Novel method to correct displacement profile images and calculate flow vector fields using saturation-tagging MR imaging.

Saturation-tagging Magnetic Resonance (MR) imaging provides a simple and robust means to directly visualize displacement profiles within fluid flow fields. Although useful for velocity quantitation as well as for qualitative depiction of flow patterns in certain well-defined flow fields, the technique is prone to distortions due to oblique flow (misregistration artifact) and ambiguity of fluid vector trajectories in complex flow situations. A novel method is proposed whereby two images are acquired, differing in the temporal position of the phase encoding gradient. Theoretical analysis shows that from the paired images, distortion of the two-dimensional displacement profile can be corrected and fluid velocity vectors extracted, even if the flow directions are unknown. In the simpler case of flow oblique to the gradient principal axes, but with a known trajectory, only one image is necessary to correct the displacement profile distortion and extract the velocity information. MRI experiments in a straight tube model have been carried out to evaluate the feasibility of this method. Good agreement is achieved between the results from MR imaging and those predicted via computer simulation.     

Quantitative comparison of CFD predicted and MRI measured velocity fields in a carotid bifurcation phantom

Steady flow of a blood mimicking fluid in a physiologically realistic model of the human carotid bifurcation was studied using both magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) modelling techniques. Quantitative comparisons of the 3D velocity field in the bifurcation phantom were made between phase contrast MRI measurements and CFD predictions. The geometry for the CFD model was reconstructed from T(1) weighted MR imaging of the test phantom. It was found that the predicted velocity fields were in fair agreement with MR measured velocities. In both the internal and external carotid arteries, the agreement between CFD predictions and MRI measurements was better along the inner-outer wall axis with a correlation factor C>0.897 (average 0.939) where the velocity profiles were skewed, than along the anterior-posterior axis (average correlation factor 0.876) where the velocity profiles were in M-shape.     

Efficient Reconstruction of Heterogeneous Networks from Time Series via Compressed Sensing

Recent years have witnessed a rapid development of network reconstruction approaches, especially for a series of methods based on compressed sensing. Although compressed-sensing based methods require much less data than conventional approaches, the compressed sensing for reconstructing heterogeneous networks has not been fully exploited because of hubs. Hub neighbors require much more data to be inferred than small-degree nodes, inducing a cask effect for the reconstruction of heterogeneous networks. Here, a conflict-based method is proposed to overcome the cast effect to considerably reduce data amounts for achieving accurate reconstruction. Moreover, an element elimination method is presented to use the partially available structural information to reduce data requirements. The integration of both methods can further improve the reconstruction performance than separately using each technique. These methods are validated by exploring two evolutionary games taking place in scale-free networks, where individual information is accessible and an attempt to decode the network structure from measurable data is made. The results demonstrate that for all of the cases, much data are saved compared to that in the absence of these two methods. Due to the prevalence of heterogeneous networks in nature and society and the high cost of data acquisition in large-scale networks, these approaches have wide applications in many fields and are valuable for understanding and controlling the collective dynamics of a variety of heterogeneous networked systems.     

Fast Keyhole MR Imaging Using Optimized k-Space Data Acquisition

In some dynamic magnetic resonance imaging (MRI) applications, the sample is still, and only the signal intensity changes with time. For such cases, the keyhole imaging principle can be used. In standard keyhole imaging, a low-frequency image signal is acquired, using a limited number of phase-encoding steps, which correspond to the rectangular sampling region in the k-space center. However, such a region practically never coincides with the position of the k-space points, which carry the most relevant low-frequency image information. In this paper we propose an improved keyhole method, which allows dynamic acquisition of a low-frequency image signal from selected most relevant k-space points via fast imaging mechanisms. Dynamic data acquisition is executed in the presence of time-varying magnetic-field (MF) gradients after single sample excitation. Special care has been taken in the design of the gradient sequence to minimize gradient load. This improved keyhole imaging method has been considered theoretically and verified experimentally on a model system.     

