Diffusion Gradient Directions Research Articles

Effects of signal averaging, gradient encoding scheme, and spatial resolution on diffusion kurtosis imaging: An empirical study using 7T MRI.

Although diffusion gradient directions and b-values have been optimized for diffusion kurtosis imaging (DKI), little is known about the effect of signal averaging on DKI reliability. To evaluate how signal averaging influences the reliability of DKI indices using two gradient encoding schemes with three spatial resolutions. Prospective. Fifteen naïve Sprague-Dawley rats. DKI was performed at 7T using two schemes (30 directions with three b-values [30d-3b] and six directions with 15 b-values [6d-15b]), three resolutions, and eight repetitions. DKI reliability was assessed using voxelwise relative error (σ) and test-retest error of fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) within gray matter (GM) and white matter (WM). The number of excitations (NEX) was optimized by considering DKI reliability. The influence of the partial volume effect (PVE) was also assessed. One-way analysis of variance. The 30d-3b scheme, compared with the 6d-15b scheme, exhibited apparently smaller σFA and σMK (eg, at NEX 1, in GM, for three resolutions, σFA : 19.9-38.2% vs. 34.2-61.4%, σMK : 6.9-11.4% vs. 14.1-15.4%) and similar σMD (all differences between two schemes <1.6%). The optimal NEX was determined as 2 for enabling a reliable measurement of DKI-derived indices. The PVE at the lowest resolution apparently increased σFA for both schemes (19.9% for 30d-3b and 34.2% for 6d-15b) and σMK for the 6d-15b scheme (14.7%) in GM, and exerted lower effects on MK values for the 30d-3b scheme (P > 0.05). A higher number of diffusion directions would benefit FA and MK estimation. A higher spatial resolution helps to reduce PVE. By using the 30d-3b scheme, MK is considered a robust index to reflect microstructural changes in GM and WM. We propose a systematic approach to determine the optimal DKI protocols for appropriate preclinical settings. 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1593-1603.

Accelerating cardiac diffusion tensor imaging combining local low-rank and 3D TV constraint.

Diffusion tensor magnetic resonance imaging (DT-MRI, or DTI) is a promising technique for invasively probing biological tissue structures. However, DTI is known to suffer from much longer acquisition time with respect to conventional MRI and the problem is worsened when dealing with in vivo acquisitions. Therefore, faster DTI for both ex vivo and in vivo scans is highly desired. This paper proposes a new compressed sensing (CS) reconstruction method that employs local low-rank (LLR) model and three-dimensional (3D) total variation (TV) constraint to reconstruct cardiac diffusion-weighted (DW) images from highly undersampled k-space data. The LLR model takes the set of DW images corresponding to different diffusion gradient directions as a 3D image volume and decomposes the latter into overlapping 3D blocks. Then, the 3D blocks are stacked as two-dimensional (2D) matrix. Finally, low-rank property is applied to each block matrix and the 3D TV constraint to the 3D image volume. The underlying constrained optimization problem is finally solved using the first-order fast method. The proposed method is evaluated on real ex vivo cardiac DTI data as a prerequisite to in vivo cardiac DTI applications. The results on real human ex vivo cardiac DTI images demonstrate that the proposed method exhibits lower reconstruction errors for DTI indices, including fractional anisotropy (FA), mean diffusivities (MD), transverse angle (TA), and helix angle (HA), compared to existing CS-based DTI image reconstruction techniques. The proposed method provides better reconstruction quality and more accurate DTI indices in comparison with the state-of-the-art CS-based DW image reconstruction methods.

Investigation of anisotropic fishing line-based phantom as tool in quality control of diffusion tensor imaging.

This work proposes a low-cost, fishing line-based phantom for quality control of diffusion tensor imaging (DTI). The device was applied to investigate the relationship between DTI indexes (DTIi) and imaging acquisition parameters. A Dyneema® fishing line phantom was built with fiber bundles of different thicknesses. DTI acquisitions were performed in a 3T magnetic resonance imaging scanner using an 8-channel and a 32-channel head coil. For each coil, the following acquisition parameters were changed, one at a time: diffusion sensitivity factor (b value), echo time, sensitivity encoding, voxel size, number of signal averages, and number of diffusion gradient directions (NDGD). DTIi including fractional anisotropy, relative anisotropy (RA), linear anisotropy (CL), and planar anisotropy (CP) were calculated for each image; the data were analyzed using the coefficient of variation (CV) and distributions of DTIi values. The 32-channel head coil presented higher CV values for the DTIi RA, CL, and CP when voxel size was changed. Using the phantom, dependences between diffusion-related parameters (b value and NDGD) and DTIi were also observed; the majority of these were for the smaller thickness fiber bundles. The device proved to be useful for the verification of the DTI performance over time.

