A chromatin remodelling SWI/SNF subunit, Snr1, regulates neural stem cell determination and differentiation.

Coordinated spatio-temporal regulation of the determination and differentiation of neural stem cells is essential for brain development. Failure to integrate multiple factors leads to defective brain structures or tumour formation. Previous studies suggest changes of chromatin state are needed to direct neural stem cell differentiation, but the mechanisms are unclear. Analysis of Snr1, the Drosophila orthologue of SMARCB1, an ATP-dependent chromatin remodelling protein, identified a key role in regulating the transition of neuroepithelial cells into neural stem cells and subsequent differentiation of neural stem cells into the cells needed to build the brain. Loss of Snr1 in neuroepithelial cells leads to premature neural stem cell formation. Additionally, loss of Snr1 in neural stem cells results in inappropriate perdurance of neural stem cells into adulthood. Snr1 reduction in neuroepithelial or neural stem cells leads to the differential expression of target genes. We find that Snr1 is associated with the actively transcribed chromatin region of these target genes. Thus, Snr1 likely regulates the chromatin state in neuroepithelial cells and maintains chromatin state in neural stem cells for proper brain development.

Auditory oddball responses in the human subthalamic nucleus and substantia nigra pars reticulata.

The auditory oddball is a mainstay in research on attention, novelty, and sensory prediction. How this task engages subcortical structures like the subthalamic nucleus and substantia nigra pars reticulata is unclear. We administered an auditory OB task while recording single unit activity (35 units) and local field potentials (57 recordings) from the subthalamic nucleus and substantia nigra pars reticulata of 30 patients with Parkinson's disease undergoing deep brain stimulation surgery. We found tone modulated and oddball modulated units in both regions. Population activity differentiated oddball from standard trials from 200 ms to 1000 ms after the tone in both regions. In the substantia nigra, beta band activity in the local field potential was decreased following oddball tones. The oddball related activity we observe may underlie attention, sensory prediction, or surprise-induced motor suppression.

Optimizing background suppression for dual-module velocity-selective arterial spin labeling: Without using additional background-suppression pulses.

PURPOSE: Background suppression (BS) is recommended in arterial spin labeling (ASL) for improved SNR but is difficult to optimize in existing velocity-selective ASL (VSASL) methods. Dual-module VSASL (dm-VSASL) enables delay-insensitive, robust, and SNR-efficient perfusion imaging, while allowing efficient BS, but its optimization has yet to be thoroughly investigated. METHODS: The inversion effects of the velocity-selective labeling pulses, such as velocity-selective inversion (VSI), can be used for BS, and were modeled for optimizing BS in dm-VSASL. In vivo experiments using dual-module VSI (dm-VSI) were performed to compare two BS strategies: a conventional one with additional BS pulses and a new one without any BS pulse. Their BS performance, temporal noise, and temporal SNR were examined and compared, with pulsed and pseudo-continuous ASL (PASL and PCASL) as the reference. RESULTS: The in vivo experiments validated the BS modeling. Strong positive linear correlations (r > 0.82, p < 0.0001) between the temporal noise and the tissue signal were found in PASL/PCASL and dm-VSI. Optimal BS can be achieved with and without additional BS pulses in dm-VSI; the latter improved the ASL signals by 8.5% in gray matter (p = 0.006) and 12.2% in white matter (p = 0.014) and tended to provide better temporal SNR. The dm-VSI measured significantly higher ASL signal (p < 0.016) and temporal SNR (p < 0.018) than PASL and PCASL. Complex reconstruction was found necessary with aggressive BS. CONCLUSION: Guided by modeling, optimal BS can be achieved without any BS pulse in dm-VSASL, further improving the ASL signal and the SNR performance.

Optimal filters for ERP research II: Recommended settings for seven common ERP components.

