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Objectives: Accurate presurgical brain mapping enables preoperative risk assessment and intraoperative guidance. This cross‐sectional study investigated whether constrained spherical deconvolution (CSD) methods were more accurate than diffusion tensor imaging (DTI)‐based methods for presurgical white matter mapping using intraoperative direct electrical stimulation (DES) as the ground truth. Methods: Five different tractography methods were compared (three DTI‐based and two CSD‐based) in 22 preoperative neurosurgical patients undergoing surgery with DES mapping. The corticospinal tract (CST, N = 20) and arcuate fasciculus (AF, N = 7) bundles were reconstructed, then minimum distances between tractograms and DES coordinates were compared between tractography methods. Receiver‐operating characteristic (ROC) curves were used for both bundles. For the CST, binary agreement, linear modeling, and posthoc testing were used to compare tractography methods while correcting for relative lesion and bundle volumes. Results: Distance measures between 154 positive (functional response, pDES) and negative (no response, nDES) coordinates, and 134 tractograms resulted in 860 data points. Higher agreement was found between pDES coordinates and CSD‐based compared to DTI‐based tractograms. ROC curves showed overall higher sensitivity at shorter distance cutoffs for CSD (8.5 mm) compared to DTI (14.5 mm). CSD‐based CST tractograms showed significantly higher agreement with pDES, which was confirmed by linear modeling and posthoc tests (PFWE <.05). Conclusions: CSD‐based CST tractograms were more accurate than DTI‐based ones when validated using DES‐based assessment of motor and sensory function. This demonstrates the potential benefits of structural mapping using CSD in clinical practice. [ABSTRACT FROM AUTHOR]

Diffusion magnetic resonance imaging is a technique for non-invasive detection of microstructure in the white matter of the human brain, which is widely used in neuroscience research of the brain. However, diffusion-weighted images(DWI) are sensitive to noise, which affects the subsequent reconstruction of fiber orientation direction, microstructural parameter estimation and fiber tracking. In order to better eliminate the noise in diffusion-weighted images, this study proposes a noise reduction method combining Marchenko-Pastur principal component analysis(MPPCA) and rotation-invariant non-local means filter(RINLM) to further remove residual noise and preserve the image texture detail information. In this study, the algorithm is applied to the fiber structure and the prevailing microstructural models within the human brain voxels based on simulated and real human brain datasets. Experimental comparisons between the proposed method and the state-of-the-art methods are performed in single-fiber, multi-fiber, crossed and curved-fiber regions as well as in different microstructure estimation models. Results demonstrated the superior performance of the proposed method in denoising DWI data, which can reduce the angular error in fiber orientation reconstruction to obtain more valid fiber structure estimation and enable more complete fiber tracking trajectories with higher coverage. Meanwhile, the method reduces the estimation errors of various white matter microstructural parameters and verifies the performance of the method in white matter microstructure estimation. [ABSTRACT FROM AUTHOR]

PurposeThe study aimed to (1) assess the feasibility constrained spherical deconvolution (CSD) tractography to reconstruct crossing fiber bundles with unsedated neonatal diffusion MRI (dMRI), and (2) demonstrate the impact of spatial and angular resolution and processing settings on tractography and derived quantitative measures.MethodsFor the purpose of this study, the term-equivalent dMRIs (single-shell b800, and b2000, both 5 b0, and 45 gradient directions) of two moderate-late preterm infants (with and without motion artifacts) from a local cohort [Brain Imaging in Moderate-late Preterm infants (BIMP) study; Calgary, Canada] and one infant from the developing human connectome project with high-quality dMRI (using the b2600 shell, comprising 20 b0 and 128 gradient directions, from the multi-shell dataset) were selected. Diffusion tensor imaging (DTI) and CSD tractography were compared on b800 and b2000 dMRI. Varying image resolution modifications, (pre-)processing and tractography settings were tested to assess their impact on tractography. Each experiment involved visualizing local modeling and tractography for the corpus callosum and corticospinal tracts, and assessment of morphological and diffusion measures.ResultsContrary to DTI, CSD enabled reconstruction of crossing fibers. Tractography was susceptible to image resolution, (pre-) processing and tractography settings. In addition to visual variations, settings were found to affect streamline count, length, and diffusion measures (fractional anisotropy and mean diffusivity). Diffusion measures exhibited variations of up to 23%.ConclusionReconstruction of crossing fiber bundles using CSD tractography with unsedated neonatal dMRI data is feasible. Tractography settings affected streamline reconstruction, warranting careful documentation of methods for reproducibility and comparison of cohorts.

The properties of fiber reinforced polymers are strongly related to the length and orientation of the fibers within the polymer matrix, the latter of which can be studied using X-ray computed tomography (XCT). Unfortunately, resolving individual fibers is challenging because they are small compared to the XCT voxel resolution and because of the low attenuation contrast between the fibers and the surrounding resin. To alleviate both problems, anisotropic dark field tomography via grating based interferometry (GBI) has been proposed. Here, the fiber orientations are extracted by applying a Funk-Radon transform (FRT) to the local scatter function. However, the FRT suffers from a low angular resolution, which complicates estimating fiber orientations for small fiber crossing angles. We propose constrained spherical deconvolution (CSD) as an alternative to the FRT to resolve fiber orientations. Instead of GBI, edge illumination phase contrast imaging is used because estimating fiber orientations with this technique has not yet been explored. Dark field images are generated by a Monte Carlo simulation framework. It is shown that the FRT cannot estimate the fiber orientation accurately for crossing angles smaller than 70 ∘ , while CSD performs well down to a crossing angle of 50 ∘ . In general, CSD outperforms the FRT in estimating fiber orientations. [ABSTRACT FROM AUTHOR]

Detection of microstructural white matter injury in traumatic brain injury (TBI) requires specialised imaging methods, of which diffusion tensor imaging (DTI) has been extensively studied. Newer fibre alignment estimation methods, such as constrained spherical deconvolution (CSD), are better than DTI in resolving crossing fibres that are ubiquitous in the brain and may improve the ability to detect microstructural injuries. Furthermore, automatic tract segmentation has the potential to improve tractography reliability and accelerate workflow compared to the manual segmentation commonly used. In this study, we compared the results of deterministic DTI based tractography and manual tract segmentation with CSD based probabilistic tractography and automatic tract segmentation using TractSeg. 37 participants with a history of TBI (with Glasgow Coma Scale 13–15) and persistent symptoms, and 41 healthy controls underwent deterministic DTI-based tractography with manual tract segmentation and probabilistic CSD-based tractography with TractSeg automatic segmentation.Fractional anisotropy (FA) and mean diffusivity of corpus callosum and three bilateral association tracts were measured. FA and MD values derived from both tractography methods were generally moderately to strongly correlated. CSD with TractSeg differentiated the groups based on FA, while DTI did not. CSD and TractSeg-based tractography may be more sensitive in detecting microstructural changes associated with TBI than deterministic DTI tractography. Additionally, CSD with TractSeg was found to be applicable at lower b-value and number of diffusion-encoding gradients data than previously reported.

