SNR Changes Research Articles

Discrete wavelet transform denoising method efficiency evaluation for processing pulse signals with harmonic components

This article reviews the problem of parameter selection for denoising methods based on the Discrete Wavelet Transform (DWT) for processing geo-signals with various noise types and external interference, followed by evaluating the effectiveness in detecting recurring signal patterns. The study reviews the theoretical impact of denoising parameters, existing wavelet and decomposition level selection methods, publications on DWT applications in different fields, and the computational challenges of increasing decomposition levels for microcontrollers. Experimental results of DWT denoising application on field-gathered signals recorded in different environments, presented as average SNR changes for specific DWT parameter combinations. Comparison of results by decomposition levels showed gradual improvements in efficiency with certain wavelets and significant drops after specific levels in some cases due to the filtering of typical samples, which emphasizes the need to review DWT parameters only in the scope of specific parameter combinations. Notable anomalies in efficiency due to the non-stationary nature of signals and parameter resonance with noise or patterns were also observed, requiring further research. Based on the findings, the most effective parameter combinations for denoising the studied geo-signal were identified, with a particularly optimal combination of three decomposition levels, hard thresholding, and rbio3.3 wavelet, which preserved and even amplified signal energy while enabling the detection of typical fragments at distances of 120–100 meters.

An MR Compatible Vascular Stenosis Method Based on Fiber Bragg Grating

Progressive stenosis of blood vessels is an important cause of cardiovascular diseases. Traditional intervention methods rely on fluoroscopy, which exposes both patients and operators to ionizing radiation. In this paper, we propose a real-time detection method for vascular stenosis intervention based on Fiber Bragg Grating (FBG) sensors that can be used under magnetic resonance imaging (MRI) guidance. An FBG sensor array with 5 sensors is developed and validated using a vascular flow phantom that simulates the morphological features of stenoses. We first verify the sensor for measuring vascular stenosis through flow rate and profile using the FBG sensor array, followed by a detailed assessment of the MRI compatibility of the sensor in terms of imaging artefact and changes in SNR, The error of FBG array is within the range of ±10με, the SNR variation is 3.608%, indicating that the FBG sensor array has excellent MR image compatibility. Experiment results show a good correlation between the degrees of stenoses with strain measurements, thus offering real-time information to aid MR guided vascular intervention.

Application of Particle Swarm Optimization with Simulated Annealing in MIT Regularization Image Reconstruction

Background and Objectives: Due to the soft-field effect of the electromagnetic field and the limit of detection, image reconstruction of magnetic induction tomography has to recover more complex electrical characteristics from very few signals. These cause a problem which have underdetermination, nonlinearity, and ill-posed characteristics, and therefore lead to many difficulties in finding its solution. Although many regularization image reconstruction methods exist, they are not suitable for MIT applications due to regularization parameter selection. The purpose of this paper is to study the principle of particle swarm optimization with simulated annealing, and to propose a regularization method for reconstruction, which will provide a new way to solve the MIT image problems. Methods and Models: Firstly, the regularization principle of image reconstruction of MIT will be analyzed. Then the hybrid regularization algorithm, including Tikhonov and NOSER regularization, will be developed, using the dimension of the Hessian matrix as a penalty term respecting the prior knowledge. PSO-SA algorithm will be applied to obtain an optimal solution for regularization parameters. Finally, six typical numerical models and approximately symmetrical cerebral hemorrhage models by COMSOL will be carried out, and the voltage signals obtained from the simulation will be used to verify the proposed reconstruction method. Results: Through the simulation results, the proposed imaging method has the average CC values of 0.9932, 0.8286 and the average RE values of 0.4982, 0.8320 for simple and complex models, respectively. Moreover, when the SNR changes from 55 dB to 35 dB, the CC value of the cerebral hemorrhage model reduced by 0.1034. The results demonstrate the effectiveness and high theoretical feasibility of the proposed method in MIT image reconstruction. Conclusions: This study indicates the potential application of PSO-SA algorithm in regularization imaging problem. Compared with traditional regularization imaging methods, the proposed method has the advantages of better accuracy, robustness and noise resistance, showing the certain application value in other similar ill-ness imaging problems.