Structure Prior Constrained Estimation of Human Cardiac Diffusion Tensors

The purpose of this paper is to increase the accuracy of human cardiac diffusion tensor (DT) estimation in diffusion magnetic resonance imaging (dMRI) with a few diffusion gradient directions. A structure prior constrained (SPC) method is proposed. The method consists in introducing two regularizers in the conventional nonlinear least squares estimator. The two regularizers penalize the dissimilarity between neighboring DTs and the difference between estimated and prior fiber orientations, respectively. A novel numerical solution is presented to ensure the positive definite estimation. Experiments on ex vivo human cardiac data show that the SPC method is able to well estimate DTs at most voxels, and is superior to state-of-the-art methods in terms of the mean errors of principal eigenvector, second eigenvector, helix angle, transverse angle, fractional anisotropy, and mean diffusivity. The SPC method is a practical and reliable alternative to current denoising- or regularization-based methods for the estimation of human cardiac DT. The SPC method is able to accurately estimate human cardiac DTs in dMRI with a few diffusion gradient directions.

Consideration of Cerebrospinal Fluid Intensity Variation in Diffusion Weighted MRI.

Diffusion weighted MRI (DW-MRI) depends on accurate quantification signal intensities that reflect directional apparent diffusion coefficients (ADC). Signal drift and fluctuations during imaging can cause systematic non-linearities that manifest as ADC changes if not corrected. Here, we present a case study on a large longitudinal dataset of typical diffusion tensor imaging. We investigate observed variation in the cerebral spinal fluid (CSF) regions of the brain, which should represent compartments with isotropic diffusivity. The study contains 3949 DW-MRI acquisitions of the human brain with 918 subjects and 542 with repeated scan sessions. We provide an analysis of the inter-scan, inter-session, and intra-session variation and an analysis of the associations with the applied diffusion gradient directions. We investigate a hypothesis that CSF models could be used in lieu of an interspersed minimally diffusion-weighted image (b0) correction. Variation in CSF signal is not largely attributable to within-scan dynamic anatomical changes (3.6%), but rather has substantial variation across scan sessions (10.6%) and increased variation across individuals (26.6%). Unfortunately, CSF intensity is not solely explained by a main drift model or a gradient model, but rather has statistically significant associations with both possible explanations. Further exploration is necessary for CSF drift to be used as an effective harmonization technique.

Overcoming Challenges of Cranial Nerve Tractography: A Targeted Review.

Diffusion imaging tractography caught the attention of the scientific community by describing the white matter architecture in vivo and noninvasively, but its application to small structures such as cranial nerves remains difficult. The few attempts to track cranial nerves presented highly variable acquisition and tracking settings. To conduct and present a targeted review collecting all technical details and pointing out challenges and solutions in cranial nerve tractography. A "targeted" review of the scientific literature was carried out using the MEDLINE database. We selected studies that reported how to perform the tractography of cranial nerves, and extracted the following: clinical context; imaging acquisition settings; tractography parameters; regions of interest (ROIs) design; and filtering methods. Twenty-one published articles were included. These studied the optic nerves in suprasellar tumors, the trigeminal nerve in neurovascular conflicts, the facial nerve position around vestibular schwannomas, or all cranial nerves. Over time, the number of MRI diffusion gradient directions increased from 6 to 101. Nine tracking software packages were used which offered various types of tridimensional display. Tracking parameters were disparately detailed except for fractional anisotropy, which ranged from 0.06 to 0.5, and curvature angle, which was set between 20° and 90°. ROI design has evolved towards a multi-ROI strategy. Furthermore, new algorithms are being developed to avoid spurious tracts and improve angular resolution. This review highlights the variability in the settings used for cranial nerve tractography. It points out challenges that originate both from cranial nerve anatomy and the tractography technology, and allows a better understanding of cranial nerve tractography.

Eddy-current-induced distortion correction using maximum reconciled mutual information in diffusion MR imaging.

