Signal-to-noise Ratio Comparison Research Articles

Flexible anisotropic magnetoresistive sensors for novel magnetic flux leakage testing capabilities

Rigid magnetic field sensors such as anisotropic magnetoresistive (AMR), giant magnetoresistive (GMR) and Hall sensors have been used for years and have become industry standard for electromagnetic non-destructive testing (NDT). Recent technological developments in the field of flexible electronics allow for the fabrication of reshapeable magnetic field sensors on flexible substrates via thin-film deposition or printing. The magnetic properties of these sensors have comparable characteristics to industry-standard rigid magnetic field sensors, with the added ability of adapting to the surface of complex components and scanning in contact with the sample surface. This improves defect detectability and magnetic signal strength by minimizing the scanning lift-off (LO) distance. In this article flexible AMR sensors mounted on a rotative mechanical holder were used to scan a semi-circular ferromagnetic sample with 3 reference defects via magnetic flux leakage (MFL) testing, thus demonstrating the applicability of this type of sensors for the scanning of curved samples. In order to benchmark the performance of these sensors in comparison to industry standard rigid magnetic field sensors, a ferromagnetic sample with 10 reference defects of different depths was scanned employing flexible AMR and rigid GMR sensors. Defects with depths ranging from 110μm up to 2240μm were detected with an signal-to-noise ratio (SNR) of 2.7 up to 27.9 (for flexible AMR sensors) and 6.2 up to 72.3 (for rigid GMR sensors), respectively. A 2D magnetometer mapping of the sample with a spatial scanning step of 10×50μm2 (flexible AMR) and 16×100μm2 (rigid GMR) was obtained. The results show that this type of sensor can be used for high-resolution and high-detail mapping of defects on the surface of planar and non-planar ferromagnetic samples since the scanning lift-off distance is equal to the substrate thickness of 20μm for in-contact scanning. The SNR comparison between flexible and rigid sensors shows that the performance of the flexible AMR sensors employed is not very far behind the performance of the rigid GMR sensors used.

Effects of Excitation Angle on Air-Puff-Stimulated Surface Acoustic Wave-Based Optical Coherence Elastography (SAW-OCE)

Increased stiffness of tissues has been recognised as a diagnostic feature of pathologies. Tissue stiffness characterisation usually involves the detection of tissue response from mechanical stimulation. Air-puff optical coherence elastography (OCE) can generate impulse surface acoustic waves (SAWs) on tissue surface without contact and evaluate the mechanical properties of tissue. This study endeavours to explore the optimal excitation angle for air-puff OCE, a parameter that lacks standardisation at present, by investigating the relationship between the frequency bandwidth and peak-to-peak signal-to-noise ratio (SNR) of SAWs for different excitation angles (relative to the normal surface) of air-puff on the sample, from 5° to 85°, with an interval of 5° applied on the phantom. Due to the unevenness of human hands, 20°, 45° and 70° angles were employed for human skin (10 healthy adults). The results show that a smaller excitation angle could produce higher wave frequency bandwidth; a 5° angle generated an SAW with 1747 Hz frequency bandwidth, while an 85° angle produced an SAW with 1205 Hz. Significant differences were not shown in peak-to-peak SNR comparison between 5° and 65° on the phantom, but between 65° and 85° at the excitation position, a reduction of 48.6% was observed. Furthermore, the group velocity of the SAWs was used to evaluate the bulk Young’s modulus of the human tissue. The outcomes could provide essential guidance for air-puff-based elastography studies in clinical applications and future tissue research.

Thermal analysis and SNR comparison of CMUT and PZT transducers using coded excitation