Background: Identifying early biomarkers of serious mental illness (SMI)—such as changes in brain structure and function—can aid in early diagnosis and treatment. Whole brain structural and functional connectomes were investigated in youth at risk for SMI. Methods: Participants were classified as healthy controls (HC; n = 33), familial risk for serious mental illness (stage 0; n = 31), mild symptoms (stage 1a; n = 37), attenuated syndromes (stage 1b; n = 61), or discrete disorder (transition; n = 9) based on clinical assessments. Imaging data was collected from two sites. Graph-theory based analysis was performed on the connectivity matrix constructed from whole-brain white matter fibers derived from constrained spherical deconvolution of the diffusion tensor imaging (DTI) scans, and from the correlations between brain regions measured with resting state functional magnetic resonance imaging (fMRI) data. Results: Linear mixed effects analysis and analysis of covariance revealed no significant differences between groups in global or nodal metrics after correction for multiple comparisons. A follow up machine learning analysis broadly supported the findings. Several non-overlapping frontal and temporal network differences were identified in the structural and functional connectomes before corrections. Conclusions: Results suggest significant brain connectome changes in youth at transdiagnostic risk may not be evident before illness onset. [ABSTRACT FROM AUTHOR]

The properties of fiber reinforced polymers are strongly related to the length and orientation of the fibers within the polymer matrix, the latter of which can be studied using X-ray computed tomography (XCT). Unfortunately, resolving individual fibers is challenging because they are small compared to the XCT voxel resolution and because of the low attenuation contrast between the fibers and the surrounding resin. To alleviate both problems, anisotropic dark field tomography via grating based interferometry (GBI) has been proposed. Here, the fiber orientations are extracted by applying a Funk-Radon transform (FRT) to the local scatter function. However, the FRT suffers from a low angular resolution, which complicates estimating fiber orientations for small fiber crossing angles. We propose constrained spherical deconvolution (CSD) as an alternative to the FRT to resolve fiber orientations. Instead of GBI, edge illumination phase contrast imaging is used because estimating fiber orientations with this technique has not yet been explored. Dark field images are generated by a Monte Carlo simulation framework. It is shown that the FRT cannot estimate the fiber orientation accurately for crossing angles smaller than 70∘, while CSD performs well down to a crossing angle of 50∘. In general, CSD outperforms the FRT in estimating fiber orientations.

Fiber tracking with diffusion magnetic resonance imaging provides a powerful tool for non-invasive observation of white matter in the brain. Constrained spherical deconvolution (CSD) is a multi-fiber tracking model, which can model the orientation of fibers in the voxel and achieve brain fiber reconstruction. This paper proposes a deterministic fiber tracking algorithm based on a non-local CSD model that combines neighborhood information and fractional regularization. The algorithm aimed to solve the ill-posed problem and loss detailed information in the conventional CSD model. The nonlocality of fractional order reduced the errors of fiber orientation distribution estimation, and the neighborhood information was used to ensure spatial consistency, reducing the effects of random noise. Simulation data and experimental human brain data were used to compare the performance of the proposed algorithm and the conventional CSD deterministic tracking algorithm. The results demonstrated that the proposed algorithm produced not only better overall visual effect, but also more complete and accurate reconstruction of the crossing fibers.

Purpose: The study aimed to (1) assess the feasibility constrained spherical deconvolution (CSD) tractography to reconstruct crossing fiber bundles with unsedated neonatal diffusion MRI (dMRI), and (2) demonstrate the impact of spatial and angular resolution and processing settings on tractography and derived quantitative measures., Methods: For the purpose of this study, the term-equivalent dMRIs (single-shell b800, and b2000, both 5 b0, and 45 gradient directions) of two moderate-late preterm infants (with and without motion artifacts) from a local cohort [Brain Imaging in Moderate-late Preterm infants (BIMP) study; Calgary, Canada] and one infant from the developing human connectome project with high-quality dMRI (using the b2600 shell, comprising 20 b0 and 128 gradient directions, from the multi-shell dataset) were selected. Diffusion tensor imaging (DTI) and CSD tractography were compared on b800 and b2000 dMRI. Varying image resolution modifications, (pre-)processing and tractography settings were tested to assess their impact on tractography. Each experiment involved visualizing local modeling and tractography for the corpus callosum and corticospinal tracts, and assessment of morphological and diffusion measures., Results: Contrary to DTI, CSD enabled reconstruction of crossing fibers. Tractography was susceptible to image resolution, (pre-) processing and tractography settings. In addition to visual variations, settings were found to affect streamline count, length, and diffusion measures (fractional anisotropy and mean diffusivity). Diffusion measures exhibited variations of up to 23%., Conclusion: Reconstruction of crossing fiber bundles using CSD tractography with unsedated neonatal dMRI data is feasible. Tractography settings affected streamline reconstruction, warranting careful documentation of methods for reproducibility and comparison of cohorts., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Verschuur, Tax, Boomsma, Carlson, van Wezel-Meijler, King, Leemans and Leijser.)

For advanced tongue cancer, the choice between surgery and organ-sparing treatment is often dependent on the expected loss of tongue functionality after treatment. Biomechanical models might assist in this choice by simulating the post-treatment function loss. However, this function loss varies between patients and should, therefore, be predicted for each patient individually. In the present study, the goal was to better predict the postoperative range of motion (ROM) of the tongue by personalizing biomechanical models using diffusion-weighted MRI and constrained spherical deconvolution reconstructions of tongue muscle architecture. Diffusion-weighted MRI scans of ten healthy volunteers were obtained to reconstruct their tongue musculature, which were subsequently registered to a previously described population average or atlas. Using the displacement fields obtained from the registration, the segmented muscle fiber tracks from the atlas were morphed back to create personalized muscle fiber tracks. Finite element models were created from the fiber tracks of the atlas and those of the individual tongues. Via inverse simulation of a protruding, downward, left and right movement, the ROM of the tongue was predicted. This prediction was compared to the ROM measured with a 3D camera. It was demonstrated that biomechanical models with personalized muscles bundles are better in approaching the measured ROM than a generic model. However, to achieve this result a correction factor was needed to compensate for the small magnitude of motion of the model. Future versions of these models may have the potential to improve the estimation of function loss after treatment for advanced tongue cancer. [ABSTRACT FROM AUTHOR]

Background: When investigating white matter (WM) microstructure, the axonal fiber orientation should be considered. Constrained spherical deconvolution (CSD) is a diffusion-weighted imaging (DWI) method that estimates distribution of fibers within each imaging voxel. Objective: To study fiber-bundle cross-section (FC) as measured by CSD in multiple sclerosis (MS) patients versus healthy controls (HCs). Methods: DWI and three-dimensional (3D) T1-weighted magnetic resonance imaging (MRI) were obtained from 45 MS patients and 45 HCs. We applied fixel-based morphometry analysis to assess differences of FC in MS against HCs and voxel-based analysis of fractional anisotropy (FA). Results: We found a significant widespread reduction of WM FC in MS compared to HCs. The decrease in FA was less extensive, mainly located in regions with high lesion occurrence such as the periventricular WM and the corpus callosum. Progressive MS patients showed a significant FC reduction in the right anterior cingulum, bilateral cerebellum, and in several mesencephalic and diencephalic regions compared to relapsing-remitting MS patients. Conclusion: The CSD method can be applied in MS for a fiber-specific study of WM microstructure and quantification of FC. Fixel-based findings offered greater anatomical specificity and biological interpretability by identifying tract-specific differences and allowed substantial abnormalities to be detected. [ABSTRACT FROM AUTHOR]

