate gradient algorithm (CG-SENSE) with the nonuniform FFT (NUFFT) to optimize the image reconstruction cost function. The proposed method is demonstrated in phantoms and in-vivo volunteer experiments for three-dimensional, high-resolution T2*-weighted imaging and functional MRI tasks. Compared to the gridding method, the high resolution protocol exhibits improved spatial resolution and reduced signal loss as a result of less intra-voxel dephasing. The fMRI task shows that the proposed model-based method produced images with reduced artifacts and blurring as well as more stable and prominent time courses. The proposed model-based reconstruction results shows improved spatial resolution and reduced artifacts. The fMRI task shows improved time series and activation map due to the reduced overlapping echoes and under-sampling artifacts.

Comparison of Novel Telemonitoring System Using the Single-lead Electrocardiogram Patch With Conventional Telemetry System.

Although a single-lead electrocardiogram (ECG) patch may provide advantages for detecting arrhythmias in outpatient settings owing to user convenience, its comparative effectiveness for real-time telemonitoring in inpatient settings remains unclear. We aimed to compare a novel telemonitoring system using a single-lead ECG patch with a conventional telemonitoring system in an inpatient setting. This was a single-center, prospective cohort study. Patients admitted to the cardiology unit for arrhythmia treatment who required a wireless ECG telemonitoring system were enrolled. A single-lead ECG patch and conventional telemetry were applied simultaneously in hospitalized patients for over 24 hours for real-time telemonitoring. The basic ECG parameters, arrhythmia episodes, and signal loss or noise were compared between the 2 systems. Eighty participants (mean age 62±10 years, 76.3% male) were enrolled. The three most common indications for ECG telemonitoring were atrial fibrillation (66.3%), sick sinus syndrome (12.5%), and atrioventricular block (10.0%). The intra-class correlation coefficients for detecting the number of total beats, atrial and ventricular premature complexes, maximal, average, and minimal heart rates, and pauses were all over 0.9 with p values for reliability <0.001. Compared to a conventional system, a novel system demonstrated significantly lower signal noise (median 0.3% [0.1-1.6%] vs. 2.4% [1.4-3.7%], p<0.001) and fewer episodes of signal loss (median 22 [2-53] vs. 64 [22-112] episodes, p=0.002). The novel telemonitoring system using a single-lead ECG patch offers performance comparable to that of a conventional system while significantly reducing signal loss and noise. Clinical Research Information Service Identifier: KCT0008176.

The Influence of Large Pendent Groups on Chain Anisotropy and Electrical Energy Loss of Polyimides at High Frequency through All-Atomic Molecular Simulation.

Polyimide is a potential material for high-performance printed circuit boards because of its chemical stability and excellent thermal and mechanical properties. Flexible printed circuit boards must have a low static dielectric constant and dielectric loss to reduce signal loss in high-speed communication devices. Engineering the molecular structure of polyimides with large pendant groups is a strategy to reduce their dielectric constant. However, there is no systematic study on how the large pendant groups influence electrical energy loss. We integrated all-atomic molecular dynamics and semi-empirical quantum mechanical calculations to examine the influence of pendant groups on polymer chain anisotropy and electrical energy loss at high frequencies. We analyzed the radius of gyration, relative shape anisotropy, dipole moment, and degree of polarization of the selected polyimides (TPAHF, TmBPHF, TpBPHF, MPDA, TriPMPDA, m-PDA, and m-TFPDA). The simulation results show that anisotropy perpendicular to chain direction and local chain rigidity correlate to electrical energy loss rather than dipole moment magnitudes. Polyimides with anisotropic pendant groups and significant local chain rigidity reduce electrical energy loss. The degree of polarization correlated well with the dielectric loss with a moderate computational cost, and difficulties in directly calculating the dielectric loss were circumvented.