In diffusion tensor imaging, a large number of diffusion-weighted (DW) images with different diffusion gradient directions are attained during scanning. However, subjects' involuntary head movements and eddy current effect related to large diffusion-sensitizing gradients will cause distortions of DW images. Therefore, for tracking accurately white matter structures and tractography, the distortions have to be realigned before model fitting. Currently, traditional methods use maximum mutual information (MMI) or normalized mutual information (NMI) as similarity measure for DW images registration. These information measures are defined by Shannon entropy. The image entropy is able to embody the global information complexity but ignore the local information complexity caused by heterogeneous intensity contrasts in DW images, making registration algorithm early converge. To overcome the above problem, we present maximum reconciled mutual information (MRMI) combining both global information and local information as the similarity measure of the registration algorithm framework. (i) In comparison with traditional methods, under our proposed MRMI method, the border of DW image is more anastomotic with the b0 image, and the fitted fractional anisotropy (FA) map after registration is closer to the true brain boundary. (ii) By quantitative analysis of registration results, our method has a significant advantage over others in terms of NMI between b0 image and the aligned DW images. The results suggest that there is a high-level matching in space between the b0 image and the DW images aligned by the MRMI method, raising the registration robustness and accuracy compared to the traditional DW registration methods. It may provide a better option for the existing diffusion image registration tools (e.g., FMRIB Software Library) and commonly multimodal medical image registration.

227. MR Diffusion Tensor Imaging fiber tractography of thalamocortical and optical radiation tracts: Comparison between probabilistic fiber tracking and evoked potential recorded in epileptic patients

Purpose The purpose of this study was to evaluate the accuracy of the probabilistic tracking method of diffusion tensor imaging fiber tractography (DTI-FT), compared to imaging-represented electrophysiology data in epileptic patients who underwent stereoelectroncephalography (SEEG) for neurosurgical planning. Methods We identified 17 epileptic patients (mean age 26 ± 11) who underwent DTI acquisition on a 1.5T Philips Achieva scanner by using echo planar imaging and a Receive Coil Head SENSE 8 channels. Sequence details include: 64 non collinear diffusion gradient directions, b-value = 1000 s/mm2, TR/TE = 6522/86 ms, FA = 90°, SENSE factor = 2 and voxel-size = 2 × 2 × 2.6 mm. In addition, a three-dimensional T1-weighted Fast Field Echo (FFE) image was acquired with a TR/TE = 7.22/3.24 ms and FA = 8° and voxel size = 0.46 × 0.46 × 0.90 mm. These data were obtained with other brain MR sequences, used for SEEG planning. Depending on electrodes location, we recorded tibial and median somatosensory-evoked potentials (SEP) in 11 patients and flash-visual evoked potential (VEP) in 12. The thalamocortical (THC) and optical radiation (OR) tracts were blindly reconstructed using a probabilistic algorithm implemented in FSL 5.0.6, using two ROIs corresponding to the sensory thalamus and white matter (WM) lying underneath the somatosensory cortex for the THC, and the lateral geniculate body and WM lying next to the calcarine cortex for the OR. The 3D tractographies were then compared to the position of SEEG electrodes contacts, on which evoked potentials (EPs) were recorded. Results Comparison between DTI-FT and EPs shown that a superposition of the neurophysiological recording contacts and the tracts resulted in 15 out of 17 patients (88%). In particular, we obtained correspondence in the reconstruction of 9 out of 11 THC and 8 out of 12 OR. Conclusions This study is a preliminary one, suggesting that EPs recorded during SEEG monitoring can be considered as a valuable tool to validate the probabilistic tracking method in the reconstruction of THC and OR tracts.

Dependence of apparent diffusion coefficient measurement on diffusion gradient direction and spatial position – A quality assurance intercomparison study of forty-four scanners for quantitative diffusion-weighted imaging

