磁共振梯度双回波序列监控高强度聚焦超声治疗

目的 利用MR梯度双回波脉冲序列监控高强度聚焦超声(MRgHIFU)治疗,同时获取温度图和解剖图,提高治疗的准确性和安全性。方法 在第一、第二个回波上分别施加独立的相位编码梯度,一个回波获取高分辨率的解剖图,另一个回波获取快速的温度图。将温度图叠加在解剖图上治疗监控。通过牛肝离体加热和水膜移动实验加以验证。结果 牛肝离体实验表明,在最快1幅/秒温度图时仍然可以很好地测量和显示温度,优于传统的温度图显示方法。水模实验证明此法对检测运动的敏感度较好,有利于监控治疗的准确性和安全性。结论 利用MR梯度双回波脉冲序列可以在HIFU实验中更好地监控温度和检测运动。     

Phase unwrapping of MR images using ΦUN – A fast and robust region growing algorithm

We present a fully automated phase unwrapping algorithm (ΦUN) which is optimized for high-resolution magnetic resonance imaging data. The algorithm is a region growing method and uses separate quality maps for seed finding and unwrapping which are retrieved from the full complex information of the data. We compared our algorithm with an established method in various phantom and in vivo data and found a very good agreement between the results of both techniques. ΦUN, however, was significantly faster at low signal to noise ratio (SNR) and data with a more complex phase topography, making it particularly suitable for applications with low SNR and high spatial resolution. ΦUN is freely available to the scientific community.     

Gradient echo plural contrast imaging--signal model and derived contrasts: T2*, T1, phase, SWI, T1f, FST2*and T2*-SWI

Gradient Echo Plural Contrast Imaging (GEPCI) is a post processing technique that, based on a widely available multiple gradient echo sequence, allows simultaneous generation of naturally co-registered images with various contrasts: T1 weighted, R2*=1/T2* maps and frequency (f) maps. Herein, we present results demonstrating the capability of GEPCI technique to generate image sets with additional contrast characteristics obtained by combing the information from these three basic contrast maps. Specifically, we report its ability to generate GEPCI-susceptibility weighted images (GEPCI-SWI) with improved SWI contrast that is free of T1 weighting and RF inhomogeneities; GEPCI-SWI-like images with the contrast similar to original SWI; T1f images that offer superior GM/WM matter contrast obtained by combining the GEPCI T1 and frequency map data; Fluid Suppressed T2* (FST2*) images that utilize GEPCI T1 data to suppress CSF signal in T2* maps and provide contrast similar to FLAIR T2 weighted images; and T2*-SWI images that combine SWI contrast with quantitative T2* map and offer advantages of visualizing venous structure with hyperintense T2* lesions (e.g. MS lesions). To analyze GEPCI images we use an improved algorithm for combining data from multi-channel RF coils and a method for unwrapping phase/frequency maps that takes advantage of the information on phase evolution as a function of gradient echo time in GEPCI echo train.     

Image distortion correction in fMRI: A quantitative evaluation

A well-recognized problem with the echo-planar imaging (EPI) technique most commonly used for functional magnetic resonance imaging (fMRI) studies is geometric distortion caused by magnetic field inhomogeneity. This makes it difficult to achieve an accurate registration between a functional activation map calculated from an EPI time series and an undistorted, high resolution anatomical image. A correction method based on mapping the spatial distribution of field inhomogeneities can be used to reduce these distortions. This approach is attractive in its simplicity but requires postprocessing to improve the robustness of the acquired field map and reduce any secondary artifacts. Furthermore, the distribution of the internal magnetic field throughout the head is position dependent resulting in an interaction between distortion and head motion. Therefore, a single field map may not be sufficient to correct for the distortions throughout a whole fMRI time series. In this paper we present a quantitative evaluation of image distortion correction for fMRI at 2T. We assess (i) methods for the acquisition and calculation of field maps, (ii) the effect of image distortion correction on the coregistration between anatomical and functional images, and (iii) the interaction between distortion and head motion, assessing the feasibility of using field maps to reduce this effect. We propose that field maps with acceptable noise levels can be generated easily using a dual echo-time EPI sequence and demonstrate the importance of distortion correction for anatomical coregistration, even for small distortions. Using a dual echo-time series to generate a unique field map at each time point, we characterize the interaction between head motion and geometric distortion. However, we suggest that the variance between successively measured field maps introduces additional unwanted variance in the voxel time-series and is therefore not adequate to correct for time-varying distortions.     