A comparison of simultaneously-obtained measures of listening effort: pupil dilation, verbal response time and self-rating

Objective The aim of this study was to assess to what extent simultaneously-obtained measures of listening effort (task-evoked pupil dilation, verbal response time [RT], and self-rating) could be sensitive to auditory and cognitive manipulations in a speech perception task. The study also aimed to explore the possible relationship between RT and pupil dilation. Design A within-group design was adopted. All participants were administered the Matrix Sentence Test in 12 conditions (signal-to-noise ratios [SNR] of −3, −6, −9 dB; attentional resources focussed vs divided; spatial priors present vs absent). Study sample Twenty-four normal-hearing adults, 20–41 years old (M = 23.5), were recruited in the study. Results A significant effect of the SNR was found for all measures. However, pupil dilation discriminated only partially between the SNRs. Neither of the cognitive manipulations were effective in modulating the measures. No relationship emerged between pupil dilation, RT and self-ratings. Conclusions RT, pupil dilation, and self-ratings can be obtained simultaneously when administering speech perception tasks, even though some limitations remain related to the absence of a retention period after the listening phase. The sensitivity of the three measures to changes in the auditory environment differs. RTs and self-ratings proved most sensitive to changes in SNR.

Performance Analysis of NLFM Signals with Doppler Effect and Background Noise

This paper focuses on the study of effect of background noise and Doppler Effect on various Nonlinear Frequency Modulation (NLFM) waveforms designed using two stage piece-wise and three stage piece-wise linear and non linear functions. The background noise investigated is Additive White Gaussian Noise (AWGN). Simulations are carried out for different target speeds ranging from 100 to 5000km/hour to study Doppler Effect. The simulations are carried out using Matlab software. Among the waveforms designed, the NLFM function designed using two piece-wise Linear Frequency Modulation (LFM) is observed to be Doppler tolerant and also not affected by noise, as the SNR changes from -20 to 20 dB the peak side-lobe level (PSL) of this signal is around -34.84 dB.

An adaptive a priori SNR estimator for perceptual speech enhancement

In this paper, an adaptive averaging a priori SNR estimation employing critical band processing is proposed. The proposed method modifies the current decision-directed a priori SNR estimation to achieve faster tracking when SNR changes. The decision-directed estimator (DD) employs a fixed weighting with the value close to one, which makes it slow in following the onsets of speech utterances. The proposed SNR estimator provides a means to solve this issue by employing an adaptive weighting factor. This allows an improved tracking of onset changes in the speech signal. As a consequence, it results in better preservation of speech components. This adaptive technique ensures that the weighting between the modified decision-directed a priori estimate and the maximum likelihood a priori estimate is a function of the speech absence probability. The estimate of the speech absence probability is modeled by a sigmoid function. Furthermore, a critical band mapping for the short-time Fourier transform analysis-synthesis system is utilized in the speech enhancement to achieve less musical noise. In addition, to evaluate the ability of the a priori SNR estimation method in preserving speech components, we proposed a modified objective measurement known as modified hamming distance. Evaluations are performed by utilizing both objective and subjective measurements. The experimental results show that the proposed method improves the speech quality under different noise conditions. Moreover, it maintains the advantage of the DD approach in eliminating the musical noise under different SNR conditions. The objective results are supported by subjective listening tests using 10 subjects (5 males and 5 females).

Monitoring Bare Soil Freeze–Thaw Process Using GPS-Interferometric Reflectometry: Simulation and Validation