Subjective tinnitus is a symptom characterized by the perception of sound with no external acoustic source, most often accompanied by co-morbidities. To date, the specific role of white matter abnormalities related to tinnitus reaches no consensus in the literature. The goal of this study was to explore the structural connectivity related to tinnitus percept per se, thus focusing on a specific population presenting chronic non-bothersome tinnitus of similar etiology (noise induced) without co-morbidities. We acquired diffusion-weighted images with high angular resolution in a homogeneous group of mildly impacted tinnitus participants (n = 19) and their matched controls (n = 19). We focused the study on two subsets of fiber bundles of interest: on one hand, we extracted the acoustic radiation and further included any intersecting fiber bundles; on the other hand, we explored the tracts related to the limbic system. We modeled the diffusion signal using constrained spherical deconvolution. We conducted a deep-learning based tractography segmentation and mapped Apparent Fiber Density (AFD) on the bundles of interest. C, as well as Fractional Anisotropy (FA) and FOD peak amplitude for comparison. Between group statistical comparison was performed along the 27 tracts of interest controlling for confounding hearing loss, tinnitus severity, and duration since onset. We tested a potential correlation with hearing loss, tinnitus duration and tinnitus handicap score along these tracts. In the tinnitus group, we observed increased AFD related to chronic tinnitus percept after acoustic trauma in two main white matter regions. First, in the right hemisphere, in the isthmus between inferior temporal and inferior frontal cortices, in the uncinate fasciculus (UF), and in the inferior fronto-occipital bundle (IFO). Second, in the left hemisphere, underneath the superior parietal region in the thalamo parietal tract and parieto-occipital pontine tract. Between-group differences in the acoustic radiations were not significant with AFD but were with FA. Furthermore, significant correlations with hearing loss were found in the left hemisphere in the inferior longitudinal fasciculus and in the fronto-pontine tract. No additional correlation was found with tinnitus duration nor with tinnitus handicap, as reflected by THI scores. The regions that displayed tinnitus related increased AFD also displayed increased FA. The isthmus of the UF and IFO in the right hemisphere appear to be involved with a number of neuropsychiatric and traumatic disorders confirming the involvement of the limbic system even in chronic non-bothersome tinnitus subjects, potentially suggesting a common pathway between these pathologies. White matter changes underneath the superior parietal cortex found here in tinnitus participants supports the implication of an auditory-somatosensory pathway in tinnitus perception.

Gradient nonlinearities in magnetic resonance imaging (MRI) cause spatially varying mismatches between the imposed and the effective gradients and can cause significant biases in rotationally invariant diffusion MRI measures derived from, for example, diffusion tensor imaging. The estimation of the orientational organization of fibrous tissue, which is nowadays frequently performed with spherical deconvolution techniques ideally using higher diffusion weightings, can likewise be biased by gradient nonlinearities. We explore the sensitivity of two established spherical deconvolution approaches to gradient nonlinearities, namely constrained spherical deconvolution (CSD) and damped Richardson‐Lucy (dRL). Additionally, we propose an extension of dRL to take into account gradient imperfections, without the need of data interpolation. Simulations show that using the effective b‐matrix can improve dRL fiber orientation estimation and reduces angular deviations, while CSD can be more robust to gradient nonlinearity depending on the implementation. Angular errors depend on a complex interplay of many factors, including the direction and magnitude of gradient deviations, underlying microstructure, SNR, anisotropy of the effective response function, and diffusion weighting. Notably, angular deviations can also be observed at lower b‐values in contrast to the perhaps common assumption that only high b‐value data are affected. In in vivo Human Connectome Project data and acquisitions from an ultrastrong gradient (300 mT/m) scanner, angular differences are observed between applying and not applying the effective gradients in dRL estimation. As even small angular differences can lead to error propagation during tractography and as such impact connectivity analyses, incorporating gradient deviations into the estimation of fiber orientations should make such analyses more reliable. [ABSTRACT FROM AUTHOR]

Purpose: To demonstrate an optimized rectification strategy for fiber orientation density functions (fODFs). Theory and Methods: In white matter, fODFs can be estimated with diffusion MRI. However, because of signal noise, imaging artifacts and other factors, experimentally determined fODFs may take on unphysical negative values in some directions. Here, we show how to rectify such fODFs to eliminate all negative values while minimizing the mean square difference between the original and rectified fODFs. The method is demonstrated for a mathematical model and for fODFs estimated from experimental human data using both constrained spherical deconvolution and fiber ball imaging. Comparison with an alternative nonoptimized rectification approach is also provided. Results: For the mathematical model, it is found that the optimized rectification procedure removes negative fODF values while at the same time reducing the mean square error. Relative to the alternative rectification approach, the optimized fODFs are substantially more accurate. For the experimental data, the optimized fODFs have a lower average fractional anisotropy axonal and often fewer small peaks than the original, unrectified fODFs. The calculation of optimized fODFs is straightforward where the main step is the finding of the root to an equation in one variable, as may be efficiently accomplished with the bisection method. Conclusion: Unphysical negative fODF values can be easily eliminated in a manner that minimizes the mean square difference between the original and rectified fODFs. Optimized fODF rectification may be useful in applications for which negative values are problematic. [ABSTRACT FROM AUTHOR]

Recent advances in diffusion magnetic resonance imaging (dMRI) analysis techniques have improved our understanding of fibre‐specific variations in white matter microstructure. Increasingly, studies are adopting multi‐shell dMRI acquisitions to improve the robustness of dMRI‐based inferences. However, the impact of b‐value choice on the estimation of dMRI measures such as apparent fibre density (AFD) derived from spherical deconvolution is not known. Here, we investigate the impact of b‐value sampling scheme on estimates of AFD. First, we performed simulations to assess the correspondence between AFD and simulated intra‐axonal signal fraction across multiple b‐value sampling schemes. We then studied the impact of sampling scheme on the relationship between AFD and age in a developmental population (n = 78) aged 8–18 (mean = 12.4, SD = 2.9 years) using hierarchical clustering and whole brain fixel‐based analyses. Multi‐shell dMRI data were collected at 3.0T using ultra‐strong gradients (300 mT/m), using 6 diffusion‐weighted shells ranging from b = 0 to 6,000 s/mm2. Simulations revealed that the correspondence between estimated AFD and simulated intra‐axonal signal fraction was improved with high b‐value shells due to increased suppression of the extra‐axonal signal. These results were supported by in vivo data, as sensitivity to developmental age‐relationships was improved with increasing b‐value (b = 6,000 s/mm2, median R2 =.34; b = 4,000 s/mm2, median R2 =.29; b = 2,400 s/mm2, median R2 =.21; b = 1,200 s/mm2, median R2 =.17) in a tract‐specific fashion. Overall, estimates of AFD and age‐related microstructural development were better characterised at high diffusion‐weightings due to improved correspondence with intra‐axonal properties. [ABSTRACT FROM AUTHOR]

Because of their high prevalence, heterogeneous clinical presentation, and wide-ranging sequelae, concussions are a challenging neurological condition, especially in children. Shearing forces transmitted across the brain during concussions often result in white matter damage. The neuropathological impact of concussions has been discerned from animal studies and includes inflammation, demyelination, and axonal loss. These pathologies can overlap during the sub-acute stage of recovery. However, due to the challenges of accurately modeling complex white matter structure, these neuropathologies have not yet been differentiated in children in vivo. In the present study, we leveraged recent advances in diffusion imaging modeling, tractography, and tractometry to better understand the neuropathology underlying working memory problems in concussion. Studying a sample of 16 concussed and 46 healthy youths, we used novel tractography methods to isolate 11 working memory tracks. Along these tracks, we measured fractional anisotropy, diffusivities, track volume, apparent fiber density, and free water fraction. In three tracks connecting the right thalamus to the right dorsolateral prefrontal cortex (DLPFC), we found microstructural differences suggestive of myelin alterations. In another track connecting the left anterior-cingulate cortex with the left DLPFC, we found microstructural changes suggestive of axonal loss. Structural differences and tractography reconstructions were reproduced using test–retest analyses. White matter structure in the three thalamo-prefrontal tracks, but not the cingulo-prefrontal track, appeared to play a key role in working memory function. The present results improve understanding of working memory neuropathology in concussions, which constitutes an important step toward developing neuropathologically informed biomarkers of concussion in children. [ABSTRACT FROM AUTHOR]

