Localized high-resolution DTI of the human midbrain using single-shot EPI,parallel imaging,and outer-volume suppression at 7 T

Localized high-resolution diffusion tensor images (DTI) from the midbrain were obtained using reduced field-of-view (rFOV) methods combined with SENSE parallel imaging and single-shot echo planar (EPI) acquisitions at 7 T. This combination aimed to diminish sensitivities of DTI to motion, susceptibility variations, and EPI artifacts at ultra-high field. Outer-volume suppression (OVS) was applied in DTI acquisitions at 2- and 1-mm² resolutions, b = 1000 s/mm², and six diffusion directions, resulting in scans of 7- and 14-min durations. Mean apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured in various fiber tract locations at the two resolutions and compared. Geometric distortion and signal-to-noise ratio (SNR) were additionally measured and compared for reduced-FOV and full-FOV DTI scans. Up to an eight-fold data reduction was achieved using DTI-OVS with SENSE at 1 mm², and geometric distortion was halved. The localization of fiber tracts was improved, enabling targeted FA and ADC measurements. Significant differences in diffusion properties were observed between resolutions for a number of regions suggesting that FA values are impacted by partial volume effects even at a 2-mm² resolution. The combined SENSE DTI-OVS approach allows large reductions in DTI data acquisition and provides improved quality for high-resolution diffusion studies of the human brain.     

Keyhole and zero-padding approaches for reduced-encoding diffusion tensor imaging of the mouse brains

Keyhole diffusion tensor imaging (keyhole DTI) was previously proposed in cardiac imaging to reconstruct DTI maps from the reduced phase-encoding images. To evaluate the feasibility of keyhole DTI in brain imaging, keyhole and zero-padding DTI algorithms were employed on in vivo mouse brain. The reduced phase-encoding portion, also termed as the sharing rate, was varied from 50% to 90% of the full k-space. Our data showed that zero-padding DTI resulted in decreased fractional anisotropy (FA) and decreased mean apparent diffusion coefficient (mean ADC) in white matter (WM) regions. Keyhole DTI showed a better edge preservation on mean ADC maps but not on FA maps as compared to the zero-padding DTI. When increasing the sharing rate in keyhole approach, an underestimation of FA and an over- or underestimation of mean ADC were measured in WM depending on the selected reference image. The inconsistency of keyhole DTI may add a challenge for the wide use of this modality. However, with a carefully selected directive diffusion-weighted image to serve as the reference image in the keyhole approach, this study demonstrated that one may obtain DTI indices of reduced-encoding images with high consistency to those derived with full k-space DTI.     

Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI

Diffusion tensor mapping with MRI can noninvasively track neural connectivity and has great potential for neural scientific research and clinical applications. For each diffusion tensor imaging (DTI) data acquisition scheme, the diffusion tensor is related to the measured apparent diffusion coefficients (ADC) by a transformation matrix. With theoretical analysis we demonstrate that the noise performance of a DTI scheme is dependent on the condition number of the transformation matrix. To test the theoretical framework, we compared the noise performances of different DTI schemes using Monte-Carlo computer simulations and experimental DTI measurements. Both the simulation and the experimental results confirmed that the noise performances of different DTI schemes are significantly correlated with the condition number of the associated transformation matrices. We therefore applied numerical algorithms to optimize a DTI scheme by minimizing the condition number, hence improving the robustness to experimental noise. In the determination of anisotropic diffusion tensors with different orientations, MRI data acquisitions using a single optimum b value based on the mean diffusivity can produce ADC maps with regional differences in noise level. This will give rise to rotational variances of eigenvalues and anisotropy when diffusion tensor mapping is performed using a DTI scheme with a limited number of diffusion-weighting gradient directions. To reduce this type of artifact, a DTI scheme with not only a small condition number but also a large number of evenly distributed diffusion-weighting gradients in 3D is preferable.     

Diffusion tensor magnetic resonance imaging of the normal breast

Purpose

The objective of this study was to evaluate diffusion anisotropy of the breast parenchyma and assess the range and repeatability of diffusion tensor imaging (DTI) parameters in normal breast tissue.