Mapping heterogenous anisotropic tissue mechanical properties with transverse isotropic nonlinear inversion MR elastography

The white matter tracts of brain tissue consist of highly-aligned, myelinated fibers; white matter is structurally anisotropic and is expected to exhibit anisotropic mechanical behavior. In vivo mechanical properties of tissue can be imaged using magnetic resonance elastography (MRE). MRE can detect and monitor natural and disease processes that affect tissue structure; however, most MRE inversion algorithms assume locally homogenous properties and/or isotropic behavior, which can cause artifacts in white matter regions. A heterogeneous, model-based transverse isotropic implementation of a subzone-based nonlinear inversion (TI-NLI) is demonstrated. TI-NLI reconstructs accurate maps of the shear modulus, damping ratio, shear anisotropy, and tensile anisotropy of in vivo brain tissue using standard MRE motion measurements and fiber directions estimated from diffusion tensor imaging (DTI). TI-NLI accuracy was investigated with using synthetic data in both controlled and realistic settings: excellent quantitative and spatial accuracy was observed and cross-talk between estimated parameters was minimal. Ten repeated, in vivo, MRE scans acquired from a healthy subject were co-registered to demonstrate repeatability of the technique. Good resolution of anatomical structures and bilateral symmetry were evident in MRE images of all mechanical property types. Repeatability was similar to isotropic MRE methods and well within the limits required for clinical success. TI-NLI MRE is a promising new technique for clinical research into anisotropic tissues such as the brain and muscle.     

Off-axis quantitative phase imaging processing using CUDA: toward real-time applications

We demonstrate real time off-axis Quantitative Phase Imaging (QPI) using a phase reconstruction algorithm based on NVIDIA's CUDA programming model. The phase unwrapping component is based on Goldstein's algorithm. By mapping the process of extracting phase information and unwrapping to GPU, we are able to speed up the whole procedure by more than 18.8× with respect to CPU processing and ultimately achieve video rate for mega-pixel images. Our CUDA implementation also supports processing of multiple images simultaneously. This enables our imaging system to support high speed, high throughput, and real-time image acquisition and visualization.     

Can MR elastography be used to measure liver stiffness in patients with iron overload?

Untreated hepatic iron overload causes hepatic fibrosis and cirrhosis and can predispose to hepatocellular carcinoma. MR elastography (MRE) provides a non-invasive means to measure liver stiffness, which correlates with liver fibrosis but standard gradient recalled echo (GRE)-based MRE techniques fail in patients with high iron due to very low hepatic signal. Short echo time (TE) 2D spin echo echoplanar imaging (SE-EPI)-based MRE may allow measurement of stiffness in the iron loaded liver. The purpose of this study was to describe the use of such an MRE sequence in patients undergoing liver iron quantification by MRI. In our preliminary study of 43 patients with mean LIC of 9.3 mg/g (range 1.8–21.5 mg/g), liver stiffness measurements could be made in 77% (33/43) of patients with a short TE, SE-EPI based MRE sequence. On average, mean LIC in patients with failed MRE was higher than in those with successful MRE (15.9 mg/g dry weight vs. 7.3 mg/g), but a cut-off value for successful MRE could not be established. Seven patients (21% of those with successful MRE) had liver stiffness values suggestive of the presence of significant fibrosis (> 2.49 kPa). A short TE, SE-EPI based MR elastography sequence allows successful measurement of liver stiffness in a majority of patients with liver iron loading, potentially allowing non-invasive screening for fibrosis.

