扩散加权磁共振成像在急性脑梗死诊断中的价值

目的：探讨扩散加权磁共振成像在急性脑梗死诊断中的价值。方法：采用Philips Gyroscan Intera 1．5T磁共振系统．对19例临床诊断为急性脑梗死的患者行扩散加权磁共振成像(MRI—DWI)，并与常规MRI结果比较，其中男11例，女8例，年龄35～70岁，平均年龄52．5岁。结果：19例患者中，MRI—DWI在发病6h以内提示急性脑梗死者17例，DWI和常规MRl的敏感性分别为100％和5．88％，其特异性均为100％，2例排除了脑梗死。结论：扩散加权磁共振成像对6h以内发病的急性脑梗死的诊断明显高于常规MRI，并对脑梗死的临床治疗有指导意义。     

扩散加权成像（DWI）在肝硬化后脾脏增大的研究

目的探讨扩散加权成像ADC值在正常脾脏与肝硬化后脾肿大间的差异。方法对12例正常志愿者及20例肝硬化脾肿大者行常规MRI平扫及扩散加权成像检查。结果正常脾脏平均ADC值为1.45×10-3mm2/s,肿大脾平均ADC值为1.49×10-3mm2/s。结论正常脾脏与肝硬化后脾肿大的ADC值间无统计学差异。     

扩散加权成像(DWI)在肝硬化后脾脏增大的研究

目的探讨扩散加权成像ADC值在正常脾脏与肝硬化后脾肿大间的差异.方法对12例正常志愿者及20例肝硬化脾肿大者行常规MRI平扫及扩散加权成像检查.结果正常脾脏平均ADC值为1.45×10-3mm2/s,肿大脾平均ADC值为1.49×10-3mm2/s.结论正常脾脏与肝硬化后脾肿大的ADC值间无统计学差异.     

扩散张量MR成像研究

本文一方面综述了8年来国际上扩散张量磁共振成像(DTI)的研究进展情况。包括总结了到目前为止所使用的4种提高DTI成像精度的方法，并指出精度的提高依赖于成像中脉冲序列的优化、实验方法的完善和后处理算法两个方面。文中比较了目前研究扩散张量的两种基本模型：扩散张量模型和q-空间模型。指出这两种模型侧重应用于不同的场合。前者侧重于研究器官或宏观组织中的扩散，而后者侧重于研究小到细胞尺度(μm量级)的扩散行为。两者在应用研究方面是互补的，所要求的实验条件是有差别的。另一方面结合文献对扩散张量模型的实验条件进行了理论分析。认为b因子取得过高并不合理。并用DTI实验数据和结果进行了初步验证。为了改进扩散张量模型本文探讨了考虑多指数衰减的设想。文中综述了DTI的导出量和一些实验结果，在此基础上分析了设计和优化各向异性指标(DAI)的原则。对于DTI的重要导出结果神经纤维柬成像(fiber tractography)重点分析了造成其成像精度不高的主要因素，指出了改进纤维束传导方向甄选算法和寻求纤维束方向场的几何性质是两种可能的解决办法。     

定量MRI新技术在腰椎间盘退行性变评价中研究进展

早期发现腰椎间盘退行性变,并对退行性变程度进行准确评价,对腰腿痛的预防、治疗有重要价值.定量MRI技术具有无创性定量评估的功能,在椎间盘退行性变评价中具有其他影像技术无可比拟的优势,包括扩散张量成像(DTI)、扩散峰度成像(DKI)、T2 mapping、T2*mapping、旋转坐标系下的自旋-晶格弛豫时间(T1ρ)...     

MRI常规扫描联合DWI技术对慢性肾脏病的评估分析

目的:分析磁共振(Magnetic resonance imaging,MRI)常规扫描联合扩散加权成像(Diffusion weighted imaging,DWI)评估慢性肾脏病(Chronic kidney disease,CKD)的价值.方法:选取2019年4月至2021年4月医院收治的80例CKD患者及40例...     

