扩散峰度成像在预测直肠癌KRAS基因突变中的应用价值

目的 探讨扩散峰度成像(DKI)定量参数在预测直肠癌KRAS基因突变中的应用价值。方法 回顾性分析山西省肿瘤医院2016年11月-2018年6月经病理证实的152例直肠腺癌患者的资料,其中男92例,女60例;年龄33～86岁,平均61岁。患者均于术前行常规MRI和功能DKI序列检查,由2名放射科医师双盲勾画感兴趣区,应用MatLab软件计算两组患者DKI定量参数平均表观扩散系数(MD)、平均峰度(MK)以及表观扩散系数(ADC),并采用组内相关系数进行一致性分析。术后均进行KRAS基因检测,依据检测结果将患者分为野生组和突变组两组,采用独立样本t检验对比两组患者的MD、MK、ADC。绘制DKI定量参数诊断KRAS基因突变的受试者工作特征曲线(ROC) ,根据约登指数确定各定量参数的最佳诊断阈值,以及相应的灵敏度、特异度,并采用DeLong检验比较各定量参数的ROC的曲线下面积(AUC)。结果 152例直肠癌患者中,KRAS基因突变组74例,野生组78例,基因突变率为48.6%(74/152)。突变组患者的ADC、MD、MK值分别为(1.18±0.18)×10^-3 mm²/s、(1.28±0.18)×10^-3 mm²/s、0.97±0.11,野生组分别为(1.33±0.18)×10^-3 mm²/s、(1.42±0.17)×10^-3 mm²/s、0.82±0.09;突变组ADC、MD值均小于野生组患者,而MK值则大于野生组患者,差异均有统计学意义(t=5.424、4.882、-8.809, P值均＜0.01)。ROC曲线显示,ADC、MD、和MK值预测KRAS基因的AUC分别为0.758、0.740、0.845,灵敏度分别为75.7%、82.4%、77.0%,特异度分别为68.0%、57.8%、84.6%。DeLong检验结果显示,MK值的AUC明显高于ADC和MD值(P值均＜0.01),而ADC值和MD值间AUC差异无统计学意义(P＞0.05)。结论 DKI定量参数MD、MK和ADC值,在预测直肠癌的KRAS基因突变方面均有一定的价值,其中MK值有更高的AUC和特异度,有更高的诊断价值。     

基于扩散磁共振的脑组织微结构成像研究综述

微结构成像是为了改善传统扩散磁共振成像的一些缺点而发展的一种新技术.微结构成像范式旨在建立组织结构特性与体素级磁共振信号相联系的模型,以此来估计并绘制微结构属性.目前该技术正在实现从实验室研究到临床应用研究的转变.首先介绍扩散磁共振成像并分析传统技术存在的主要问题,然后阐述微结构成像原理;随后,对受阻与受限制复合扩散模...     

核磁共振弥散峰度成像在脑中风诊断中的应用

目的 研究弥散峰度成像(DKI)对脑组织灰质和白质的描述以及在脑中风诊断中的应用.方法 采用2例正常人以及15例脑中风患者(包含9例脑梗死,急性、亚急性和陈旧性各占3例)的脑部核磁共振图像作为试验数据.针对每例数据各个像素位置,分别对9个不同弥散梯度场下各个信号强度进行非线性拟合得到弥散系数(D值)和弥散峰度(K值),进而做出ADC图和DKI图.观察比较分析各例在ADC图和DKI图的表现.结果 DKI成像具有更多的纹理细节,包含更丰富的组织特征.急性、亚急性脑梗死病灶在DKI图呈现高信号,陈旧性脑梗死病灶在DKI图呈现低信号,平均峰度相对值(rMK)分别为2.193±0.166,1.789±0.162,0.564±0.069.结论 DKI对脑组织尤其是灰质以及一些脑中风病灶的描述相对于ADC图包含更多的组织信息.脑梗死病灶的rMK值具有特征性演变规律.     

