Peritumoral diffusion tensor imaging of high-grade gliomas and metastatic brain tumors

BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) is an advanced MR technique that describes the movement of water molecules by using two metrics, mean diffusivity (MD), and fractional anisotropy (FA), which represent the magnitude and directionality of water diffusion, respectively. We hypothesize that alterations in these values within the tissue surrounding brain tumors reflect combinations of increased water content and tumor infiltration and that these changes can be used to differentiate high-grade gliomas from metastatic lesions. METHODS: DTI was performed in 12 patients with high-grade gliomas and in 12 with metastatic lesions. DTI measurements were obtained from regions of interest (ROIs) placed on normal-appearing white matter and on the vasogenic edema, the T2 signal intensity abnormality surrounding each tumor. RESULTS: The peritumoral region of both gliomas and metastatic tumors displayed significant increases in MD (P <.005) and significant decreases in FA (P <.005) when compared with those of normal-appearing white matter. Furthermore, the peritumoral MD of metastatic lesions measured significantly greater than that of gliomas (P <.005). Peritumoral FA measurements, on the other hand, showed no such discrepancy. CONCLUSION: When compared with an internal control, diffusion metrics are clearly altered within the vasogenic edema surrounding both high-grade gliomas and metastatic tumors, reflecting increased extracellular water. Although peritumoral MD can be used to distinguish high-grade gliomas from metastatic tumors, peritumoral FA demonstrated no statistically significant difference. The FA changes surrounding gliomas, therefore, can be attributed not only to increased water content, but also to tumor infiltration.     

Image contrast using the secondary and tertiary eigenvectors in diffusion tensor imaging.

Diffusion tensor imaging (DTI) is a new imaging modality that can provide unique information on brain white matter anatomy. Measurements of water diffusion constant along multiple axes are fitted to a tensor model, from which the diffusion anisotropy and dominant fiber orientation can be estimated. Even though the tensor model is an oversimplification of the underlying neuroanatomy, information within the tensor has not been fully utilized in routine research and clinical studies. In this study we proposed and examined the properties and anatomical contents of several DTI-derived image contrasts that utilize all three eigenvectors. The new contrasts are studied and validated using known anatomical structures in ex vivo mouse brain and embryonic mouse cortex. Application to human white matter is illustrated. Our results suggest that when these contrasts are combined with a priori anatomical knowledge, they reveal neuroanatomical information that is useful for tissue segmentation and diagnosis of white matter lesions.     

Theory of diffusion tensor imaging and fiber tractography analysis

Magnetic Resonance Imaging (MRI) techniques have been increasingly applied to the study of molecular displacement (diffusion) in biologic tissue. The magnetic resonance measurement of an effective diffusion tensor of water in tissues can provide unique biologically and clinically relevant information that is not available from other imaging modalities. For this purpose Diffusion Tensor Imaging (DTI) is applied. DTI is an MRI variation that may significantly improve our understanding of brain structure and neural connectivity. DTI measures are thought to be representative of brain tissue microstructure and are particularly useful for examining organized brain regions, such as white matter tract areas. DTI measures the water diffusion tensor using diffusion weighted pulse sequences sensitive to microscopic random water motion. The resultant images display and allow for quantification of how water diffuses along axes or diffusion encoding directions. This can help measure and quantify a tissue's orientation and structure, making it an ideal tool for examining cerebral white matter and neural fiber tracts. In this article we discuss the theory on which DTI depends on, how can be used in mapping fiber tracts. Also the fiber tracking algorithms are presented.     

