User‐independent diffusion tensor imaging analysis pipelines in a rat model presenting ventriculomegalia: A comparison study

Automated analysis of diffusion tensor imaging (DTI) data is an appealing way to process large datasets in an unbiased manner. However, automation can sometimes be linked to a lack of interpretability. Two whole‐brain, automated and voxelwise methods exist: voxel‐based analysis (VBA) and tract‐based spatial statistics (TBSS). In VBA, the amount of smoothing has been shown to influence the results. TBSS is free of this step, but a projection procedure is introduced to correct for residual misalignments. This projection assigns the local highest fractional anisotropy (FA) value to the mean FA skeleton, which represents white matter tract centers. For both methods, the normalization procedure has a major impact. These issues are well documented in humans but, to our knowledge, not in rodents. In this study, we assessed the quality of three different registration algorithms (ANTs SyN, DTI‐TK and FNIRT) using study‐specific templates and their impact on automated analysis methods (VBA and TBSS) in a rat pup model of diffuse white matter injury presenting large unilateral deformations. VBA and TBSS results were stable and anatomically coherent across the three pipelines. For VBA, in regions around the large deformations, interpretability was limited because of the increased partial volume effect. With TBSS, two of the three pipelines found a significant decrease in axial diffusivity (AD) at the known injury site. These results demonstrate that automated voxelwise analyses can be used in an animal model with large deformations.     

Longitudinal diffusion tensor imaging in a rat brain glioma model

In order to investigate the properties of water motion within and around brain tumors as a function of tumor growth, longitudinal diffusion tensor imaging (DTI) was carried out in a rat brain glioma (C6) model. As tumors grew in size, significant anisotropy of water diffusion was seen both within and around the tumor. The tissue water surrounding the tumor exhibited high planar anisotropy, as opposed to the linear anisotropy normally seen in white matter, indicating that cells were experiencing stress in a direction normal to the tumor border. When tumors were sufficiently large, significant anisotropy was also seen within the tumor because of longer-range organization of cancer cells within the tumor borders. These findings have important implications for diffusion-weighted MRI experiments examining tumor growth and response to therapy. Copyright (c) 2008 John Wiley & Sons, Ltd.     

弥散张量磁共振成像的新进展

弥散张量磁共振成像技术是近年来出现的一项新技术,由于其对脑白质纤维具有高度敏感性以致在临床上的应用日益广泛,并为人体中枢神经系统的深入研究提供了有效的工具。     

Prognosis of cervical myelopathy based on diffusion tensor imaging with artificial intelligence methods

Diffusion tensor imaging (DTI) has been proposed for the prognosis of cervical myelopathy (CM), but the manual analysis of DTI features is complicated and time consuming. This study evaluated the potential of artificial intelligence (AI) methods in the analysis of DTI for the prognosis of CM. Seventy‐five patients who underwent surgical treatment for CM were recruited for DTI imaging and were divided into two groups based on their one‐year follow‐up recovery. The DTI features of fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity were extracted from DTI maps of all cervical levels. Conventional AI models using logistic regression (LR), k‐nearest neighbors (KNN), and a radial basis function kernel support vector machine (RBF‐SVM) were built using these DTI features. In addition, a deep learning model was applied to the DTI maps. Their performances were compared using 50 repeated 10‐fold cross‐validations. The accuracy of the classifications reached 74.2% ± 1.6% for LR, 85.6% ± 1.4% for KNN, 89.7% ± 1.6% for RBF‐SVM, and 59.2% ± 3.8% for the deep leaning model. The RBF‐SVM algorithm achieved the best accuracy, with sensitivity and specificity of 85.0% ± 3.4% and 92.4% ± 1.9% respectively. This finding indicates that AI methods are feasible and effective for DTI analysis for the prognosis of CM.     