Materials and Methods

The study was approved by our institutional review board and included 12 healthy females (median age, 36 years). Diffusion tensor imaging was performed at 1.5 T using a diffusion-weighted echo planar imaging sequence. Diffusion tensor imaging parameters including tensor eigenvalues (λ₁, λ₂, λ₃), fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were measured for anterior, central and posterior breast regions.

Results

Mean normal breast DTI measures were λ₁=2.51×10⁻³ mm²/s, λ₂=1.89×10⁻³ mm²/s, λ₃=1.39×10⁻³ mm²/s, ADC=1.95±0.24×10⁻³ mm²/s and FA=0.29±0.05 for b=600 s/mm². Significant regional differences were observed for both FA and ADC (P<.05), with higher ADC in the central breast and higher FA in the posterior breast. Comparison of DTI values calculated using b=0, 600 s/mm² vs. b=0, 1000 s/mm², showed significant differences in ADC (P<.001), but not FA. Repeatability assessment produced within-subject coefficient of variations of 4.5% for ADC and 11.4% for FA measures.

Conclusion

This study demonstrates anisotropy of water diffusion in normal breast tissue and establishes a normative range of breast FA values. Attention to the influence of breast region and b value on breast DTI measurements may be important for clinical interpretation and standardization of techniques.     

Geometric analysis of the b-dependent effects of Rician signal noise on diffusion tensor imaging estimates and determining an optimal b value

The optimal diffusion weighting (DW) factor, b, for use in diffusion tensor imaging (DTI) studies remains uncertain. In this study, the geometric relations of DW quantities are examined, in particular, the effects of Rician noise in the measured magnetic resonance signal. This geometric analysis is used to make theoretical predictions for selecting a b value to reduce the influence of noise. It is shown that the optimal b value for DTI studies in healthy human parenchyma is approximately b=1200 s mm⁻², with a simple relation given as well for a given expected apparent diffusion coefficient. Monte-Carlo simulations on sets of realistic DTI measures are then performed, verifying the optimal DW for minimizing estimate errors. The effects of noise on various DTI parameters such as anisotropy indices (fractional anisotropy and scaled relative anisotropy), mean diffusivity, radial diffusivity, eigenvalues and the direction of the first eigenvector are investigated as well.     

描述人体内水分子扩散各向异性特征的新方法

通过核磁共振扩散张量成像(DTI)得到的特定值域的扩散各向异性指数(DAI) 可用于揭示水分子扩散椭球的形态学特征, 定量反映被成像物体内部水分子扩散的优势方向和强度, 间接得到被成像物体内部的组织结构信息. DAI的可靠性直接影响对DTI数据的分析和理解. 本文基于扩散张量椭球的几何学信息, 提出利用扩散椭球几何比(EGR)定量描述水分子扩散的各向异性程度. 通过蒙特卡罗模拟实验和对人脑DTI数据进行分析, 并与当前广泛应用的水分子扩散各向异性分数(FA)和近期文献提出的扩散椭球面积比(EAR)进行对比. 实验发现EGR在不同级别噪声影响下的对比度效果和抗噪性都优于FA及EAR. 而且EGR 加入了体积修正, 增强了盘形扩散张量情况下的敏感性, 能够更好地鉴别神经纤维束交叉情况, 对于各向异性扩散程度较高的白质深层和相对均质的表层都有较好的量化区分结果. 关键词： 扩散系数 各向异性扩散 扩散张量成像 扩散椭球几何比     

Renal diffusion tensor imaging: is it possible to define the tubular pathway? A case report

The authors report a case of unilateral xanthogranulomatous pyelonephritis, associated with chronic lithiasis studied by standard clinical magnetic resonance imaging protocol and diffusion tensor imaging (DTI). Maps of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) and tractography were reconstructed on both healthy and pathologic kidney. ADC and FA values are in agreement with the literature. Tractography reconstruction of tubular renal architecture was confirmed by histology. This result suggests the potential ability of DTI to detect structural alterations in the architecture of the kidney, as noninvasive tool, preceding the onset of clinical-laboratory alterations.     