Ultrasound-driven cardiac MRI

PurposeOne of the challenges of cardiac MR imaging is the compensation of respiratory motion, which causes the heart and the surrounding tissues to move. Commonly-used methods to overcome this effect, breath-holding and MR navigation, present shortcomings in terms of available acquisition time or need to periodically interrupt the acquisition, respectively. In this work, an implementation of respiratory motion compensation that obtains information from abdominal ultrasound and continuously adapts the imaged slice position in real time is presented.MethodsA custom workflow was developed, comprising an MR-compatible ultrasound acquisition system, a feature-motion-tracking system with polynomial predictive capability, and a custom MR sequence that continuously adapts the position of the acquired slice according to the tracked position. The system was evaluated on a moving phantom by comparing sharpness and image blurring between static and moving conditions, and in vivo by tracking the motion of the blood vessels of the liver to estimate the cardiac motion. Cine images of the heart were acquired during free breathing.ResultsIn vitro, the predictive motion correction yielded significantly better results than non-predictive or non-corrected acquisitions (p ≪ 0.01). In vivo, the predictive correction resulted in an image quality very similar to the breath-hold acquisition, whereas the uncorrected images show noticeable blurring artifacts.ConclusionIn this work, the possibility of using ultrasound navigation with tracking for the real-time adaptation of MR imaging slices was demonstrated. The implemented technique enabled efficient imaging of the heart with resolutions that would not be feasible in a single breath-hold.     

Modelling Temporal Stability of EPI Time Series Using Magnitude Images Acquired with Multi-Channel Receiver Coils

In 2001, Krueger and Glover introduced a model describing the temporal SNR (tSNR) of an EPI time series as a function of image SNR (SNR₀). This model has been used to study physiological noise in fMRI, to optimize fMRI acquisition parameters, and to estimate maximum attainable tSNR for a given set of MR image acquisition and processing parameters. In its current form, this noise model requires the accurate estimation of image SNR. For multi-channel receiver coils, this is not straightforward because it requires export and reconstruction of large amounts of k-space raw data and detailed, custom-made image reconstruction methods. Here we present a simple extension to the model that allows characterization of the temporal noise properties of EPI time series acquired with multi-channel receiver coils, and reconstructed with standard root-sum-of-squares combination, without the need for raw data or custom-made image reconstruction. The proposed extended model includes an additional parameter κ which reflects the impact of noise correlations between receiver channels on the data and scales an apparent image SNR (SNR′₀) measured directly from root-sum-of-squares reconstructed magnitude images so that κ = SNR′₀/SNR₀ (under the condition of SNR₀>50 and number of channels ≤32). Using Monte Carlo simulations we show that the extended model parameters can be estimated with high accuracy. The estimation of the parameter κ was validated using an independent measure of the actual SNR₀ for non-accelerated phantom data acquired at 3T with a 32-channel receiver coil. We also demonstrate that compared to the original model the extended model results in an improved fit to human task-free non-accelerated fMRI data acquired at 7T with a 24-channel receiver coil. In particular, the extended model improves the prediction of low to medium tSNR values and so can play an important role in the optimization of high-resolution fMRI experiments at lower SNR levels.     

Echo Particle Image Velocimetry

The transport of mass, momentum, and energy in fluid flows is ultimately determined by spatiotemporal distributions of the fluid velocity field.¹ Consequently, a prerequisite for understanding, predicting, and controlling fluid flows is the capability to measure the velocity field with adequate spatial and temporal resolution.² For velocity measurements in optically opaque fluids or through optically opaque geometries, echo particle image velocimetry (EPIV) is an attractive diagnostic technique to generate "instantaneous" two-dimensional fields of velocity.^3,4,5,6 In this paper, the operating protocol for an EPIV system built by integrating a commercial medical ultrasound machine⁷ with a PC running commercial particle image velocimetry (PIV) software⁸ is described, and validation measurements in Hagen-Poiseuille (i.e., laminar pipe) flow are reported.For the EPIV measurements, a phased array probe connected to the medical ultrasound machine is used to generate a two-dimensional ultrasound image by pulsing the piezoelectric probe elements at different times. Each probe element transmits an ultrasound pulse into the fluid, and tracer particles in the fluid (either naturally occurring or seeded) reflect ultrasound echoes back to the probe where they are recorded. The amplitude of the reflected ultrasound waves and their time delay relative to transmission are used to create what is known as B-mode (brightness mode) two-dimensional ultrasound images. Specifically, the time delay is used to determine the position of the scatterer in the fluid and the amplitude is used to assign intensity to the scatterer. The time required to obtain a single B-mode image, t, is determined by the time it take to pulse all the elements of the phased array probe. For acquiring multiple B-mode images, the frame rate of the system in frames per second (fps) = 1/δt. (See 9 for a review of ultrasound imaging.)For a typical EPIV experiment, the frame rate is between 20-60 fps, depending on flow conditions, and 100-1000 B-mode images of the spatial distribution of the tracer particles in the flow are acquired. Once acquired, the B-mode ultrasound images are transmitted via an ethernet connection to the PC running the PIV commercial software. Using the PIV software, tracer particle displacement fields, D(x,y)[pixels], (where x and y denote horizontal and vertical spatial position in the ultrasound image, respectively) are acquired by applying cross correlation algorithms to successive ultrasound B-mode images.¹⁰ The velocity fields, u(x,y)[m/s], are determined from the displacements fields, knowing the time step between image pairs, ΔT[s], and the image magnification, M[meter/pixel], i.e., u(x,y) = MD(x,y)/ΔT. The time step between images ΔT = 1/fps + D(x,y)/B, where B[pixels/s] is the time it takes for the ultrasound probe to sweep across the image width. In the present study, M = 77[μm/pixel], fps = 49.5[1/s], and B = 25,047[pixels/s]. Once acquired, the velocity fields can be analyzed to compute flow quantities of interest.     