扩散时间及扩散梯度磁场对水分子表观扩散系数的影响

脉冲梯度自旋回波方法在磁共振扩散成像实验中得到广泛应用,扩散时间和扩散梯度磁场强度是脉冲梯度自旋回波方法中两个重要的参数.扩散时间对结果的影响在前人所作研究报告中存在争议, 扩散梯度磁场强度对结果的影响没有被重视.本研究用新的试验方法研究这两个参数对表观扩散系数的影响.结果显示,延长扩散时间或增加扩散梯度磁场强度均会使表观扩散系数值下降,原有理论不能解释此结果.通过理论分析,我们发现脉冲梯度自旋回波方法本身的一个缺陷, 并找到已发表文献中出现争议的原因.     

人脑扩散MR参考图像研究

本文阐述了扩散-MRI，扩散张量成像（DTI）的原理以及平均扩散率D-map的导出关系，由于不同人脑大小，形态，结构跟人体相貌有差异一样也存在大小的差异。本文对七个健康志愿者的脑D-map进行了归一化处理，之后利用基于小波金子塔的图像配准，融合方法把七个人脑D-map配准后融合在一起，导出有统计意义的参数图像，为将来计算机自动认读图像，辅助诊断铺平道路，理论，算法，实验都已取得初步成功并给出了实验结果，只是需要进一步提高精度，提高信噪比。     

磁共振扩散张量成像扩散椭球面积的简化计算方法

目的:提出一种可以精确计算磁共振扩散张量成像扩散椭球表面积的方法。方法:根据理想扩散椭球是旋转椭球及扩散张量矩阵均正定,可将三轴椭球校正为旋转椭球,进而由A.M.Legendre公式推出计算扩散椭球表面积的简化公式。分别利用A.M.Legendre、Knud Thomsen及本文提出的方法计算四种扩散椭球的表面积以评价本文方法的可行性。结果:对于旋转椭球,本文所提方法的计算结果与A.M.Legendre方法的结果一致。结论:本文所提方法计算量较小,可以精确地计算扩散椭球表面积。     

基于机器学习方法的前列腺癌DWI多参数分析及其应用

探究使用机器学习方法,提升对扩散加权成像(DWI)多参数图的前列腺癌(PCa)诊断的准确性。对39例前列腺癌患者、56例良性患者,进行磁共振扩散加权图像的采集,并使用传统单指数模型(Mono)、拉伸指数模型(SEM)、弥散张量成像(DTI)模型、弥散峰度成像(DKI)模型以及体内素不相干运动扩散(IVIM)模型等5种重建模型,得到共计16个参数图,而后对于每一个参数图进行直方图分析,得到相关图像特征后使用机器学习的方法进行分类。 使用支持向量机和随机森林两种分类器对前列腺病变进行良恶性分类,随机森林分类器的AUC值可以达到0.98,具有较高的分类性能。另外,对特征进行重要性排序后,发现DKI参数图是肿瘤分类的重要指标。     

Acute renal impairment characterization using diffusion magnetic resonance imaging: Validation by histology

Diffusion magnetic resonance imaging has been demonstrated to be a simple, noninvasive and accurate method for the detection of renal microstructure and microcirculation, which are closely linked to renal function. Moreover, serum endothelin‐1 (ET‐1) was also reported as a good indicator of early renal injury. The aim of this study was to evaluate the feasibility and capability of diffusion MRI and ET‐1 to detect acute kidney injury by an operation simulating high‐pressure renal pelvic perfusion, which is commonly used during ureteroscopic lithotripsy. Histological findings were used as a reference. Fourteen New Zealand rabbits in an experimental group and 14 in a control group were used in this study. Diffusion tensor imaging and intravoxel incoherent motion diffusion‐weighted imaging were acquired by a 3.0 T MRI scanner. Significant corticomedullary differences were found in the values of the apparent diffusion coefficient (ADC), pure tissue diffusion, volume fraction of pseudo‐diffusion (fp) and fractional anisotropy (FA) (P < 0.05 for all) in both preoperation and postoperation experimental groups. Compared with the control group, the values of cortical fp_mean, medullary ADC_mean and FA_mean decreased significantly (P < 0.05) after the operation in the experimental group. Also, the change rate of medullary ADC_mean in the experimental group was more pronounced than that in the control group (P = 0.018). No significant change was found in serum ET‐1 concentration after surgery in either the experimental (P = 0.80) or control (P = 0.17) groups. In the experimental group, histological changes were observed in the medulla, while no visible change was found in the cortex. This study demonstrated the feasibility of diffusion MRI to detect the changes of renal microstructure and microcirculation in acute kidney injury, with the potential to evaluate renal function. Moreover, the sensitivity of diffusion MRI to acute kidney injury appears to be superior to that of serum ET‐1.     