Frozen soil and permafrost affect ecosystem diversity and productivity as well as global energy and water cycles. Although some space-based Radar techniques or ground-based sensors can monitor frozen soil and permafrost variations, there are some shortcomings and challenges. For the first time, we use GPS-Interferometric Reflectometry (GPS-IR) to monitor and investigate the bare soil freeze–thaw process as a new remote sensing tool. The mixed-texture permittivity models are employed to calculate the frozen and thawed soil permittivities. When the soil freeze/thaw process occurs, there is an abrupt change in the soil permittivity, which will result in soil scattering variations. The corresponding theoretical simulation results from the forward GPS multipath simulator show variations of GPS multipath observables. As for the in-situ measurements, virtual bistatic radar is employed to simplify the analysis. Within the GPS-IR spatial resolution, one SNOTEL site (ID 958) and one corresponding PBO (plate boundary observatory) GPS site (AB33) are used for analysis. In 2011, two representative days (frozen soil on Doy of Year (DOY) 318 and thawed soil on DOY 322) show the SNR changes of phase and amplitude. The GPS site and the corresponding SNOTEL site in four different years are analyzed for comparisons. When the soil freeze/thaw process occurred and no confounding snow depth and soil moisture effects existed, it exhibited a good absolute correlation (|R| = 0.72 in 2009, |R| = 0.902 in 2012, |R| = 0.646 in 2013, and |R| = 0.7017 in 2014) with the average detrended SNR data. Our theoretical simulation and experimental results demonstrate that GPS-IR has potential for monitoring the bare soil temperature during the soil freeze–thaw process, while more test works should be done in the future. GNSS-R polarimetry is also discussed as an option for detection. More retrieval work about elevation and polarization combinations are the focus of future development.

Relationship between entropy and SNR changes in image enhancement

There are many techniques of image enhancement. Their parameters are traditionally tuned by maximization of SNR criterion, which is unfortunately based on the knowledge of an ideal image. Our approach is based on Hartley entropy, its estimation, and differentiation. Resulting gradient of entropy is estimated without knowledge of ideal images, and it is a subject of minimization. Both SNR maximization and gradient magnitude minimization cause various settings of the given filter. The optimum settings are compared, and their differences are discussed.

Performance Evaluation of CDMA - MIMO (STBC) System over Rayleigh Fading Channel for Image Transmission

Data transmission via wireless communication system is not only in text form but it also can be in image form. In the process of sending data or information, it often experiences interference in transmission media, which is fading. The method used in this research is by simulation using MATLAB. The simulation of CDMA-MIMO (STBC) system with Walsh spreading code is expected to reduce the disturbance of fading. Fading channels can be modeled using Rayleigh distribution. The number of users and spreading factors affect the performance of CDMA-MIMO (STBC) systems. The parameters used in this simulation were SNR, BER, and PSNR. The results showed that image reconstruction passing CDMAMIMO system with spreading factor 4 has better image quality. Its PSNR 33.9589dB when SNR -10dB. SNR was increased 10 dB then PSNR 60.00 dB. The increasing of spreading factor to 8 and 16 was obtained by increasing PSNR, PSNR 35.0685 dB and PSNR 37.5665 dB, respectively. For 4 users with Spreading Factor 4 and SNR 0 to 5 dB, it was changed the BER. This is influenced by changes in SNR. The higher SNR value, the average value of BER will be smaller. A growing number of users from 1 to 4 users were decreased the performance of the MIMO CDMA system when observed from the BER and PSNR.

Probing Individual Sources during Reionization and Cosmic Dawn using Square Kilometre Array HI 21-cm Observations

Detection of individual luminous sources during the reionization epoch and cosmic dawn through their signatures in the HI 21-cm signal is one of the direct approaches to probe the epoch. Here, we summarize our previous works on this and present preliminary results on the prospects of detecting such sources using the SKA1-low experiment. We first discuss the expected HI 21-cm signal around luminous sources at different stages of reionization and cosmic dawn. We then introduce two visibility based estimators for detecting such signal: one based on the matched filtering technique and the other relies on simply combing the visibility signal from different baselines and frequency channels. We find that that the SKA1-low should be able to detect ionized bubbles of radius $R_b \gtrsim 10$ Mpc with $\sim 100$ hr of observations at redshift $z \sim 8$ provided that the mean outside neutral Hydrogen fraction $ x_{\rm HI} \gtrsim 0.5$. We also investigate the possibility of detecting HII regions around known bright QSOs such as around ULASJ1120+0641 discovered by Mortlock et al. 2011. We find that a $5 \sigma$ detection is possible with $600$ hr of SKA1-low observations if the QSO age and the outside $ x_{\rm HI} $ are at least $\sim 2 \times 10^7$ Myr and $\sim 0.2$ respectively. Finally, we investigate the possibility of detecting the very first X-ray and Ly-$\alpha$ sources during the cosmic dawn. We consider mini-QSOs like sources which emits in X-ray frequency band. We find that with a total $\sim 1000$ hr of observations, SKA1-low should be able to detect those sources individually with a $\sim 9 \sigma$ significance at redshift $z=15$. We summarize how the SNR changes with various parameters related to the source properties.