Correlation of proton MR spectroscopy and diffusion tensor imaging

Proton magnetic resonance spectroscopy ((1)H-MRS) provides indices of neuronal damage. Diffusion tensor imaging (DTI) relates to water diffusivity and fiber tract orientation. A method to compare (1)H-MRS and DTI findings was developed, tested on phantom and applied on normal brain. Point-resolved spectroscopy (T(R)/T(E)=1500/135) was used for chemical shift imaging of a supraventricular volume of interest of 8 x 8 x 2 cm(3) (64 voxels). In DTI, a segmental spin-echo sequence (T(R)/T(E)=5500/91) was used and slices were stacked to reproduce the slab used in MRS. The spatial distributions of choline and N-acetylaspartate (NAA) correlated to mean fractional anisotropy and apparent diffusion coefficient (ADC) for the inner 6 x 6=36 voxels defined in MRS, most notably NAA and ADC value (r=-.70, P<.00001; correlation across four subjects, 144 data pairs). This is the first association of neuron metabolite contents in volunteers with structure as indicated by DTI.     

低场MRI系统中线扫描扩散张量成像方法的研究

磁共振扩散张量成像(DTI)是在扩散加权成像(DWI)基础上发展起来的一种新型技术,可以无创伤显示脑白质纤维,诊断脑白质病变. 但是由于各种原因,DTI一般只在超导高场磁共振成像(MRI)仪器上进行,这就限制了这一重要诊断手段临床应用的广泛性. 本文在低场磁共振成像系统上应用线扫描实现了扩散张量成像,并测量了健康志愿者大脑内主要解剖结构的表观扩散系数(ADC)和各项异性分数(FA),得到的数据与高场仪器上的相关数据比较是吻合的. 因此临床上使用在低场强上得到的DTI图像评价脑白质是可行的,而且通常在临床上这也是足够的.     

Minimal gradient encoding for robust estimation of diffusion anisotropy

This study has investigated the relationship between the noise sensitivity of measurement by magnetic resonance imaging (MRI) of the diffusion tensor (D) of water and the number N of diffusion-weighting (DW) gradient directions, using computer simulations of strongly anisotropic fibers with variable orientation. The DW directions uniformly sampled the diffusion ellipsoid surface. It is shown that the variation of the signal-to-noise ratio (SNR) of three ideally rotationally invariant scalars of D due to variable fiber orientation provides an objective quantitative measure for the diffusion ellipsoid sampling efficiency, which is independent of the SNR value of the baseline signal obtained without DW; the SNR variation decreased asymptotically with increasing N. The minimum number N(0) of DW directions, which minimized the SNR variation of the three scalars of D was determined, thereby achieving the most efficient ellipsoid sampling. The resulting time efficient diffusion tensor imaging (DTI) protocols provide robust estimation of diffusion anisotropy in the presence of noise and can improve the repeatability/reliability of DTI experiments when there is high variability in the orientation of similar anisotropic structures, as for example, in studies which require repeated measurement of one individual, intersubject comparisons or multicenter studies.     

Diffusion tensor imaging reveals microstructural alteration of the trigeminal nerve root in classical trigeminal neuralgia without neurovascular compression and correlation with outcome after internal neurolysis

ObjectivesDiffusion tensor imaging (DTI) has been used to detect microstructural alteration and effect of surgical treatment of the trigeminal nerve root (TR) in patients with classical trigeminal neuralgia (CTN) underwent microvascular decompression (MVD). Patients with CTN without neurovascular compression (woNVC) is a special population of TN, however, the pathogenesy of CTN woNVC and the mechanism of internal neurolysis (IN) remain unknown.Materials and methods21 patients with CTN woNVC who underwent IN and 20 healthy controls were included in this study. The differences in the means, kurtosis and skewness of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) between the affected and unaffected nerves in patients and both nerves in controls were investigated by independent t-test and paired t-test respectively. Longitudinal changes of FA and ADC were correlated with outcome of IN via Spearman correlation coefficient.ResultsSignificant differences were found in preoperative mean and kurtosis values for both FA and ADC of the affected side TR, compared to the unaffected side and control group respectively. However, these differences remarkably reduced postoperatively. Further, the Spearman correlation coefficient showed a strong negative correlation between decrease of ADC in the affected side and the surgical outcome in BNI total score.ConclusionThe changes of diffusive property of TR, especially the FA and ADC, provide alternative radiological evidence for evaluating the mechanism of CTN woNVC. The modification of DTI metrics could be an effective factor for providing potential noninvasive biomarkers for determining the prognosis of patients with CTN woNVC underwent IN.     