Feature-guided deep learning reduces signal loss and increases lesion CNR in diffusion-weighted imaging of the liver

PurposeThis research aims to develop a feature-guided deep learning approach and compare it with an optimized conventional post-processing algorithm in order to enhance the image quality of diffusion-weighted liver images and, in particular, to reduce the pulsation-induced signal loss occurring predominantly in the left liver lobe. MethodsData from 40 patients with liver lesions were used. For the conventional approach, the best-suited out of five examined algorithms was chosen. For the deep learning approach, a U-Net was trained. Instead of learning “gold-standard” target images, the network was trained to optimize four image features (lesion CNR, vessel darkness, data consistency, and pulsation artifact reduction), which could be assessed quantitatively using manually drawn ROIs. A quality score was calculated from these four features. As an additional quality assessment, three radiologists rated different features of the resulting images. ResultsThe conventional approach could substantially increase the lesion CNR and reduce the pulsation-induced signal loss. However, the vessel darkness was reduced. The deep learning approach increased the lesion CNR and reduced the signal loss to a slightly lower extent, but it could additionally increase the vessel darkness. According to the image quality score, the quality of the deep-learning images was higher than that of the images obtained using the conventional approach. The radiologist ratings were mostly consistent with the quantitative scores, but the overall quality ratings differed among the readers. ConclusionUnlike the conventional algorithm, the deep-learning algorithm increased the vessel darkness. Therefore, it may be a viable alternative to conventional algorithms.

A Personalized Compression Method for Steady-State Visual Evoked Potential EEG Signals

As an informative electroencephalogram (EEG) signal, steady-state visual evoked potential (SSVEP) stands out from many paradigms for application in wireless wearable devices. However, its data are usually enormous, occupy too many bandwidth sources and require immense power when transmitted in the raw data form, so it is necessary to compress the signal. This paper proposes a personalized EEG compression and reconstruction algorithm for the SSVEP application. In the algorithm, to realize personalization, a primary artificial neural network (ANN) model is first pre-trained with the open benchmark database towards BCI application (BETA). Then, an adaptive ANN model is generated with incremental learning for each subject to compress their individual data. Additionally, a personalized, non-uniform quantization method is proposed to reduce the errors caused by compression. The recognition accuracy only decreases by 3.79% when the compression rate is 12.7 times, and is tested on BETA. The proposed algorithm can reduce signal loss by from 50.43% to 81.08% in the accuracy test compared to the case without ANN and uniform quantization.

In vivo 1 H MR spectroscopy with J-refocusing.

The goal of this study was to propose a novel localized proton MR spectroscopy (MRS) sequence that reduces signal loss due to J-modulation in the rat brain in vivo. Sprague-Dawley rats were studied at 9.4 T. A semi-LASER sequence with evenly distributed echo-time (TE ) was used, and a 90° J-refocusing pulse was inserted at TE /2. Proton spectra were acquired at two TE s (30 and 68 ms), with and without the J-refocused pulse. Data were processed in MATLAB and quantified with LCModel. The J-refocused spectrum acquired at TE = 30 ms did not show any signal losses due to J-modulation and had comparable spectral pattern to the one acquired with semi-LASER using the minimum achievable TE . Higher signal amplitudes for glutamine, γ-aminobutyric acid and glutathione led to more reliable quantification precision for these metabolites. The refocused signal intensities at TE = 68 ms were also unaffected by J-modulation but were smaller than the signals at TE = 30 ms mainly due to transverse T2 relaxation of metabolites. The proposed localized MRS sequence will be beneficial in both animal and human MRS studies when using ultra-short TE is not possible while also providing more reliable quantification precision for J-coupled metabolites.

A 16-Element Fully Integrated 28-GHz Digital RX Beamforming Receiver

A 16-element fully integrated 28-GHz digital beamformer combines with a custom eight-layer LTCC substrate with a 4 $\times \,\,{4}$ patch antenna array for a complete 16-element single-chip 28-GHz millimeter-wave (mm-wave)-to-digital beamforming system. Sixteen-element digital beamforming in a single integrated circuit (IC) represents an excellent tradeoff between die size, signal loss, and I/O routing complexity. Per-element RX slices with an inductor-less mm-wave front end and 4 $\times $ parallel continuous-time bandpass delta–sigma analog-to-digital conversion (ADC) arrays enable compact mm-wave-to-digital conversion. The 4 $\times $ parallel ADC array provides in-built finite-impulse response (FIR) filtering for additional harmonic suppression and anti-alias filtering. ADC sampling of a high (1 GHz) IF facilitates single-phase mm-wave local oscillator (LO) routing and moves the I/Q mixing into the digital domain. Optimum bump and RX slice placement shortens LO and mm-wave signal routing and reduces signal loss. Bit-stream processing (BSP) takes advantage of the narrow bit-width raw outputs of the RX slices to implement digital beamforming with area- and energy-efficient MUXes. The prototype 16-element beamformer generates four independent, simultaneous beams. Over-the-air measurements confirm accurate 3-D beam patterns and indicate a measured overall noise figure of 7 dB and QAM-4 error vector magnitude (EVM) of −18 dB.