Diffusion tensor imaging and fiber tractography of C6 rat glioma

PURPOSE: To apply diffusion tensor images using 30 noncollinear directions for diffusion-weighted gradient schemes to characterize diffusion tensor imaging (DTI) features associated with C6 glioma-bearing rat brains, and ideally visualize fiber tractography datasets. MATERIALS AND METHODS: Fiber tractographies of normal male Fischer 344 rat brains were constructed from DTI datasets acquired with a 30 noncollinear diffusion gradient scheme. Cultured C6 cell were intracranially injected into the cortex of male Fischer 344 rats. The time course of the tumor growth was monitored with DTI and fiber tractography using diffusion-weighting gradients in 30 noncollinear directions. RESULTS: Fiber tractographies through the corpus callosum (CC) were easily visualized with the 30-direction gradient scheme, and the fiber trajectories of the motor cortex and striatum were well represented in normal rats. Fiber tractography indicated that the neuronal fibers of the CC were compressed or disappeared by growing C6 glioma, which affected surrounding brain tissue. CONCLUSION: We have demonstrated in this study that fiber tractography with the 30 noncollinear diffusion gradient scheme method can be used to help provide a better understanding regarding the influence of a tumor on the surrounding regions of normal brain tissue in vivo.     

Study of the effect of CSF suppression on white matter diffusion anisotropy mapping of healthy human brain.

Healthy human brain diffusion anisotropy maps derived from standard spin echo diffusion tensor imaging (DTI) were compared with those using fluid-attenuated inversion recovery (FLAIR) preparation prior to DTI to null the signal from cerebrospinal fluid (CSF). Consistent comparisons entailed development of DTI postprocessing methods, image masking based on fitting quality, and an objective region-of-interest-based method for assessment of white matter extent. FLAIR DTI achieved an extended delineation of major white-matter tracts (genu, splenium, and body of the corpus callosum) close to large CSF-filled spaces (lateral ventricles), but did not affect representation of tracts remote from CSF (internal and external capsules and coronal radiation). This result, which was detectable qualitatively (visual inspection), was verified quantitatively by analyses of the relative anisotropy (RA) distribution over white matter structures for 11 subjects. FLAIR DTI thus suppresses the CSF signal that otherwise masks underlying anisotropic parenchymal tissue through partial volume averaging.     

Correcting eddy current and motion effects by affine whole‐brain registrations: Evaluation of three‐dimensional distortions and comparison with slicewise correction

Eddy‐current (EC) and motion effects in diffusion‐tensor imaging (DTI) bias the estimation of quantitative diffusion indices, such as the fractional anisotropy. Both effects can be retrospectively corrected by registering the strongly distorted diffusion‐weighted images to less‐distorted T2‐weighted images acquired without diffusion weighting. Two different affine spatial transformations are usually employed for this correction: slicewise and whole‐brain transformations. However, a relation between estimated transformation parameters and EC distortions has not been established yet for the latter approach. In this study, a novel diffusion‐gradient‐direction–independent estimation of the EC field is proposed based solely on affine whole‐brain registration parameters. Using this model, it is demonstrated that a more distinct evaluation of the whole‐brain EC effects is possible if the through‐plane distortion was considered in addition to the well‐known in‐plane distortions. Moreover, a comparison of different whole‐brain registrations relative to a slicewise approach is performed, in terms of the relative tensor error. Our findings suggest that for appropriate intersubject comparison of DTI data, a whole‐brain registration containing nine affine parameters provides comparable performance (between 0 and 3%) to slicewise methods and can be performed in a fraction of the time. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.     

3D diffusion tensor MRI with isotropic resolution using a steady‐state radial acquisition

Purpose

To obtain diffusion tensor images (DTI) over a large image volume rapidly with 3D isotropic spatial resolution, minimal spatial distortions, and reduced motion artifacts, a diffusion‐weighted steady‐state 3D projection (SS 3DPR) pulse sequence was developed.

Materials and Methods

A diffusion gradient was inserted in a SS 3DPR pulse sequence. The acquisition was synchronized to the cardiac cycle, linear phase errors were corrected along the readout direction, and each projection was weighted by measures of consistency with other data. A new iterative parallel imaging reconstruction method was also implemented for removing off‐resonance and undersampling artifacts simultaneously.