Objectives: In this pilot study we investigated the effects of transcranial direct current stimulation (tDCS) on language recovery in the subacute stage of post-stroke aphasia using clinical parameters and diffusion imaging with constrained spherical deconvolution-based tractography. Methods: The study included 21 patients with subacute post-stroke aphasia. Patients were randomly classified into two groups with a ratio of 2:1 to receive real tDCS or sham tDCS as placebo control. Patients received 10 sessions (5/week) bi-hemispheric tDCS treatments over the left affected Broca’s area (anodal electrode) and over the right unaffected Broca’s area (cathodal stimulation). Aphasia score was assessed clinically using the language section of the Hemispheric Stroke Scale (HSS) before and after treatment sessions. Diffusion imaging and tractography were performed for seven patients of the real group, both before and after the 10th session. Dissection of language-related white matter tracts was achieved, and diffusion measures were extracted. A paired Student’s t-test was used to compare the clinical recovery and diffusion measures of the dissected tracts both pre- and post- treatment. The partial correlation between changes in diffusion measures and the language improvements was calculated. Results: At baseline assessment, there were no significant differences between groups in demographic and clinical HSS language score. No significant clinical recovery in HSS was evident in the sham group. However, significant improvements in the different components of HSS were only observed in patients receiving real tDCS. Associated significant increase in the fractional anisotropy of the right uncinate fasciculus and a significant reduction in the mean diffusivity of the right frontal aslant tract were reported. A significant positive correlation was found between the changes in the right uncinate fasciculus and fluency improvement. Conclusions: Aphasia recovery after bi-hemispheric transcranial direct current stimulation was associated with contralesional right-sided white matter changes at the subacute stage. These changes probably reflect neuroplasticity that could contribute to the recovery. Both the right uncinate fasciculus and right frontal aslant tract seem to be involved in aphasia recovery.

Purpose: In diffusion‐weighted magnetic resonance imaging (DW‐MRI), the fiber orientation distribution function (fODF) is of great importance for solving complex fiber configurations to achieve reliable tractography throughout the brain, which ultimately facilitates the understanding of brain connectivity and exploration of neurological dysfunction. Recently, multi‐shell multi‐tissue constrained spherical deconvolution (MSMT‐CSD) method has been explored for reconstructing full fODFs. To achieve a reliable fitting, similar to other model‐based approaches, a large number of diffusion measurements is typically required for MSMT‐CSD method. The prolonged acquisition is, however, not feasible in practical clinical routine and is prone to motion artifacts. To accelerate the acquisition, we proposed a method to reconstruct the fODF from downsampled diffusion‐weighted images (DWIs) by leveraging the strong inference ability of the deep convolutional neural network (CNN). Methods: The method treats spherical harmonics (SH)‐represented DWI signals and fODF coefficients as inputs and outputs, respectively. To compensate for the reduced gradient directions with reduced number of DWIs in acquisition in each voxel, its surrounding voxels are incorporated by the network for exploiting their spatial continuity. The resulting fODF coefficients are fitted with applying the CNN in a multi‐target regression model. The network is composed of two convolutional layers and three fully connected layers. To obtain an initial evaluation of the method, we quantitatively measured its performance on a simulated dataset. Then, for in vivo tests, we employed data from 24 subjects from the Human Connectome Project (HCP) as training set and six subjects as test set. The performance of the proposed method was primarily compared to the super‐resolved MSMT‐CSD with the decreasing number of DWIs. The fODFs reconstructed by MSMT‐CSD from all available 288 DWIs were used as training labels and the reference standard. The performance was quantitatively measured by the angular correlation coefficient (ACC) and the mean angular error (MAE). Results: For the simulated dataset, the proposed method exhibited the potential advantage over the model reconstruction. For the in vivo dataset, it achieved superior results over the MSMT‐CSD in all the investigated cases, with its advantage more obvious when a limited number of DWIs were used. As the number of DWIs was reduced from 95 to 25, the median ACC ranged from 0.96 to 0.91 for the CNN, but 0.93 to 0.77 for the MSMT‐CSD (with perfect score of 1). The angular error in the typical regions of interest (ROIs) was also much lower, especially in multi‐fiber regions. The average MAE for the CNN method in regions containing one, two, three fibers was, respectively, 1.09°, 2.75°, and 8.35° smaller than the MSMT‐CSD method. The visual inception of the fODF further confirmed this superiority. Moreover, the tractography results validated the effectiveness of the learned fODF, in preserving known major branching fibers with only 25 DWIs. Conclusion: Experiments on HCP datasets demonstrated the feasibility of the proposed method in recovering fODFs from up to 11‐fold reduced number of DWIs. The proposed method offers a new streamlined reconstruction procedure and exhibits promising potential in acquisition acceleration for the reconstruction of fODFs with good accuracy. [ABSTRACT FROM AUTHOR]

Background: Surgical resection of tongue cancer may impair swallowing and speech. Knowledge of tongue muscle architecture affected by the resection could aid in patient counseling. Diffusion tensor imaging (DTI) enables reconstructions of muscle architecture in vivo. Reconstructing crossing fibers in the tongue requires a higher-order diffusion model.Purpose: To develop a clinically feasible diffusion imaging protocol, which facilitates both DTI and constrained spherical deconvolution (CSD) reconstructions of tongue muscle architecture in vivo.Study Type: Cross-sectional study.Subjects/specimen: One ex vivo bovine tongue resected en bloc from mandible to hyoid bone. Ten healthy volunteers (mean age 25.5 years; range 21-34 years; four female).Field Strength/sequence: Diffusion-weighted echo planar imaging at 3 T using a high-angular resolution diffusion imaging scheme acquired twice with opposing phase-encoding for B0 -field inhomogeneity correction. The scan of the healthy volunteers was divided into four parts, in between which the volunteers were allowed to swallow, resulting in a total acquisition time of 10 minutes.Assessment: The ability of resolving crossing muscle fibers using CSD was determined on the bovine tongue specimen. A reproducible response function was estimated and the optimal peak threshold was determined for the in vivo tongue. The quality of tractography of the in vivo tongue was graded by three experts.Statistical Tests: The within-subject coefficient of variance was calculated for the response function. The qualitative results of the grading of DTI and CSD tractography were analyzed using a multilevel proportional odds model.Results: Fiber orientation distributions in the bovine tongue specimen showed that CSD was able to resolve crossing muscle fibers. The response function could be determined reproducibly in vivo. CSD tractography displayed significantly improved tractography compared with DTI tractography (P = 0.015).Data Conclusion: The 10-minute diffusion imaging protocol facilitates CSD fiber tracking with improved reconstructions of crossing tongue muscle fibers compared with DTI.Level Of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:96-105. [ABSTRACT FROM AUTHOR]