Sex dimorphism in gray/white matter volume and diffusion tensor during normal aging

The purpose of this study is to elucidate sex differences in global and regional gray/white matter volume, mean diffusivity (MD), and fractional anisotropy (FA) during normal aging using voxel‐based analysis. We studied 245 healthy right‐handed subjects with a wide range of ages (115 women, 22–70 years; 130 men, 21–71 years). Regarding global effects, inclusion of a quadratic age term improved the fit to data for white matter fraction and MD, but not for global gray matter volume/fraction or FA. Regarding regional effects, we found anterior‐dominant volume loss, FA decrease predominantly in the anterior white matter, and MD increase predominantly in perisylvian regions and periventricular white matter against age for both sexes. Compared with women, we found a steeper FA decline for men in the right inferior fronto‐temporal areas, extending to the anterior cingulate cortex, and an accelerated MD increase for men in the bilateral frontal, temporal, and parietal areas. There was no area in which interaction of sex with age was significant for regional volume, or in which a steeper FA decline or accelerated MD increase for women was significant. Our results provide strong evidence of sex dimorphism in global and focal diffusion characteristics during normal aging. Copyright © 2010 John Wiley & Sons, Ltd.     

Supervised segmentation framework for evaluation of diffusion tensor imaging indices in skeletal muscle

Diffusion tensor imaging (DTI) is becoming a relevant diagnostic tool to understand muscle disease and map muscle recovery processes following physical activity or after injury. Segmenting all the individual leg muscles, necessary for quantification, is still a time‐consuming manual process. The purpose of this study was to evaluate the impact of a supervised semi‐automatic segmentation pipeline on the quantification of DTI indices in individual upper leg muscles. Longitudinally acquired MRI datasets (baseline, post‐marathon and follow‐up) of the upper legs of 11 subjects were used in this study. MR datasets consisted of a DTI and Dixon acquisition. Semi‐automatic segmentations for the upper leg muscles were performed using a transversal propagation approach developed by Ogier et al on the out‐of‐phase Dixon images at baseline. These segmentations were longitudinally propagated for the post‐marathon and follow‐up time points. Manual segmentations were performed on the water image of the Dixon for each of the time points. Dice similarity coefficients (DSCs) were calculated to compare the manual and semi‐automatic segmentations. Bland‐Altman and regression analyses were performed, to evaluate the impact of the two segmentation methods on mean diffusivity (MD), fractional anisotropy (FA) and the third eigenvalue (λ₃). The average DSC for all analyzed muscles over all time points was 0.92 ± 0.01, ranging between 0.48 and 0.99. Bland‐Altman analysis showed that the 95% limits of agreement for MD, FA and λ₃ ranged between 0.5% and 3.0% for the transversal propagation and between 0.7% and 3.0% for the longitudinal propagations. Similarly, regression analysis showed good correlation for MD, FA and λ₃ (r = 0.99, p < 60; 0.0001). In conclusion, the supervised semi‐automatic segmentation framework successfully quantified DTI indices in the upper‐leg muscles compared with manual segmentation while only requiring manual input of 30% of the slices, resulting in a threefold reduction in segmentation time.     

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.     

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.     

精神分裂症白质损害与发病年龄的弥散张量成像研究

目的:应用弥散张量成像(DTI)比较精神分裂症患者脑白质与正常人群间的差异,并探究各向异性比值(FA)的改变与发病年龄之间的相关性。方法:纳入27例精神分裂症患者和29名性别、年龄及受教育程度相匹配的健康对照。两组研究对象均接受头颅磁共振检测。患者组按照发病年龄分为早发组(发病年龄18岁)和成年发病组(发病年龄≥18岁)。采用基于体素的分析方法,分别比较患者组和对照组、早发组和成年发病组之间FA值的差异,并在控制性别、病程和药物剂量影响的前提下,分析FA值与患者发病年龄的相关性。结果:与健康对照比较,患者组在右侧上纵束、右侧放射冠上部的FA值降低;患者组中早发组和成年发病组间FA值的差异无显著性。患者组FA值与发病年龄呈正相关的脑区包括右侧放射冠前部(r=0.70,P0.01)、右侧胼胝体膝部(r=0.65,P0.01);未发现呈负相关的脑区。结论:本研究提示精神分裂症患者右侧脑区上纵束及放射冠部位存在白质损害,发病年龄愈早,右侧放射冠及胼胝体膝部白质纤维的受损愈重。这对精神分裂症病理生理改变及脑结构异常的进一步研究具有提示作用。     