Results

The contrast and appearance of both the fractional anisotropy and eigenvector color maps were substantially improved after all correction techniques were applied. True 3D DTI datasets were obtained in vivo over the whole brain (240 mm field of view in all directions) with 1.87 mm isotropic spatial resolution, six diffusion encoding directions in under 19 minutes.

Conclusion

A true 3D DTI pulse sequence with high isotropic spatial resolution was developed for whole brain imaging in under 20 minutes. To minimize the effects of brain motion, a cardiac synchronized, multiecho, DW‐SSFP pulse sequence was implemented. Motion artifacts were further reduced by a combination of linear phase correction, corrupt projection detection and rejection, sampling density reweighting, and parallel imaging reconstruction. The combination of these methods greatly improved the quality of 3D DTI in the brain. J. Magn. Reson. Imaging 2009;29:1175–1184. © 2009 Wiley‐Liss, Inc.     

Relative indices of water diffusion anisotropy are equivalent in live and formalin-fixed mouse brains.

Formalin fixation of tissue is a common laboratory practice. A direct comparison of diffusion tensor imaging (DTI) parameters from mouse brains before (in vivo) and after (ex vivo) formalin fixation is reported herein. Five diffusion indices were examined in a cohort of seven mice: relative anisotropy (RA), directional correlation (DC), trace (Tr(D)), trace-normalized axial diffusivity (D(axially)), and radial diffusivity (D(radially)). Seven regions of interest (ROIs), including five in white matter and two in gray matter, were selected for examination. Consistent with previous findings, a significant decrease of Tr(D) was observed for all ROIs after fixation. However, water diffusion anisotropy, as defined by the indices RA, DC, D(axially), and D(radially), remained unchanged after fixation. Thus, fixation does not appear to alter diffusion anisotropy in the mouse brain. This finding supports the utility of diffusion anisotropy analysis of fixed tissue. The combination of DTI measurements and standard histology may shed light on the microstructural determinants of diffusion anisotropy in normal and disease states.     

Diffusion tensor and tensor metrics imaging in intracranial epidermoid cysts

Purpose

To explore the utility of diffusion tensor imaging (DTI) and diffusion tensor metrics (DTM) in characterizing the structural pathology of epidermoid cysts. DTI gives information about the tissue structure; a high fractional anisotropy (FA) indicates a highly structured orientation of the tissue, fibers, or white matter tracts. Based on the tensor rank, a set of three metrics has been described that can be used to measure the directional dependence of diffusion: linear anisotropy (CL), planar anisotropy (CP), and spherical anisotropy (CS). DTM takes into account the shape of diffusion anisotropy and hence may provide better insight into the orientation of structures than FA.

Materials and Methods

DTI was performed in three patients with epidermoid cysts. FA, directionally‐averaged mean diffusivity (Dav), exponential apparent diffusion coefficient (eADC), and DTM, such as CL, CP, and CS, were measured from the tumor core as well as from the normal‐appearing white matter. Histopathological correlation was obtained.

Results

Epidermoid cysts showed high FA with Dav values similar to that of normal white matter. eADC maps did not show any restriction of diffusion. FA values were high, but not as high as that for the white matter. CP values were higher and CL values were lower than those obtained for the white matter in various regions.

Conclusion

High CP values suggest preferential diffusion of water molecules along a two‐dimensional geometry, which could be attributed to the well‐structured orientation of keratin filaments and flakes within the tumor as demonstrated by histopathology. Advanced imaging modalities like DTI with DTM can provide information regarding the microstructural anatomy of the epidermoid cysts. J. Magn. Reson. Imaging 2009;29:967–970. © 2009 Wiley‐Liss, Inc.     

Characterization of white matter alterations in phenylketonuria by magnetic resonance relaxometry and diffusion tensor imaging.

