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Previously, researchers used functional MRI to identify regional brain activations associated with sensory processing sensitivity (SPS), a proposed normal phenotype trait. To further validate SPS as a behavioral entity, to characterize it anatomically, and to test the usefulness in psychology of methodologies that assess axonal properties, the present study correlated SPS proxy questionnaire scores (adjusted for neuroticism) with diffusion tensor imaging measures. Participants (n=408) from the Young Adult Human Connectome Project that are free of neurologic and psychiatric disorders were investigated. We computed mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and fractional anisotropy (FA). A voxelwise, exploratory analysis showed that MD and RD correlated positively with SPS proxy scores in the right and left subcallosal and anterior ventral cingulum bundle, and the right forceps minor of the corpus callosum (peak Cohen’s D effect size = 0.269). Further analyses showed correlations throughout the entire right and left ventromedial prefrontal cortex, including the superior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate and arcuate fasciculus. These prefrontal regions are generally involved in emotion, reward and social processing. FA was negatively correlated with SPS proxy scores in white matter of the right premotor/motor/somatosensory/supramarginal gyrus regions, which are associated with empathy, theory of mind, primary and secondary somatosensory processing. Region of interest (ROI) analysis, based-on previous fMRI results and Freesurfer atlas-defined areas, showed small effect sizes, (+0.151 to -0.165) in white matter of the precuneus and inferior frontal gyrus. Other ROI effects were found in regions of the dorsal and ventral visual pathways and primary auditory cortex. The results reveal that in a large, diverse group of participants axonal microarchitectural differences can be identified with SPS traits that are subtle and in the range of typical behavior. The results suggest that the heightened sensory processing in people who show SPS may be influenced by the microstructure of white matter in specific neocortical regions. Although previous fMRI studies had identified most of these general neocortical regions, the DTI results put a new focus on brain areas related to attention and cognitive flexibility, empathy, emotion and low-level sensory processing, as in the primary sensory cortex. Psychological trait characterization may benefit from diffusion tensor imaging methodology by identifying influential brain systems for traits.

Background and Purpose\ud Diffusion MRI of the brain enables to quantify white matter fiber orientations noninvasively. Several approaches have been proposed to estimate such characteristics from diffusion MRI data with spherical deconvolution being one of the most widely used methods. Spherical deconvolution requires to define––or derive from the data––a response function, which is used to compute the fiber orientation distribution (FOD). Different characteristics of the response function are expected to affect the FOD computation and the subsequent fiber tracking.\ud \ud Methods\ud In this work, we explored the effects of inaccuracies in the shape factors of the response function on the FOD characteristics.\ud \ud Results\ud With simulations, we show that the apparent fiber density could be doubled in the presence of underestimated shape factors in the response functions, whereas the overestimation of the shape factor will cause more spurious peaks in the FOD, especially when the signal-to-noise ratio is below 15. Moreover, crossing fiber populations with a separation angle smaller than 60° were more sensitive to inaccuracies in the response function than fiber populations with more orthogonal separation angles. Results with in vivo data demonstrate angular deviations in the FODs and spurious peaks as a result of modified shape factors of the response function, while the reconstruction of the main parts of fiber bundles is well preserved.\ud \ud Conclusions\ud This work sheds light on how specific aspects of the response function shape can affect the estimated FODs, and highlights the importance of a proper calibration/definition of the response function.

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Diffusion MRI of the brain enables to quantify white matter fiber orientations noninvasively. Several approaches have been proposed to estimate such characteristics from diffusion MRI data with spherical deconvolution being one of the most widely used methods. Constrained spherical deconvolution requires to define – or derive from the data – a response function, which is used to compute the fiber orientation distribution (FOD). This definition or derivation is not unequivocal and can thus result in different characteristics of the response function which are expected to affect the FOD computation and the subsequent fiber tracking. In this work, we explored the effects of inaccuracies in the shape and scaling factors of the response function on the FOD characteristics. With simulations, we show that underestimation of the shape factor in the response functions has a larger effect on the FOD peaks than overestimation of the shape factor, whereas the latter will cause more spurious peaks. Moreover, crossing fiber populations with a smaller separation angle were more sensitive to the response function inaccuracy than fiber populations with more orthogonal separation angles. Furthermore, the FOD characteristics show deviations as a result of modified shape and scaling factors of the response function. Results with the in vivo data demonstrate that the deviations of the FODs and spurious peaks can further deviate the termination of propagation in fiber tracking. This work highlights the importance of proper definition of the response function and how specific calibration factors can affect the FOD and fiber tractography results.