皮层下缺血性血管性痴呆胼胝体的扩散张量成像研究

目的：应用扩散张量成像（DTI）技术探讨皮层下缺血性血管性痴呆（SIVD）病人胼胝体各项异性及平均扩散率变化特点及其与认知状态或其他临床表现的关系。方法：对SIVD病人34例及同期进行体检的健康老年人26例进行DTI扫描，测量胼胝体前部和后部FA值、PA值及平均ADC值，并对结果进行统计分析。结果：健康对照组及SIVD组胼胝体后部FA及PA均大于前部（P〈0．05）；SIVD组胼胝体前后部FA及PA值均明显下降，ADC值均明显增加；胼胝体前部ADC与MMSE评分成负相关，r=-0．361，P=0，036。结论：应用DTI可显示SIVD病人胼胝体完整性破坏，髓鞘和轴索的损伤和丢失。胼胝体的DTI的各参数变化有助于SIVD的早期预防及治疗，阻止或逆转认知下降。     

Bilateral substantia nigra and pyramidal tract changes following experimental intracerebral hemorrhage: an MR diffusion tensor imaging study

The amelioration of secondary neurological damage is among the most important therapeutic goals for patients with intracerebral hemorrhage (ICH). Secondary injury of the ipsilateral substantia nigra (SN) and pyramidal tract (PY) is common after cerebral stroke. Such injury has been characterized previously by anatomical or diffusion MRI, but not in a comprehensive manner, and the knowledge regarding the contralateral changes is relatively poor. This study examined longitudinally both contralateral and ipsilateral SN and PY changes following experimental ICH with diffusion tensor imaging (DTI) and histology. ICH was induced in 14 Sprague‐Dawley rats by the infusion of collagenase into the right striatum. Four‐shot, spin‐echo, echo‐planar DTI was performed at 7 T with a b value of 1000 s/mm² and 30 diffusion gradient directions at 3.5 h and days 1, 3, 7, 14, 42 and 120 after ICH. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ_//) and radial diffusivity (λ_┴) were measured in SN and PY accordingly. Two to three rats were sacrificed at days 3, 7, 42 and 120 for histology. The contralateral SN showed an increase in λ_// with perivascular enlargement during the first 3 days after ICH. The ipsilateral SN showed increases in FA, λ_//, λ_┴ and MD at day 1, dramatic decreases at day 3 with neuronal degeneration and neuropil vacuolation, and subsequent gradual normalization. The contralateral PY showed diffusivity decreases at day 1. The ipsilateral PY showed early decreases and then late increases in MD and λ_┴, and continuously decreasing FA and λ_// with progressive axonal loss and demyelination. In summary, DTI revealed early bilateral changes in SN and PY following ICH. The evolution of the ipsilateral parameters correlated with the histological findings. In the ipsilateral PY, λ_// and λ_┴ changes indicated evolving and complex pathological processes underlying the monotonic FA decrease. These results support the use of quantitative multiparametric DTI for the evaluation of SN and PY injuries in clinical and preclinical investigations of ICH. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatiotemporal changes in diffusion,T2 and susceptibility of white matter following mild traumatic brain injury

Impaired white matter integrity in traumatic brain injury (TBI) can lead to deficits in various neurological functions. The differentiation of the underlying pathological processes, e.g. edema, demyelination, axonal damage, to name a few, is of key clinical interest for the assessment of white matter injury. In this study, a combination of T₂, diffusion and susceptibility MRI was used to study the spatiotemporal changes in white matter at 1 h, 3 h, and 1, 2, 7 and 14 days following TBI, using a rat controlled cortical impact (CCI) model. Based on radial diffusivity (RD), the rats were divided into two groups: group 1 showed widespread increases in RD along the corpus callosum of the ipsilesional hemisphere at day 2, and group 2 showed normal RD. Based on this group separation, group 1 also showed similar widespread changes in fractional anisotropy (FA) and T₂ at day 2, and group 2 showed normal FA and T₂. The widespread changes in RD and T₂ in group 1 on day 2 were apparently dominated by edema, which obscured possible myelin and axonal damage. In contrast, the susceptibility of group 1 showed more localized increases near the impact site on day 2, and otherwise similar contrast to the contralesional hemisphere. The localized susceptibility increase is probably a result of demyelination and axonal injury. The extent of brain damage between the two groups revealed by MRI was consistent with behavioral results, with the first group showing significantly increased forelimb asymmetry and increased forelimb foot fault deficits. Our results suggest that the combination of T₂, diffusion and susceptibility MRI may provide an opportunity for the differential assessment of edema and axonal damage in TBI. Copyright © 2016 John Wiley & Sons, Ltd.     