PurposeTo propose an MRI quality assurance procedure that can be used for routine controls and multi-centre comparison of different MR-scanners for quantitative diffusion-weighted imaging (DWI). Materials and methods44 MR-scanners with different field strengths (1 T, 1.5 T and 3 T) were included in the study. DWI acquisitions (b-value range 0–1000 s/mm2), with three different orthogonal diffusion gradient directions, were performed for each MR-scanner. All DWI acquisitions were performed by using a standard spherical plastic doped water phantom. Phantom solution ADC value and its dependence with temperature was measured using a DOSY sequence on a 600 MHz NMR spectrometer. Apparent diffusion coefficient (ADC) along each diffusion gradient direction and mean ADC were estimated, both at magnet isocentre and in six different position 50 mm away from isocentre, along positive and negative AP, RL and HF directions. ResultsA good agreement was found between the nominal and measured mean ADC at isocentre: more than 90% of mean ADC measurements were within 5% from the nominal value, and the highest deviation was 11.3%. Away from isocentre, the effect of the diffusion gradient direction on ADC estimation was larger than 5% in 47% of included scanners and a spatial non uniformity larger than 5% was reported in 13% of centres. ConclusionADC accuracy and spatial uniformity can vary appreciably depending on MR scanner model, sequence implementation (i.e. gradient diffusion direction) and hardware characteristics. The DWI quality assurance protocol proposed in this study can be employed in order to assess the accuracy and spatial uniformity of estimated ADC values, in single- as well as multi-centre studies.

Angular resolution enhancement technique for diffusion-weighted imaging (DWI) using predicted diffusion gradient directions

Anisotropic diffusion MRI techniques using single-shell or multi-shell acquisitions have been proposed as a means to overcome some limitations imposed by diffusion tensor imaging (DTI), especially in complex models of fibre orientation distribution in voxels. A long acquisition time for the angular resolution of diffusion MRI is a major obstacle to practical clinical implementations. In this paper, we propose a novel method to improve angular resolution of diffusion MRI acquisition using given diffusion gradient (DG) directions. First, we define a local diffusion pattern map of diffusion MR signals on a single shell in given DG directions. Using the local diffusion pattern map, we design a prediction scheme to determine the best DG direction to be synthesized within a nearest neighborhood DG directions group. Second, the local diffusion pattern map and the spherical distance on the shell are combined to determine a synthesized diffusion signal in the new DG direction. Using the synthesized and measured diffusion signals on a single sphere, we estimate a spin orientation distribution function (SDF) with human brain data. Although the proposed method is applied to SDF, a basic idea is to increase the angular resolution using the measured diffusion signals in various DG directions. The method can be applicable to different acquired multi-shell data or diffusion spectroscopic imaging (DSI) data. We validate the proposed method by comparing the recovered SDFs using the angular resolution enhanced diffusion signals with the recovered SDF using the measured diffusion data. The developed method provides an enhanced SDF resolution and improved multiple fiber structure by incorporating synthesized signals. The proposed method was also applied neurite orientation dispersion and density imaging (NODDI) using multi-shell acquisitions.

Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI

Diffusion MRI of the cortical gray matter is challenging because the micro-environment probed by water molecules is much more complex than within the white matter. High spatial and angular resolutions are therefore necessary to uncover anisotropic diffusion patterns and laminar structures, which provide complementary (e.g. to anatomical and functional MRI) microstructural information about the cortex architectonic. Several ex-vivo and in-vivo MRI studies have recently addressed this question, however predominantly with an emphasis on specific cortical areas. There is currently no whole brain in-vivo data leveraging multi-shell diffusion MRI acquisition at high spatial resolution, and depth dependent analysis, to characterize the complex organization of cortical fibers. Here, we present unique in-vivo human 7T diffusion MRI data, and a dedicated cortical depth dependent analysis pipeline. We leverage the high spatial (1.05 mm isotropic) and angular (198 diffusion gradient directions) resolution of this whole brain dataset to improve cortical fiber orientations mapping, and study neurites (axons and/or dendrites) trajectories across cortical depths. Tangential fibers in superficial cortical depths and crossing fiber configurations in deep cortical depths are identified. Fibers gradually inserting into the gyral walls are visualized, which contributes to mitigating the gyral bias effect. Quantitative radiality maps and histograms in individual subjects and cortex-based aligned datasets further support our results.