Coded excitation (CE) has the ability to enhance image quality and penetration depth by improving the signal-to-noise ratio (SNR). Their usefulness has been extensively proven in the literature, however, there are very few publications that have discussed the practicality of using CEs, as they can increase the operating temperature of a transducer beyond the safety limits. In this paper, the potential for capacitive micromachined ultrasonic transducers (CMUTs) to handle CEs is investigated and compared to a geometrically similar Lead Zirconate Titanate (PZT) probe. It is hypothesized that CMUTs are comparatively advantageous for CE and can generate CE signals more effectively while operating within the safety limits of temperature specified by the International Electrotechnical Commission (IEC). Simple chirp signals were used for excitation and the temperature of the transducer assembly was measured under two different test conditions following the IEC standards. The still air test showed that at the pulse repetition frequency of 4 kHz and a signal duration of 8μs, the PZT probe reached the safe limit of 27 °C within 3 min of acquisition, whereas the CMUT probe showed an increase of only 4–5 °C over 30 min of scan time. The phantom experiments showed that for the maximum temperature rise allowed at the object-transducer interface by the IEC, the gain in SNR possible for the CMUT probe was 13–14 dB and the increase in penetration depth was 30 mm, whereas no gain in SNR and penetration depth was achieved for the PZT probe. The peak mechanical index and the derated spatial peak temporal averaged intensity were found to be less than half the FDA limits for both probes in all cases, proving temperature to be the first limiting factor when using CE. Therefore, the CMUT has shown to be thermally more efficient than the PZT probe and a good candidate for CE imaging.

Comparison of quick speech-in-noise test and pure tone audiometry in noise-induced hearing loss

Objective Complaints of speech understanding in situations where background noise exists, can be seen from early stages of Noise-Induced Hearing Loss (NIHL); therefore, speech-in-noise tests including Quick speech-in-noise (Q-SIN) tests may be a suitable method for screening NIHL. The Q-SIN test uses the Signal to Noise Ratio (SNR) to evaluates speech perception in the presence of noise. This study aimed to compare pure tone audiometry and Q-SIN tests in patients with NIHL and normal hearing subjects. Methods In this cross-sectional study, according to the result of audiometry, subjects were classified into two groups: 45 individuals with audiograms suggestive of NIHL as a case group and 57 normal-hearing individuals as controls. The Persian version of the Quick-SIN test was performed for two study groups. The Mann-Whitney U Test was used for the comparison of mean SNR and hearing thresholds between the study groups. Spearman test was implemented for evaluation of the correlation between mean SNR and mean hearing thresholds in high and low frequencies in both ears. Results The median SNR loss was significantly higher in the NIHL group [0.75 (IQR: −0.75, 2.75)] than in the normal hearing group [−1.25 (−0.25, 1.25)] (p < 0.0001). It was also found that in the NIHL group, SNR loss had a direct and significant correlation with the high frequencies of both ears and the low frequency of the left ear, as the average hearing threshold increases at high frequencies and low frequencies of the left ear, the SNR loss mean increases as well. Conclusion The present study showed that the Q-SIN test as a rapid, easily applicable test has a positive correlation with pure tone audiometry results, especially at higher frequencies.

AI-assisted compressed sensing and parallel imaging sequences for MRI of patients with nasopharyngeal carcinoma: comparison of their capabilities in terms of examination time and image quality

ObjectiveTo compare examination time and image quality between artificial intelligence (AI)–assisted compressed sensing (ACS) technique and parallel imaging (PI) technique in MRI of patients with nasopharyngeal carcinoma (NPC).MethodsSixty-six patients with pathologically confirmed NPC underwent nasopharynx and neck examination using a 3.0-T MRI system. Transverse T2-weighted fast spin-echo (FSE) sequence, transverse T1-weighted FSE sequence, post-contrast transverse T1-weighted FSE sequence, and post-contrast coronal T1-weighted FSE were obtained by both ACS and PI techniques, respectively. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and duration of scanning of both sets of images analyzed by ACS and PI techniques were compared. The images from the ACS and PI techniques were scored for lesion detection, margin sharpness of lesions, artifacts, and overall image quality using the 5-point Likert scale.ResultsThe examination time with ACS technique was significantly shorter than that with PI technique (p < 0.0001). The comparison of SNR and CNR showed that ACS technique was significantly superior with PI technique (p < 0.005). Qualitative image analysis showed that the scores of lesion detection, margin sharpness of lesions, artifacts, and overall image quality were higher in the ACS sequences than those in the PI sequences (p < 0.0001). Inter-observer agreement was evaluated for all qualitative indicators for each method, in which the results showed satisfactory-to-excellent agreement (p < 0.0001).ConclusionCompared with the PI technique, the ACS technique for MR examination of NPC can not only shorten scanning time but also improve image quality.Clinical relevance statementThe artificial intelligence (AI)–assisted compressed sensing (ACS) technique shortens examination time for patients with nasopharyngeal carcinoma, while improving the image quality and examination success rate, which will benefit more patients.Key Points• Compared with the parallel imaging (PI) technique, the artificial intelligence (AI)–assisted compressed sensing (ACS) technique not only reduced examination time, but also improved image quality.• Artificial intelligence (AI)–assisted compressed sensing (ACS) pulls the state-of-the-art deep learning technique into the reconstruction procedure and helps find an optimal balance of imaging speed and image quality.