应用DTI技术对人脑白质纤维束的初步研究

目的建立扩散张量纤维束成像对人脑白质纤维的显示方法,并应用中国数字化可视人体数据进行对照观察,验证扩散张量成像(DTI)方法的可靠性。方法选择5名健康志愿者进行DTI成像,采用DtiStudio软件进行分析处理,重建出部分各向异性(FA)图、容积比(VR)图、相对各向异性(RA)图、表面扩散系数(ADC)图以及二维彩色张量图。应用中国数字化可视人体数据集断面图像、FA图及彩色FA图进行对照观察,利用fibertracking纤维跟踪软件及3DMRI软件进行三维重建显示脑内主要白质纤维束,辨认脑内白质纤维束的位置、形态。结果应用DTI纤维束成像可以清晰准确地描绘脑白质内主要神经纤维束的解剖图谱,包括联络纤维如弓形纤维、钩束、扣带束、上纵束和下纵束,连合纤维如胼胝体、前连合和穹隆,投射纤维如锥体束、视放射、内侧丘系等。DTI纤维束成像结果与已知解剖知识、中国可视化人体断面图像具有很好的一致性。结论应用DTI纤维束成像可以清晰准确地描绘脑白质内主要神经纤维束的解剖图谱,其结果与中国可视化人体断面图像、已知解剖知识是一致的,应用DTI纤维束成像研究脑内纤维连通性是可靠的。     

Diffusion tensor imaging of white matter in the superior temporal gyrus and temporal stem in autism

Recent MRI studies have indicated that regions of the temporal lobe including the superior temporal gyrus (STG) and the temporal stem (TS) appear to be abnormal in autism. In this study, diffusion tensor imaging (DTI) measurements of white matter in the STG and the TS were compared in 43 autism and 34 control subjects. DTI measures of mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were compared between groups. In all regions, fractional anisotropy was significantly decreased and both mean diffusivity and radial diffusivity were significantly increased in the autism group. These results suggest that white matter microstructure in autism is abnormal in these temporal lobe regions, which is consistent with theories of aberrant brain connectivity in autism.     

应用弥散张量成像技术检测慢性原发性闭角型青光眼患者脑白质结构

目的 采用磁共振弥散张量成像(DTI)检测慢性闭角型青光眼(PACG)患者脑白质病变,用各向异性指数(FA)改变分析病变部位。方法 回顾性分析2008-2009年在天津医科大学总医院眼科就诊并行颅脑MRI检查患者的临床资料,其中确诊为慢性PACG并同时行DTI扫描的患者25例为慢性PACG组,根据视野损害程度分为轻度组和重度组;选取同一时间段行颅脑DTI扫描的健康人25例为正常对照组。采用FSL和DTIstudio软件处理原始数据得到FA图,输入SPM5软件做标准化处理,然后进行灰白质分割,对分割后的白质FA图进行平滑处理,最后对慢性PACG组和正常对照组FA图进行两样本t检验比较,采用FWE方法校正统计结果,取P＜0.05有统计学意义,将结果叠加于标准模板,显示阈值设定为10个体素。采用同样方法分析慢性PACG轻度组和重度组FA图差异。结果剔除头动明显受试者图像后,慢性PACG组和正常对照组各有22例入组,慢性PACG组分为轻度组13例、重度组9例。与正常对照组比较,慢性PACG患者双侧视束脚周段FA值明显降低(P＜0.05,FWE校正),左侧包含98个体素,右侧包含56个体素。慢性PACG轻度组与重度组FA值差异无统计学意义(P＞0.05)。结论 DTI可检测慢性PACG患者脑白质结构病变。FA值可反应双侧视束脚周段病变。     