SUMMARY: Diffusion tensor imaging is a valuable measure in clinical settings to assess diagnosis and prognosis of neonatal brain development. However, obtaining reliable images is not straightforward because of the tissue characteristics of the neonatal brain and the high likelihood of motion artifacts. In this review, we present guidelines on how to acquire DTI data of the neonatal brain and recommend high-quality data acquisition and processing as an essential means to obtain accurate and robust parametric maps. Sudden head movements are problematic for DTI in neonates, and these may lead to incorrect values. We describe strategies to minimize the corrupting effects both in terms of acquisition (eg, more gradient directions) and postprocessing (eg, tensor estimation methods). In addition, tools are described that can help assess whether a dataset is of sufficient quality for further assessment.

Purpose To determine the minimum water percentage in a muscle region of interest that would allow diffusion tensor (DT−) MRI data to reflect the diffusion properties of pure muscle accurately. Materials and Methods Proton density-weighted images with and without fat saturation were obtained at the mid-thigh in four subjects. Co-registered DT-MR images were used to calculate the diffusion tensor's eigenvalues and fractional anisotropy. Results The eigenvalues transitioned monotonically as a function of water signal percentage from values near to those expected for pure fat to those for pure muscle. Also, the fractional anisotropy transitioned monotonically from 0.50 (fat) to 0.20 (muscle). For water signal percentages >55%, none of the diffusion indices differed significantly from those for regions of >90% muscle. Conclusion Accounting for the T1 and T2 values of muscle and fat and the pulse sequence properties, it is concluded that, as a conservative estimate, regions must contain at least 76% muscle tissue to reflect the diffusion properties of pure muscle accurately. J. Magn. Reson. Imaging 2013;38:1292–1297. © 2013 Wiley Periodicals, Inc.

Fiber tractography based on non-invasive diffusion imaging is at the heart of connectivity studies of the human brain. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain dataset with ground truth white matter tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. While most state-of-the-art algorithms reconstructed 90% of ground truth bundles to at least some extent, on average they produced four times more invalid than valid bundles. About half of the invalid bundles occurred systematically in the majority of submissions. Our results demonstrate fundamental ambiguities inherent to tract reconstruction methods based on diffusion orientation information, with critical consequences for the approach of diffusion tractography in particular and human connectivity studies in general.

Diffusion tensor imaging (DTI)-based muscle fiber tracking enables the measurement of muscle architectural parameters, such as pennation angle (θ) and fiber tract length (Lft), throughout the entire muscle. Little is known, however, about the repeatability of either the muscle architectural measures or the underlying diffusion measures. Therefore, the goal of this study was to investigate the repeatability of DTI fiber tracking-based measurements and θ and Lft. Four DTI acquisitions were performed on two days that allowed for between acquisition, within day, and between day analyses. The eigenvalues and fractional anisotropy were calculated at the maximum cross-sectional area of, and fiber tracking was performed in, the tibialis anterior muscle of nine healthy subjects. The between acquisitions condition had the highest repeatability for the DTI indices and the architectural parameters. The overall inter class correlation coefficients (ICC’s) were greater than 0.6 for both θ and Lft and the repeatability coefficients were θ

Diffusion tensor imaging-based fiber tracking in skeletal muscle has been used to reconstruct and quantify muscle architecture. In addition, the consistent pattern of muscle fiber geometry enables a quantitative assessment of the fiber tracking. This work describes a method to determine the accuracy of individual muscle fiber tracts based on the location at which the fibers terminate, the fiber path, and similarity to the neighboring fibers. In addition, the effect of different stop criteria settings on this quantitative assessment was investigated. Fiber tracking was performed on the tibialis anterior muscle of nine healthy subjects. Complete fiber tracts covered 89.4 +/- 9.6% and 75.0 +/- 15.2% of the aponeurosis area in the superficial and deep compartments, respectively. Applications of the method include the exclusion of erroneous fiber-tracking results, quantitative assessment of data set quality, and the assessment of fiber-tracking stop criteria.