Preliminary experience of cardiac proton spectroscopy at 0.75 T.

Recent work on high-performance lower-field MR systems has renewed the interest in assessing relative advantages and disadvantages of magnetic fields less than 1 T. The objective of the present work was to investigate signal-to-noise ratio (SNR) scaling of point-resolved spectroscopy as a function of field strength and to test the feasibility of proton MRS of triglycerides (TGs) in human in vivo myocardium at 0.75 T relative to 1.5 T and 3 T. Measurements at 0.75 T were obtained by temporarily ramping down a clinical 3 T MR scanner. System configurations at 0.75, 1.5 and 3 T featured identical hard- and software, except for differences in transmit/receive coil geometries and receive channel count, which were accounted for in SNR comparisons. Proton MRS was performed at 0.75 T, 1.5 T and 3 T in ex vivo tissue and in vivo calf muscle to measure T1 and T2 values as a function of field strength, which in turn served as input to simulations of SNR scaling and field-dependent TG fit errors. Preliminary in vivo spectra of myocardium were acquired at 0.75 T, 1.5 T and 3 T in healthy subjects. Measurements of both ex vivo tissue and in vivo muscle tissue at 0.75 T versus 1.5 T and 3 T confirmed decreasing T1 and increasing T2 * for decreasing field strengths. Using measured T1 , T2 and T2 * as input and using field-dependent echo time and bandwidth scaling, simulated Cramér-Rao lower bounds of TG amplitudes at 0.75 T were 2.3 and 4.5 times larger with respect to 1.5 T and 3 T, respectively. In vivo measurements demonstrate that human proton spectroscopy of TGs in cardiac muscle is feasible at 0.75 T, supporting the potential practical value of lower-field high-performance MR systems.

Project-Oriented RF Coil Comparison and Optimization for Preclinical, Single-Voxel MR Spectroscopy of the Rat Visual Cortex at 9.4 T

As one of the most important cortical structures in the brain, the visual cortex plays a primary role in processing visual data. Observing the metabolic changes in this region using single-voxel MR spectroscopy (MRS) can provide a plethora of information on the disease stage and progress in vivo. For single-voxel MRS experiments, a target voxel is always chosen and specifically investigated. The volume of the voxel must be sufficiently small to avoid any interference from adjacent areas but large enough to maximise its signal-to-noise ratio (SNR). Of the factors used to improve SNR, e.g. enlarging voxel size or increasing the number of signal averaging, the optimisation of the RF coil can contribute significantly to the SNR improvement. In this work, we compared and optimised RF coils which include a circularly-polarised (CP) high-pass birdcage coil and two CP surface coils with different dimensions. The coils were particularly designed for the entire rat head, brain and the target region (visual cortex), respectively. The performance of these coils was evaluated based on the project-specific purpose of investigating metabolite concentration changes in the visual cortex of the in vivo rat brain, assessed by means of single-voxel MRS at 9.4 T. In the SNR comparison, the values obtained using the optimised small loop coil were found to be approximately 5 and 1.35 times higher than those using the birdcage volume head coil and the medium-sized loop coil, respectively. In other words, using the optimised coil rather than, for example, the birdcage coil allows the acquisition to be completed more quickly by a factor of 25 times. In conclusion, by using the optimised setup, we can i) benefit either from reduced measurement time or in the acquisition of high-quality MR images or ii) obtain spectra with a minimum quantification error.

Robust Distributed Noise Suppression in Acoustic Sensor Networks

In acoustic sensor networks (ASNs), speech-related applications often perform poorly due to serious noise interference. To address this problem, a robust distributed noise suppression method for ASNs is proposed in this article. Specifically, by using the maximum input signal-to-noise ratio (SNR) subarray as the reference array, the robust distributed parameterized multichannel Wiener filter (RD-PMWF) is proposed for a tradeoff between the desired signal distortion and the noise suppression in the fully connected ASNs, where each subarray fuses its multiple speech signals into a single-channel signal by a compression vector. Then, to seek out the maximum input SNR subarray in any topology, an in-network compare method that takes place on the tree topology is presented based on a data-driven signal flow. Finally, the RD-PMWF without topology constraints is obtained, relying on the in-network comparison of input SNR, and the communication cost and computational complexity are analyzed. The proposed method is robust to the change of network topology and speaker positions even at low input SNR situations and successfully suppresses noise by using only the subarray with the maximum input SNR and its neighbors in any topology. Simulation and real-world experimental results illustrate that the proposed method achieves good noise suppression performance in noisy and reverberant ASNs while exhibiting an even lower computational complexity.