Bilateral thalamocortical abnormalities in focal cortical dysplasia

Background and purposeFocal cortical dysplasia (FCD), a congenital malformation of the neocortex and one of the most common causes of medication resistant epilepsy in pediatric populations, can be studied noninvasively by diffusion tensor imaging (DTI). The present study aimed to quantify changes in the thalamus and thalamocortical pathways with respect to fractional anisotropy (FA), apparent diffusion coefficient (ADC), volume, and other common measures. Materials and methodsThe study quantified data collected from pediatric patients with a prior diagnosis of FCD; 75 patients (35 females, 10.1 ± 6.5 years) for analysis of thalamic volume and 68 patients (32 females, 10.2 ± 6.4 years) for DTI analysis. DTI scans were taken at 3 Tesla MRI scanners (30 diffusion gradient directions; b = 1000 s/mm2 and 5 non diffusion-weighted measurements). DTI tractography was performed using the FACT algorithm with an angle threshold of 45 degrees. Manually delineated ROIs were used to compare the hemisphere containing the dysplasia to the contralateral hemisphere and controls. ResultsA significant decrease in the volume of the FCD hemisphere thalamus was detected as compared to the contralateral hemisphere. In comparison to controls, there was an observed reduction in tract volume, length, count, FA of thalami, and FA of thalamocortical pathways in FCD patients. FCD patients had higher odds of exhibiting high ADC in both the thalamus and thalamocortical pathways. ConclusionThe data implied a widespread reduction in structural connectivity of the thalamocortical network. MRI analysis suggests a potential influence of FCD on thalamic volume.

Value of diffusion kurtosis imaging in assessing low-grade gliomas.

Diffusion kurtosis imaging (DKI) measures have been shown to provide increased sensitivity relative to diffusion tensor imaging (DTI) in detecting pathologies. To compare the sensitivity of DKI-derived kurtosis and diffusion maps for assessment of low-grade gliomas (LGG). Prospective study. In all, 19 LGG patients and 26 healthy control subjects were recruited. Echo-planar-imaging diffusion-weighted MR images (b-values = 0, 1000, and 2000 with 30 diffusion gradient directions) were acquired on a 3T scanner. Maps for mean, axial, and radial diffusivity (MD, AD, and RD) and kurtosis (MK, AK, and RK), and fractional anisotropy (FA) were evaluated in the tumor, perilesional white matter, and contralateral normal-appearing white matter regions. General linear models (GLM), Cohen's d for effect size estimates, false discovery rate (FDR) for multiple corrections, Cochran Q-test. Pairwise differences were observed for all diffusion and kurtosis measures between the studied regions (FDR P < 0.001), except an FA map that failed to show significant differences between the lesion and perilesional white matter (FDR P = 0.373). Effect size analysis showed that kurtosis metrics were found to be 18.8% (RK, P = 0.144) to 29.1% (AK, P < 0.05) more sensitive in discriminating perilesional regions from the lesion than corresponding diffusion metrics, whereas AK provided a 25.0% (P < 0.05) increase in sensitivity in discriminating perilesional and contralateral white matter. RK was found to be the most sensitive to contralateral white matter differences between low-grade gliomas and controls, with MK and RK providing a significantly greater sensitivity of 587.2% (P < 0.001) and 320.7% (P < 0.001) than MD and RD, respectively. Kurtosis maps showed increased sensitivity, as compared to counterpart diffusion maps, for evaluation of microstructural changes in gliomas with a 3-6-fold increment in assessing changes in contralateral white matter. 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;48:1551-1558.

A study of neurite orientation dispersion and density imaging in wilson's disease.

Previous studies have indicated that neurite orientation dispersion and density imaging (NODDI) could be used as a biomarker for detecting microstructural changes of brain. To quantitatively evaluate the changes in basal ganglia (BG) and thalamus in Wilson's disease (WD) by NODDI and assess the correlation between parameters and disease severity. Prospective case-control study. In total, 24 WD patients and 25 age- and sex-matched normal controls were involved in this study. EPI diffusion-weighted MR images (b-values = 0, 1000, and 2000 with 30 diffusion gradient directions) were acquired on a 3T scanner. Diffusion data were analyzed using voxel-based analysis. NODDI indices including intracellular volume fraction (Vic), orientation dispersion index (ODI), and isotropic volume fraction (Viso) were estimated from the BG and thalamus. The disease severity was assessed by two experienced neurologists based on the Global Assessment Scale (GAS). The relative importance of NODDI indices in diagnosing WD and predictive accuracy were also analyzed. The Shapiro-Wilk test, Student's t-test, χ2 test, Mann-Whitney-Wilcoxon test, Spearman rank correlation coefficient analysis and random-forest analysis were used for statistical analyses. The Vic and ODI in the BG and thalamus were significantly lower in WD patients than normal controls, while the Viso in the BG and thalamus were significantly higher (P < 0.01). The Vic in the putamen and ODI in the globus pallidus were negatively correlated with clinical severity (rvic = -0.727, P < 0.001; rodi = -0.705, P < 0.001). The Vic in the putamen was the most valuable predictor for diagnosing WD and the prediction accuracy of NODDI was 95.92%. NODDI can effectively evaluate the changes of microstructure and metabolism during copper deposition in WD, and thus, it is likely to be useful in detecting the changes in the brain of this disease and assessing its progression. 2 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2018;48:423-430.