Multi-Reception Strategy with Improved SNR for Multichannel MR Imaging

A multi-reception strategy with extended GRAPPA is proposed in this work to improve MR imaging performance at ultra-high field MR systems with limited receiver channels. In this method, coil elements are separated to two or more groups under appropriate grouping criteria. Those groups are enabled in sequence for imaging first, and then parallel acquisition is performed to compensate for the redundant scan time caused by the multiple receptions. To efficiently reconstruct the data acquired from elements of each group, a specific extended GRAPPA was developed. This approach was evaluated by using a 16-element head array on a 7 Tesla whole-body MRI scanner with 8 receive channels. The in-vivo experiments demonstrate that with the same scan time, the 16-element array with twice receptions and acceleration rate of 2 can achieve significant SNR gain in the periphery area of the brain and keep nearly the same SNR in the center area over an eight-element array, which indicates the proposed multi-reception strategy and extended GRAPPA are feasible to improve image quality for MRI systems with limited receive channels. This study also suggests that it is advantageous for a MR system with N receiver channels to utilize a coil array with more than N elements if an appropriate acquisition strategy is applied.     

The accuracy of magnetic resonance phase velocity measurements in stenotic flow

Nuclear magnetic resonance (MR) can be used to measure velocities in fluid flow using the technique of phase velocity mapping. Advantages of MR velocimetry include the simultaneous mapping of the entire flow field through a non-contacting, magnetic window. The phase velocity mapping technique assumes that velocity is constant over the measurement time (typically around 10 ms). For many fluid flows, this assumption is not valid. The current study showed that MR phase velocity measurements of velocity through stenotic flow can be in error by over 100% immediately upstream and downstream of the stenosis throat and by 20% far downstream of the throat in comparison with laser Doppler anemometer measurements taken at the same location. Highly turbulent flow also led to significant errors in velocity measurement. These errors can be attributed to several sources including low signal-to-noise ratio, additional phase shifts due to non-constant velocities, and non-stationary transit-time effects. Velocity measurement errors could be reduced to under 30% at all measurement locations through the use of MR sequences with high signal-to-noise ratios, low echo times, and thick slices.     

TOM software toolbox: acquisition and analysis for electron tomography

Automated data acquisition procedures have changed the perspectives of electron tomography (ET) in a profound manner. Elaborate data acquisition schemes with autotuning functions minimize exposure of the specimen to the electron beam and sophisticated image analysis routines retrieve a maximum of information from noisy data sets. "TOM software toolbox" integrates established algorithms and new concepts tailored to the special needs of low dose ET. It provides a user-friendly unified platform for all processing steps: acquisition, alignment, reconstruction, and analysis. Designed as a collection of computational procedures it is a complete software solution within a highly flexible framework. TOM represents a new way of working with the electron microscope and can serve as the basis for future high-throughput applications.     