Diffusion-tensor magnetic resonance imaging (DTI) offers great potential for understanding structure-function relationships in skeletal muscle. The basis for these studies is that water diffuses more readily along the long axes of muscle fibers than along their transverse axes. This diffusion anisotropy can be characterized using a tensor, with the orientation of the principal eigenvalue corresponding to the long axis of the muscle fiber. These local, voxel-based directions can be combined by a fiber tracking algorithm to reconstruct the whole-muscle architecture. The fiber tracking data can be used to characterize important muscle architectural parameters, such as pennation angle, fiber length, and physiological cross-sectional area. The second and third eigenvalues convey information about muscle structural properties along the fibers' transverse axes. A comprehensive description of the sources of transverse diffusion restriction in muscle and how their relative importance may vary with the image acquisition conditions does not yet exist, but may ultimately make DTI a useful tool in studies of skeletal muscle microstructure as well. Ultimately, DTI-based longitudinal studies of changes in muscle architecture may provide insight into the relationships between structure and function in muscle, the time frames of muscle wasting, and in studying adaptations that maintain muscle functionality.

MR offers powerful tools to measure molecular diffusion in intact tissues under in vivo conditions. This review focuses on the use of diffusion-weighted MR imaging (DW-MRI) and spectroscopy (DW-MRS) to noninvasively study structural and functional aspects of skeletal muscle. It will be shown that DW-MRI allows for a high-resolution reconstruction of the orientation of the muscle fibers, which represents vital input for mathematical models of muscle biomechanics and an improved understanding of contractile dysfunction in muscle disease. DW-MRS can be used to quantitatively measure the translational displacement of endogenous metabolites in intact muscle. DW-MRS is of fundamental interest because it enables one to probe the in situ status of the intracellular space from the diffusion characteristics of the metabolites, while at the same time providing information on the intrinsic diffusion properties of the metabolites themselves. This yields information on cellular architecture and on the intrinsic capacity for diffusional mass transport.

To determine the minimum water percentage in a muscle region of interest that would allow diffusion tensor (DT-) MRI data to reflect the diffusion properties of pure muscle accurately.Proton density-weighted images with and without fat saturation were obtained at the mid-thigh in four subjects. Co-registered DT-MR images were used to calculate the diffusion tensor's eigenvalues and fractional anisotropy.The eigenvalues transitioned monotonically as a function of water signal percentage from values near to those expected for pure fat to those for pure muscle. Also, the fractional anisotropy transitioned monotonically from 0.50 (fat) to 0.20 (muscle). For water signal percentages55%, none of the diffusion indices differed significantly from those for regions of90% muscle.Accounting for the T1 and T2 values of muscle and fat and the pulse sequence properties, it is concluded that, as a conservative estimate, regions must contain at least 76% muscle tissue to reflect the diffusion properties of pure muscle accurately.

Fiber curvature is a functionally significant muscle structural property, but its estimation from diffusion-tensor magnetic resonance imaging fiber tracking data may be confounded by noise. The purpose of this study was to investigate the use of polynomial fitting of fiber tracts for improving the accuracy and precision of fiber curvature ( κ ) measurements. Simulated image data sets were created in order to provide data with known values for κ and pennation angle ( θ ). Simulations were designed to test the effects of increasing inherent fiber curvature (3.8, 7.9, 11.8 and 15.3 m −1 ), signal-to-noise ratio (50, 75, 100 and 150) and voxel geometry (13.8- and 27.0-mm 3 voxel volume with isotropic resolution; 13.5-mm 3 volume with an aspect ratio of 4.0) on κ and θ measurements. In the originally reconstructed tracts, θ was estimated accurately under most curvature and all imaging conditions studied; however, the estimates of κ were imprecise and inaccurate. Fitting the tracts to second-order polynomial functions provided accurate and precise estimates of κ for all conditions except very high curvature ( κ =15.3 m −1 ), while preserving the accuracy of the θ estimates. Similarly, polynomial fitting of in vivo fiber tracking data reduced the κ values of fitted tracts from those of unfitted tracts and did not change the θ values. Polynomial fitting of fiber tracts allows accurate estimation of physiologically reasonable values of κ , while preserving the accuracy of θ estimation.

