Diffusional kurtosis imaging of cingulate fibers in Parkinson disease: Comparison with conventional diffusion tensor imaging

Objective

The pathological changes in Parkinson disease begin in the brainstem; reach the limbic system and ultimately spread to the cerebral cortex. In Parkinson disease (PD) patients, we evaluated the alteration of cingulate fibers, which comprise part of the limbic system, by using diffusional kurtosis imaging (DKI).

Methods

Seventeen patients with PD and 15 age-matched healthy controls underwent DKI with a 3-T MR imager. Diffusion tensor tractography images of the anterior and posterior cingulum were generated. The mean kurtosis (MK) and conventional diffusion tensor parameters measured along the images in the anterior and posterior cingulum were compared between the groups. Receiver operating characteristic (ROC) analysis was also performed to compare the diagnostic abilities of the MK and conventional diffusion tensor parameters.

Results

The MK and fractional anisotropy (FA) in the anterior cingulum were significantly lower in PD patients than in healthy controls. The area under the ROC curve was 0.912 for MK and 0.747 for FA in the anterior cingulum. MK in the anterior cingulum had the best diagnostic performance (mean cutoff, 0.967; sensitivity, 0.87; specificity, 0.94).

Conclusions

DKI can detect alterations of the anterior cingulum in PD patients more sensitively than can conventional diffusion tensor imaging. Use of DKI can be expected to improve the ability to diagnose PD.     

Correlations between microstructural alterations and severity of cognitive deficiency in Alzheimer's disease and mild cognitive impairment: a diffusional kurtosis imaging study

Object

Diffusional kurtosis imaging (DKI), a natural extension of diffusion tensor imaging (DTI), can characterize non-Gaussian diffusion in the brain. We investigated the capability of DKI parameters for detecting microstructural changes in both gray matter (GM) and white matter (WM) in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) and sought to determine whether these DKI parameters could serve as imaging biomarkers to indicate the severity of cognitive deficiency.

Materials and Methods

DKI was performed on 18 AD patients and 12 MCI patients. Fractional anisotropy, kurtosis and diffusivity parameters in the temporal, parietal, frontal and occipital lobes were compared between the two groups using Mann–Whitney U test. The correlations between regional DKI parameters and mini-mental state examination (MMSE) score were tested using Pearson's correlation.

Results

In ADs, significantly increased diffusivity and decreased kurtosis parameters were observed in both the GM and WM of the parietal and occipital lobes as compared to MCIs. Significantly decreased fractional anisotropy was also observed in the WM of these lobes in ADs. With the exception of fractional anisotropy and radial kurtosis, all the five other DKI parameters exhibited significant correlations with MMSE score in both GM and WM.

Conclusion

Bearing additional information, the DKI model can provide sensitive imaging biomarkers for assessing the severity of cognitive deficiency in reference to MMSE score and potentially improve early detection and progression monitoring of AD based on characterizing microstructures in both the WM and especially the GM.     

Role of diffusion tensor imaging metrics and in vivo proton magnetic resonance spectroscopy in the differential diagnosis of cystic intracranial mass lesions

The purpose of this study was to determine whether proton magnetic resonance spectroscopy (PMRS) and diffusion tensor imaging (DTI) indices, fractional anisotropy (FA) and mean diffusivity (MD) can be used to distinguish brain abscess from cystic brain tumors, which are difficult to distinguish by conventional magnetic resonance imaging (MRI). Fifty-three patients with intracranial cystic mass lesions and 10 normal controls were studied. Conventional MRI, PMRS and DTI of all the patients were performed on a 1.5-T GE scanner. Forty patients were with brain abscess and 13 with cystic tumors. Cytosolic amino acids (AAs) were present in 32 of 40 brain abscess patients. Out of 13 patients with cystic tumors, lactate and choline were seen in 3 and only lactate was present in 10 patients on PMRS. All 40 cases of abscess had high FA, while all 13 cases of tumor cysts had high MD values. We conclude that FA measurements are more sensitive in predicting the abscess, while PMRS and MD are more specific in differentiating abscess from cystic tumors. We suggest that PMRS should be combined with DTI rather than with diffusion-weighted imaging as FA can be used as an additional parameter for separation of abscess from other cystic intracranial mass lesions.     