High-Resolution Simultaneous Multi-Slice Accelerated Turbo Spin-Echo Musculoskeletal Imaging: A Head-to-Head Comparison With Routine Turbo Spin-Echo Imaging.

Background/Aim: The turbo spin-echo (TSE) sequence is widely used for musculoskeletal (MSK) imaging; however, its acquisition speed is limited and can be easily affected by motion artifacts. We aimed to evaluate whether the use of a simultaneous multi-slice TSE (SMS-TSE) sequence can accelerate MSK imaging while maintaining image quality when compared with the routine TSE sequence.Methods: We prospectively enrolled 71 patients [mean age, 37.43 ± 12.56 (range, 20–67) years], including 37 men and 34 women, to undergo TSE and SMS sequences. The total scanning times for the wrist, ankle and knee joint with routine sequence were 14.92, 13.97, and 13.48 min, respectively. For the SMS-TSE sequence, they were 7.52, 7.20, and 6.87 min. Quantitative parameters, including the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), were measured. Three experienced MSK imaging radiologists qualitatively evaluated the image quality of bone texture, cartilage, tendons, ligament, meniscus, and artifact using a 5-point evaluation system, and the diagnostic performance of the SMS-TSE sequences was evaluated.Results: Compared with the routine TSE sequences, the scanning time was lower by 49.60, 48.46, and 49.04% using SMS-TSE sequences for the wrist, ankle, and knee joints, respectively. For the SNR comparison, the SMS-TSE sequences were significantly higher than the routine TSE sequence for wrist (except for Axial-T2WI-FS), ankle, and knee joint MR imaging (all p < 0.05), but no statistical significance was obtained for the CNR measurement (all p > 0.05, except for Sag-PDWI-FS in ankle joint). For the wrist joint, the diagnostic sensitivity, specificity, and accuracy were 88.24, 100, and 92%. For the ankle joint, they were 100, 75, and 93.33%. For the knee joint, they were 87.50, 85.71, and 87.10%.Conclusion: The use of the SMS-TSE sequence in the wrist, ankle, and knee joints can significantly reduce the scanning time and show similar image quality when compared with the routine TSE sequence.

SUPPRESSION OF WHITE NOISE FROM THE MIXTURE OF SPEECH AND IMAGE FOR QUALITY ENHANCEMENT

This study proposed a correlation analysis of two recent approaches. The FAST ICA technique is used for the separation of the multimodal data (i.e, mixture of audio, noise and image signal) and the minimum mean-square error (MMSE) is used for the removal of white noise from the audio signal. Initially, multimodal data will be formed by combining all the three signals (i.e. a mixture of audio, noise and image signals). For creating an ideal situation and for SNR comparisons, separation of the signals will be performed using the Fast ICA technique. ICA, Independent element analysis is a recently developed technique in which the goal is to seek a linear interpretation of non-Gaussian knowledge for the elements to be as statistically free as possible. Such representations record the key structure of the data in several applications, including signal quality and signal separation. ICA learns a linear decay of the data. ICA can find the basic elements and sources included in the data found where traditional methods fail. After the separation of the mixed data, denoising will be performed using the MMSE technique. The main purpose of the MMSE technique is to remove White Noise from the unmixed audio signal which will be further used for overall and segmental SNR comparisons for quality enhancement. Based on the designed algorithms, both of these techniques are real-time data-driven programs. These techniques are explored with standard De-noising methods using several different estimation methods like signal-to-noise ratio (SNR). Experimental results prove that the proposed MMSE technique works well for both noise segmentation and overall consideration of noise distortion signals. These statistical techniques can be used in many applications, such as in different communication systems to eliminate background noise and in channels to reduce channel interference between different applications in speech communications

A pulsed time-varying method for improving the spin readout efficiency of nitrogen vacancy centers

In this work, a time-varying pulse waveform spin readout sequence method is proposed to improve the spin readout efficiency of nitrogen-vacancy (NV) centers. The method consists of performing the readout signal-to-noise ratio (SNR) analysis via the construction of a rate equation model of the NV center. We demonstrate a superior performance from the time-varying waveform readout approach and focus on the role of the readout optimization in quantum measurements. A detailed comparison of the readout SNR of the time-varying waveform and conventional waveform is provided. We experimentally demonstrate that the readout SNR is increased by 8% by utilizing an optimized waveform. It is anticipated that the improved method will effectively benefit the sensing capability of NV center ensembles and provide support for high-precision measurements of solid systems.