Diffusion‐weighted MRI measurements on stroke patients reveal water‐exchange mechanisms in sub‐acute ischaemic lesions

The aim of this study was to investigate the diffusion time dependence of signal‐versus‐b curves obtained from diffusion‐weighted magnetic resonance imaging (DW‐MRI) of sub‐acute ischaemic lesions in stroke patients. In this case series study, 16 patients with sub‐acute ischaemic stroke were examined with DW‐MRI using two different diffusion times (60 and 260 ms). Nine of these patients showed sufficiently large lesions without artefacts to merit further analysis. The signal‐versus‐b curves from the lesions were plotted and analysed using a two‐compartment model including compartmental exchange. To validate the model and to aid the interpretation of the estimated model parameters, Monte Carlo simulations were performed. In eight cases, the plotted signal‐versus‐b curves, obtained from the lesions, showed a signal–curve split‐up when data for the two diffusion times were compared, revealing effects of compartmental water exchange. For one of the patients, parametric maps were generated based on the extracted model parameters. These novel observations suggest that water exchange between different water pools is measurable and thus potentially useful for clinical assessment. The information can improve the understanding of the relationship between the DW‐MRI signal intensity and the microstructural properties of the lesions. Copyright © 2009 John Wiley & Sons, Ltd.     

High angular resolution diffusion imaging with stimulated echoes: compensation and correction in experiment design and analysis

Stimulated echo acquisition mode (STEAM) diffusion MRI can be advantageous over pulsed‐gradient spin‐echo (PGSE) for diffusion times that are long compared with T₂. It therefore has potential for biomedical diffusion imaging applications at 7T and above where T₂ is short. However, gradient pulses other than the diffusion gradients in the STEAM sequence contribute much greater diffusion weighting than in PGSE and lead to a disrupted experimental design. Here, we introduce a simple compensation to the STEAM acquisition that avoids the orientational bias and disrupted experiment design that these gradient pulses can otherwise produce. The compensation is simple to implement by adjusting the gradient vectors in the diffusion pulses of the STEAM sequence, so that the net effective gradient vector including contributions from diffusion and other gradient pulses is as the experiment intends. High angular resolution diffusion imaging (HARDI) data were acquired with and without the proposed compensation. The data were processed to derive standard diffusion tensor imaging (DTI) maps, which highlight the need for the compensation. Ignoring the other gradient pulses, a bias in DTI parameters from STEAM acquisition is found, due both to confounds in the analysis and the experiment design. Retrospectively correcting the analysis with a calculation of the full B matrix can partly correct for these confounds, but an acquisition that is compensated as proposed is needed to remove the effect entirely. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd.     

Comparison of basis functions and q‐space sampling schemes for robust compressed sensing reconstruction accelerating diffusion spectrum imaging

Time constraints placed on magnetic resonance imaging often restrict the application of advanced diffusion MRI (dMRI) protocols in clinical practice and in high throughput research studies. Therefore, acquisition strategies for accelerated dMRI have been investigated to allow for the collection of versatile and high quality imaging data, even if stringent scan time limits are imposed. Diffusion spectrum imaging (DSI), an advanced acquisition strategy that allows for a high resolution of intra‐voxel microstructure, can be sufficiently accelerated by means of compressed sensing (CS) theory. CS theory describes a framework for the efficient collection of fewer samples of a data set than conventionally required followed by robust reconstruction to recover the full data set from sparse measurements. For an accurate recovery of DSI data, a suitable acquisition scheme for sparse q‐space sampling and the sensing and sparsifying bases for CS reconstruction need to be selected. In this work we explore three different types of q‐space undersampling schemes and two frameworks for CS reconstruction based on either Fourier or SHORE basis functions. After CS recovery, diffusion and microstructural parameters and orientational information are estimated from the reconstructed data by means of state‐of‐the‐art processing techniques for dMRI analysis. By means of simulation, diffusion phantom and in vivo DSI data, an isotropic distribution of q‐space samples was found to be optimal for sparse DSI. The CS reconstruction results indicate superior performance of Fourier‐based CS‐DSI compared to the SHORE‐based approach. Based on these findings we outline an experimental design for accelerated DSI and robust CS reconstruction of the sparse measurements that is suitable for the application within time‐limited studies.     