Interpolated Compressed Sensing for 2D Multiple Slice Fast MR Imaging

Sparse MRI has been introduced to reduce the acquisition time and raw data size by undersampling the k-space data. However, the image quality, particularly the contrast to noise ratio (CNR), decreases with the undersampling rate. In this work, we proposed an interpolated Compressed Sensing (iCS) method to further enhance the imaging speed or reduce data size without significant sacrifice of image quality and CNR for multi-slice two-dimensional sparse MR imaging in humans. This method utilizes the k-space data of the neighboring slice in the multi-slice acquisition. The missing k-space data of a highly undersampled slice are estimated by using the raw data of its neighboring slice multiplied by a weighting function generated from low resolution full k-space reference images. In-vivo MR imaging in human feet has been used to investigate the feasibility and the performance of the proposed iCS method. The results show that by using the proposed iCS reconstruction method, the average image error can be reduced and the average CNR can be improved, compared with the conventional sparse MRI reconstruction at the same undersampling rate.     

Time Efficient 3D Radial UTE Sampling with Fully Automatic Delay Compensation on a Clinical 3T MR Scanner

This work’s aim was to minimize the acquisition time of a radial 3D ultra-short echo-time (UTE) sequence and to provide fully automated, gradient delay compensated, and therefore artifact free, reconstruction. The radial 3D UTE sequence (echo time 60 μs) was implemented as single echo acquisition with center-out readouts and improved time efficient spoiling on a clinical 3T scanner without hardware modifications. To assess the sequence parameter dependent gradient delays each acquisition contained a quick calibration scan and utilized the phase of the readouts to detect the actual k-space center. This calibration scan does not require any user interaction. To evaluate the robustness of this automatic delay estimation phantom experiments were performed and 19 in vivo imaging data of the head, tibial cortical bone, feet and lung were acquired from 6 volunteers. As clinical application of this fast 3D UTE acquisition single breath-hold lung imaging is demonstrated. The proposed sequence allowed very short repetition times (TR~1ms), thus reducing total acquisition time. The proposed, fully automated k-phase based gradient delay calibration resulted in accurate delay estimations (difference to manually determined optimal delay −0.13 ± 0.45 μs) and allowed unsupervised reconstruction of high quality images for both phantom and in vivo data. The employed fast spoiling scheme efficiently suppressed artifacts caused by incorrectly refocused echoes. The sequence proved to be quite insensitive to motion, flow and susceptibility artifacts and provides oversampling protection against aliasing foldovers in all directions. Due to the short TR, acquisition times are attractive for a wide range of clinical applications. For short T2* mapping this sequence provides free choice of the second TE, usually within less scan time as a comparable dual echo UTE sequence.     

Nontraumatic aortic blood flow sensing by use of an ultrasonic esophageal probe.

The measurement of blood velocity fields, volume flow, and arterial wall motion in the descending thoracic aorta provides essential hemodynamic information for both research and clinical diagnosis. The close proximity of the esophagus to the aorta in the dog makes it possible to obtain such data nonsurgically using an ultrasonic esophageal probe; however, the accuracy of such a probe is limited if the angle between the sound beam and the flow axis, known as the Doppler angle, is not precisely known. By use of a pulsed Doppler velocity meter (PUDVM) and a triangulation procedure, accurate empirical measurement of the Doppler angle has been obtained, allowing quantification of blood velocity scans across the aorta. Volume flow is obtained by integration of blood velocity profiles and arterial wall motion is measured with an ultrasonic echo tracking device. Accuracy of the probe was substantiated by comparison with ultrasonic and electromagnetic implanted flow cuff measurements. Use of the probe in measurement of blood velocity, volume flow and arterial wall motion at various locations along the 8- and 10-cm length of the descending thoracic aorta in adult beagle dogs is detailed. The simplicity, accuracy, and nontraumatic aspect of the technique should allow increasing use of such a probe in numerous research and clinical applications.     