Analytical Evaluation of Signal-to-Noise Ratios for Avalanche- and Single-Photon Avalanche Diodes

Performance of systems for optical detection depends on the choice of the right detector for the right application. Designers of optical systems for ranging applications can choose from a variety of highly sensitive photodetectors, of which the two most prominent ones are linear mode avalanche photodiodes (LM-APDs or APDs) and Geiger-mode APDs or single-photon avalanche diodes (SPADs). Both achieve high responsivity and fast optical response, while maintaining low noise characteristics, which is crucial in low-light applications such as fluorescence lifetime measurements or high intensity measurements, for example, Light Detection and Ranging (LiDAR), in outdoor scenarios. The signal-to-noise ratio (SNR) of detectors is used as an analytical, scenario-dependent tool to simplify detector choice for optical system designers depending on technologically achievable photodiode parameters. In this article, analytical methods are used to obtain a universal SNR comparison of APDs and SPADs for the first time. Different signal and ambient light power levels are evaluated. The low noise characteristic of a typical SPAD leads to high SNR in scenarios with overall low signal power, but high background illumination can saturate the detector. LM-APDs achieve higher SNR in systems with higher signal and noise power but compromise signals with low power because of the noise characteristic of the diode and its readout electronics. Besides pure differentiation of signal levels without time information, ranging performance in LiDAR with time-dependent signals is discussed for a reference distance of 100 m. This evaluation should support LiDAR system designers in choosing a matching photodiode and allows for further discussion regarding future technological development and multi pixel detector designs in a common framework.

Development of a dynamic imaging method for gravitropism in pea sprouts using clinical magnetic resonance imaging system.

Although magnetic resonance imaging (MRI) is a useful technique, only a few studies have investigated the dynamic behavior of small subjects using MRI owing to constraints such as experimental space and signal amount. In this study, to acquire high-resolution continuous three-dimensional gravitropism data of pea (Pisum sativum) sprouts, we developed a small-bore MRI signal receiver coil that can be used in a clinical MRI and adjusted the imaging sequence. It was expected that such an arrangement would improve signal sensitivity and improve the signal-to-noise ratio (SNR) of the acquired image. All MRI experiments were performed using a 3.0-T clinical MRI scanner. An SNR comparison using an agarose gel phantom to confirm the improved performance of the small-bore receiver coil and an imaging experiment of pea sprouts exhibiting gravitropism were performed. The SNRs of the images acquired with a standard 32-channel head coil and the new small-bore receiver coil were 5.23±0.90 and 57.75±12.53, respectively. The SNR of the images recorded using the new coil was approximately 11-fold higher than that of the standard coil. In addition, when the accuracy of MR imaging that captures the movement of pea sprout was verified, the difference in position information from the optical image was found to be small and could be used for measurements. These results of this study enable the application of a clinical MRI system for dynamic plant MRI. We believe that this study is a significant first step in the development of plant MRI technique.

Reliability Assessment for Time-Slice Enhanced Bidirectional Thermal Wave Radar Thermography of Hybrid C/GFRP Defects