Validation of diffusion measurements obtained on a 0.35 T MR in Malawi: Important insights for radiologists in low income settings with low field MRI

PurposeTo investigate the reliability of diffusion weighted image (DWI) measurements obtained on a 0.35T MR scanner in Malawi for malaria research. Materials and methodsThe same healthy volunteers (n=6) were scanned on a 0.35T MR scanner in Malawi and a 3T scanner in the US. Three subjects had two repeated DWI scans at 0.35T. Due to scanner constraints, only three diffusion gradient directions for DWI on 0.35T could be obtained. An apparent diffusion coefficient (ADC) map was reconstructed from the 0.35T and the result was compared to standard DWI acquisition on the 3T scanner. The mean ADC from 15 different regions and the voxel-wise coefficient of variation (CV) were calculated to investigate the intra-scanner and inter-scanner variability. Reproducibility was calculated using intra-class correlation coefficient (ICC). ResultsThe 0.35T intra-scanner ADC repeatability was high for all three subjects with repeated scans (ICC>0.7). The intra-scanner correlation between repeated scans was also high (r>0.67, p< 0.01). Comparing the ADC findings from the 0.35T and 3T MRs, the high inter-scanner correlation suggested that the 0.35T ADC results were valid (ICC>0.7, r>0.5, p<0.01). Voxel-wise CV revealed a few regions with larger variation (CV>20%), which were primarily located in peripheral regions and the boundary of lateral ventricles, and likely due to partial volume effects in low field scans. ConclusionThese findings support the validity of DWI obtained from low field MR scanners used in many low income countries.

Low frequency oscillating gradient spin-echo sequences improve sensitivity to axon diameter: An experimental study in viable nerve tissue

Mapping axon diameters within the central and peripheral nervous system could play an important role in our understanding of nerve pathways, and help diagnose and monitor an array of neurological disorders. Numerous diffusion MRI methods have been proposed for imaging axon diameters, most of which use conventional single diffusion encoding (SDE) spin echo sequences. However, a growing number of studies show that oscillating gradient spin echo (OGSE) sequences can provide additional advantages over conventional SDE sequences. Recent theoretical results suggest that this is especially the case in realistic scenarios, such as when fibres have unknown or dispersed orientation. In the present study, we adopt the ActiveAx approach to experimentally investigate the extent of these advantages by comparing the performances of SDE and trapezoidal OGSE in viable nerve tissue. We optimise SDE and OGSE ActiveAx protocols for a rat peripheral nerve tissue and test their performance using Monte Carlo simulations and a 800 mT/m gradient strength pre-clinical imaging experiment. The imaging experiment uses excised sciatic nerve from a rat's leg placed in a MRI compatible viable isolated tissue (VIT) maintenance chamber, which keeps the tissue in a viable physiological state that preserves the structural complexity of the nerve and enables lengthy scan times. We compare model estimates to histology, which we perform on the nerve post scanning. Optimisation produces a three-shell SDE and OGSE ActiveAx protocol, with the OGSE protocol consisting of one SDE sequence and two low-frequency oscillating gradient waveform sequences. Both simulation and imaging results show that the OGSE ActiveAx estimates of the axon diameter index have a higher accuracy and a higher precision compared to those from SDE. Histology estimates of the axon diameter index in our nerve tissue samples are 4–5.8 μm and these are excellently matched with the OGSE estimates 4.2–6.5 μm, while SDE overestimates at 5.2–8 μm for the same sample. We found OGSE estimates to be more precise with on average a 0.5 μm standard deviation compared to the SDE estimates which have a 2 μm standard deviation. When testing the robustness of the estimates when the number of the diffusion gradient directions reduces, we found that both OGSE and SDE estimates are affected, however OGSE is more robust to these changes than the SDE. Overall, these results suggest, quantitatively and in in vivo conditions, that low-frequency OGSE sequences may provide improved accuracy of axon diameter mapping compared to standard SDE sequences.