     

Magnetic resonance elastography: Non-invasive mapping of tissue elasticity

Magnetic resonance elastography (MRE) is a phase-contrast-based MRI imaging technique that can directly visualize and quantitatively measure propagating acoustic strain waves in tissue-like materials subjected to harmonic mechanical excitation. The data acquired allows the calculation of local quantitative values of shear modulus and the generation of images that depict tissue elasticity or stiffness. This is significant because palpation, a physical examination that assesses the stiffness of tissue, can be an effective method of detecting tumors, but is restricted to parts of the body that are accessible to the physician's hand. MRE shows promise as a potential technique for 'palpation by imaging', with possible applications in tumor detection (particularly in breast, liver, kidney and prostate), characterization of disease, and assessment of rehabilitation (particularly in muscle). We describe MRE in the context of other recent techniques for imaging elasticity, discuss the processing algorithms for elasticity reconstruction and the issues and assumptions they involve, and present recent ex vivo and in vivo results.     

A region-growing technique to improve multi-temporal DInSAR interferogram phase unwrapping performance

We present an efficient solution to mitigate phase unwrapping (PhU) errors that can affect a sequence of multi-temporal differential synthetic aperture radar (SAR) interferograms. To this aim, we propose a strategy that, starting from a properly chosen network of differential interferograms, complements PhU operations with an advanced multi-temporal region-growing (RG) procedure that exploits the space-time relationships among the computed interferograms. In particular, the proposed method implements an iterative procedure that, at each step, allows correcting a sequence of previously unwrapped interferograms at one selected pixel, namely candidate pixel, by exploiting the (unwrapped) phase values at its neighbouring ‘seed’ pixels (i.e. the ones already correctly unwrapped). Following their estimation, the unwrapped phases are then used to retrieve surface deformation products, such as mean deformation velocity maps and displacement time series, through (advanced) small baseline differential SAR interferometry (DInSAR) techniques. The effectiveness of the presented RG PhU algorithm is demonstrated by analysing a data set of SAR images acquired by the European Remote Sensing (ERS)-1/2 sensors over the megacity area of Istanbul, Turkey.     

Development of a robust method for generating 7.0 T multichannel phase images of the brain with application to normal volunteers and patients with neurological diseases

The increased susceptibility effects and high signal-to-noise ratio at 7.0 T enable imaging of the brain using the phase of the magnetic resonance signal. This study describes and evaluates a robust method for calculating phase images from gradient-recalled echo (GRE) scans. The GRE scans were acquired at 7.0 T using an eight-channel receive coil at spatial resolutions up to 0.195 x 0.260 x 2.00 mm. The entire 7.0 T protocol took less than 10 min. Data were acquired from forty-seven subjects including clinical patients with multiple sclerosis (MS) or brain tumors. The phase images were post-processed using a fully automated phase unwrapping algorithm that combined the data from the different channels. The technique was used to create the first phase images of MS patients at any field strength and the first phase images of brain tumor patients above 1.5 T. The clinical images showed novel contrast in MS plaques and depicted microhemorrhages and abnormal vasculature in brain tumors with unsurpassed resolution and contrast.     

Automated phase unwrapping in digital holography with deep learning

Digital holography can provide quantitative phase images related to the morphology and content of biological samples. After the numerical image reconstruction, the phase values are limited between −π and π; thus, discontinuity may occur due to the modulo 2π operation. We propose a new deep learning model that can automatically reconstruct unwrapped focused-phase images by combining digital holography and a Pix2Pix generative adversarial network (GAN) for image-to-image translation. Compared with numerical phase unwrapping methods, the proposed GAN model overcomes the difficulty of accurate phase unwrapping due to abrupt phase changes and can perform phase unwrapping at a twice faster rate. We show that the proposed model can generalize well to different types of cell images and has high performance compared to recent U-net models. The proposed method can be useful in observing the morphology and movement of biological cells in real-time applications.     

Tomoelastography by multifrequency wave number recovery from time-harmonic propagating shear waves

Palpation is one of the most sensitive, effective diagnostic practices, motivating the quantitative and spatially resolved determination of soft tissue elasticity parameters by medical ultrasound or MRI. However, this so-called elastography often suffers from limited anatomical resolution due to noise and insufficient elastic deformation, currently precluding its use as a tomographic modality on its own. We here introduce an efficient way of processing wave images acquired by multifrequency magnetic resonance elastography (MMRE), which relies on wave number reconstruction at different harmonic frequencies followed by their amplitude-weighted averaging prior to inversion. This results in compound maps of wave speed, which reveal variations in tissue elasticity in a tomographic fashion, i.e. an unmasked, slice-wise display of anatomical details at pixel-wise resolution. The method is demonstrated using MMRE data from the literature including abdominal and pelvic organs such as the liver, spleen, uterus body and uterus cervix. Even in small regions with low wave amplitudes, such as nucleus pulposus and spinal cord, elastic parameters consistent with literature values were obtained. Overall, the proposed method provides a simple and noise-robust strategy of in-plane wave analysis of MMRE data, with a pixel-wise resolution producing superior detail to MRE direct inversion methods.     