Effect of Number of Acquisitions in Diffusion Tensor Imaging of the Pediatric Brain: Optimizing Scan Time and Diagnostic Experience

Diffusion tensor imaging (DTI) is useful for multiple clinical applications, but its routine implementation for children may be difficult due to long scan times. This study evaluates the impact of decreasing the number of DTI acquisitions (NEX) on interpretability of pediatric brain DTI. 15 children with MRI-visible neuropathologies were imaged at 3T using our motion-corrected, parallel imaging- accelerated DT-EPI technique with 3 NEX (scan time 8.25 min). Using these acquisitions, NEX = 1 (scan time 2.75 min) and NEX = 2 (scan time 5.5 min) images were simulated. Two neuroradiologists scored diffusion-weighted images (DWI), apparent diffusion coefficient (ADC), fractional anisotropy (FA), and first eigenvector color-encoded (EV) images from each NEX for perceived SNR, lesion conspicuity and clinical confidence. ROI FA/ADC and image SNR values were also compared across NEX. NEX = 2 perceived SNR, lesion conspicuity, and clinical confidence were not inferior to NEX = 3 images. NEX = 1 images showed comparable lesion conspicuity and clinical confidence as NEX = 3, but inferior perceived SNR. FA and ADC ROI measurements demonstrated no significant difference across NEX. The greatest SNR increase was seen between NEX = 1 and NEX = 2. Reducing NEX to shorten imaging time may impact clinical utility in a manner that does not directly correspond with SNR changes.

A Novel Expectation-Maximization Framework for Speech Enhancement in Non-Stationary Noise Environments

Voiced speeches have a quasi-periodic nature that allows them to be compactly represented in the cepstral domain. It is a distinctive feature compared with noises. Recently, the temporal cepstrum smoothing (TCS) algorithm was proposed and was shown to be effective for speech enhancement in non-stationary noise environments. However, the missing of an automatic parameter updating mechanism limits its adaptability to noisy speeches with abrupt changes in SNR across time frames or frequency components. In this paper, an improved speech enhancement algorithm based on a novel expectation-maximization (EM) framework is proposed. The new algorithm starts with the traditional TCS method which gives the initial guess of the periodogram of the clean speech. It is then applied to an <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${L_1}$</tex> </formula> norm regularizer in the M-step of the EM framework to estimate the true power spectrum of the original speech. It in turn enables the estimation of the a-priori SNR and is used in the E-step, which is indeed a logmmse gain function, to refine the estimation of the clean speech periodogram. The M-step and E-step iterate alternately until converged. A notable improvement of the proposed algorithm over the traditional TCS method is its adaptability to the changes (even abrupt changes) in SNR of the noisy speech. Performance of the proposed algorithm is evaluated using standard measures based on a large set of speech and noise signals. Evaluation results show that a significant improvement is achieved compared to conventional approaches especially in non-stationary noise environment where most conventional algorithms fail to perform.