A diffusion gradient optimization framework for spinal cord diffusion tensor imaging

The uncertainty in the estimation of diffusion model parameters in diffusion tensor imaging (DTI) can be reduced by optimally selecting the diffusion gradient directions utilizing some prior structural information. This is beneficial for spinal cord DTI, where the magnetic resonance images have low signal-to-noise ratio and thus high uncertainty in diffusion model parameter estimation. Presented is a gradient optimization scheme based on D-optimality, which reduces the overall estimation uncertainty by minimizing the Rician Cramer-Rao lower bound of the variance of the model parameter estimates. The tensor-based diffusion model for DTI is simplified to a four-parameter axisymmetric DTI model where diffusion transverse to the principal eigenvector of the tensor is assumed isotropic. Through simulations and experimental validation, we demonstrate that an optimized gradient scheme based on D-optimality is able to reduce the overall uncertainty in the estimation of diffusion model parameters for the cervical spinal cord and brain stem white matter tracts.     

Evaluation of Disease Stage of Radiation-Induced Brain Injury: a DTI Study with Pathological Correlation

The aim of this study is to evaluate if diffusion tensor imaging (DTI) can distinguish the disease process of radiation-induced brain injury when combined with apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values. Twenty-one rabbits received irradiation of 100 Gy in the right brain hemisphere. Twelve rabbits were screened with magnetic resonance imaging (MRI) and DTI before radiation, and imaged at every week until week 9 following radiation. The rabbits that had MRI were euthanized at week 9 for histologic evaluation, while other nine rabbits without MRI were randomly killed for histologic evaluation at weeks 2, 4 and 6, respectively. From the DTI, the ADC and FA values were measured, and rADC and rFA were calculated. After radiation, the trend of the ADC value can be divided into three stages. In the first stage, the ADC value of the target tissues gradually decreased. In the second stage, the ADC value of white matter in the target tissues showed a recovery trend, back to the initial level similar to that in contralateral. In the third stage, the ADC value of white matter in the target tissue continues to increase over the ADC value of baseline and contralateral white matter. The FA value of radiation-targeted area showed continuous decreasing tendency. Pathological evaluation showed the different features in three stages. DTI can distinguish the different disease stages when combined with the ADC and FA values.     

Use of capillaries in the construction of an MRI phantom for the assessment of diffusion tensor imaging: demonstration of performance

Although diffusion tensor imaging (DTI) shows great potential for the diagnosis of a variety of pathologies, no consensus for an appropriate assessment standard of DTI exists. This study examined the feasibility of using water-filled arrays of glass capillaries to construct a DTI phantom suitable for making repeated and reproducible measurements required in a quality assessment program. Three phantoms were constructed using arrays of capillaries with three inner diameters (23, 48, and 82 μm). Data were acquired using DTI protocols; the fractional anisotropy (FA), mean apparent diffusion coefficient (ADC) and principal eigenvectors of the diffusion tensors were calculated. This study demonstrated four results: (1) echo-planar images show that susceptibility within the capillary arrays does not lead to substantial differences in precessional frequency in regions containing the arrays and neither do the regions show noticeable image distortion; (2) principal eigenvectors of the diffusion tensors agree to within <10.3° of the array orientations; (3) mean FA values (0.18–0.50) and ADC values (1.40–1.93×10−³ mm²/s) within specified regions of interest are in general agreement with simulations after a simple noise correction; and (4) these array performance characteristics are observable using a typical clinical DTI protocol.     