磁共振弹性成像评价主动脉壁硬度

目的 探讨磁共振弹性成像（MRE）评价主动脉壁硬度的可行性。方法 采用MRE技术观察5名健康志愿者的腹主动脉,将气动震动装置置于前腹壁,使其产生60 Hz低频率机械波,经腹部传播至腹主动脉,并在主动脉管腔内产生机械波传播;以梯度回波为基础的MRE序列对主动脉内传播的机械波进行成像。结果 机械波在腹主动脉管腔内沿腹其长轴传播良好;通过测量机械波波长,初步估算得出腹主动脉的硬度。结论 MRE技术对评价主动脉壁硬度具有一定可行性。     

基于一种改进的相位校正算法消除MRI运动伪影

背景：近年来,MRI由于具有高的空间分辨率和软组织对比度,在临床上的运用越来越广泛。但是其成像时间较长,所以容易受到患者身体运动的影响,产生运动伪影。目的：去除MRI图像成像时产生的伪影,改善图像质量。方法：使用改进的相位矫正算法,并结合水平集算法去除图像伪影。去除伪影后使用模糊增强改善处理后图像的质量。结果与结论：实验证明使用改进的相位矫正算法得到的图像比使用原始的相位矫正算法得到的图像效果更加理想。     

High fidelity tonotopic mapping using swept source functional magnetic resonance imaging

Tonotopy, the topographic encoding of sound frequency, is the fundamental property of the auditory system. Invasive techniques lack the spatial coverage or frequency resolution to rigorously investigate tonotopy. Conventional auditory fMRI is corrupted by significant image distortion, sporadic acoustic noise and inadequate frequency resolution. We developed an efficient and high fidelity auditory fMRI method that integrates continuous frequency sweeping stimulus, distortion free MRI sequence with stable scanner noise and Fourier analysis. We demonstrated this swept source imaging (SSI) in the rat inferior colliculus and obtained tonotopic maps with ~2 kHz resolution and 40 kHz bandwidth. The results were vastly superior to those obtained by conventional fMRI mapping approach and in excellent agreement with invasive findings. We applied SSI to examine tonotopic injury following developmental noise exposure and observed that the tonotopic organization was significantly disrupted. With SSI, we also observed the subtle effects of sound pressure level on tonotopic maps, reflecting the complex neuronal responses associated with asymmetric tuning curves. This in vivo and noninvasive technique will greatly facilitate future investigation of tonotopic plasticity and disorders and auditory information processing. SSI can also be adapted to study topographic organization in other sensory systems such as retinotopy and somatotopy.     

New insights into regional systolic and diastolic left ventricular function with tissue Doppler echocardiography: from qualitative analysis to a quantitative approach.

Tissue Doppler echocardiography is a variation of conventional Doppler flow imaging. This modality allows quantification of the Doppler shift within the range of myocardial tissue motion. The velocity at a variety of myocardial sites can be determined and distinguished very rapidly by using Doppler techniques. The velocity of moving tissue can be studied with pulsed wave tissue Doppler sampling, which displays the velocity of a selected myocardial region against time, with high temporal resolution. In addition, the velocities can be calculated with time-velocity maps and displayed as color-encoded velocity maps in either an M-mode or 2-dimensional format. This review will focus on the technical aspects and the different methods of tissue Doppler echocardiography for the analysis of regional systolic and diastolic left ventricular function. Whereas pulsed wave tissue Doppler echocardiography allows measurements of velocities of a selected myocardial region, color tissue Doppler gives the best overview of cardiac dynamics because the entire scanned color data are displayed simultaneously. However, there is an increasing need for objective evaluation of tissue Doppler information. Digital images and postprocessing of the data allow for quantitative off-line analysis, and the different approaches and parameters proposed from different centers are discussed.     