Diffusion tensor imaging (DTI)-based muscle fiber tracking enables the measurement of muscle architectural parameters, such as pennation angle (theta) and fiber tract length (L(ft)), throughout the entire muscle. Little is known, however, about the repeatability of either the muscle architectural measures or the underlying diffusion measures. Therefore, the goal of this study was to investigate the repeatability of DTI fiber tracking-based measurements and theta and L(ft). Four DTI acquisitions were performed on two days that allowed for between acquisition, within day, and between day analyses. The eigenvalues and fractional anisotropy were calculated at the maximum cross-sectional area of, and fiber tracking was performed in, the tibialis anterior muscle of nine healthy subjects. The between acquisitions condition had the highest repeatability for the DTI indices and the architectural parameters. The overall inter class correlation coefficients (ICC's) were greater than 0.6 for both theta and L(ft) and the repeatability coefficients were theta10.2 degrees and L(ft)50 mm. In conclusion, under the experimental and data analysis conditions used, the repeatability of the diffusion measures is very good and repeatability of the architectural measurements is acceptable. Therefore, this study demonstrates the feasibility for longitudinal studies of alterations in muscle architecture using DTI-based fiber tracking, under similar noise conditions and with similar diffusion characteristics.

Purpose—To determine the feasibility of utilizing diffusion tensor MRI (DT-MRI) based muscle fiber tracking to create biomechanical models of the quadriceps mechanism in healthy subjects and those with chronic lateral patellar dislocation (LPD). Materials and Methods—Four healthy (average 14.5 years old; BMI 21.8) and four chronic LPD (average 17.3 years old; BMI 22.4) females underwent DT and axial T1W MRI of the thighs. The anatomical and physiologic cross sectional areas (ACSA and PCSA, respectively) and pennation angle were calculated of the vastus lateralis oblique (VLO) and vastus medialis oblique (VMO) muscles. The predicted resultant force vector on the patella was calculated. Results—The VLO pennation angles in healthy and LPD subjects were 18.7 and 14.5°, respectively (p=0.141). The VMO pennation angles in healthy and LPD subjects were 11.4 and 14.8°, respectively (p=0.02). The ACSA and PCSA VLO:VMO ratios in healthy and LPD subjects were 1.9:1.6 and 2.1:1.6, respectively (p=0.025 and 0.202, respectively). Regardless of whether ACSA or PCSA was used to predict resultant lateral force vectors, the values differed between healthy and LPD subjects (~2 and ~5.3°, respectively; p

Contains fulltext : 53284scheenen.pdf (Publisher’s version ) (Closed access) Due to the fragile pressure gradients present in the xylem and phloem, methods to study sap flow must be minimally invasive. Magnetic resonance imaging (MRI) meets this condition. A dedicated MRI method to study sap flow has been applied to quantify long-distance xylem flow and hydraulics in an intact cucumber (Cucumis sativus) plant. The accuracy of this MRI method to quantify sap flow and effective flow-conducting area is demonstrated by measuring the flow characteristics of the water in a virtual slice through the stem and comparing the results with water uptake data and microscopy. The in-plane image resolution of 120 x 120 microm was high enough to distinguish large individual xylem vessels. Cooling the roots of the plant severely inhibited water uptake by the roots and increased the hydraulic resistance of the plant stem. This increase is at least partially due to the formation of embolisms in the xylem vessels. Refilling the larger vessels seems to be a lengthy process. Refilling started in the night after root cooling and continued while neighboring vessels at a distance of not more than 0.4 mm transported an equal amount of water as before root cooling. Relative differences in volume flow in different vascular bundles suggest differences in xylem tension for different vascular bundles. The amount of data and detail that are presented for this single plant demonstrates new possibilities for using MRI in studying the dynamics of long-distance transport in plants.