DTI at 7 and 3 T: systematic comparison of SNR and its influence on quantitative metrics

Diffusion tensor imaging (DTI) and advanced related methods such as diffusion spectrum and kurtosis imaging are limited by low signal-to-noise ratio (SNR) at conventional field strengths. DTI at 7 T can provide increased SNR; however, B0 and B1 inhomogeneity and shorter T2? still pose formidable challenges. The purpose of this study was to quantify and compare SNR at 7 and 3 T for different parallel imaging reduction factors, R, and TE, and to evaluate SNRs influences on fractional anisotropy (FA) and apparent diffusion coefficient (ADC). We found that R>4 at 7 T and R≥2 at 3 T were needed to reduce geometric distortions due to B0 inhomogeneity. For these R at 7 T, SNR was 70-90 for b=0 s/mm² and 22-28 for b=1000s/mm² in central brain regions. SNR was lower at 3 T (40 for b=0 s/mm² and 15 for b=1000 s/mm²) and in lateral brain regions at 7 T due to B1 inhomogeneity. FA and ADC did not change with MRI field strength, SENSE factor or TE in the tested range. However, the coefficient of variation for FA increased for SNR <15 and for SNR <10 in ADC, consistent with published theoretical studies. Our study demonstrates that 7 T is advantageous for DTI and lays the groundwork for further development. Foremost, future work should further address challenges with B0 and B1 inhomogeneity to take full advantage for the increased SNR at 7 T.     

Multiple sclerosis: Benefits of q-space imaging in evaluation of normal-appearing and periplaque white matter

Introduction

Diffusion tensor imaging (DTI) reveals white matter pathology in patients with multiple sclerosis (MS). A recent non-Gaussian diffusion imaging technique, q-space imaging (QSI), may provide several advantages over conventional MRI techniques in regard to in vivo evaluation of the disease process in patients with MS. The purpose of this study is to investigate the use of root mean square displacement (RMSD) derived from QSI data to characterize plaques, periplaque white matter (PWM), and normal-appearing white matter (NAWM) in patients with MS.

Methods

We generated apparent diffusion coefficient (ADC) and fractional anisotropy (FA) maps by using conventional DTI data from 21 MS patients; we generated RMSD maps by using QSI data from these patients. We used the Steel–Dwass test to compare the diffusion metrics of regions of interest in plaques, PWM, and NAWM.

Results

ADC differed (P < 0.05) between plaques and PWM and between plaques and NAWM. FA differed (P < 0.05) between plaques and NAWM. RMSD differed (P < 0.05) between plaques and PWM, plaques and NAWM, and PWM and NAWM.

Conclusion

RMSD values from QSI may reflect microstructural changes and white-matter damage in patients with MS with higher sensitivity than do conventional ADC and FA values.     

Repeatability of echo-planar-based diffusion measurements of the human prostate at 3 T

Echo-planar-based diffusion-weighted imaging (DWI) of the prostate is increasingly being suggested as a viable technique, complementing information derived from conventional magnetic resonance imaging methods for use in tissue discrimination. DWI has also been suggested as a potentially useful tool in the assessment of tumor response to treatment. In this study, the repeatability of apparent diffusion coefficient (ADC) values obtained from both DWI and diffusion tensor imaging (DTI) has been assessed as a precursor to determining the magnitude of treatment-induced changes required for reliable detection. The repeatability values of DWI and DTI were found to be similar, with ADC values repeatable to within 35% or less over a short time period of a few minutes and a longer time period of a month. Fractional anisotropy measurements were found to be less repeatable (between 26% and 71%), and any changes duly recorded in longitudinal studies must therefore be treated with a degree of caution.     