In research with event-related potentials (ERPs), aggressive filters can substantially improve the signal-to-noise ratio and maximize statistical power, but they can also produce significant waveform distortion. Although this tradeoff has been well documented, the field lacks recommendations for filter cutoffs that quantitatively address both of these competing considerations. To fill this gap, we quantified the effects of a broad range of low-pass filter and high-pass filter cutoffs for seven common ERP components (P3b, N400, N170, N2pc, mismatch negativity, error-related negativity, and lateralized readiness potential) recorded from a set of neurotypical young adults. We also examined four common scoring methods (mean amplitude, peak amplitude, peak latency, and 50% area latency). For each combination of component and scoring methods, we quantified the effects of filtering on data quality (noise level and signal-to-noise ratio) and waveform distortion. This led to recommendations for optimal low-pass and high-pass filter cutoffs. We repeated the analyses after adding artificial noise to provide recommendations for data sets with moderately greater noise levels. For researchers who are analyzing data with similar ERP components, noise levels, and participant populations, using the recommended filter settings should lead to improved data quality and statistical power without creating problematic waveform distortion.

Evaluating the effectiveness of artifact correction and rejection in event-related potential research.

Eyeblinks and other large artifacts can create two major problems in event-related potential (ERP) research, namely confounds and increased noise. Here, we developed a method for assessing the effectiveness of artifact correction and rejection methods in minimizing these two problems. We then used this method to assess a common artifact minimization approach, in which independent component analysis (ICA) is used to correct ocular artifacts, and artifact rejection is used to reject trials with extreme values resulting from other sources (e.g., movement artifacts). This approach was applied to data from five common ERP components (P3b, N400, N170, mismatch negativity, and error-related negativity). Four common scoring methods (mean amplitude, peak amplitude, peak latency, and 50% area latency) were examined for each component. We found that eyeblinks differed systematically across experimental conditions for several of the components. We also found that artifact correction was reasonably effective at minimizing these confounds, although it did not usually eliminate them completely. In addition, we found that the rejection of trials with extreme voltage values was effective at reducing noise, with the benefits of eliminating these trials outweighing the reduced number of trials available for averaging. For researchers who are analyzing similar ERP components and participant populations, this combination of artifact correction and rejection approaches should minimize artifact-related confounds and lead to improved data quality. Researchers who are analyzing other components or participant populations can use the method developed in this study to determine which artifact minimization approaches are effective in their data.

HiHi fMRI: a data-reordering method for measuring the hemodynamic response of the brain with high temporal resolution and high SNR.

There is emerging evidence that sampling the blood-oxygen-level-dependent (BOLD) response with high temporal resolution opens up new avenues to study the in vivo functioning of the human brain with functional magnetic resonance imaging. Because the speed of sampling and the signal level are intrinsically connected in magnetic resonance imaging via the T1 relaxation time, optimization efforts usually must make a trade-off to increase the temporal sampling rate at the cost of the signal level. We present a method, which combines a sparse event-related stimulus paradigm with subsequent data reshuffling to achieve high temporal resolution while maintaining high signal levels (HiHi). The proof-of-principle is presented by separately measuring the single-voxel time course of the BOLD response in both the primary visual and primary motor cortices with 100-ms temporal resolution.

Speech perception outcomes in hearing-impaired individuals with microphone & receiver in the ear (M&RIE) hearing aids.

PURPOSE: The Microphone and Receiver in the ear (M&RIE) hearing aid is designed to consider the pinna cues by placing an additional microphone along with a standard receiver at the entrance of the ear canal. There is a need to clinically validate the technology using speech identification measures, as a literature shortage exists. The objective of the study was to evaluate speech identification and quality rating with hearing aids fitted with standard and M&RIE receivers. METHOD: Twenty individuals (mean ± SD age being 34.10 ± 11.9 years) with mild-to-moderately severe sensorineural hearing loss were divided into two groups: naïve and experienced. Their speech identification obtained using the receiver in the ear hearing aid compatible with standard and M&RIE receivers were compared. The study assessed speech identification in quiet using ten sentences, calculated SNR-50 using the Spearman-Karber equation, and used an 11-point scale for self-perceived quality rating. RESULTS: The study analyzed data using SPSS and found no significant difference between naive and experienced hearing aid users in quiet and SNR-50 conditions (p > 0.05). However, naive users rated higher in clarity, naturalness, pleasantness, and overall impression of standard receiver settings. Across different receiver settings, both naïve and experienced groups revealed better speech identification with the M&RIE receiver for both SIS (p < 0.05) and SNR-50 (p < 0.05) measures. CONCLUSION: The study found that placing a third microphone in the ear canal improves speech identification and quality rating in both naïve and experienced users, with pinna and ear canal resonance playing a crucial role in prescribing hearing aid gain.