Non-Gaussian water diffusion in aging white matter

Age-associated white matter degeneration has been well documented and is likely an important mechanism contributing to cognitive decline in older adults. Recent work has explored a range of noninvasive neuroimaging procedures to differentially highlight alterations in the tissue microenvironment. Diffusional kurtosis imaging (DKI) is an extension of diffusion tensor imaging (DTI) that accounts for non-Gaussian water diffusion and can reflect alterations in the distribution and diffusion properties of tissue compartments. We used DKI to produce whole-brain voxel-based maps of mean, axial, and radial diffusional kurtoses, quantitative indices of the tissue microstructure's diffusional heterogeneity, in 111 participants ranging from the age of 33 to 91 years. As suggested from prior DTI studies, greater age was associated with alterations in white-matter tissue microstructure, which was reflected by a reduction in all 3 DKI metrics. Prominent effects were found in prefrontal and association white matter compared with relatively preserved primary motor and visual areas. Although DKI metrics co-varied with DTI metrics on a global level, DKI provided unique regional sensitivity to the effects of age not available with DTI. DKI metrics were additionally useful in combination with DTI metrics for the classification of regions according to their multivariate “diffusion footprint”, or pattern of relative age effect sizes. It is possible that the specific multivariate patterns of age-associated changes measured are representative of different types of microstructural pathology. These results suggest that DKI provides important complementary indices of brain microstructure for the study of brain aging and neurologic disease.     

Diffusion tensor imaging and T2 relaxometry of bilateral lumbar nerve roots: feasibility of in‐plane imaging

Lower back pain is a common problem frequently encountered without specific biomarkers that correlate well with an individual patient's pain generators. MRI quantification of diffusion and T₂ relaxation properties may provide novel insight into the mechanical and inflammatory changes that occur in the lumbosacral nerve roots in patients with lower back pain. Accurate imaging of the spinal nerve roots is difficult because of their small caliber and oblique course in all three planes. Two‐dimensional in‐plane imaging of the lumbosacral nerve roots requires oblique coronal imaging with large field of view (FOV) in both dimensions, resulting in severe geometric distortions using single‐shot echo planar imaging (EPI) techniques. The present work describes initial success using a reduced‐FOV single‐shot spin‐echo EPI acquisition to obtain in‐plane diffusion tensor imaging (DTI) and T₂ mapping of the bilateral lumbar nerve roots at the L4 level of healthy subjects, minimizing partial volume effects, breathing artifacts and geometric distortions. A significant variation in DTI and T₂ mapping metrics is also reported along the course of the normal nerve root. The fractional anisotropy is statistically significantly lower in the dorsal root ganglia (0.287 ± 0.068) than in more distal regions in the spinal nerve (0.402 ± 0.040) (p < 10^–5). The T₂ relaxation value is statistically significantly higher in the dorsal root ganglia (78.0 ± 11.9 ms) than in more distal regions in the spinal nerve (59.5 ± 7.4 ms) (p < 10^–5). The quantification of nerve root DTI and T₂ properties using the proposed methodology may identify the specific site of any degenerative and inflammatory changes along the nerve roots of patients with lower back pain. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

A meta-analysis of diffusion tensor imaging studies in amyotrophic lateral sclerosis

Studies involving diffusion tensor imaging (DTI) of amyotrophic lateral sclerosis (ALS) with whole-brain voxel-based analysis yielded variable findings. A systematic review was conducted on whole-brain voxel-based diffusion tensor imaging fractional anisotropy (FA) studies of ALS patients and healthy controls (HC) in PubMed, ISI Web of Science, Embase, and MEDLINE databases from 1990 to December 25, 2010. Coordinates were extracted from clusters with significant difference in FA between ALS patients and HC. Meta-analysis was performed using signed differential mapping. Eight studies were enrolled, comprising 143 ALS patients and 145 HC. The included studies reported FA reduction at 67 coordinates in ALS and no FA increased. Significant reductions were present in the bilateral frontal white matter/cingulate gyrus and the posterior limb of bilateral internal capsule. The findings remain largely unchanged in quartile and jackknife sensitivity analyses. Our finding suggests that ALS is a multisystem disease beyond motor dysfunction and provides evidence that FA reduction in the frontal white matter and cingulate gyrus may be a special biomarker of ALS.