Changes in diffusion tensor imaging (DTI) eigenvalues of skeletal muscle due to hybrid exercise training

Several studies have proposed the cell membrane as the main water diffusion restricting factor in the skeletal muscle cell. We sought to establish whether a particular form of exercise training (which is likely to affect only intracellular components) could affect water diffusion. The purpose of this study is to characterise prospectively the changes in diffusion tensor imaging (DTI) eigenvalues of thigh muscle resulting from hybrid training (HYBT) in patients with non-alcoholic fatty liver disease (NAFLD). Twenty-one NAFLD patients underwent HYBT for 30 minutes per day, twice a week for 6 months. Patients were scanned using DTI of the thigh pre- and post-HYBT. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), the three eigenvalues lambda 1 (λ1), λ2, λ3, and the maximal cross sectional area (CSA) were measured in bilateral thigh muscles: knee flexors (biceps femoris (BF), semitendinosus (ST), semimembranous (SM)) and knee extensors (medial vastus (MV), intermediate vastus (IV), lateral vastus (LV), and rectus femoris (RF)), and compared pre- and post-HYBT by paired t-test. Muscle strength of extensors (P < 0.01), but not flexors, increased significantly post-HYBT. For FA, ADC and eigenvalues, the overall picture was of increase. Some (P < 0.05 in λ2 and P < 0.01 in λ1) eigenvalues of flexors and all (λ1-λ3) eigenvalues of extensors increased significantly (P < 0.01) post-HYBT. HYBT increased all 3 eigenvalues. We suggest this might be caused by enlargement of muscle intracellular space.     

Importance of exactb-tensor calculation for quantitative diffusion tensor imaging and tracking of neuronal fiber bundles

Quantitative diffusion tensor imaging (DTI) is a novel method of magnetic resonance (MR) imaging providing information on the brain’s microstructure in vivo. DTI can be effectively measured with modern clinical MR scanners. However, imaging sequence details required for accurateb matrix calculation and for following DTI quantification are normally unknown to the user. In this work, we investigated the accuracy ofb value approximation if theb matrix is calculated without taking into account the effect of imaging gradients. It was found that an error of more than 4% in DTI estimation arises for a quite typical brain imaging protocol. The errors in mean diffusivity and fractional anisotropy index depend on diffusion tensor shape and eigenvectors orientation and exceed noise level in DTI quantification. These errors however have a strong impact on fiber tracking — up to 30% difference was found between the fiber tracks corresponding to exact and approximate calculated DTI data. Since these errors are dependent on imaging parameters and sequence implementation, accurateb matrix calculations are important for adequate comparison between data acquired on different MR scanners and also for data measured with the different imaging protocols.     

Exploratory voxel-based analysis of diffusion indices and hemispheric asymmetry in normal aging

Age-related microstructural changes in brain white matter can be studied by utilizing indices derived from diffusion tensor imaging (DTI): apparent diffusion coefficient (ADC) and fractional anisotropy (FA). The objective of this study is to examine alterations in FA and ADC by employing exploratory voxel-based analysis (VBA) and region(s) of interest (ROI)-based analysis. A highly nonlinear registration algorithm was used to align the ADC and FA image volumes of different subjects to perform accurate voxel-level statistics for two age groups, as well as for hemispheric asymmetry for both age groups. VBA shows significant age-related decline in FA with frontal predominance (frontal white matter, and genu and anterior body of the corpus callosum), superior portions of a splenium and highly oriented fibers of the posterior limb of the internal capsule and the anterior and posterior limbs of the external capsule. Hemispheric asymmetry of FA, as assessed by VBA, showed that for the young-age group, significant right-greater-than-left asymmetry exists in the genu, splenium and body of the corpus callosum and that left-greater-than-right asymmetry exists in the anterior limb of the external capsule and in the posterior limb of the internal capsule, thalamus, cerebral peduncle and temporal-parietal regions. VBA of the hemispheric asymmetry of the middle-age group revealed much less asymmetry. Regions showing age-related changes and hemispheric asymmetry from VBA were, for a majority of the findings, in conformance with ROI analysis and with the known pattern of development and age-related degradation of fiber tracks. The study shows the feasibility of the VBA of DTI indices for exploratory investigations of subtle differences in population cohorts, especially when findings are not localized and/or known a priori.