A Comparison Study of Rectifier Designs for 2.45 GHz EM Energy Harvesting

Energy harvesting is a rapidly growing area in many scientific and engineering-related fields due to the demand for many applications. This paper focuses on the design and simulation of the voltage doubler rectifier circuit at 2.45 GHz operating frequency. The design of a rectifier is optimized based on the use of Schottky diode HSMS 286 B due to its low forward voltage at this frequency. 2 stages of the Schottky diode voltage doublers circuit are designed and simulated in this paper. The shunt capacitor and optimal load resistance are also introduced in the course to reduce signal loss. A multi-stage rectifier is used to produce maximum power conversion from AC to DC. The simulated results present that the maximum output voltage of 6.651 V with an input power of 25 dBm is produced, which presents a maximum power conversion efficiency of 73.13%, which applicable in small device applications.

Rotated spiral RARE for high spatial and temporal resolution volumetric arterial spin labeling acquisition

BackgroundArterial Spin Labeling (ASL) MRI can provide quantitative images that are sensitive to both time averaged blood flow and its temporal fluctuations. 3D image acquisitions for ASL are desirable because they are more readily compatible with background suppression to reduce noise, can reduce signal loss and distortion, and provide uniform flow sensitivity across the brain. However, single-shot 3D acquisition for maximal temporal resolution typically involves degradation of image quality through blurring or noise amplification by parallel imaging. Here, we report a new approach to accelerate a common stack of spirals 3D image acquisition by pseudo golden-angle rotation and compressed sensing reconstruction without any degradation of time averaged blood flow images. Methods28 healthy volunteers were imaged at 3T with background-suppressed unbalanced pseudo-continuous ASL combined with a pseudo golden-angle Stack-of-Spirals 3D RARE readout. A fully-sampled perfusion-weighted volume was reconstructed by 3D non-uniform Fast Fourier Transform (nuFFT) followed by sum-of-squares combination of the 32 individual channels. Coil sensitivities were estimated followed by reconstruction of the 39 single-shot volumes using an L1-wavelet Compressed-Sensing reconstruction. Finally, brain connectivity analyses were performed in regions where BOLD signal suffers from low signal-to-noise ratio and susceptibility artifacts. ResultsImage quality, assessed with a non-reference 3D blurring metric, of full time averaged blood flow was comparable to a conventional interleaved acquisition. The temporal resolution provided by the acceleration enabled identification and quantification of resting-state networks even in inferior regions such as the amygdala and inferior frontal lobes, where susceptibility artifacts can degrade conventional resting-state fMRI acquisitions. ConclusionThis approach can provide measures of blood flow modulations and resting-state networks for free within any research or clinical protocol employing ASL for resting blood flow.

Evaluation of a position-sensitive prototype detector unit for fast neutron imaging and spectroscopy

A novel fast neutron scatter camera with capabilities of neutron imaging and spectroscopy is under development. The detection principle is based on multiple neutron–proton (n–p) elastic scattering interactions in organic scintillator. In order to improve position measurement accuracy of recoil protons, a position-sensitive prototype detector unit has been designed and characterized experimentally. The presented detector unit consisted of a plastic scintillator sheet of 10 cm × 10 cm × 1 cm dimensions and two groups (6 × 2) of wavelength-shifting fibers with orthogonal directions embedded into grooves on two opposite scintillator surfaces. Scintillation signals were read out by silicon photomultipliers (SiPMs). A collimated Sr-90 radioactive source was utilized for system calibration and position resolution measurement. Light output of the unidimensional six fiber channels from one side of the detector unit was calibrated to be 14.45 photoelectrons per MeVee. Position resolution of the detector unit was measured to be 0.35–0.44 times fiber pitch, corresponding to 5.48 mm for proton recoil energy interval of 1.63–2.60 MeV, and 4.60 mm for proton recoil energy interval of 4.82–5.50 MeV. Energy threshold for recoil proton localization was estimated to be 1.18 MeV. The results shown satisfy basic requirements of the scatter camera, while space exists for further improvements. The positioning performance optimization consists of three aspects. The first one is to increase the fiber diameter so as to reduce signal loss. The second one is to depress dark rate of the SiPMs. The last one is to decrease the number of channels involved in position reconstruction by narrowing the scintillation signal distribution function of the detector unit.