High spatial and angular resolution diffusion-weighted imaging reveals forniceal damage related to memory impairment

Introduction

Diffusion tensor imaging (DTI) measures in patients with multiple sclerosis (MS), particularly those measures associated with a specific white matter pathway, have consistently shown correlations with function. This study sought to investigate correlations between DTI measures in the fornix and common cognitive deficits in MS patients, including episodic memory, working memory and attention.

Materials and Methods

Patients with MS and group age- and sex-matched controls underwent high-resolution diffusion scanning (1-mm isotropic voxels) and cognitive testing. Manually drawn forniceal regions of interest were applied to individual maps of tensor-derived measures, and mean values of transverse diffusivity (TD), mean diffusivity (MD), longitudinal diffusivity (LD) and fractional anisotropy (FA) were calculated.

Results

In 40 patients with MS [mean age±S.D.= 42.55±9.1 years; Expanded Disability Status Scale (EDSS)=2.0±1.2; Multiple Sclerosis Functional Composite (MSFC) score=0.38±0.46] and 20 healthy controls (mean age±S.D.= 41.35±9.7 years; EDSS=0.0±0; MSFC score=0.74±0.24), we found that FA, MD and TD values in the fornix were significantly different between groups (P< .03), and patient performance on the Brief Visuospatial Memory Test-Revised (BVMT-R) was correlated with DTI measures (P< .03).

Discussion

These results are consistent with findings of axonal degeneration in MS and support the use of DTI as an indicator of disease progression.     

Age-related diffusion patterns in human lumbar intervertebral discs: a pilot study in asymptomatic subjects

Diffusion tensor imaging (DTI) may provide an accurate noninvasive method of detecting degenerative matrix alterations in human lumbar intervertebral discs (IVDs). This study aimed to investigate age-related degenerative changes in human lumbar IVDs using DTI. Thirty asymptomatic volunteers ranging in age from 25 to 67 years underwent single-shot diffusion weighted echo-planar imaging on a 3 T scanner. DTI-derived metrics including fractional anisotropy (FA) and mean diffusivity (MD) were analyzed by a histogram analysis method. A Mann-Whitney test was used to compare subject groups (young and elderly) with respect to the diffusion measures, and piecewise linear regression was used to characterize the change in each metric as a function of age. We found significant age-related changes in the elderly adult group, with decrease of MD (11%, P<.001) and increase of FA (20%, P<.001). Our results demonstrate that the degenerative-related changes taking place in the IVDs through aging can be quantitatively accessed by DTI-derived metrics, while the morphologic changes are difficult to be identified in conventional T(2)-weighted images. Our initial findings suggest that it would be worthwhile to validate the relationship between DTI metrics and the actual degenerative status of IVDs using extracted disc samples and to extend it to studies on patients with degenerative discs in order to further explore the clinical usefulness and relevance of DTI.     

Diffusion tensor imaging of oral carcinoma: Clinical evaluation and comparison with histopathological findings

PurposeThis study aims to assess the usefulness of diffusion tensor imaging (DTI) as a noninvasive method for the evaluation of histological grade and lymph node metastasis in patients with oral carcinoma (OC).Materials and methodsThirty-six consecutive patients with histologically confirmed OC underwent examination by 3-T MRI. DTI was performed using a single-shot echo-planar imaging sequence with b values of 0 and 1000 s/mm² and motion-probing gradients in 12 noncollinear directions. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) maps were compared with histopathological findings. The DTI parameters were correlated with the histological grade of the OCs based on the World Health Organization grading criteria and the presence or absence of lymph node metastasis.ResultsThe FA values (0.275 ± 0.058) of OC were significantly lower than those of normal tongue, muscle, and parotid glands (P < 0.001 for all), and the MD, AD, and RD values (1.220 ± 0.149, 1.434 ± 0.172, and 1.019 ± 0.165 × 10⁻³ mm²/s, respectively) were significantly higher than their respective normal values (P < 0.001 for all). Significant inverse correlations with histological grades were shown for FA, MD, AD, and RD values in OC patients (r = −0.862, r = −0.797, r = −0.747, and r = −0.844, respectively; P < 0.001 for all). In addition, there was a significant difference in the FA values of metastatic and nonmetastatic lymph nodes (0.186 vs. 0.276), MD (0.923 vs. 1.242 × 10⁻³ mm²/s), AD (1.246 vs. 1.621 × 10⁻³ mm²/s), and RD (0.792 vs. 1.100 × 10⁻³ mm²/s; P < 0.001 for all).ConclusionsDTI may be clinically useful for the noninvasive evaluation of histological grade and lymph node metastasis in OC patients.     