磁共振扩散峰度成像研究进展及新应用

扩散峰度成像(DKI)是一种新兴的扩散磁共振技术,它在传统扩散张量成像的基础上引入了四阶峰度,并以此量化组织中水分子扩散位移概率分布偏离高斯分布的程度,其附加的峰度信息对大脑组织的微观结构更敏感。从扩散峰度成像模型、数据采集参数、模型拟合以及由DKI发展而来的微观结构模型等方面,介绍DKI模型的研究进展和临床应用。最后简要讨论DKI模型存在的问题,并展望其在神经放射学各个方面所具有的广泛深远影响。     

Investigation of field and diffusion time dependence of the diffusion‐weighted signal at ultrahigh magnetic fields

Over the last decade, there has been a significant increase in the number of high‐magnetic‐field MRI magnets. However, the exact effect of a high magnetic field strength (B₀) on diffusion‐weighted MR signals is not yet fully understood. The goal of this study was to investigate the influence of different high magnetic field strengths (9.4 T and 14.1 T) and diffusion times (9, 11, 13, 15, 17 and 24 ms) on the diffusion‐weighted signal in rat brain white matter. At a short diffusion time (9 ms), fractional anisotropy values were found to be lower at 14.1 T than at 9.4 T, but this difference disappeared at longer diffusion times. A simple two‐pool model was used to explain these findings. The model describes the white matter as a first hindered compartment (often associated with the extra‐axonal space), characterized by a faster orthogonal diffusion and a lower fractional anisotropy, and a second restricted compartment (often associated with the intra‐axonal space), characterized by a slower orthogonal diffusion (i.e. orthogonal to the axon direction) and a higher fractional anisotropy. Apparent T₂ relaxation time measurements of the hindered and restricted pools were performed. The shortening of the pseudo‐T₂ value from the restricted compartment with B₀ is likely to be more pronounced than the apparent T₂ changes in the hindered compartment. This study suggests that the observed differences in diffusion tensor imaging parameters between the two magnetic field strengths at short diffusion time may be related to differences in the apparent T₂ values between the pools. Copyright © 2013 John Wiley & Sons, Ltd.     

Reliable estimation of brain intravoxel incoherent motion parameters using denoised diffusion‐weighted MRI

In this study, we evaluate whether diffusion‐weighted magnetic resonance imaging (DW‐MRI) data after denoising can provide a reliable estimation of brain intravoxel incoherent motion (IVIM) perfusion parameters. Brain DW‐MRI was performed in five healthy volunteers on a 3 T clinical scanner with 12 different b‐values ranging from 0 to 1000 s/mm². DW‐MRI data denoised using the proposed method were fitted with a biexponential model to extract perfusion fraction (PF), diffusion coefficient (D) and pseudo‐diffusion coefficient (D*). To further evaluate the accuracy and precision of parameter estimation, IVIM parametric images obtained from one volunteer were used to resimulate the DW‐MRI data using the biexponential model with the same b‐values. Rician noise was added to generate DW‐MRI data with various signal‐to‐noise ratio (SNR) levels. The experimental results showed that the denoised DW‐MRI data yielded precise estimates for all IVIM parameters. We also found that IVIM parameters were significantly different between gray matter and white matter (P < 0.05), except for D* (P = 0.6). Our simulation results show that the proposed image denoising method displays good performance in estimating IVIM parameters (both bias and coefficient of variation were <12% for PF, D and D*) in the presence of different levels of simulated Rician noise (SNR_b=0 = 20‐40). Simulations and experiments show that brain DW‐MRI data after denoising can provide a reliable estimation of IVIM parameters.     