Improving the Quality of Diffusion-weighted Imaging of the Left Hepatic Lobe Using Weighted Averaging of Signals from Multiple Excitations.

Background:Diffusion-weighted imaging (DWI) is useful for detecting and characterizing liver lesions but is sensitive to organ motion artifact, especially in the left lobe.Purpose:To assess the signal intensity (SI) loss in the left hepatic lobe on DWI depending on motion-proving gradient (MPG) pulse direction (preliminary study) and to evaluate the usefulness of modified signal averaging to reduce the SI loss on DWI (application study).Methods:About 48 (preliminary) and 35 (application) patients were included. In the preliminary study, DWI with four different MPG directions, only a single MPG pulse direction (x-, y-, or z-axis) and all three directions combined (standard DWI), were reconstructed from the original data. In the application study, we examined the usefulness of the weighted averaging number of excitations (wNEX) method, in which a larger weighting factor is applied to the higher signal in pixel-by-pixel NEX signal averaging by comparing four reconstruction methods. We assumed that true signals would be the same in both lobes. The SI and apparent diffusion coefficient (ADC) ratios for the left versus right lobe were calculated by dividing the SI/ADC of the right lobe by that of the left lobe.Results:In the preliminary study, the SI ratio was significantly lower on DWI using only the x-axis but was significantly higher on DWI using only the z-axis (both P < 0.0001) when compared with standard DWI. In the application study, the SI (mean, 1.15–1.17) and ADC (0.90–0.92) ratios on DWI with wNEX were closer to 1.0 than those on standard DWI (SI ratio, 1.32–1.38; ADC ratio 0.80–0.81); the differences were significant (all P < 0.0001).Conclusion:The MPG pulse along the z-axis caused signal loss in the left hepatic lobe. The wNEX reconstruction method effectively reduced signal loss in the left lobe on DWI.

Quantum Trajectories and Their Statistics for Remotely Entangled Quantum Bits

We experimentally and theoretically investigate the quantum trajectories of jointly monitored transmon qubits embedded in spatially separated microwave cavities. Using nearly quantum-noise limited superconducting amplifiers and an optimized setup to reduce signal loss between cavities, we can efficiently track measurement-induced entanglement generation as a continuous process for single realizations of the experiment. The quantum trajectories of transmon qubits naturally split into low and high entanglement classes corresponding to half-parity collapse. The distribution of concurrence is found at any given time and we explore the dynamics of entanglement creation in the state space. The distribution exhibits a sharp cut-off in the high concurrence limit, defining a maximal concurrence boundary. The most likely paths of the qubits' trajectories are also investigated, resulting in three probable paths, gradually projecting the system to two even subspaces and an odd subspace. We also investigate the most likely time for the individual trajectories to reach their most entangled state, and find that there are two solutions for the local maximum, corresponding to the low and high entanglement routes. The theoretical predictions show excellent agreement with the experimental entangled qubit trajectory data.

Reducing signal loss of the parahippocampal gyrus improves imaging of the default-mode network in 3.0-T MRI: the effect of susceptibility-induced field gradients.

Previous investigations have indicated that the default-mode network (DMN) is highly involved in memory processing in the parahippocampal gyrus (PHC). However, because of susceptibility-related signal loss, parahippocampal activation in the DMN is difficult to detect in resting-state functional MRI experiments that are conducted using a 3.0-T MRI scanner. This study investigated the magnetic field gradients of various brain regions and attempted to compensate for signal loss in the PHC using an optimized slice orientation. The field gradients, signal intensities and DMN functional connectivity (FC) of the PHC were investigated using datasets acquired from 18 healthy volunteers. The results show that the field gradient component parallel to the main magnetic field dominates the PHC. The results indicate that the signal intensities and FC of the DMN are significantly low in the PHC when the slice orientation of the imaging plane is transversal. Whether the voxel dimension is isotropic or anisotropic exerts a minimal effect in altering the slice orientation dependence. In conclusion, the results of this study support the selection of the coronal or sagittal planes for imaging of the DMN.