Diffusion tensor imaging of native and degenerated human articular cartilage

Diffusion tensor imaging (DTI) is potentially sensitive to collagen degeneration in cartilage. In this study, DTI was measured on human cartilage samples with interventions of trypsin and collagenase. The measured preferred diffusion direction was consistent with the zonal structure of collagen network. The glycosaminoglycan concentration decreased and apparent diffusion coefficient increased with both interventions. The fractional anisotropy (FA) was not affected by trypsin and showed a slight increase with combined trypsin and collagenase intervention. DTI in cartilage is technically challenging due to the low FA and the almost undetectable change with collagen disruption seen here.     

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.     

Understanding changes in DTI metrics in patients with different stages of neurocysticercosis

Diffusion tensor imaging (DTI) was performed on 25 patients with neurocysticercosis (NCC). The aim of this study was to investigate the changes in DTI measures during the evolutionary course of NCC lesions from vesicular to calcified stage in the brain. DTI measures were quantified from the NCC lesions of all patients. On the basis of conventional imaging findings, NCC lesions were classified into vesicular, vesicular colloidal, granular nodular and calcified stages. Significant inverse correlation was observed between the evolutionary stage of NCC lesion and mean diffusivity (MD; r=−0.748, P<0.001) and spherical anisotropy (CS; r=−0.585, P<.001) values. Significant direct correlations were observed between evolutionary stages of NCC lesion and mean fractional anisotropy (FA; r=0.575, P<0.001), linear anisotropy (CL; r=0.478, p<0.001) and planar anisotropy (CP; r=0.561, p<0.001) values. Successive decrease in MD values calculated from NCC lesions was observed, moving from vesicular to granular nodular stage. On FA, CL and CP maps, a significant increase in signal intensity value was observed in calcified as compared to other stages. We conclude that DTI measures may indicate the evolutionary changes in NCC from vesicular to calcified stage.     

Discriminative analysis of multivariate features from structural MRI and diffusion tensor images

Imaging markers derived from magnetic resonance images, together with machine learning techniques allow for the recognition of unique anatomical patterns and further differentiating Alzheimer's disease (AD) from normal states. T1-based imaging markers, especially volumetric patterns have demonstrated their discriminative potential, however, rely on the tissue abnormalities of gray matter alone. White matter abnormalities and their contribution to AD discrimination have been studied by measuring voxel-based intensities in diffusion tensor images (DTI); however, no systematic study has been done on the discriminative power of either region-of-interest (ROI)-based features from DTI or the combined features extracted from both T1 images and DTI. ROI-based analysis could potentially reduce the feature dimensionality of DTI indices, usually from more than 10e + 5, to 10–150 which is almost equal to the order of magnitude with respect to volumetric features from T1. Therefore it allows for straight forward combination of intensity based landmarks of DTI indices and volumetric features of T1. In the present study, the feasibility of tract-based features related to Alzheimer's disease was first evaluated by measuring its discriminative capability using support vector machine on fractional anisotropy (FA) maps collected from 21 subjects with Alzheimer's disease and 15 normal controls. Then the performance of the tract-based FA + gray matter volumes-combined feature was evaluated by cross-validation. The combined feature yielded good classification result with 94.3% accuracy, 95.0% sensitivity, 93.3% specificity, and 0.96 area under the receiver operating characteristic curve. The tract-based FA and the tract-based FA + gray matter volumes-combined features are certified their feasibilities for the recognition of anatomical features and may serve to complement classification methods based on other imaging markers.     