A multimodal MR study including relaxometry, diffusion tensor imaging (DTI), and MR spectroscopy was performed on patients with classical phenylketonuria (PKU) and matched controls, to improve our understanding of white matter (WM) lesions. Relaxometry yields information on myelin loss or malformation and may substantiate results from DTI attributed to myelin changes. Relaxometry was used to determine four brain compartments in normal-appearing brain tissue (NABT) and in lesions: water in myelin bilayers (myelin water, MW), water in gray matter (GM), water in WM, and water with long relaxation times (cerebrospinal fluid [CSF]-like signals). DTI yielded apparent diffusion coefficients (ADCs) and fractional anisotropies. MW and WM content were reduced in NABT and in lesions of PKU patients, while CSF-like signals were significantly increased. ADC values were reduced in PKU lesions, but also in the corpus callosum. Diffusion anisotropy was reduced in lesions because of a stronger decrease in the longitudinal than in the transverse diffusion. WM content and CSF-like components in lesions correlated with anisotropy and ADC. ADC values in lesions and in the corpus callosum correlated negatively with blood and brain phenylalanine (Phe) concentrations. Intramyelinic edema combined with vacuolization is a likely cause of the WM alterations. Correlations between diffusivity and Phe concentrations confirm vulnerability of WM to high Phe concentrations.     

Magnetic resonance diffusion characteristics of histologically defined prostate cancer in humans

The contrast provided by diffusion‐sensitive magnetic resonance offers the promise of improved tumor localization in organ‐confined human prostate cancer (PCa). Diffusion tensor imaging (DTI) measurements of PCa were performed in vivo, in patients undergoing radical prostatectomy, and later, ex vivo, in the same patients' prostatectomy specimens. The imaging data were coregistered to histological sections of the prostatectomy specimens, thereby enabling unambiguous characterization of diffusion parameters in cancerous and benign tissues. Increased cellularity, and hence decreased luminal spaces, in peripheral zone PCa led to approximately 40% and 50% apparent diffusion policy (ADC) decrease compared with benign peripheral zone tissues in vivo and ex vivo, respectively. In contrast, no significant diffusion anisotropy differences were observed between the cancerous and noncancerous peripheral zone tissues. However, the dense fibromuscular tissues in prostate, such as stromal tissues in benign prostatic hyperplasia in central gland, exhibited high diffusion anisotropy. A tissue classification method is proposed to combine DTI and T2‐weighted image contrasts that may provide improved specificity of PCa detection over T2‐weighted imaging alone. PCa identified in volume rendered MR images qualitatively correlates well with histologically determined PCa foci. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.     

High‐resolution diffusion tensor imaging of the human pons with a reduced field‐of‐view,multishot, variable‐density,spiral acquisition at 3 T

Diffusion tensor imaging of localized anatomic regions, such as brainstem, cervical spinal cord, and optic nerve, is challenging because of the existence of significant susceptibility differences, severe physiologic motion in the surrounding tissues, and the need for high spatial resolution to resolve the underlying complex neuroarchitecture. The aim of the methodology presented here is to achieve high‐resolution diffusion tensor imaging in localized regions of the central nervous system that is motion insensitive and immune to susceptibility while acquiring a set of two‐dimensional images with more than six diffusion encoding directions within a reasonable total scan time. We accomplish this aim by implementing self‐navigated, multishot, variable‐density, spiral encoding with outer volume suppression. We establish scan protocols for achieving equal signal‐to‐noise ratio at 1.2 mm and 0.8 mm in‐plane resolution for reduced field‐of‐view diffusion tensor imaging of the brainstem. In vivo application of the technique on the human pons of three subjects shows a clear delineation of the multiple local neural tracts. By comparing scans acquired with varying in‐plane resolution but with constant signal‐to‐noise ratio, we demonstrate that increasing the resolution and reducing the partial volume effect result in higher fractional anisotropy values for the corticospinal tracts. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.     