Highlights • Reproducibility of CSD-based structural brain connectomics is generally excellent. • A minimum of one million streamlines are required for excellent reproducibility. • Reproducibility continues to increase further for higher numbers of streamlines. • Thresholds in the reconstruction of binary networks should be sufficiently high. • Higher order models decrease the reproducibility, but only slightly. Abstract Diffusion-weighted magnetic resonance imaging can be used to non-invasively probe the brain microstructure. In addition, recent advances have enabled the identification of complex fiber configurations present in most of the white matter. This has improved the investigation of structural connectivity with tractography methods. Whole-brain structural connectivity networks, or connectomes, are reconstructed by parcellating the gray matter and performing tractography to determine connectivity between these regions. These complex networks can be analyzed with graph theoretical methods, which measure their global and local properties. However, as these tools have only recently been applied to structural brain networks, there is little information about the reproducibility and intercorrelation of network properties, connectivity weights and fiber tractography reconstruction parameters in the brain. We studied the reproducibility and correlation in structural brain connectivity networks reconstructed with constrained spherical deconvolution based probabilistic streamlines tractography. Diffusion-weighted data from 19 subjects were acquired with b = 2800 s/mm2 and 75 gradient orientations. Intrasubject variability was computed with residual bootstrapping. Our findings indicate that the reproducibility of graph theoretical metrics is generally excellent with the exception of betweenness centrality. A reconstruction density of approximately one million streamlines is necessary for excellent reproducibility, but the reproducibility increases further with higher densities. The reproducibility decreases, but only slightly, when switching to a higher order in constrained spherical deconvolution. Moreover, in binary networks, using sufficiently high threshold values improves the reproducibility. We show that multiple network properties and connectivity weights are highly intercorrelated. The experiments were replicated by using a test-retest dataset of 44 healthy subjects provided by the Human Connectome Project. In conclusion, our results provide guidelines for reproducible investigation of structural brain networks. Graphical abstract Image, graphical abstract [ABSTRACT FROM AUTHOR]

Abstract Purpose We propose a new along-tract algorithm to compare different tractography algorithms in tract curvature mapping and along-tract analysis of the arcuate fasciculus (AF). In particular, we quantified along-tract diffusion parameters and AF spatial distribution evaluating hemispheric asymmetries in a group of healthy subjects. Methods The AF was bilaterally reconstructed in a group of 29 healthy subjects using the probabilistic ball-and-sticks model, and both deterministic and probabilistic constrained spherical deconvolution. We chose cortical ROIs as tractography targets and the developed along-tract algorithm used the Laplacian operator to parameterize the volume of the tract, allowing along-tract analysis and tract curvature mapping independent of the tractography algorithm used. Results The Laplacian parameterization successfully described the tract geometry underlying hemispheric asymmetries in the AF curvature. Using the probabilistic tractography methods, we found more tracts branching towards cortical terminations in the left hemisphere. This influenced the left AF curvature and its diffusion parameters, which were significantly different with respect to the right. In particular, we detected projections towards the middle temporal and inferior frontal gyri bilaterally, and towards the superior temporal and precentral gyri in the left hemisphere, with a significantly increased volume and connectivity. Conclusions The approach we propose is useful to evaluate brain asymmetries, assessing the volume, the diffusion properties and the quantitative spatial localization of the AF. [ABSTRACT FROM AUTHOR]

Diffusion tensor imaging (DTI)-based tractography has been used to demonstrate functionally relevant differences in white matter pathway status after stroke. However, it is now known that the tensor model is insensitive to the complex fiber architectures found in the vast majority of voxels in the human brain. The inability to resolve intra-voxel fiber orientations may have important implications for the utility of standard DTI-based tract reconstruction methods. Intra-voxel fiber orientations can now be identified using novel, tensor-free approaches. Constrained spherical deconvolution (CSD) is one approach to characterize intra-voxel diffusion behavior. In the current study, we performed DTI- and CSD-based tract reconstruction of the corticospinal tract (CST) and corpus callosum (CC) to test the hypothesis that characterization of complex fiber orientations may improve the robustness of fiber tract reconstruction and increase the sensitivity to identify functionally relevant white matter abnormalities in individuals with chronic stroke. Diffusion weighted magnetic resonance imaging was performed in 27 chronic post-stroke participants and 12 healthy controls. Transcallosal pathways and the CST bilaterally were reconstructed using DTI- and CSD-based tractography. Mean fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusivity (AD), and radial diffusivity (RD) were calculated across the tracts of interest. The total number and volume of reconstructed tracts was also determined. Diffusion measures were compared between groups (Stroke, Control) and methods (CSD, DTI). The relationship between post-stroke motor behavior and diffusion measures was evaluated. Overall, CSD methods identified more tracts than the DTI-based approach for both CC and CST pathways. Mean FA, ADC, and RD differed between DTI and CSD for CC-mediated tracts. In these tracts, we discovered a difference in FA for the CC between stroke and healthy control groups using CSD but not DTI. CSD identified ipsilesional CST pathways in 9 stroke participants who did not have tracts identified with DTI. Additionally, CSD differentiated between stroke ipsilesional and healthy control non-dominant CST for several measures (number of tracts, tract volume, FA, ADC, and RD) whereas DTI only detected group differences for number of tracts. In the stroke group, motor behavior correlated with fewer diffusion metrics derived from the DTI as compared to CSD-reconstructed ipsilesional CST and CC. CSD is superior to DTI-based tractography in detecting differences in diffusion characteristics between the nondominant healthy control and ipsilesional CST. CSD measures of microstructure tissue properties related to more motor outcomes than DTI measures did. Our results suggest the potential utility and functional relevance of characterizing complex fiber organization using tensor-free diffusion modeling approaches to investigate white matter pathways in the brain after stroke.

In this study we described a case of lipofibromatous hamartoma involving the median nerve. We adopted diffusion tensor imaging and constrained spherical deconvolution-based tractography to reconstruct the affected median nerve. Moreover, we extracted diffusion-based parameters reflecting axonal integrity loss of median nerve fibres. Our data showed that constrained spherical deconvolution-based tractography outperformed the diffusion tensor imaging-based method, allowing the detection of the entire median nerve, including its branches, thus offering a robust method to investigate the involvement of the median nerve in pathological conditions. All clinical and technical implications are extensively described. [ABSTRACT FROM AUTHOR]

Background: In Parkinson's disease cognitive impairment is an early nonmotor feature, but it is still unclear why some patients are able to maintain their cognitive performance at normal levels, as quantified by neuropsychological tests, whereas others cannot. The objectives of this study were to perform a cross-sectional study and analyze the white matter changes in the cognitive and motor bundles in patients with Parkinson's disease.Methods: Sixteen Parkinson's disease patients with normal cognitive performance, 19 with mild cognitive impairment (based on their performance of 1.5 standard deviations below the healthy population mean), and 16 healthy controls were compared with respect to their tractography patterns between the cortical cognitive / motor regions and subcortical structures, using high angular resolution diffusion imaging and constrained spherical deconvolution computation.Results: Motor bundles showed decreased apparent fiber density in both PD groups, associated with a significant increase in diffusivity metrics, number of reconstructed streamlines, and track volumes, compared with healthy controls. By contrast, in the cognitive bundles, decreased fiber density in both Parkinson's groups was compounded by the absence of changes in diffusivity in patients with normal cognition, whereas patients with cognitive impairment had increased diffusivity metrics, lower numbers of reconstructed streamlines, and lower track volumes.Conclusions: Both PD groups showed similar patterns of white matter neurodegeneration in the motor bundles, whereas cognitive bundles showed a distinct pattern: Parkinson's patients with normal cognition had white matter diffusivity metrics similar to healthy controls, whereas in patients with cognitive impairment white matter showed a neurodegeneration pattern. © 2018 International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Diffusion MRI (dMRI)-based tractography offers unique abilities to map whole-brain structural connections in human and animal brains. However, dMRI-based tractography indirectly measures white matter tracts, with suboptimal accuracy and reliability. Recently, sophisticated methods including constrained spherical deconvolution (CSD) and global tractography have been developed to improve tract reconstructions through modeling of more complex fiber orientations. Our study aimed to determine the accuracy of connectome reconstruction for three dMRI-based tractography approaches: diffusion tensor (DT)-based, CSD-based and global tractography. Therefore, we validated whole brain structural connectome reconstructions based on ten ultrahigh-resolution dMRI rat brain scans and 106 cortical regions, from which varying tractography parameters were compared against standardized neuronal tracer data. All tested tractography methods generated considerable numbers of false positive and false negative connections. There was a parameter range trade-off between sensitivity: 0.06-0.63 interhemispherically and 0.22-0.86 intrahemispherically; and specificity: 0.99-0.60 interhemispherically and 0.99-0.23 intrahemispherically. Furthermore, performance of all tractography methods decreased with increasing spatial distance between connected regions. Similar patterns and trade-offs were found, when we applied spherical deconvolution informed filtering of tractograms, streamline thresholding and group-based average network thresholding. Despite the potential of CSD-based and global tractography to handle complex fiber orientations at voxel level, reconstruction accuracy, especially for long-distance connections, remains a challenge. Hence, connectome reconstruction benefits from varying parameter settings and combination of tractography methods to account for anatomical variation of neuronal pathways. [ABSTRACT FROM AUTHOR]