Novel formulation of a double threshold algorithm for the estimation of muscle activation intervals designed for variable SNR environments

The aim of this work is the development of an improved formulation of the double threshold algorithm for sEMG onset–offset detection presented by Bonato and co-workers. The original formulation, which keeps the threshold fixed, suffers from performance degradation whenever the SNR changes during the analysis. The novel approach is designed to be adaptive to SNR changes in either burst or inter-burst zones of sEMG signals recorded in static and dynamic conditions. The detection parameters (i.e. detection and false alarm probabilities) are updated on the basis of an on-line estimation of the SNR. The proposed formulation has been assessed on both simulated and real sEMG data. For constant SNR the performance of the original formulation is confirmed (for SNR>8dB, bias and standard deviation less than 10 and 15ms, respectively; detection percentage higher than 95%), while the novel implementation performs better with time-varying SNR (for SNR varying in the range 10–25dB the standard approach detection percentage decreases at 50%). Detection on signals recorded during isometric contractions at different force levels confirms the performance on simulated signals (StD=134ms; FP=22%, and StD=42ms; FP=2%, respectively for standard and novel implementation calculated as average on five experimental trials). The pseudo real-time detection allowed by this formulation can be profitably exploited by biofeedback applications based on myoelectric information.

Does quantification of USPIO uptake‐related signal loss allow differentiation of benign and malignant normal‐sized pelvic lymph nodes?

Ultrasmall superparamagnetic iron oxide (USPIO) particles are promising contrast media, especially for molecular and cellular imaging besides lymph node staging owing to their superior NMR efficacy, macrophage uptake and lymphotropic properties. The goal of the present prospective clinical work was to validate quantification of signal decrease on high-resolution T(2)-weighted MR sequences before and 24-36 h after USPIO administration for accurate differentiation between benign and malignant normal-sized pelvic lymph nodes. Fifty-eight patients with bladder or prostate cancer were examined on a 3 T MR unit and their respective lymph node signal intensities (SI), signal-to-noise (SNR) and contrast-to-noise (CNR) were determined on pre- and post-contrast 3D T(2)-weighted turbo spin echo (TSE) images. Based on histology and/or localization, USPIO-uptake-related SI/SNR decrease of benign vs malignant and pelvic vs inguinal lymph nodes was compared. Out of 2182 resected lymph nodes 366 were selected for MRI post-processing. Benign pelvic lymph nodes showed a significantly higher SI/SNR decrease compared with malignant nodes (p < 0.0001). Inguinal lymph nodes in comparison to pelvic lymph nodes presented a reduced SI/SNR decrease (p < 0.0001). CNR did not differ significantly between benign and malignant lymph nodes. The receiver operating curve analysis yielded an area under the curve of 0.96, and the point with optimal accuracy was found at a threshold value of 13.5% SNR decrease. Overlap of SI and SNR changes between benign and malignant lymph nodes were attributed to partial voluming, lipomatosis, histiocytosis or focal lymphoreticular hyperplasia. USPIO-enhanced MRI improves the diagnostic ability of lymph node staging in normal-sized lymph nodes, although some overlap of SI/SNR-changes remained. Quantification of USPIO-dependent SNR decrease will enable the validation of this promising technique with the final goal of improving and individualizing patient care.

Signal/Noise Analysis of FRET-Based Sensors

Molecular sensors based on intramolecular Förster resonance energy transfer (FRET) have become versatile tools to monitor regulatory molecules in living tissue. However, their use is often compromised by low signal strength and excessive noise. We analyzed signal/noise (SNR) aspects of spectral FRET analysis methods, with the following conclusions: The most commonly used method (measurement of the emission ratio after a single short wavelength excitation) is optimal in terms of signal/noise, if only relative changes of this uncalibrated ratio are of interest. In the case that quantitative data on FRET efficiencies are required, these can be calculated from the emission ratio and some calibration parameters, but at reduced SNR. Lux-FRET, a recently described method for spectral analysis of FRET data, allows one to do so in three different ways, each based on a ratio of two out of three measured fluorescence signals (the donor and acceptor signal during a short-wavelength excitation and the acceptor signal during long wavelength excitation). Lux-FRET also allows for calculation of the total abundance of donor and acceptor fluorophores. The SNR for all these quantities is lower than that of the plain emission ratio due to unfavorable error propagation. However, if ligand concentration is calculated either from lux-FRET values or else, after its calibration, from the emission ratio, SNR for both analysis modes is very similar. Likewise, SNR values are similar, if the noise of these quantities is related to the expected dynamic range. We demonstrate these relationships based on data from an Epac-based cAMP sensor and discuss how the SNR changes with the FRET efficiency and the number of photons collected.