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.     

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.     

Reproducibility and biases in high field brain diffusion MRI: An evaluation of acquisition and analysis variables

Diffusion tensor imaging (DTI) of in-vivo human brain provides insights into white matter anatomical connectivity, but little is known about measurement difference biases and reliability of data obtained with last generation high field scanners (> 3 T) as function of MRI acquisition and analyses variables. Here we assess the impact of acquisition (voxel size: 1.8 × 1.8 × 1.8, 2 × 2 × 2 and 2.5 × 2.5 × 2.5 mm³, b-value: 700, 1000 and 1300 s/mm²) and analysis variables (within-session averaging and co-registration methods) on biases and test-retest reproducibility of some common tensor derived quantities like fractional anisotropy (FA), mean diffusivity (MD), axial and radial diffusivity in a group of healthy subjects at 4 T in three regions: arcuate fasciculus, corpus callosum and cingulum. Averaging effects are also evaluated on a full-brain voxel based approach. The main results are: i) group FA and MD reproducibility errors across scan sessions are on average double of those found in within-session repetitions (≈ 1.3 %), regardless of acquisition protocol and region; ii) within-session averaging of two DTI acquisitions does not improve reproducibility of any of the quantities across sessions at the group level, regardless of acquisition protocol; iii) increasing voxel size biased MD, axial and radial diffusivities to higher values and FA to lower values; iv) increasing b-value biased all quantities to lower values, axial diffusivity showing the strongest effects; v) the two co-registration methods evaluated gave similar bias and reproducibility results. Altogether these results show that reproducibility of FA and MD is comparable to that found at lower fields, not significantly dependent on pre-processing and acquisition protocol manipulations, but that the specific choice of acquisition parameters can significantly bias the group measures of FA, MD, axial and radial diffusivities.     

How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study

PURPOSE: The purpose of this study was to determine a suitable registration algorithm for diffusion tensor imaging (DTI) using conventional preprocessing tools [statistical parametric mapping (SPM) and automated image registration (AIR)] and to investigate how anisotropic indices for clinical assessments are affected by these distortion corrections. MATERIALS AND METHODS: Brain DTI data from 15 normal healthy volunteers were used to evaluate four spatial registration schemes within subjects to correct image distortions: noncorrection, SPM-based affine registration, AIR-based affine registration and AIR-based nonlinear polynomial warping. The performance of each distortion correction was assessed using: (a) quantitative parameters: tensor-fitting error (Ef), mean dispersion index (MDI), mean fractional anisotropy (MFA) and mean variance (MV) within 11 regions of interest (ROI) defined from homogeneous fiber bundles; and (b) fiber tractography through the uncinate fasciculus and the corpus callosum. Fractional anisotropy (FA) and mean diffusivity (MD) were calculated to demonstrate the effects of distortion correction. Repeated-measures analysis of variance was used to investigate differences among the four registration paradigms. RESULTS: AIR-based nonlinear registration showed the best performance for reducing image distortions with respect to smaller Ef (P<.02), MDI (P<.01) and MV (P<.01) with larger MFA (P<.01). FA was decreased to correct distortions (P<.0001) whether the applied registration was linear or nonlinear and was lowest after nonlinear correction (P<.001). No significant differences were found in MD. CONCLUSION: In conventional DTI processing, anisotropic indices of FA can be misestimated by noncorrection or inappropriate distortion correction, which leads to an erroneous increase in FA. AIR-based nonlinear distortion correction would be required for a more accurate measurement of this diffusion parameter.     

Dependence of the fractional anisotropy in cervical spine from the number of diffusion gradients,repeated acquisition and voxel size

The aim of this study is to investigate the consequences of using different gradient schemes, number of repeated measurements and voxel size on the fractional anisotropy (FA) value in a diffusion tensor imaging (DTI) sequence on the cervical tract of the spinal cord. Twenty healthy volunteers underwent a total of 86 DTI axial acquisitions performed by using different voxel size and number of diffusion gradient directions (NDGDs). Three different diffusion gradient schemes were applied, named 6, 15 and 32 according to the NDGD. Furthermore, some acquisitions were repeated to investigate the effects of image averaging on FA value.     