Diffusion tensor imaging (DTI) is frequently applied to characterize the microscopic geometrical properties of tissue. To establish whether and how diffusion MRI responds to transient ischemia of skeletal muscle, we studied the effects of ischemia and reperfusion using DTI and T2-weighted MRI before and during ischemia and up to 24 hr after reperfusion. Ischemia was induced by 50 min of hindlimb occlusion with or without dorsal flexor stimulation. During ischemia the apparent diffusion coefficient (ADC) tended to decrease (up to 15%), whereas the fractional anisotropy (FA) and T2 showed a varied response depending on the protocol and muscle type. During reperfusion the ADC and T2 initially increased and subsequently renormalized for the occlusion protocol. For the occlusion plus stimulation (OS) protocol, the FA was decreased by 13% and the ADC and T2 were increased by 20% and 57%, respectively, after 24 hr in the stimulated muscle complex. In the latter tissue the three DTI eigenvalues gradually increased upon reperfusion. The smallest eigenvalue (lambda3) showed the largest relative increase. Changes in DTI indices in the reperfusion phases followed a similar time course as the changes in T2. The changes in MR indices after 24 hr correlated with the tissue damage quantified with histology. The highest correlation was observed for lambda3 (R2 = 0.81). This study shows that DTI can be used to assess ischemia-induced damage to skeletal muscle.

Background and Aims Diffusion Tensor Imaging (DTI) has become valuable for quantitative evaluation of white matter maturation in preterm infants. Because of the occurrence of head movement, gathering good quality data is challenging in neonatal neuroimaging. This is especially of concern for DTI, where motion can result in severe signal drop-out and therefore miscalculation of DTI parameters if data outliers are not handled correctly. This study was aimed to quantify the occurrence of motion artefacts in neonatal DTI and to evaluate different methods for tensor estimation. Methods We prospectively collected DTI data of 27 preterm infants that were scanned at 30 weeks gestational age. DTI data was acquired in 25 directions. Percentage outliers per slice was calculated. With Explore DTI, we assessed the effect of motion artefacts on tensor estimation using different methods. Results 60% of subjects had slightly corrupted data (>15 slices with >30% outliers) of which 40% had severely corrupted data (>10 slices with >50% outliers). Corrupted data resulted in erroneous DTI parameters. This was especially true for the tensor estimation (ordinary least squares) typically performed by vendors and popular DTI software. More advanced tensor estimations showed more reliable data. Conclusions Motion artefacts are a major problem in neonatal DTI as it can compromise accurate calculation of DTI parameters. These results press the need for careful data inclusion and the use of reliable methods for tensor estimation. Targeted acquisition, processing and quality assessment is needed in this population to obtain reliable evaluation of white matter maturation.

Background and aims: Preterm infants are at risk of brain injury with consequent neurodevelopmental impairment. As part of standard clinical care, we screen for possible brain injury by performing cerebral MRI at 30 weeks postmenstrual age. Our aim was to evaluate safety of MRI procedures in this population. Methods: We retrospectively collected data regarding patients‘ safety and (avoidable) adverse events of 41 VLBW infants, whose MRI scans were routinely performed at 30 weeks of gestation. MRI procedures were carried out according to our multidisciplinary based guideline. This includes a time-out procedure and registration of vital parameters, adverse events and safety incidents related to the procedure. Results: Mean gestational age (GA) and weight at image acquisition were 30.05 weeks (29.43-30.57) and 1112 grams (659-1580) respectively. No major adverse events occurred, but (preventable) incidents and minor adverse events were encountered: MRI procedure was interrupted in 3 infants (7.3%) because of respiratory instability. Minor increased respiratory support within 24 hours after the MR procedure was necessary in 10 infants (24.4%). Hypothermia (temperature < 36°C) occurred in 7 infants (17.1%). There was no significant correlation between temperature and GA at birth, weight at image acquisition, mode of respiratory support or hemodynamic instability. Conclusions: Although MRI scanning at 30 weeks gestational age is relatively safe for preterm infants, adverse events are common and should not be underestimated. A tailored guideline for MRI procedures in preterm infants including registration of patient data, time-out procedures and incident review is essential and the guideline should continuously be re-evaluated.