Stochastic resonance aided tactile sensing

SUMMARYStochastic resonance (SR) is one of the basic principles intrinsically possessed by any living thing to highly adapt to complicated environments including various disturbances. Although a noise is inevitably mixed by contact with an object and a sensor's movement on it in tactile sensing, a human being can evaluate the several micrometers of unevenness on the object surface by means of SR. We intend to apply SR to tactile sensing and to develop a tactile sensing system capable of measuring an object surface with high precision in not only a controlled environment like a precision measurement room but also in a living environment. First, we investigate the SR characteristic possessed by a Hodgkin–Huxley model capable of emulating squid's neuron activities. According to the simulation results, we develop a new electronic circuit capable of generating the SR. We perform the object surface scan using a linear stage equipped with a tactile sensor and the circuit. A series of object surface scanning tests is repeated while changing the intensity of applied noise, and the signal to noise ratio (SNR, hereafter) is calculated from the obtained measurement data to check the effect of the SR. In the experiment, striped textures with a height of δ = 5 ~ 30 μm are used as specimens. The SNR changes depending on the noise intensity, and the local maximum appears under a proper noise. It is found that the sensing accuracy is improved according to the aforementioned SR theory. Therefore, SR, which is usually applied to noisy environments, is effective for a tactile sensing system.

WE-D-BRC-03: Real-Time MR-Guided Radiotherapy: Integration of a Low-Field MR System

There has been increased interest in developing real‐time MR‐guided radiotherapy systems because of the potential of 3D imaging in real time with the improved soft‐tissue contrast provided by MR. An overview of the issues related to the integration of a radiotherapy source (e.g. linac) with a low field magnetic system are discussed. The effects of the MRmagnetic fields on radiation treatment plans for the various generic designs, and on the performance of the linac are presented. The effects of radio frequency fields from the linac upon the MR image acquisition process is introduced. Advantages of low fields are discussed: minimization of the magnetic field‐induced distortions on plans; use conventional RTP instead of Monte Carlo for high fields; avoidance of hot/cold radiation spots at air‐tissue interfaces seen with high fields; reduced susceptibility artifacts; reduced geometric distortions; reduced magnetic shielding issues; exploitation of the increased T1 contrasts at low fields for fast imaging. The main disadvantage at low fields is decreased SNR. Some proposed designs are given. In particular, the first reported successful system providing any MRimaging during radiotherapy irradiation is discussed. This head prototype involves a 6 MV linac mounted onto an opening of a biplanar 0.2 T MR system. The linac‐MR gantry would rotate together to the prescribed angle of irradiation delivery. The only observable difference between the MRimages obtained with linac‐radiation ON to linac OFF is the small changes in SNR. Other possible enhancements (replacing low field with high field MR if required, different types of magnets, etc) to the generic design are also given. The lecture will offer an overview of the advantages and disadvantages of low field MR for real‐time MR‐guided radiotherapy (with the introduction of a working prototype). Learning Objectives: 1. Understand the technical issues in integrating an MR system with a radiotherapy source, especially with a linac 2. Understand the issues related to distortions of the characteristics of dose deposition because of the MRmagnetic field 3. Understand the imaging advantages of low field MR, as well as, its disadvantage 4. Understand the technical advantages in the integration of low field system with a linac 5. Understand the advantages/disadvantages of the different generic designs proposed to date

First MR images obtained during megavoltage photon irradiation from a prototype integrated linac‐MR system