White matter maturation in the brains of Long Evans shaker myelin mutant rats by ex-vivo QSI and DTI

The brains of Long Evans shaker (les) rats, a model of dysmyelination, and their age- matched controls were studied by ex-vivo q-space diffusion imaging (QSI) and diffusion tensor imaging (DTI). The QSI and DTI indices were computed from the same acquisition. The les and the control brains were studied at different stages of maturation and disease progression. The mean displacement, the probability for zero displacement and kurtosis were computed from QSI data while the fractional anisotropy (FA) and the eigenvalues were computed from DTI. It was found that all QSI indices detect the les pathology, at all stages of maturation, while only some of the DTI indices could detect the les pathology. The QSI mean displacement was larger in the les group as compared with their age-matched controls while the probability for zero displacement and the kurtosis were both lower all indicating higher degree of restriction in the control brains. Since all the DTI eigenvalues were higher in the les brains as compared to controls, the less efficient DTI measure for discerning the les pathology was found to be the FA. Clearly, the most sensitive DTI parameter to the les pathology is λ₃, i.e. the minimal diffusivity. Since the QSI and DTI data were obtained from the same acquisition, despite the somewhat higher SNR of the QSI data compared to the DTI data, it seems that the higher diagnostic capacity of the QSI data in this experimental model of dysmyelination, originates mainly from the higher diffusing weighting of the QSI data.     

Diffusion properties of cortical and pericortical tissue: regional variations, reliability and methodological issues

Characterizing the diffusion properties of cortical tissue is complicated by intersubject variability in the relative locations of gyri and sulci. Here we extend methods of measuring the average diffusion properties of gyral and sulcal structures after they have been aligned to a common template of cortical surface anatomy. Diffusion tensor image (DTI) data were gathered from 82 young subjects and co-registered with high-resolution T1 images that had been inflated and co-registered to a hemispherically unified spherical coordinate system based on FreeSurfer. We analyzed fractional anisotropy (FA), mean diffusivity (MD) and the novel quantity of cortical primary diffusion direction (cPDD) at five surfaces parallel to the white/gray junction, spanning approximately 5 mm from the pial surface into white matter. FA increased with increasing depth, whereas MD and cPDD were reduced. There were highly significant and reliable regional differences in FA, MD and cPDD as well as systematic differences between cortical lobes and between the two hemispheres. The influence of nearby cortical spinal fluid (CSF), local cortical curvature and thickness, and sulcal depth was also investigated. We found that FA correlated significantly with cortical curvature and sulcal depth, while MD was strongly influenced by nearby CSF. The measurement of FA, MD and cPDD near the cortical surface clarifies the organization of fiber projections to and from the cortex.     

Learning-based structurally-guided construction of resting-state functional correlation tensors

Functional magnetic resonance imaging (fMRI) measures changes in blood-oxygenation-level-dependent (BOLD) signals to detect brain activities. It has been recently reported that the spatial correlation patterns of resting-state BOLD signals in the white matter (WM) also give WM information often measured by diffusion tensor imaging (DTI). These correlation patterns can be captured using functional correlation tensor (FCT), which is analogous to the diffusion tensor (DT) obtained from DTI. In this paper, we propose a noise-robust FCT method aiming at further improving its quality, and making it eligible for further neuroscience study. The novel FCT estimation method consists of three major steps: First, we estimate the initial FCT using a patch-based approach for BOLD signal correlation to improve the noise robustness. Second, by utilizing the relationship between functional and diffusion data, we employ a regression forest model to learn the mapping between the initial FCTs and the corresponding DTs using the training data. The learned forest can then be applied to predict the DTI-like tensors given the initial FCTs from the testing fMRI data. Third, we re-estimate the enhanced FCT by utilizing the DTI-like tensors as a feedback guidance to further improve FCT computation. We have demonstrated the utility of our enhanced FCTs in Alzheimer's disease (AD) diagnosis by identifying mild cognitive impairment (MCI) patients from normal subjects.     

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.     

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.