一种新的磁共振扩散成像实验参数控制方法

扩散敏感梯度磁度的方向及强度是磁共振扩散成像实验的重要参数，但这二个参数不能由用户通过设备自带的软件设定。本文介绍一种新的方法，通过修改MRI扫描机内部的数据文件，用户可以方便与精确地设定扩散加权成像DWI及扩散张景成像DTI的实验参数，而且可以为MRI扫描机增加新的功能。     

磁共振扩散张量成像的可视化方法研究进展

磁共振扩散张量成像(DT-MRI)与传统的扩散加权成像(DWI)相比能够更加准确地反映分子扩散的方向.大脑白质区的水分子扩散表现出显著的各向异性,因而DT-MRI技术在显示白质神经纤维和功能束的走行方向以及三维形态等方面具有极大的优越性.主要介绍了该技术的基本原理及目前常用的数据集可视化的方法.     

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。     

弥散峰度成像与直肠癌临床病理预后因素的相关性研究

目的 探讨弥散峰度成像(DKI)定量参数和表观扩散系数(ADC)与直肠癌临床病理预后因素之间的潜在关系,为临床预测评估直肠癌的恶性程度提供一定的参考依据。方法 对2016年11月—2017年4月山西省肿瘤医院122例术前行MRI检查的直肠腺癌患者的影像和临床资料进行回顾性分析,其中女48例(39.3%)、男74例 (60.7%),年龄42~81岁。利用相关软件测得平均表观扩散系数(MD)、平均峰度(MK)和ADC值,通过独立样本t检验或Mann-Whitney U检验、ROC曲线和Spearman相关性分析进行统计学分析。结果 直肠癌高T分期及淋巴结转移与低MD值(r=-0.367、-0.240)和低ADC值(r=-0.391、-0.254)相关,不同分组间差异均有统计学意义(P值均＜0.05);同样,不同组织病理学分级的MD值之间差异亦有统计学意义(P＜0.05)且呈负相关(r=-0.210, P＜0.05);随着组织病理学分级的升高、淋巴结受累、瘤周血管浸润(LVI)或神经侵犯及环周切缘(CRM)受侵,MK值相应增大,差异均有统计学意义(P值均＜0.05)呈正相关(r=0.478、0.206、0.237、0.228, P值均＜0.05)。MD、MK和ADC值均与淋巴结转移有相关(P值均＜0.01)性;ROC曲线显示MK值较其他参数在诊断淋巴结转移与否的曲线下面积高为0.784(95%CI 0.703~0.865),当其阈值取0.984时,具有较高的敏感度及特异度,分别为65.9%和88.7%。结论直肠癌DKI定量参数值和ADC值,尤其MK值,与其重要的临床病理预后因素均有明显相关性,对于预测直肠癌患者预后有一定意义。     

基于参考图像的压缩感知磁共振扩散张量成像

基于参考图像的压缩感知磁共振扩散张量成像方法,利用相邻方向的扩散加权图像差异较小的特点,采用压缩感知理论实现快速扩散张量成像,回顾性选取扩散张量图像数据进行实验研究,在采样率为50%的均匀分布辐射线欠采样方式下进行基于参考图像的压缩感知扩散张量图像重建,结果表明重建后的扩散加权图的平均结构相似性（MSSIM）和峰值信噪比（PSNR）分别为0.904±0.044、（37.92±3.89） dB,各向异性分数图的MSSIM和PSNR分别为0.992、41.64 dB。因此,该方法在保证重建图像质量的前提下,可显著缩短数据采集时间,减少由于时间过长引起的图像伪影等问题。     