The authors report the first magnetic resonance (MR) images produced by their prototype MR system integrated with a radiation therapy source. The prototype consists of a 6 MV linac mounted onto the open end of a biplanar 0.2 T permanent MR system which has 27.9 cm pole-to-pole opening with flat gradients (40 mT/m) running under a TMX NRC console. The distance from the magnet isocenter to the linac target is 80 cm. The authors' design has resolved the mutual interferences between the two devices such that the MR magnetic field does not interfere with the trajectory of the electron in the linac waveguide, and the radiofrequency (RF) signals from each system do not interfere with the operation of the other system. Magnetic and RF shielding calculations were performed and confirmed with appropriate measurements. The prototype is currently on a fixed gantry; however, in the very near future, the linac and MR magnet will rotate in unison such that the linac is always aimed through the opening in the biplanar magnet. MR imaging was found to be fully operational during linac irradiation and proven by imaging a phantom with conventional gradient echo sequences. Except for small changes in SNR, MR images produced during irradiation were visually and quantitatively very similar to those taken with the linac turned off. This prototype system provides proof of concept that the design has decreased the mutual interferences sufficiently to allow the development of real-time MR-guided radiotherapy. Low field-strength systems (0.2-0.5 T) have been used clinically as diagnostic tools. The task of the linac-MR system is, however, to provide MR guidance to the radiotherapy beam. Therefore, the 0.2 T field strength would provide adequate image quality for this purpose and, with the addition of fast imaging techniques, has the potential to provide 4D soft-tissue visualization not presently available in image-guided radiotherapy systems. The authors' initial design incorporates a permanent magnet; however, other types of magnets and field strengths could also be incorporated. Usable MR images were obtained during linac irradiation from the linac-MR prototype. The authors' prototype design can be used as the functional starting point in developing real-time MR guidance offering soft-tissue contrast that can be coupled with tumor tracking for real-time adaptive radiotherapy.

Sensing Glove for Brain Studies: Design and Assessment of Its Compatibility for fMRI With a Robust Test

In this paper, we describe a biomimetic-fabric-based sensing glove that can be used to monitor hand posture and gesture. Our device is made of a distributed sensor network of piezoresistive conductive elastomers integrated into an elastic fabric. This solution does not affect natural movement and hand gestures, and can be worn for a long time with no discomfort. The glove could be fruitfully employed in behavioral and functional studies with functional MRI (fMRI) during specific tactile or motor tasks. To assess MR compatibility of the system, a statistical test on phantoms is introduced. This test can also be used for testing the compatibility of mechatronic devices designed to produce different stimuli inside the MR environment. We propose a statistical test to evaluate changes in SNR and time-domain standard deviations between image sequences acquired under different experimental conditions. fMRI experiments on subjects wearing the glove are reported. The reproducibility of fMRI results obtained with and without the glove was estimated. A good similarity between the activated regions was found in the two conditions.

Reproducibility of brain tissue volumes in longitudinal studies: Effects of changes in signal-to-noise ratio and scanner software

It is imperative that users of voxel-based morphometry (VBM) be aware of its reproducibility and the factors which influence results. We assessed the reproducibility of a VBM software package (SPM5) in measuring gray matter (GM) and white matter (WM) volumes from at least two consecutive 3D T1-weighted studies in 64 subjects. Factors investigated were the inter-study interval (ISI: 2.2 h to 124 days), signal-to-noise ratio (SNR: number of image averages (NA)=1 or 2), scanner software version and idle time. SNR was measured by direct estimation of tissue noise (SNRTN) and mean intensity in noise-only voxels (SNRNO). After the scanner software upgrade, voxel intensity increased 5-fold and WM mean SNRTN by 24% (p<0.001). Mean WM and GM volume changes in consecutive studies were near 0% (absolute SD of 7 ml and 10 ml respectively). Studies acquired with original scanner software showed a small (1.6%) mean GM volume increase attributed to SNRTN increases in five subjects due to scanner maintenance. GM volumes increased with SNRTN across the software upgrade (up to 4.3%; p<0.01) and NA=2 acquisitions (up to 4.1%; p<0.001). GM and WM volumes were independent of ISI when ISI did not encompass the software change. Scanner idle times of >6 h decreased SNR by 7% (p<0.001). SPM5 failed to include visible peripheral GM in only 2 subjects. SNRTN increases were greater than SNRNO increases across the software upgrade. It was concluded that SNR changes significantly influence SPM5-derived GM volumes. SNR may be influenced by scanner software upgrades and hardware condition and should be routinely assessed in studies of brain volume.