Diffusion-weighted imaging (DWI)-based tractography has gained increasing popularity as a method for detailed visualization of white matter (WM) tracts. Different imaging techniques, and more novel, advanced imaging methods provide significant WM structural detail. While there has been greater focus on improving tract visualization for larger WM pathways, the relative value of each method for cranial nerve reconstruction and how this methodology can assist surgical decision-making is still understudied. Images from 10 patients with posterior fossa tumors (4 male, mean age: 63.5), affecting either the trigeminal nerve (CN V) or the facial/vestibular complex (CN VII/VIII), were employed. Three distinct reconstruction methods [two tensor-based methods: single diffusion tensor tractography (SDT) (3D Slicer), eXtended streamline tractography (XST), and one fiber orientation distribution (FOD)-based method: streamline tractography using constrained spherical deconvolution (CSD)-derived estimates (MRtrix3)], were compared to determine which of these was best suited for use in a neurosurgical setting in terms of processing speed, anatomical accuracy, and accurate depiction of the relationship between the tumor and affected CN. Computation of the tensor map was faster when compared to the implementation of CSD to provide estimates of FOD. Both XST and CSD-based reconstruction methods tended to give more detailed representations of the projections of CN V and CN VII/VIII compared to SDT. These reconstruction methods were able to more accurately delineate the course of CN V and CN VII/VIII, differentiate CN V from the cerebellar peduncle, and delineate compression of CN VII/VIII in situations where SDT could not. However, CSD-based reconstruction methods tended to generate more invalid streamlines. XST offers the best combination of anatomical accuracy and speed of reconstruction of cranial nerves within this patient population. Given the possible anatomical limitations of single tensor models, supplementation with more advanced tensor-based reconstruction methods might be beneficial.

The current model of basal ganglia circuits has been introduced almost two decades ago and has settled the basis for our understanding of basal ganglia physiology and movement disorders. Although many questions are yet to be answered, several efforts have been recently made to shed new light on basal ganglia function. The traditional concept of “direct” and “indirect” pathways, obtained from axonal tracing studies in non-human primates and post-mortem fiber dissection in the human brain, still retains a remarkable appeal but is somehow obsolete. Therefore, a better comprehension of human structural basal ganglia connectivity in vivo, in humans, is of uttermost importance given the involvement of these deep brain structures in many motor and non-motor functions as well as in the pathophysiology of several movement disorders. By using diffusion magnetic resonance imaging and tractography, we have recently challenged the traditional model of basal ganglia network by showing the possible existence, in the human brain, of cortico-pallidal, cortico-nigral projections, which could be mono- or polysynaptic, and an extensive subcortical network connecting the cerebellum and basal ganglia. Herein, we aimed at reconstructing the basal ganglia connectome providing a quantitative connectivity analysis of the reconstructed pathways. The present findings reinforce the idea of an intricate, not yet unraveled, network involving the cerebral cortex, basal ganglia, and cerebellum. Our findings may pave the way for a more comprehensive and holistic pathophysiological model of basal ganglia circuits.

IntroductionDiffusion-weighted magnetic resonance imaging (DW-MRI) allows noninvasive investigation of brain structure in vivo. Diffusion tensor imaging (DTI) is a frequently used application of DW-MRI that assumes a single main diffusion direction per voxel, and is therefore not well suited for reconstructing crossing fiber tracts. Among the solutions developed to overcome this problem, constrained spherical deconvolution with probabilistic tractography (CSD-PT) has provided superior quality results in clinical settings on adult subjects; however, it requires particular acquisition parameters and long sequences, which may limit clinical usage in the pediatric age group. The aim of this work was to compare the results of DTI with those of track density imaging (TDI) maps and CSD-PT on data from neonates and children, acquired with low angular resolution and low b-value diffusion sequences commonly used in pediatric clinical MRI examinations.Materials and methodsWe analyzed DW-MRI studies of 50 children (eight neonates aged 3–28 days, 20 infants aged 1–8 months, and 22 children aged 2–17 years) acquired on a 1.5 T Philips scanner using 34 gradient directions and a b-value of 1,000 s/mm2. Other sequence parameters included 60 axial slices; acquisition matrix, 128 × 128; average scan time, 5:34 min; voxel size, 1.75 mm × 1.75 mm × 2 mm; one b = 0 image. For each subject, we computed principal eigenvector (EV) maps and directionally encoded color TDI maps (DEC-TDI maps) from whole-brain tractograms obtained with CSD-PT; the cerebellar-thalamic, corticopontocerebellar, and corticospinal tracts were reconstructed using both CSD-PT and DTI. Results were compared by two neuroradiologists using a 5-point qualitative score.ResultsThe DEC-TDI maps obtained presented higher anatomical detail than EV maps, as assessed by visual inspection. In all subjects, white matter (WM) tracts were successfully reconstructed using both tractography methodologies. The mean qualitative scores of all tracts obtained with CSD-PT were significantly higher than those obtained with DTI (p-value

Diffusion-weighted imaging (DWI)-based tractography has gained increasing popularity as a method for detailed visualization of white matter (WM) tracts. Different imaging techniques, and more novel, advanced imaging methods provide significant WM structural detail. While there has been greater focus on improving tract visualization for larger WM pathways, the relative value of each method for cranial nerve reconstruction and how this methodology can assist surgical decision-making is still understudied. Images from 10 patients with posterior fossa tumors (4 male, mean age: 63.5), affecting either the trigeminal nerve (CN V) or the facial/vestibular complex (CN VII/VIII), were employed. Three distinct reconstruction methods [two tensor-based methods: single diffusion tensor tractography (SDT) (3D Slicer), eXtended streamline tractography (XST), and one fiber orientation distribution (FOD)-based method: streamline tractography using constrained spherical deconvolution (CSD)-derived estimates (MRtrix3)], were compared to determine which of these was best suited for use in a neurosurgical setting in terms of processing speed, anatomical accuracy, and accurate depiction of the relationship between the tumor and affected CN. Computation of the tensor map was faster when compared to the implementation of CSD to provide estimates of FOD. Both XST and CSD-based reconstruction methods tended to give more detailed representations of the projections of CN V and CN VII/VIII compared to SDT. These reconstruction methods were able to more accurately delineate the course of CN V and CN VII/VIII, differentiate CN V from the cerebellar peduncle, and delineate compression of CN VII/VIII in situations where SDT could not. However, CSD-based reconstruction methods tended to generate more invalid streamlines. XST offers the best combination of anatomical accuracy and speed of reconstruction of cranial nerves within this patient population. Given the possible anatomical limitations of single tensor models, supplementation with more advanced tensor-based reconstruction methods might be beneficial. [ABSTRACT FROM AUTHOR]