GNSS Signal Tracking Performance Improvement for Highly Dynamic Receivers by Gyroscopic Mounting Crystal Oscillator.

In this paper, the efficiency of the gyroscopic mounting method is studied for a highly dynamic GNSS receiver’s reference oscillator for reducing signal loss. Analyses are performed separately in two phases, atmospheric and upper atmospheric flights. Results show that the proposed mounting reduces signal loss, especially in parts of the trajectory where its probability is the highest. This reduction effect appears especially for crystal oscillators with a low elevation angle g-sensitivity vector. The gyroscopic mounting influences frequency deviation or jitter caused by dynamic loads on replica carrier and affects the frequency locked loop (FLL) as the dominant tracking loop in highly dynamic GNSS receivers. In terms of steady-state load, the proposed mounting mostly reduces the frequency deviation below the one-sigma threshold of FLL (1σFLL). The mounting method can also reduce the frequency jitter caused by sinusoidal vibrations and reduces the probability of signal loss in parts of the trajectory where the other error sources accompany this vibration load. In the case of random vibration, which is the main disturbance source of FLL, gyroscopic mounting is even able to suppress the disturbances greater than the three-sigma threshold of FLL (3σFLL). In this way, signal tracking performance can be improved by the gyroscopic mounting method for highly dynamic GNSS receivers.

Variable slice-thickness (VAST) EPI for the reduction of signal voids in GE-EPI at 7 Tesla

2D gradient-echo EPI of the human brain suffers from signal loss artifacts caused by susceptibility-induced gradients perpendicular to the slice plane. The problem is most pronounced near the skull's air cavities and compromises BOLD fMRI studies in regions including orbito-frontal and temporal cortex. The spins across the excited rectangular target slice profile are effectively dephased by through-plane gradient GS,z as can be seen for two slices in Fig 1 at 7 T. According to the expression on the right (see Fig 1) many methods exist to address the issue, including z-shimming[1], tailored RF excitations[2], short or slice-dependent TE[3] and the use of thin slices for a defined region[4]. The drawback is that optimizing parameters for a certain region will compromise sensitivity elsewhere and result in unfeasibly long TR for whole brain coverage. Hence, we propose a new technique dubbed 'Variable SliceThickness EPI' (VAST EPI) to reduce signal loss and keeping TR manageable in 2D GE-EPI. The slice thickness is varied across the brain, with thinner slices being used in the inferior regions where signal voids are most severe. Various scheme of slice thickness variation are evaluated and compared to regular EPI.

A comparison of dual gradient‐echo and spin‐echo fMRI of the inferior temporal lobe

Magnetic susceptibility differences at tissue interfaces lead to signal loss in conventional gradient-echo (GE) EPI. This poses a problem for fMRI in language and memory paradigms, which activate the most affected regions. Two methods proposed to overcome this are spin-echo EPI and dual GE EPI, where two EPI read-outs are serially collected at a short and longer echo time. The spin-echo method applies a refocusing pulse to recover dephased MR signal due to static field inhomogeneities, but is known to have a relatively low blood oxygenation level dependant (BOLD) sensitivity. In comparison, GE has superior BOLD sensitivity, and by employing an additional shorter echo, in a dual GE sequence, it can reduce signal loss due to spin dephasing. We directly compared dual GE and spin-echo fMRI during a semantic categorization task, which has been shown to activate the inferior temporal region-a region known to be affected by magnetic susceptibility. A whole brain analysis showed that the dual GE resulted in significantly higher activation within the left inferior temporal fusiform (ITF) cortex, compared to spin-echo. The inferior frontal gyrus (IFG) was activated for dual GE, but not spin-echo. Regions of interest analysis was carried out on the anterior and posterior ITF, left and right IFG, and part of the cerebellum. Dual GE outperformed spin-echo in the anterior and posterior ITF and bilateral IFG regions, whilst being equal in the cerebellum. Hence, dual GE should be the method of choice for fMRI studies of inferior temporal regions.