Receive coil quality assurance procedure and automated analysis for ViewRay MRIdian MR-Linac.

PURPOSE: Regular receiving coil quality assurance (QA) is required to ensure image quality of an MRIdian Linac system. The manufacturer provides a spherical phantom and positioning tube for single-slice signal-to-noise ratio (SNR) and uniformity assessments. We aimed to improve imaging setup and coverage and eliminate inter-scan variability by employing multi-slice imaging of a stable phantom. Additionally, we strived to expedite analysis by developing objective, automated analysis software. METHODS: A 5300 mL cylindrical plastic bottle placed in plastic bins was scanned at isocenter using a spin-echo sequence with NEMA-recommended parameters and 18 axial slices, avoiding phantom repositioning. Acquisition was repeated with and without prescan normalization filtering and by saving uncombined element images. Obtained data were analyzed using custom open-source MATLAB code. Signal and noise images were automatically assigned, and ROIs for SNR and uniformity calculations were defined using image thresholding. SNR and uniformity pass/fail decisions were made using baseline comparisons. RESULTS: The proposed method was successfully implemented as monthly coil QA for 3.5 years. Setup and scanning took 41 min on average for a coil set. Automated image analysis was completed in a few minutes. Signal intensity peaked around +90 or -90 mm for Torso or Head/Neck coil unfiltered images. Noise peaked and minimized SNR inside ±30 mm from isocenter, while maximizing it around ±130 mm. Prescan normalization smoothed signal response, reduced SNR and increased uniformity. Individual coil element image analysis identified their position, signal or noise response and SNR. SNR and uniformity pass/fail thresholds were set for already tested and new coils. Conspicuous and subtle Torso coil malfunctions were detected considering baseline deviations of combined and individual element results. CONCLUSIONS: Our QA method eliminated observer bias and provided insights into coil function, image filtering performance and coil element location. It provided SNR and uniformity thresholds and identified faulty coil elements.

Human Observer Sensitivity to Temporal Noise During B-Mode Ultrasound Scanning: Characterization and Imaging Implications.

This work measures temporal signal-to-noise ratio (SNR) thresholds that indicate when random noise during ultrasound scanning becomes imperceptible to expert human observers. Visible noise compromises image quality and can potentially lead to non-diagnostic scans. Noise can arise from both stable acoustic sources (clutter) or randomly varying electronic sources (temporal noise). Extensive engineering effort has focused on decreasing noise in both of these categories. In this work, an observer study with five practicing sonographers was performed to assess sonographer sensitivity to temporal noise in ultrasound cine clips. Understanding the conditions where temporal noise is no longer visible during ultrasound imaging can inform engineering efforts seeking to minimize the impact this noise has on image quality. The sonographers were presented with paired temporal noise-free and noise-added simulated speckle cine clips and asked to select the noise-added clips. The degree of motion in the imaging target was found to have a significant effect on the SNR levels where noise was perceived, while changing imaging frequency had little impact. At realistic in vivo motion levels, temporal noise was not perceived in cine clips at and above 28 dB SNR. In a case study presented here, the potential of adaptive intensity adjustment based on this noise perception threshold is validated in a fetal imaging scenario. This study demonstrates how noise perception thresholds can be applied to help design or tune ultrasound systems for different imaging tasks and noise conditions.