健康儿童颈髓磁共振扩散张量成像

目的 应用扩散张量成像技术研究儿童颈髓发育规律。方法 使用单次激发自旋回波平面回波序列对90例健康儿童行颈髓扩散张量成像。在颈髓节段分别测量其表观扩散系数值（ADC）、各向异性分数值（FA）、纤维束平均长度（Ltract）以及纤维束体积（Vtract）。结果 各组的ADC值、FA值、Ltract及Vtract分别如下：0.9747±0.2777、0.8493±0.2236、0.8210±0.1432、0.9198±0.1444、0.9048±0.1676;0.4117±0.0391、0.4712±0.0199、0.4944±0.0439、0.5608±0.0443、0.6169±0.0551;25.61±8.63、24.66±7.14、27.03±7.23、34.93±10.99、37.63±10.22;3.07±1.49、3.00±1.52、3.81±1.33、5.41±2.35、6.64±2.84。各年龄组的FA值、Ltract和Vtract不完全相同（P<0.001）,而ADC值各年龄组的均值差异无统计学意义（F=1.758, P=0.145）。在组间的两两比较中：1、2组间FA值差异具有统计学意义;3、4组间FA值、Ltract和Vtract差异均具有统计学意义;4、5组间FA值差异具有统计学意义。FA值、Ltract和Vtract与年龄呈正相关。
结论 儿童颈髓发育具有阶段性,且具有阶段性特征;磁共振扩散张量技术可用于观测儿童颈髓并评价其发育。     

Validation of fast diffusion kurtosis MRI for imaging acute ischemia in a rodent model of stroke

Diffusion‐weighted imaging (DWI) captures ischemic tissue that is likely to infarct, and has become one of the most widely used acute stroke imaging techniques. Diffusion kurtosis imaging (DKI) has lately been postulated as a complementary MRI method to stratify the heterogeneously damaged DWI lesion. However, the conventional DKI acquisition time is relatively long, limiting its use in the acute stroke setting. Recently, a fast kurtosis mapping method has been demonstrated in fixed brains and control subjects. The fast DKI approach provides mean diffusion and kurtosis measurements under substantially reduced scan time, making it amenable to acute stroke imaging. Because it is not practical to obtain and compare different means of DKI to test whether the fast DKI method can reliably detect diffusion and kurtosis lesions in acute stroke patients, our study investigated its diagnostic value using an animal model of acute stroke, a critical step before fast DKI acquisition can be routinely applied in the acute stroke setting. We found significant correlation, per voxel, between the diffusion and kurtosis coefficients measured using the fast and conventional DKI protocols. In acute stroke rats, the two DKI methods yielded diffusion and kurtosis lesions that were in good agreement. Importantly, substantial kurtosis–diffusion lesion mismatch was observed using the conventional (26 ± 13%, P < 0.01) and fast DKI methods (23 ± 8%, P < 0.01). In addition, regression analysis showed that the kurtosis–diffusion lesion mismatches obtained using conventional and fast DKI methods were substantially correlated (R² = 0.57, P = 0.02). Our results confirmed that the recently proposed fast DKI method is capable of capturing heterogeneous diffusion and kurtosis lesions in acute ischemic stroke, and thus is suitable for translational applications in the acute stroke clinical setting. Copyright © 2014 John Wiley & Sons, Ltd.     

磁共振弥散张量成像的脑白质纤维优化重建

磁共振弥散张量成像(DTI)可对大脑白质纤维束的三维几何结构进行无创研究,其主要方法为DTI纤维追踪成像.研究打破现有DTI纤维追踪成像从初始种子区域逐步追踪增长的框架,提出脑白质的纤维优化重建方法,从全局角度描述追踪纤维,通过其对弥散倾向和几何结构的优化估计,重构最优纤维路径.结果表明,该方法可提供连接两个感兴趣区域(ROI)的有效和对称连接,同时通过全局优化手段消除累积噪声及局部随机噪声,提高长距离成像的可靠性;在人工合成数据集和真实人体数据集中均能较好成像,较之现有纤维追踪成像具有更高的可靠性和可重复性.     