The tensor distribution function

Diffusion weighted magnetic resonance imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion‐sensitized gradients along a minimum of six directions, second‐order tensors (represented by three‐by‐three positive definite matrices) can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g., crossing fiber tracts. Recently, a number of high‐angular resolution schemes with more than six gradient directions have been employed to address this issue. In this article, we introduce the tensor distribution function (TDF), a probability function defined on the space of symmetric positive definite matrices. Using the calculus of variations, we solve the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function. Moreover, a tensor orientation distribution function (TOD) may also be derived from the TDF, allowing for the estimation of principal fiber directions and their corresponding eigenvalues. Magn Reson Med 61:205–214, 2009. © 2008 Wiley‐Liss, Inc.     

Robust correction of spike noise: Application to diffusion tensor imaging

Echo‐planar imaging (EPI) ‐based diffusion tensor imaging (DTI) is particularly prone to spike noise. However, existing spike noise correction methods are impractical for corrupted DTI data because the methods correct the complex MRI signal, which is not usually stored on clinical MRI systems. The present work describes a novel Outlier Detection De‐spiking technique (ODD) that consists of three steps: detection, localization, and correction. Using automated outlier detection schemes, ODD exploits the data redundancy available in DTI data sets that are acquired with a minimum of six different diffusion‐weighted images (DWIs) with similar signal and noise properties. A mathematical formulation, describing the effects of spike noise on magnitude images, yields appropriate measures for an outlier detection scheme used for spike detection while a normalization‐dependent outlier detection scheme is used for spike localization. ODD performs accurately on diverse DTI data sets corrupted by spike noise and can be used for automated control of DTI data quality. ODD can also be extended to other MRI applications with data redundancy, such as dynamic imaging and functional MRI. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.     

扩散峰度成像的基本原理及其在脑肿瘤中的应用

扩散峰度成像（DKI）是近年发展起来的一项新的MR扩散加权成像（DWI）技术,不同于传统的DWI及扩散张量成像（DTI）,DKI主要是通过描述组织内水分子扩散运动偏离正态分布的程度,评价组织的微结构,间接反映组织生理、病理情况。DKI目前已广泛应用于中枢神经系统的临床研究,尤其在脑肿瘤方面。对DKI的基本原理及其在脑肿瘤中的临床应用予以综述。     

In vivo mapping of the fast and slow diffusion tensors in human brain.

Recent studies have shown that the diffusional signal decay in human brain is non-monoexponential and may be described in terms of compartmentalized water fractions. Diffusion tensor imaging (DTI), which provides information about tissue structure and orientation, typically uses b values up to 1000 s x mm(-2) so that the signal is dominated by the fast diffusing fraction. In this study b factors up to 3500 s x mm(-2) are utilized, allowing the diffusion tensor properties of the more slowly diffusing fraction to be mapped for the first time. The mean diffusivity (MD) of the slow diffusion tensor was found to exhibit strong white/gray matter (WM/GM) contrast. Maps depicting the principal direction of the slow tensor indicated alignment with the fast tensor and the known orientation of the WM pathways.     

Gray and white matter delineation in the human spinal cord using diffusion tensor imaging and fuzzy logic

RATIONALE AND OBJECTIVES: Diffusion tensor imaging (DTI) has been used extensively in determining morphology and connectivity of the brain; however, similar analysis in the spinal cord has proven difficult. The objective of this study was to improve the delineation of gray and white matter in the spinal cord by applying signal processing techniques to the eigenvalues of the diffusion tensor. Our approach involved creating anisotropy indices based on the difference between eigenvalues and mean diffusivity then using a fuzzy inference system (FIS) to delineate between gray and white matter in the human cervical spinal cord. MATERIALS AND METHODS: DTI was performed on the cervical spinal cord in five neurologically intact subjects. Distributions were extracted for regions of gray and white matter through the use of a digitized histologic template. Fuzzy membership functions were created based on these distributions. Detectability index and receiver operating characteristic (ROC) analysis was performed on traditional DTI indices and FIS classified regions. RESULTS: A significantly higher contrast between gray and white matter was observed using fuzzy classification compared with traditionally used DTI indices based on the detectability index (P < .001) and trends in the ROC analysis. Reconstructed images from the FIS qualitatively showed a better anatomical representation of the spinal cord compared with traditionally used DTI indices. CONCLUSIONS: Diffusion tensor imaging using an FIS for tissue classification provides high contrast between spinal gray and white matter compared with traditional DTI indices and may provide a noninvasive technique to quantify the integrity and morphology of the human spinal cord following injury.     