The current model of basal ganglia circuits has been introduced almost two decades ago and has settled the basis for our understanding of basal ganglia physiology and movement disorders. Although many questions are yet to be answered, several efforts have been recently made to shed new light on basal ganglia function. The traditional concept of "direct" and "indirect" pathways, obtained from axonal tracing studies in non-human primates and post-mortem fiber dissection in the human brain, still retains a remarkable appeal but is somehow obsolete. Therefore, a better comprehension of human structural basal ganglia connectivity in vivo, in humans, is of uttermost importance given the involvement of these deep brain structures in many motor and non-motor functions as well as in the pathophysiology of several movement disorders. By using diffusion magnetic resonance imaging and tractography, we have recently challenged the traditional model of basal ganglia network by showing the possible existence, in the human brain, of cortico-pallidal, cortico-nigral projections, which could be mono- or polysynaptic, and an extensive subcortical network connecting the cerebellum and basal ganglia. Herein, we aimed at reconstructing the basal ganglia connectome providing a quantitative connectivity analysis of the reconstructed pathways. The present findings reinforce the idea of an intricate, not yet unraveled, network involving the cerebral cortex, basal ganglia, and cerebellum. Our findings may pave the way for a more comprehensive and holistic pathophysiological model of basal ganglia circuits. [ABSTRACT FROM AUTHOR]

Purpose: Complex claustral connection network was widely demonstrated both in humans and animals. Moreover, several studies have suggested that claustral connections directly involve also the contralateral hemisphere. Detection of contralateral cortico-claustral and inter-claustral connections was reported mainly in animals and only partially in humans. The main purpose of this study was to provide more robust tractography-driven support of the existence of inter-hemispheric claustral connections in humans, by means of a dedicated optimized tractographic protocol. Methods: Fifteen healthy subjects were examined by means of an advanced magnetic resonance imaging-based probabilistic constrained spherical deconvolution tractographic protocol. Moreover, quantitative diffusion parameters were extracted by each reconstructed pathway. Results: In this study, further imaging-based support on the possible existence in humans of contralateral cortico-claustral and inter-claustral connections was provided. These connections were found to involve almost all the superior portion of each claustrum, showing a topographical organization. Moreover, the detection of inter-claustral connections passing through the anterior commissure was reported, for the first time, in humans. Conclusions: The possible existence of inter-claustral and cortico-claustral contralateral pathways might provide the morphological basis for the complex functional phenomena observed in previous studies. Furthermore, these connections might have several important clinical implications, since they might explain how the inter-hemispheric coordination governed by the claustrum, as well as the functional recovery subsequent to damages involving one claustrum, takes place. [ABSTRACT FROM AUTHOR]

Purpose: Develop a multi-fiber tractography method that produces fast and robust results based on input data from a wide range of diffusion MRI protocols, including high angular resolution diffusion imaging, multi-shell imaging, and clinical diffusion spectrum imaging (DSI) Methods: In a unified deconvolution framework for different types of diffusion MRI protocols, we represent fiber orientation distribution functions as higher-order tensors, which permits use of a novel positive definiteness constraint (H-psd) that makes estimation from noisy input more robust. The resulting directions are used for deterministic fiber tracking with branching. Results: We quantify accuracy on simulated data, as well as condition numbers and computation times on clinical data. We qualitatively investigate the benefits when processing suboptimal data, and show direct comparisons to several state-of-the-art techniques. Conclusion: The proposed method works faster than state-of-the-art approaches, achieves higher angular resolution on simulated data with known ground truth, and plausible results on clinical data. In addition to working with the same data as previous methods for multi-tissue deconvolution, it also supports DSI data. [ABSTRACT FROM AUTHOR]

The organisational and architectural configuration of white matter pathways connecting brain regions has ramifications for all facets of the human condition, including manifestations of incipient neurodegeneration. Although diffusion tensor imaging (DTI) has been used extensively to visualise white matter connectivity, due to the widespread presence of crossing fibres, the lateral projections of the corpus callosum are not normally detected using this methodology. Detailed knowledge of the transcallosal connectivity of the human cortical motor network has, therefore, remained elusive. We employed constrained spherical deconvolution (CSD) tractography-an approach that is much less susceptible to the influence of crossing fibres, in order to derive complete in vivo characterizations of white matter pathways connecting specific motor cortical regions to their counterparts and other loci in the opposite hemisphere. The revealed patterns of connectivity closely resemble those derived from anatomical tracing in primates. It was established that dorsal premotor cortex (PMd) and supplementary motor area (SMA) have extensive interhemispheric connectivity-exhibiting both dense homologous projections, and widespread structural relations with every other region in the contralateral motor network. Through this in vivo portrayal, the importance of non-primary motor regions for interhemispheric communication is emphasised. Additionally, distinct connectivity profiles were detected for the anterior and posterior subdivisions of primary motor cortex. The present findings provide a comprehensive representation of transcallosal white matter projections in humans, and have the potential to inform the development of models and hypotheses relating structural and functional brain connectivity. [ABSTRACT FROM AUTHOR]

To characterize the anatomical connectivity of the prelemniscal radiations (Raprl), a white matter region within the posterior subthalamic area (PSA) that is an effective neurosurgical target for treating motor symptoms of Parkinson's disease (PD). Diffusion-weighted images were acquired from twelve healthy subjects using a 3T scanner. Constrained spherical deconvolution, a method that allows the distinction of crossing fibers within a voxel, was used to compute track-density images with sufficient resolution to accurately delineate distinct PSA regions and probabilistic tractography of Raprl in both hemispheres. Raprl connectivity was reproducible across all subjects and showed fibers traversing through this region towards primary and supplementary motor cortices, the orbitofrontal cortex, ventrolateral thalamus, and the globus pallidus, cerebellum and dorsal brainstem. All brain regions reached by Raprl fibers are part of motor circuits involved in the pathophysiology of PD; while these fiber systems converge at the level of the PSA, they can be spatially segregated. Fibers of distinct and specific motor control networks are identified within Raprl. The description of this anatomical crossroad suggests that, in the future, tractography could allow deep brain stimulation or lesional therapies in white matter targets according to individual patient's symptoms. [ABSTRACT FROM AUTHOR]