Fast diffusion kurtosis imaging (DKI) with Inherent COrrelation‐based Normalization (ICON) enhances automatic segmentation of heterogeneous diffusion MRI lesion in acute stroke

Diffusion kurtosis imaging (DKI) has been shown to augment diffusion‐weighted imaging (DWI) for the definition of irreversible ischemic injury. However, the complexity of cerebral structure/composition makes the kurtosis map heterogeneous, limiting the specificity of kurtosis hyperintensity to acute ischemia. We propose an Inherent COrrelation‐based Normalization (ICON) analysis to suppress the intrinsic kurtosis heterogeneity for improved characterization of heterogeneous ischemic tissue injury. Fast DKI and relaxation measurements were performed on normal (n = 10) and stroke rats following middle cerebral artery occlusion (MCAO) (n = 20). We evaluated the correlations between mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) derived from the fast DKI sequence and relaxation rates R₁ and R₂, and found a highly significant correlation between MK and R₁ (p < 0.001). We showed that ICON analysis suppressed the intrinsic kurtosis heterogeneity in normal cerebral tissue, enabling automated tissue segmentation in an animal stroke model. We found significantly different kurtosis and diffusivity lesion volumes: 147 ± 59 and 180 ± 66 mm³, respectively (p = 0.003, paired t‐test). The ratio of kurtosis to diffusivity lesion volume was 84% ± 19% (p < 0.001, one‐sample t‐test). We found that relaxation‐normalized MK (RNMK), but not MD, values were significantly different between kurtosis and diffusivity lesions (p < 0.001, analysis of variance). Our study showed that fast DKI with ICON analysis provides a promising means of demarcation of heterogeneous DWI stroke lesions.     

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。     

Diffusional kurtosis imaging and white matter microstructure modeling in a clinical study of major depressive disorder

Major depressive disorder (MDD) is a globally prevalent psychiatric disorder that results from disruption of multiple neural circuits involved in emotional regulation. Although previous studies using diffusion tensor imaging (DTI) found smaller values of fractional anisotropy (FA) in the white matter, predominantly in the frontal lobe, of patients with MDD, studies using diffusion kurtosis imaging (DKI) are scarce. Here, we used DKI whole‐brain analysis with tract‐based spatial statistics (TBSS) to investigate the brain microstructural abnormalities in MDD. Twenty‐six patients with MDD and 42 age‐ and sex‐matched control subjects were enrolled. To investigate the microstructural pathology underlying the observations in DKI, a compartment model analysis was conducted focusing on the corpus callosum. In TBSS, the patients with MDD showed significantly smaller values of FA in the genu and frontal portion of the body of the corpus callosum. The patients also had smaller values of mean kurtosis (MK) and radial kurtosis (RK), but MK and RK abnormalities were distributed more widely compared with FA, predominantly in the frontal lobe but also in the parietal, occipital, and temporal lobes. Within the callosum, the regions with smaller MK and RK were located more posteriorly than the region with smaller FA. Model analysis suggested significantly smaller values of intra‐neurite signal fraction in the body of the callosum and greater fiber dispersion in the genu, which were compatible with the existing literature of white matter pathology in MDD. Our results show that DKI is capable of demonstrating microstructural alterations in the brains of patients with MDD that cannot be fully depicted by conventional DTI. Though the issues of model validation and parameter estimation still remain, it is suggested that diffusion MRI combined with a biophysical model is a promising approach for investigation of the pathophysiology of MDD.     

基于弥散张量成像的儿童失神癫痫认知控制网络的结构连接研究

已有研究表明儿童失神癫痫患者的认知控制网络（CCN）中功能连接发生了改变。为了探索这些改变相应的结构基础,采用基于弥散张量成像（DTI）的纤维束追踪技术,对9名儿童失神癫痫患者和12名正常对照,分别构建了每个人CCN网络的结构连接,然后对两组间的纤维束连接的条数、长度、连接强度、平均部分各向异性值（FA）和平均弥散度（MD）等参数使用双样本T检验进行了统计比较。结果发现患者组CCN网络中主要纤维束上平均FA值显著降低,MD值显著增加（P_s<0.05,Bonferroni 校正）,并且左侧前额叶皮层到丘脑的纤维束上平均FA值与病程呈显著的负相关关系（P=0.011）。本研究结果为儿童失神癫痫患者CCN网络的功能连接异常提供了相应的结构基础,这些白质纤维异常的连接可能是导致患者认知控制功能异常的重要原因之一。