Comparison Of Number Of Diffusion Gradient Direction In Brain Imaging Diffusion Tensor; Case Study Of Tumor Brain

Background : Diffusion Tensor Imaging (DTI), namely MRI sequence which is the diffusion of water analysis that shows the complex structure of brain tissue. The weakness of this sequence is scanning time. Number of Diffusion Gradient Direction (NDGD) is one of parameter that effect scanning time. Purpose: This study has aim to compare between NDGD 25 and NDGD 15 in brain tumor. Methods: This study used observational analytic study with prospective approach. Five patients were examined using DTI sequence with NDGD 25 and NDGD 15. The parameter for evaluating the quality image is of Fractional Anisotropy (FA) and Fiber Tracking (FT). Result: Image with NDGD 25 was better than NDGD 15, but the difference was not significantly. Conclusion: It can be concluded that NDGD 15 can be solution to get informative image with short scan time when DTI sequence is used to examine brain tumor.

White matter alterations at pubertal onset

Recent neurodevelopmental research supports the contribution of pubertal stage to local and global grey and white matter remodelling. Little is known, however, about white matter microstructural alterations at pubertal onset. This study investigated differences in white matter properties between pre-pubertal and pubertal children using whole brain fixel-based analysis (FBA) of the microscopic density and macroscopic cross-section of fibre bundles. Diffusion-weighted imaging data were acquired for 74 typically developing children (M=10.4, SD=.43 years, 31 female) at 3.0T (60 diffusion gradient directions, b-value=2800s/mm2). Group comparisons of fibre density (FD) and fibre cross-section (FC) were made between age-matched pre-pubertal and pubertal groups, and post-hoc analyses were performed on regions of interest (ROIs) defined in the splenium, body and genu of the corpus callosum. Significant fixel-wise differences in FD were observed between the pubertal groups, where the pubertal group had significantly higher FD compared with age-matched pre-pubertal children, localised to the posterior corpus callosum. Post-hoc analyses on mean FD in the corpus callosum ROIs revealed group differences between the pubertal groups in the splenium, but not body or genu. The observed higher apparent fibre density in the splenium suggests that pubertal onset coincides with white matter differences explained by increasing axon diameter. This may be an important effect to account for over pubertal development, particularly for group studies where age-matched clinical and typical populations may be at various stages of puberty.

The influence of diffusion gradient direction on diffusion-weighted imaging of breast mass-like lesions at 3.0T

Background It has been challenging to achieve ideal breast diffusion-weighted imaging (DWI). The optimization of diffusion gradient direction is of great importance. Purpose To evaluate the effect of diffusion gradient direction on the apparent diffusion coefficient (ADC) values of breast mass-like lesions and the visual grades of image quality, lesion visibility, and sharpness of breast contour at 3.0T. Material and Methods Sixty consecutive patients with mass-like lesions were enrolled in this study. In addition to typical breast magnetic resonance imaging (MRI) protocols, the breasts were scanned with conventional orthogonal DWI (c-DWI), tetrahedral DWI (t-DWI), and 3in1 DWI (3in1-DWI) sequences. The DW images were observed and visually graded by two radiologists independently. For ADC measurement, one radiographer manually selected the region of interest (ROI). Results For both readers, t-DWI had better image quality and sharpness of breast contour than c-DWI. Regarding lesion visibility, no significant differences were observed among three sequences. The mean ADC values were 1.462 × 10-3, 1.490 × 10-3, and 1.446 × 10-3 mm2 s-1 for c-DWI, t-DWI, and 3in1-DWI, respectively. The ADC values extracted from both t-DWI and 3in1-DWI were not statistically different compared with those from c-DWI. In all DWI sequences, the ADC of malignant lesions was significantly reduced compared with benign lesions. Conclusion DWI with tetrahedral or 3in1 diffusion gradients is a more useful technique in clinical breast MRI than c-DWI because the image quality and sharpness of breast contour are improved. ADC is comparable to c-DWI.

Altered brain structural networks in the APP/PS1 mice: evidence from multi-shell diffusion imaging

Altered brain structural networks in the APP/PS1 mice: evidence from multi-shell diffusion imaging