利用3.0T磁共振观察子宫恶性肿瘤组织弥散效应的初步研究

目的： 利用磁共振成像（MRI）的弥散加权成像（DWI）技术,观察子宫恶性肿瘤的弥散受限程度。方法: 采用3.0 T磁共振成像仪,对子宫颈癌病例及正常子宫颈对照组、子宫内膜癌病例及正常子宫内膜对照组进行常规MRI及DWI扫描,测量其表观弥散系数（ADC）,并对子宫颈癌与正常子宫颈、子宫内膜癌与正常子宫内膜的ADC值进行统计学分析。结果: (1)37例子宫颈癌和16例正常子宫颈的ADC值分别为（0.92±0.20）×10-3 mm2/s和（1.26±0.24）×10-3 mm2/s,子宫颈癌和正常子宫颈2组ADC值比较有显著差异（P<0.01）。(2)14例子宫内膜癌和14例正常子宫内膜的ADC值分别为（0.87±0.17）×10-3 mm2/s和 （1.34±0.26）×10-3 mm2/s,子宫内膜癌和正常子宫内膜2组ADC值比较有显著差异（P<0.01）。结论: 子宫颈癌和子宫内膜癌较正常子宫组织弥散受限,3.0T磁共振DWI的ADC值测量能够定量反映子宫恶性肿瘤的弥散受限程度。     

Fast and accurate initialization of the free‐water imaging model parameters from multi‐shell diffusion MRI

Cerebrospinal fluid partial volume effect is a known bias in the estimation of Diffusion Tensor Imaging (DTI) parameters from diffusion MRI data. The Free‐Water Imaging model for diffusion MRI data adds a second compartment to the DTI model, which explicitly accounts for the signal contribution of extracellular free‐water, such as cerebrospinal fluid. As a result the DTI parameters obtained through the free‐water model are corrected for partial volume effects, and thus better represent tissue microstructure. In addition, the model estimates the fractional volume of free‐water, and can be used to monitor changes in the extracellular space. Under certain assumptions, the model can be estimated from single‐shell diffusion MRI data. However, by using data from multi‐shell diffusion acquisitions, these assumptions can be relaxed, and the fit becomes more robust. Nevertheless, fitting the model to multi‐shell data requires high computational cost, with a non‐linear iterative minimization, which has to be initialized close enough to the global minimum to avoid local minima and to robustly estimate the model parameters. Here we investigate the properties of the main initialization approaches that are currently being used, and suggest new fast approaches to improve the initial estimates of the model parameters. We show that our proposed approaches provide a fast and accurate initial approximation of the model parameters, which is very close to the final solution. We demonstrate that the proposed initializations improve the final outcome of non‐linear model fitting.     

Water diffusion in the different microenvironments of breast cancer

The parameters that characterize the intricate water diffusion in tumors may serve to reveal their distinct pathology. Specifically, the application of diffusion magnetic resonance imaging (MRI) can aid in characterizing breast cancer, as well as monitoring response to therapy. We present here a non-invasive, quantitative MRI investigation, at high spatial resolution, of water diffusion in hormonal dependent MCF7 breast tumors implanted orthotopically in immunodeficient mice. Distinctive MRI protocols were designed in this study, utilizing a broad range of diffusion times and diffusion gradient strengths. Application of these protocols allowed water diffusion in the tissue extracellular and intracellular compartments to be distinguished, and the effect of restricted diffusion and water exchange on the water diffusion in these compartments to be evaluated. Pixel-by-pixel analysis yielded parametric maps of the estimated volume fraction and apparent diffusion coefficient of each compartment. The diffusion of the water in the extracellular microenvironment was approximately two fold slower than that of free water, and in the intracellular compartment was about one order of magnitude slower than that of free water and demonstrated restriction of water diffusion at long diffusion times. Mapping of the water fraction in each compartment was further employed to monitor changes during tumor progression and to assess tumor response to hormonal manipulation with a new antiestrogenic drug, tamoxifen methiodide (TMI). It was found that, in parallel to the growth arrest by this drug, the volume fraction of the slowly diffusing water increased, suggesting a TMI-induced cell swelling. This study can serve as a basis for extending diffusion breast MRI in the clinical setting.