Prediction-based phase unwrapping for differential interferograms of coal mining areas using a stochastic medium model

This paper presents a novel phase unwrapping method for differential interferograms of coal mining areas, which takes full account of the mechanism of mining subsidence. The model uses a predicted deformation value for deformation caused by underground coal mining to assist the phase unwrapping and improve its accuracy. This method can overcome the defects of existing phase unwrapping algorithms that are not applicable to regions experiencing rapid deformation. The availability of the proposed method is first verified with noise-free simulated data, and then further tested with 3D laser scanning data and real synthetic aperture radar interferometry images. The results show that the prediction-based phase unwrapping method is able to realize phase unwrapping of differential interferograms covering coal mining areas that experience rapid deformation, and the results obtained are reasonable.     

Phase contrast x-ray velocimetry of small animal lungs: optimising imaging rates

Chronic lung diseases affect a vast portion of the world’s population. One of the key difficulties in accurately diagnosing and treating chronic lung disease is our inability to measure dynamic motion of the lungs in vivo. Phase contrast x-ray imaging (PCXI) allows us to image the lungs in high resolution by exploiting the difference in refractive indices between tissue and air. Combining PCXI with x-ray velocimetry (XV) allows us to track the local motion of the lungs, improving our ability to locate small regions of disease under natural ventilation conditions. Via simulation, we investigate the optimal imaging speed and sequence to capture lung motion in vivo in small animals using XV on both synchrotron and laboratory x-ray sources, balancing the noise inherent in a short exposure with motion blur that results from a long exposure.OCIS codes: (170.7440) X-ray imaging, (110.6150) Speckle imaging     

Artificial neural networks for magnetic resonance elastography stiffness estimation in inhomogeneous materials

PurposeTo test the hypothesis that removing the assumption of material homogeneity will improve the spatial accuracy of stiffness estimates made by Magnetic Resonance Elastography (MRE).MethodsAn artificial neural network was trained using synthetic wave data computed using a coupled harmonic oscillator model. Material properties were allowed to vary in a piecewise smooth pattern. This neural network inversion (Inhomogeneous Learned Inversion (ILI)) was compared against a previous homogeneous neural network inversion (Homogeneous Learned Inversion (HLI)) and conventional direct inversion (DI) in simulation, phantom, and in-vivo experiments.ResultsIn simulation experiments, ILI was more accurate than HLI and DI in predicting the stiffness of an inclusion in noise-free, low-noise, and high-noise data. In the phantom experiment, ILI delineated inclusions ≤ 2.25 cm in diameter more clearly than HLI and DI, and provided a higher contrast-to-noise ratio for all inclusions. In a series of stiff brain tumors, ILI shows sharper stiffness transitions at the edges of tumors than the other inversions evaluated.ConclusionILI is an artificial neural network based framework for MRE inversion that does not assume homogeneity in material stiffness. Preliminary results suggest that it provides more accurate stiffness estimates and better contrast in small inclusions and at large stiffness gradients than existing algorithms that assume local homogeneity. These results support the need for continued exploration of learning-based approaches to MRE inversion, particularly for applications where high resolution is required.     

Objective assessment of left ventricular wall motion from contrast-enhanced power modulation images.

There is no method to objectively evaluate left ventricular (LV) function from contrast-enhanced images. We tested the feasibility of evaluating regional LV function by using power modulation imaging. In protocol 1, 9 anesthetized closed-chest pigs were studied. Images were obtained during contrast infusion at baseline, during LAD occlusion and reperfusion. In protocol 2, images were obtained in 20 patients (14 wall-motion abnormalities; 6 controls) during contrast enhancement. Off-line, frame-by-frame, semiautomated endocardial border detection was followed by color encoding of endocardial motion, followed by segmentation and calculation of regional fractional area changes. In all animals, coronary occlusions resulted in hypokinesis and decreased fractional area changes in LAD-related segments only, which were reversed during reperfusion. In patients, wall-motion analysis was in agreement with an expert reader of dynamic images in 92.5% segments, with interobserver variability of 12.5%. Color encoding of endocardial motion from contrast-enhanced power modulation images allows accurate quantitative assessment of regional LV function.