In this article, a bidirectional thermal wave radar thermography (BTWRT) is used for the inspection of hybrid carbon/glass fiber reinforced polymer (C/GFRP) laminates with subsurface defects, and the reliability of BTWRT is deeply investigated based on the probability of detection (POD) analysis. Three classes of C/GFRP laminates are prepared for experimental study, and the hybrid volume ratio of glass fiber and carbon fiber is 1:4, 1:1, and 4:1, respectively. Each class of C/GFRP laminate includes a total of 72 artificial flat-bottom holes with different diameter-to-depth ratios. An 808-nm laser is used as external excitation and modulated by a bidirectional chirp signal. Thermal wave radar feature images are obtained by time-slice imaging algorithms [dynamic component extraction, Hilbert transform (HT), and analytical chirp correlation (ACC)] and conventional algorithms (cross-correlation, chirp lock-in, HT mean, and fast Fourier transform). The imaging quality and reliability of different algorithms are compared and evaluated through the signal-to-noise ratio (SNR) and POD assessment using a hit/miss method, respectively. The SNR comparison and POD assessment results indicate that the ACC time-slice algorithm is more suitable for C/GFRP delamination defect inspection using BTWRT in view of the optimal detectability and reliability. This work provides a valuable reference for BTWRT inspection of hybrid C/GFRP subsurface defects, and the ACC time-slice imaging algorithm has the potential to develop into a highly reliable vision inspection method for the industrial applications out of laboratory.

A study on the SNR performance analysis of laser-generated bidirectional thermal wave radar imaging inspection for hybrid C/GFRP laminate defects

In this paper, the detection capability of laser-generated bidirectional thermal wave radar imaging (BTWRI) inspection for carbon/glass fiber reinforced polymer (C/GFRP) defects was quantitatively evaluated by signal-to-noise ratio (SNR) analysis of characteristic images. A low-power experimental system was devised, and the C/GFRP specimens with multi-scale diameter-to-depth ratio were tested. An improved imaging algorithm (analytical chirp correlation, ACC) was presented by applying analytical bidirectional chirp signal to extract the correlation phase and amplitude of thermal wave radar signal corresponding to the expected delay time. The optimal ACC detection image is obtained by the SNR comparison of characteristic images frame by frame. The conventional imaging inspection results of using cross-correlation (CC), cross-correlation phase (CCP), chirp lock-in (CLI), and Hilbert transform mean (HTM) algorithms were performed for SNR comparison. Experimental results indicate that the ACC algorithm displays almost the same detection capability as the traditional CCP algorithm by a simpler calculation process, and the optimal ACC detection image has a significant enhancement on SNR performance for C/GFRP subsurface defects compared with conventional imaging algorithms.

Evaluation of fluorine-19 magnetic resonance imaging of the lungs using octafluorocyclobutane in a rat model.

PurposeTo test octafluorocyclobutane (OFCB) as an inhalation contrast agent for fluorine‐19 MRI of the lung, and to compare the image quality of OFCB scans with perfluoropropane (PFP) scansTheory and MethodsAfter normalizing for the number of signal averages, a theoretical comparison between the OFCB signal‐to‐noise ratio (SNR) and PFP SNR predicted the average SNR advantage of 90% using OFCB during gradient echo imaging. The OFCB relaxometry was conducted using single‐voxel spectroscopy and spin‐echo imaging. A comparison of OFCB and PFP SNRs was performed in vitro and in vivo. Five healthy Sprague‐Dawley rats were imaged during single breath‐hold and continuous breathing using a Philips Achieva 3.0T MRI scanner (Philips, Andover, MA). The scan time was constant for both gases. Statistical comparison between PFP and OFCB scans was conducted using a paired t test and by calculating the Bayes factor.ResultsSpin‐lattice (T1) and effective spin‐spin (T2∗) relaxation time constants of the pure OFCB gas were determined as 28.5 ± 1.2 ms and 10.5 ± 1.8 ms, respectively. Mixing with 21% of oxygen decreased T1 by 30% and T2∗ by 20%. The OFCB in vivo images showed 73% higher normalized SNR on average compared with images acquired using PFP. The statistical significance was shown by both paired t test and calculated Bayes factors. The experimental results agree with theoretical calculations within the error of the relaxation parameter measurements.ConclusionThe quality of the lung images acquired using OFCB was significantly better compared with PFP scans. The OFCB images had higher a SNR and were artifact‐free.