Concurrent Visualization of Acoustic Radiation Force Displacement and Shear Wave Propagation with 7T MRI

Manual palpation is a common and very informative diagnostic tool based on estimation of changes in the stiffness of tissues that result from pathology. In the case of a small lesion or a lesion that is located deep within the body, it is difficult for changes in mechanical properties of tissue to be detected or evaluated via palpation. Furthermore, palpation is non-quantitative and cannot be used to localize the lesion. Magnetic Resonance-guided Focused Ultrasound (MRgFUS) can also be used to evaluate the properties of biological tissues non-invasively. In this study, an MRgFUS system combines high field (7T) MR and 3 MHz focused ultrasound to provide high resolution MR imaging and a small ultrasonic interrogation region (~0.5 x 0.5 x 2 mm), as compared with current clinical systems. MR-Acoustic Radiation Force Imaging (MR-ARFI) provides a reliable and efficient method for beam localization by detecting micron-scale displacements induced by ultrasound mechanical forces. The first aim of this study is to develop a sequence that can concurrently quantify acoustic radiation force displacements and image the resulting transient shear wave. Our motivation in combining these two measurements is to develop a technique that can rapidly provide both ARFI and shear wave velocity estimation data, making it suitable for use in interventional radiology. Secondly, we validate this sequence in vivo by estimating the displacement before and after high intensity focused ultrasound (HIFU) ablation, and we validate the shear wave velocity in vitro using tissue-mimicking gelatin and tofu phantoms. Such rapid acquisitions are especially useful in interventional radiology applications where minimizing scan time is highly desirable.     

Evaluation of radiomic texture feature error due to MRI acquisition and reconstruction: A simulation study utilizing ground truth

The purpose of this study was to examine the dependence of image texture features on MR acquisition parameters and reconstruction using a digital MR imaging phantom. MR signal was simulated in a parallel imaging radiofrequency coil setting as well as a single element volume coil setting, with varying levels of acquisition noise, three acceleration factors, and four image reconstruction algorithms. Twenty-six texture features were measured on the simulated images, ground truth images, and clinical brain images. Subtle algorithm-dependent errors were observed on reconstructed phantom images, even in the absence of added noise. Sources of image error include Gibbs ringing at image edge gradients (tissue interfaces) and well-known artifacts due to high acceleration; two of the iterative reconstruction algorithms studied were able to mitigate these image errors. The difference of the texture features from ground truth, and their variance over reconstruction algorithm and parallel imaging acceleration factor, were compared to the clinical “effect size”, i.e., the feature difference between high- and low-grade tumors on T1- and T2-weighted brain MR images of twenty glioma patients. The measured feature error (difference from ground truth) was small for some features, but substantial for others. The feature variance due to reconstruction algorithm and acceleration factor were generally smaller than the clinical effect size. Certain texture features may be preserved by MR imaging, but adequate precautions need to be taken regarding their validity and reliability. We present a general simulation framework for assessing the robustness and accuracy of radiomic textural features under various MR acquisition/reconstruction scenarios.     

The optical flow of planar surfaces

The human visual system can recover the 3-D shape of moving objects on the basis of motion information alone. Computational studies of this capacity have considered primarily non-planar rigid objects. With respect to moving planar surfaces, previous studies have shown that the planar velocity field has in general a two-fold ambiguity: there are two different planes engaged in different motions that can induce the same velocity field. The current analysis extends the analysis of the planar velocity field in four directions: (1) the use of flow parameters of the type suggested by Koenderink and van Doorn (Optica Acta, 1975, 22, 773-791), (2) the exclusion of confusable non-planar solutions, (3) a new proof and a new method for computing the 3-D motion and surface orientation (4) a comparison with the information available in orthographic velocity fields, which is important for determining the stability of the 3-D recovery process.     

MITICS (MALDI Imaging Team Imaging Computing System): a new open source mass spectrometry imaging software

MITICS is a new software developed for MALDI imaging. We tried to render this software compatible with all types of instruments. MITICS is divided in two parts: MITICS control for data acquisition and MITICS Image for data processing and images reconstruction. MITICS control is available for Applied BioSystems MALDI-TOF instruments and MITICS Image for both Applied BioSystems and Bruker Daltonics ones. MITICS Control provides an interface to the user for setting the acquisition parameters for the imaging sequence, namely set instruments acquisition parameters, create the raster of acquisition and control post-acquisition data processing, and provide this settings to the automatic acquisition software of the MALDI instrument. MITICS Image ensures image reconstruction, files are first converted to XML files before being loaded in a database. In MITICS image we have chosen to implement different data representations and calculations for image reconstruction. MITICS Image uses three different representations that have shown to ease extraction of information from the whole data set. It also offers image reconstruction base either on the maximum peak intensity or the peak area. Image reconstruction is possible for single ions but also by summing signals of different ions. MITICS was validated on biological cases.