An SNR Enhancement Method for Φ-OTDR Vibration Signals Based on the PCA-VSS-NLMS Algorithm.

To improve the signal-to-noise ratio (SNR) of vibration signals in a phase-sensitive optical time-domain reflectometer (Φ-OTDR) system, a principal component analysis variable step-size normalized least mean square (PCA-VSS-NLMS) denoising method was proposed in this study. First, the mathematical principle of the PCA-VSS-NLMS algorithm was constructed. This algorithm can adjust the input signal to achieve the best filter effect. Second, the effectiveness of the algorithm was verified via simulation, and the simulation results show that compared with the wavelet denoising (WD), Wiener filtering, variational mode decomposition (VMD), and variable step-size normalized least mean square (VSS-NLMS) algorithms, the PCA-VSS-NLMS algorithm can improve the SNR to 30.68 dB when the initial SNR is -1.23 dB. Finally, the PCA-VSS-NLMS algorithm was embedded into the built Φ-OTDR system, an 11.22 km fiber was measured, and PZT was added at 10.19-10.24 km to impose multiple sets of fixed-frequency disturbances. The experimental results show that the SNR of the vibration signal is 8.77 dB at 100 Hz and 0.07 s, and the SNR is improved to 26.17 dB after PCA-VSS-NLMS filtering; thus, the SNR is improved by 17.40 dB. This method can improve the SNR of the system's position information without the need to change the existing hardware conditions, and it provides a new scheme for the detection and recognition of long-distance vibration signals.

Time-Efficient SNR Optimization of WMS-Based Gas Sensor Using a Genetic Algorithm.

This paper presents the description of the wavelength modulation spectroscopy (WMS) experiment, the parameters of which were established by use of the Artificial Intelligence (AI) algorithm. As a result, a significant improvement in the signal power to noise power ratio (SNR) was achieved, ranging from 1.6 to 6.5 times, depending on the harmonic. Typically, optimizing the operation conditions of WMS-based gas sensors is based on long-term simulations, complex mathematical model analysis, and iterative experimental trials. An innovative approach based on a biological-inspired genetic algorithm (GA) and custom-made electronics for laser control is proposed. The experimental setup was equipped with a 31.23 m Heriott multipass cell, software lock-in, and algorithms to control the modulation process of the quantum cascade laser (QCL) operating in the long-wavelength-infrared (LWIR) spectral range. The research results show that the applied evolutionary approach can efficiently and precisely explore a wide range of WMS parameter combinations, enabling researchers to dramatically reduce the time needed to identify optimal settings. It took only 300 s to test approximately 1.39 × 1032 combinations of parameters for key system components. Moreover, because the system is able to check all possible component settings, it is possible to unquestionably determine the operating conditions of WMS-based gas sensors for which the limit of detection (LOD) is the most favorable.

A Method for Correcting Signal Aberrations in Ultrasonic Indoor Positioning.

The increasing focus on the development of positioning techniques reflects the growing interest in applications and services based on indoor positioning. Many applications necessitate precise indoor positioning or tracking of individuals and assets, leading to rapid growth in products based on these technologies in certain market sectors. Ultrasonic systems have already proven effective in achieving the desired positioning accuracy and refresh rates. The typical signal used in ultrasonic positioning systems for estimating the range between the target and reference points is the linear chirp. Unfortunately, it can undergo shape aberration due to the effects of acoustic diffraction when the aperture exceeds a certain limit. The extent of the aberration is influenced by the shape and size of the transducer, as well as the angle at which the transducer is observed by the receiver. This aberration also affects the shape of the cross-correlation, causing it to lose its easily detectable characteristic of a single global peak, which typically corresponds to the correct lag associated with the signal's time of arrival. In such instances, cross-correlation techniques yield results with a significantly higher error than anticipated. In fact, the correct lag no longer corresponds to the peak of the cross-correlation. In this study, an alternative technique to global peak detection is proposed, leveraging the inherent symmetry observed in the shape of the aberrated cross-correlation. The numerical simulations, performed using the academic acoustic simulation software Field II, conducted using a typical ultrasonic chirp and ultrasonic emitter, compare the classical and the proposed range techniques in a standard office room. The analysis includes the effects of acoustical reflection in the room and of the acoustic noise at different levels of power. The results demonstrate that the proposed technique enables accurate range estimation even in the presence of severe cross-correlation shape aberrations and for signal-to-noise ratio levels common in office and room environments, even in presence of typical reflections. This allows the use of emitting transducers with a much larger aperture than that allowed by the classical cross-correlation technique. Consequently, it becomes possible to have greater acoustic power available, leading to improved signal-to-noise ratio (SNR).