Quantitative analysis of spatial averaging effect on chemical shift imaging SNR and noise coherence with k-space sampling schemes

Spatial averaging of multiple voxels from high-resolution chemical shift imaging (hrCSI) is a common strategy for in vivo metabolic studies to achieve a better signal-to-noise ratio (SNR) for a region-of-interest. However, the mechanism about how the spatial averaging approach influences the respective spectral signal and noise and its relevance to the k-space sampling schemes remains unclear. Using three-dimension 17O CSI technique with the weighted k-space sampling method of Fourier series window, we performed quantitative SNR comparisons between a single low-resolution CSI (lrCSI) voxel (being 27 times larger than the hrCSI voxel size) and the spatially averaged hrCSI voxels with matched sampling volume and location. We demonstrated that the averaged hrCSI voxel spectrum had a large SNR loss (> 4 times) compared to the lrCSI voxel, which was resulted from unmatched increases in signal (~1.9 fold) and noise (~9.3 fold). The signal increase was caused by the spatial overlapping between the adjacent hrCSI voxels. The substantial noise increase was mainly attributed to the strong noise coherence among hrCSI voxels acquired with the weighted k-space sampling. This study presents a quantitative relation between the k-space sampling schemes to an apparent SNR penalty of the spatial averaging approach. The information could be useful for designing CSI acquisition method and determination of optimal spatial resolution for in vivo metabolic imaging studies.

Phosphorus magnetic resonance spectroscopic imaging using flyback echo planar readout trajectories.

To present and evaluate a fast phosphorus magnetic resonance spectroscopic imaging (MRSI) sequence using echo planar spectroscopic imaging with flyback readout gradient trajectories. Waveforms were designed and implemented using a 3 Tesla MRI system. 31P spectra were acquired with 2×2cm2 and 3×3cm2 resolution over a 20- and 21-cm field of view and spectral bandwidths up to 1923Hz. The sequence was first tested using a 20-cm-diameter phosphate phantom, and subsequent in vivo tests were performed on healthy human calf muscles and brains from five volunteers. Flyback EPSI achieved 10× and 7× reductions in acquisition time, with 68.0±1.2 and 69.8±2.2% signal-to-noise ratio (SNR) per unit of time efficiency (theoretical SNR efficiency was 74.5 and 76.4%) for the in vivo experiments, compared to conventional phase-encoded MRSI for the 2×2cm2 and 3×3cm2 resolution waveforms, respectively. Statistical analysis showed no difference in the quantification of most metabolites. Time savings and SNR comparisons were consistent across phantom, leg and brain experiments. EPSI using flyback readout trajectories was found to be a reliable alternative for acquiring 31P-MRSI data in a shorter acquisition time.

Enhanced Fluorine-19 MRI Sensitivity using a Cryogenic Radiofrequency Probe: Technical Developments and Ex Vivo Demonstration in a Mouse Model of Neuroinflammation

Neuroinflammation can be monitored using fluorine-19 (19F)-containing nanoparticles and 19F MRI. Previously we studied neuroinflammation in experimental autoimmune encephalomyelitis (EAE) using room temperature (RT) 19F radiofrequency (RF) coils and low spatial resolution 19F MRI to overcome constraints in signal-to-noise ratio (SNR). This yielded an approximate localization of inflammatory lesions. Here we used a new 19F transceive cryogenic quadrature RF probe (19F-CRP) that provides the SNR necessary to acquire superior spatially-resolved 19F MRI. First we characterized the signal-transmission profile of the 19F-CRP. The 19F-CRP was then benchmarked against a RT 19F/1H RF coil. For SNR comparison we used reference compounds including 19F-nanoparticles and ex vivo brains from EAE mice administered with 19F-nanoparticles. The transmit/receive profile of the 19F-CRP diminished with increasing distance from the surface. This was counterbalanced by a substantial SNR gain compared to the RT coil. Intraparenchymal inflammation in the ex vivo EAE brains was more sharply defined when using 150 μm isotropic resolution with the 19F-CRP, and reflected the known distribution of EAE histopathology. At this spatial resolution, most 19F signals were undetectable using the RT coil. The 19F-CRP is a valuable tool that will allow us to study neuroinflammation with greater detail in future in vivo studies.

Reconfigurable multi‐channel RF crossbar switch matrix for MRI receiver front‐end

In this Letter, a highly reconfigurable crossbar transmission line switch matrix for magnetic resonance imaging (MRI) system is proposed. Unlike the conventional M × N crossbar switch configuration, the proposed structure can manipulate 2M × N matrix without doubling the area occupancy. Also, the proposed structure includes the signal loss-compensation circuitry based on inductor banks to enhance signal-to-noise ratio (SNR). Thus, for any required numbers of input and output channels, the proposed structure can reduce the overall size, the number of required component, and even increase the quality of MR images by SNR enhancement. The proposed structure was implemented and verified at 4-Tesla (170 MHz) MR system through the comparison of RF path loss, SNR and phantom test image qualities.