基于扩散张量成像利用一阶有限元方法计算脑白质各向异性电导率对脑电位分布的影响

目的 研究脑白质各向异性电导率对头皮电位分布的影响.方法 把由扩散张量成像得到的水分子扩散张量采用体积约束规则计算出白质组织的电导率张量,并根据成像的空间信息建立了包括头皮、颅骨、灰质、脑脊液及白质5种组织的真实头的有限元模型.基于此模型,推导了各向异性电导率脑电正问题的一阶有限元数值算法.最后,采用电流偶极子模型计算头皮电位分布.结果 脑白质各向异性电导率对头皮电位分布有一定的影响,径切比越大,影响越大;左右分布偶极子比上下分布的影响要大.结论 脑电研究中,白质电导率的各向异性为一不可忽略的因素.     

白血病脑实质浸润的弥散张量成像应用研究

目的探讨1．5T磁共振弥散张量成像（diffusiontensorimaging,DTI）,部分各向异性（fractionalanisotropy,FA）和表观扩散系数（apparentdiffusioncoefficient,ADC）及弥散张量纤维束成像（diffusiontensortractography,DTT）在成人白血病脑实质浸润的应用价值。方法回顾性分析经临床证实的8例白血病脑实质浸润病例DTI之ADC、FA参数图,分别测量病变、水肿及健侧相应部位FA值和ADC值;观察各例在DTT图的变化。结果白血病脑实质浸润的肿瘤实质部分FA值8例全部较健侧降低,ADC值5例减低,3例增高;周围水肿区FA值全部降低,ADC值全部增高;脑白质纤维束DTT显示有中断、移位、浸润。结论DTI对脑侵犯神经纤维束损伤具有独特诊断价值;DTI的参数变化能够量化神经纤维受压后微细结构的变化,DTT图像重建能直观显示脑白质纤维束的完整性及损伤程度,DTI联合DTT可更加准确地评估白血病脑侵犯的损害程度。     

Evaluation of measurement uncertainties in human diffusion tensor imaging (DTI)‐derived parameters and optimization of clinical DTI protocols with a wild bootstrap analysis

Purpose

To quantify measurement uncertainties of fractional anisotropy, mean diffusivity, and principal eigenvector orientations in human diffusion tensor imaging (DTI) data acquired with common clinical protocols using a wild bootstrap analysis, and to establish optimal scan protocols for clinical DTI acquisitions.

Materials and Methods

A group of 13 healthy volunteers were scanned using three commonly used DTI protocols with similar total scan times. Two important parameters—the number of unique diffusion gradient directions (NUDG) and the ratio of the total number of diffusion‐weighted (DW) images to the total number of non‐DW images (DTIR)—were analyzed in order to investigate their combined effects on uncertainties of DTI‐derived parameters, using results from both the Monte Carlo simulation and the wild bootstrap analysis of uncertainties in human DTI data.

Results

The wild bootstrap analysis showed that uncertainties in human DTI data are significantly affected by both NUDG and DTIR in many brain regions. These results agree with previous predictions based on error‐propagations as well as results from simulations.

Conclusion

Our results demonstrate that within a clinically feasible DTI scan time of about 10 minutes, a protocol with number of diffusion gradient directions close to 30 provides nearly optimal measurement results when combined with a ratio of the total number of DW images over non‐DW images equal to six. Wild bootstrap can serve as a useful tool to quantify the measurement uncertainty from human DTI data. J. Magn. Reson. Imaging 2009;29:422–435. © 2009 Wiley‐Liss, Inc.