Performance Estimation of a Medium-Resolution Earth Observation Sensor Using Nanosatellite Replica.

In many areas of engineering, the design of a new system usually involves estimating performance-related parameters from early stages of the project to determine whether a given solution will be compliant with the defined requirements. This aspect is particularly relevant during the design of satellite payloads, where the target environment is not easily accessible in most cases. In the context of Earth observation sensors, this problem has been typically solved with the help of a set of complex pseudo-empirical models and/or expensive laboratory equipment. This paper describes a more practical approach: the illumination conditions measured by an in-orbit payload are recreated on ground with the help of a replica of the same payload so the performance of another Earth observation sensor in development can be evaluated. The proposed method is specially relevant in the context of small satellites, as the possibility of having extra units devoted to these tasks becomes greater as costs are reduced. The results obtained using this method in an actual space mission are presented in this paper, giving valuable information that will help in further stages of the project.

A Critical Review of the Propagation Models Employed in LoRa Systems.

LoRa systems are emerging as a promising technology for wireless sensor networks due to their exceptional range and low power consumption. The successful deployment of LoRa networks relies on accurate propagation models to facilitate effective network planning. Therefore, this review explores the landscape of propagation models supporting LoRa networks. Specifically, we examine empirical propagation models commonly employed in communication systems, assessing their applicability across various environments such as outdoor, indoor, and within vegetation. Our investigation underscores the prevalence of logarithmic decay in most empirical models. In addition, we survey the relationship between model parameters and environmental factors, clearing their nuanced interplay. Analyzing published measurement results, we extract the log-distance model parameters to decipher environmental influences comprehensively. Drawing insights from published measurement results for LoRa, we compare them with the model's outcomes, highlighting successes and limitations. We additionally explore the application of multi-slope models to LoRa measurements to evaluate its effectiveness in enhancing the accuracy of path loss prediction. Finally, we propose new lines for future research in propagation modelling to improve empirical models.

Performance Analysis of Centralized Cooperative Schemes for Compressed Sensing.

This paper presents a performance analysis of centralized spectrum sensing based on compressed measurements. We assume cooperative sensing, where unlicensed users individually perform compressed sensing and send their results to a fusion center, which makes the final decision about the presence or absence of a licensed user signal. Several cooperation schemes are considered, such as and-rule, or-rule, majority voting, soft equal-gain combining (EGC). The proposed analysis provides simplified closed-form expressions that calculate the required number of sensors, the required number of samples, the required compression ratio, and the required signal-to-noise ratio (SNR) as a function of the probability of detection and the probability of the false alarm of the fusion center and of the sensors. The resulting expressions are derived by exploiting some accurate approximations of the test statistics of the fusion center and of the sensors, equipped with energy detectors. The obtained results are useful, especially for a low number of sensors and low sample sizes, where conventional closed-form expressions based on the central limit theorem (CLT) fail to provide accurate approximations. The proposed analysis also allows the self-computation of the performance of each sensor and of the fusion center with reduced complexity.

High SNR rapid T1 -weighted MPRAGE using spiral imaging with long readouts and improved deblurring.

PURPOSE: The goal of this work is to present the implementation of 3D spiral high-resolution MPRAGE and to demonstrate that SNR and scan efficiency increase with the increment of readout time. THEORY: Simplified signal equations for MPRAGE indicate that the T1 contrast can be kept approximately the same by a simple relationship between the flip angle and the TR. Furthermore, if T1 contrast remains the same, image SNR depends on the square root of the product of the total scan time and the readout time. METHODS: MPRAGE spiral sequences were implemented with distributed spirals and spiral staircase on 3 Tesla scanners. Brain images of three volunteers were acquired with different readout times. Spiral images were processed with a joint water-fat separation and deblurring algorithm and compared to Cartesian images. Pure noise data sets were also acquired for SNR evaluation. RESULTS: Consistent T1 weighting can be achieved with various spiral readout lengths, and between spiral MPRAGE imaging and the traditional Cartesian MPRAGE imaging. Noise performance analysis demonstrates higher SNR efficiency of spiral MPRAGE imaging with matched T1 contrast compared to the Cartesian reference imaging. CONCLUSION: Fast, high SNR MPRAGE imaging is feasible with long readout spiral trajectories.

Quadrature transceive wireless coil: Design concept and application for bilateral breast MRI at 1.5 T.

PURPOSE: Development of a novel quadrature inductively driven transceive wireless coil for breast MRI at 1.5 T. METHODS: A quadrature wireless coil (HHMM-coil) design has been developed as a combination of two linearly polarized coils: a pair of 'metasolenoid' coils (MM-coil) and a pair of Helmholtz-type coils (HH-coil). The MM-coil consisted of an array of split-loop resonators. The HH-coil design included two electrically connected flat spirals. All the wireless coils were coupled to a whole-body birdcage coil. The HHMM-coil was studied and compared to the linear coils in terms of transmit and SAR efficiencies via numerical simulations. A prototype of HHMM-coil was built and tested on a 1.5 T scanner in a phantom and healthy volunteer. We also proposed an extended design of the HHMM-coil and compared its performance to a dedicated breast array. RESULTS: Numerical simulations of the HHMM-coil with a female voxel model have shown more than a 2.5-fold increase in transmit efficiency and a 1.7-fold enhancement of SAR efficiency compared to the linearly polarized coils. Phantom and in vivo imaging showed good agreement with the numerical simulations. Moreover, the HHMM-coil provided good image quality, visualizing all areas of interest similar to a multichannel breast array with a 32% reduction in signal-to-noise ratio. CONCLUSION: The proposed quadrature HHMM-coil allows the B 1 + $$ {\mathrm{B}}_1^{+} $$ -field to be significantly better focused in the region-of-interest compared to the linearly polarized coils. Thus, the HHMM-coil provides high-quality breast imaging on a 1.5 T scanner using a whole-body birdcage coil for transmit and receive.

Three-dimensional diffusion MRI using simultaneous multislab with blipped-CAIPI in a 4D k-space framework.

PURPOSE: To develop an efficient simultaneous multislab imaging method with blipped-controlled aliasing in parallel imaging (blipped-SMSlab) in a 4D k-space framework, and to demonstrate its efficacy in high-resolution diffusion MRI (dMRI). THEORY AND METHODS: First, the SMSlab 4D k-space signal expression is formulated, and the phase interferences from intraslab and interslab encodings on the same physical z-axis are analyzed. Then, the blipped-SMSlab dMRI sequence is designed, with blipped-controlled aliasing in parallel imaging (blipped-CAIPI) gradients for interslab encoding, and a 2D multiband accelerated navigator for inter-kz-shot phase correction. Third, strategies are developed to remove the phase interferences, by RF phase modulation and/or phase correction during reconstruction, thus decoupling intraslab and interslab encodings that are otherwise entangled. In vivo experiments are performed to validate the blipped-SMSlab method and preliminarily evaluate its performance in high-resolution dMRI compared with traditional 2D imaging. RESULTS: In the 4D k-space framework, interslab and intraslab phase interferences of blipped-SMSlab are successfully removed using the proposed strategies. Compared with non-CAIPI sampling, the blipped-SMSlab acquisition reduces the g-factor and g-factor-related SNR penalty by about 12%. In addition, in vivo experiments show the SNR advantage of blipped-SMSlab dMRI over traditional 2D dMRI for 1.3-mm and 1.0-mm isotropic resolution imaging with matched acquisition time. CONCLUSION: Removing interslab and intraslab phase interferences enables SMSlab dMRI with blipped-CAIPI in a 4D k-space framework. The proposed blipped-SMSlab dMRI is demonstrated to be more SNR-efficient than 2D dMRI and thus capable of high-quality, high-resolution fiber orientation detection.

Optimized flip angle schemes for the split acquisition of fast spin-echo signals (SPLICE) sequence and application to diffusion-weighted imaging.

PURPOSE: The diffusion-weighted SPLICE (split acquisition of fast spin-echo signals) sequence employs split-echo rapid acquisition with relaxation enhancement (RARE) readout to provide images almost free of geometric distortions. However, due to the varying T 2 $$ {}_2 $$ -weighting during k-space traversal, SPLICE suffers from blurring. This work extends a method for controlling the spatial point spread function (PSF) while optimizing the signal-to-noise ratio (SNR) achieved by adjusting the flip angles in the refocusing pulse train of SPLICE. METHODS: An algorithm based on extended phase graph (EPG) simulations optimizes the flip angles by maximizing SNR for a flexibly chosen predefined target PSF that describes the desired k-space density weighting and spatial resolution. An optimized flip angle scheme and a corresponding post-processing correction filter which together achieve the target PSF was tested by healthy subject brain imaging using a clinical 1.5 T scanner. RESULTS: Brain images showed a clear and consistent improvement over those obtained with a standard constant flip angle scheme. SNR was increased and apparent diffusion coefficient estimates were more accurate. For a modified Hann k-space weighting example, considerable benefits resulted from acquisition weighting by flip angle control. CONCLUSION: The presented flexible method for optimizing SPLICE flip angle schemes offers improved MR image quality of geometrically accurate diffusion-weighted images that makes the sequence a strong candidate for radiotherapy planning or stereotactic surgery.

Robust dual-module velocity-selective arterial spin labeling (dm-VSASL) with velocity-selective saturation and inversion.

PURPOSE: Compared to conventional arterial spin labeling (ASL) methods, velocity-selective ASL (VSASL) is more sensitive to artifacts from eddy currents, diffusion attenuation, and motion. Background suppression is typically suboptimal in VSASL, especially of CSF. As a result, the temporal SNR and quantification accuracy of VSASL are compromised, hindering its application despite its advantage of being delay-insensitive. METHODS: A novel dual-module VSASL (dm-VSASL) strategy is developed to improve the SNR efficiency and the temporal SNR with a more balanced gradient configuration in the label/control image acquisition. This strategy applies for both VS saturation (VSS) and VS inversion (VSI) labeling. The dm-VSASL schemes were compared with single-module labeling and a previously developed multi-module schemes for the SNR performance, background suppression efficacy, and sensitivity to artifacts in simulation and in vivo experiments, using pulsed ASL as the reference. RESULTS: Dm-VSASL enabled more robust labeling and efficient backgroud suppre across brain tissues, especially of CSF, resulting in significantly reduced artifacts and improved temporal SNR. Compared to single-module labeling, dm-VSASL significantly improved the temporal SNR in gray (by 90.8% and 94.9% for dm-VSS and dm-VSI, respectively; P < 0.001) and white (by 41.5% and 55.1% for dm-VSS and dm-VSI, respectively; P < 0.002) matter. Dm-VSI also improved the SNR of VSI by 5.4% (P = 0.018). CONCLUSION: Dm-VSASL can significantly improve the robustness of VS labeling, reduce artifacts, and allow efficient background suppression. When implemented with VSI, it provides the highest SNR efficiency among VSASL methods. Dm-VSASL is a powerful ASL method for robust, accurate, and delay-insensitive perfusion mapping.