A growing body of work utilizing structural and functional brain imaging and neurocognitive measures of executive and attentional function indicates anomalous asymmetry in ADHD. This study examined the white-matter volume and diffusion properties of frontostriatal tracts, as a function of hemisphere, in ADHD and healthy controls. Forty-three young males (21 ADHD-Combined Type and 22 controls) aged 10-18 years underwent structural and diffusion weighted MRI. Tractography applying constrained spherical deconvolution (CSD) was used to construct frontostriatal tracts between each of caudate and putamen and each of dorsolateral prefrontal, ventrolateral prefrontal and orbitofrontal cortices (DLPFC, VLPFC and OFC) in each hemisphere, to examine both volumetric and diffusion microstructure properties. Young people with ADHD did not show the right hemisphere lateralization of volume in the Caudate-VLPFC and Caudate-DLPFC tracts that was evident in controls, however the ADHD group displayed a pronounced lateralization to the left for fractional anisotropy in the Putamen-VLPFC tracts. The degree of volume asymmetry did not correlate with symptom severity; however fractional anisotropy (FA) values that were more strongly lateralized to the left in the Putamen-VLPFC white matter were associated with greater symptom severity. ADHD was associated with anomalous hemispheric asymmetries in both tract volume and underlying white-matter microstructure in major fibre tracts of the frontostriatal system. Our observations of both weaker lateralization to the right in terms of tract volume and stronger lateralization to the left in terms of FA values for the ADHD group, suggests that previous inconsistencies in the literature may reflect the influence of such asymmetries. [ABSTRACT FROM AUTHOR]

Introduction: The need to improve surgical efficacy in patients affected by high-grade gliomas has led to development of advanced pre-surgical MRI-based techniques such as tractography. This study investigates pre-surgical planning of optic radiations (ORs) in patients affected by occipito-temporo-parietal high-grade gliomas, by means of constrained spherical deconvolution (CSD) and diffusion tensor imaging (DTI) tractography. Methods: Twelve patients with occipito-temporo-parietal high-grade gliomas were recruited and analyzed using a 3 T MRI scanner. Diffusion-weighted imaging (DWI) was conducted with 64 gradient diffusion directions. OR alterations were assessed qualitatively and quantitatively to evaluate the effectiveness of CSD- and DTI-based pre-surgical planning. Results: CSD-based tractography provided better qualitative evaluation of affected white matter tracts when compared to DTI; by thresholding tractographic probabilistic maps coming from all reconstructions, we detected, at the highest cutoff level, OR involvement in 75 % of patients (vs 41.67 % of patients with probabilistic DTI). Quantitative analysis of diffusion parameters revealed a statistically significant decrease in fractional anisotropy (FA) in the affected side following CSD-based reconstructions; on the contrary, DTI-based reconstructions did not show any significant quantitative alteration. Conclusion: Our results showed improvement in pre-surgical planning of high-grade gliomas involving ORs with use of CSD-based tractography. This technique provided more useful information regarding the white matter spatial relationship with brain neoplasm and its involvement in the glioma, when compared to DTI. Using CSD model for OR evaluation may optimize safe surgical resection margins, helping to reduce risk of post-operative visual deficits. [ABSTRACT FROM AUTHOR]

Background Diffusion-weighted magnetic resonance imaging (DW-MRI) is commonly used to assess white matter properties after stroke. Novel work is utilizing constrained spherical deconvolution (CSD) to estimate complex intra-voxel fiber architecture unaccounted for with tensor-based fiber tractography. However, the reliability of CSD-based tractography has not been established in people with chronic stroke. New method Establishing the reliability of CSD-based DW-MRI in chronic stroke. High-resolution DW-MRI was performed in ten adults with chronic stroke during two separate sessions. Deterministic region of interest-based fiber tractography using CSD was performed by two raters. Mean fractional anisotropy (FA), apparent diffusion coefficient (ADC), tract number, and tract volume were extracted from reconstructed fiber pathways in the corticospinal tract (CST) and superior longitudinal fasciculus (SLF). Callosal fiber pathways connecting the primary motor cortices were also evaluated. Inter-rater and test–retest reliability were determined by intra-class correlation coefficients (ICCs). Results ICCs revealed excellent reliability for FA and ADC in ipsilesional (0.86–1.00; p < 0.05) and contralesional hemispheres (0.94–1.00; p < 0.0001), for CST and SLF fibers; and excellent reliability for all metrics in callosal fibers (0.85–1.00; p < 0.05). ICC ranged from poor to excellent for tract number and tract volume in ipsilesional (−0.11 to 0.92; p ≤ 0.57) and contralesional hemispheres (−0.27 to 0.93; p ≤ 0.64), for CST and SLF fibers. Comparison with existing method Like other select DW-MRI approaches, CSD-based tractography is a reliable approach to evaluate FA and ADC in major white matter pathways, in chronic stroke. Conclusion Future work should address the reproducibility and utility of CSD-based metrics of tract number and tract volume. [ABSTRACT FROM AUTHOR]

Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a noninvasive imaging method, which can be used to investigate neural tracts in the white matter (WM) of the brain. Significant partial volume effects (PVE) are present in the DW signal due to relatively large voxel sizes. These PVEs can be caused by both non-WM tissue, such as gray matter (GM) and cerebrospinal fluid (CSF), and by multiple nonparallel WM fiber populations. High angular resolution diffusion imaging (HARDI) methods have been developed to correctly characterize complex WM fiber configurations, but to date, many of the HARDI methods do not account for non-WM PVEs. In this work, we investigated the isotropic PVEs caused by non-WM tissue in WM voxels on fiber orientations extracted with constrained spherical deconvolution (CSD). Experiments were performed on simulated and real DW-MRI data. In particular, simulations were performed to demonstrate the effects of varying the diffusion weightings, signal-to-noise ratios (SNR), fiber configurations, and tissue fractions.Our results show that the presence of non-WM tissue signal causes a decrease in the precision of the detected fiber orientations and an increase in the detection of false peaks in CSD. We estimated 35-50 % of WM voxels to be affected by non-WM PVEs. For HARDI sequences, which typically have a relatively high degree of diffusion weighting, these adverse effects are most pronounced in voxels with GM PVEs. The non-WM PVEs become severe with 50 % GM volume for maximum spherical harmonics orders of 8 and below, and already with 25 % GM volume for higher orders. In addition, a low diffusion weighting or SNR increases the effects. The non-WM PVEs may cause problems in connectomics, where reliable fiber tracking at the WM-GM interface is especially important. We suggest acquiring data with high diffusion-weighting 2500-3000 s/mm2, reasonable SNR (~30) and using lower SH orders in GM contaminated regions to minimize the non-WM PVEs in CSD.

Detection of microstructural white matter injury in traumatic brain injury (TBI) requires specialised imaging methods, of which diffusion tensor imaging (DTI) has been extensively studied. Newer fibre alignment estimation methods, such as constrained spherical deconvolution (CSD), are better than DTI in resolving crossing fibres that are ubiquitous in the brain and may improve the ability to detect microstructural injuries. Furthermore, automatic tract segmentation has the potential to improve tractography reliability and accelerate workflow compared to the manual segmentation commonly used. In this study, we compared the results of deterministic DTI based tractography and manual tract segmentation with CSD based probabilistic tractography and automatic tract segmentation using TractSeg. 37 participants with a history of TBI (with Glasgow Coma Scale 13-15) and persistent symptoms, and 41 healthy controls underwent deterministic DTI-based tractography with manual tract segmentation and probabilistic CSD-based tractography with TractSeg automatic segmentation.Fractional anisotropy (FA) and mean diffusivity of corpus callosum and three bilateral association tracts were measured. FA and MD values derived from both tractography methods were generally moderately to strongly correlated. CSD with TractSeg differentiated the groups based on FA, while DTI did not. CSD and TractSeg-based tractography may be more sensitive in detecting microstructural changes associated with TBI than deterministic DTI tractography. Additionally, CSD with TractSeg was found to be applicable at lower b-value and number of diffusion-encoding gradients data than previously reported., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a noninvasive imaging method, which can be used to investigate neural tracts in the white matter (WM) of the brain. However, the voxel sizes used in DW-MRI are relatively large, making DW-MRI prone to significant partial volume effects (PVE). These PVEs can be caused both by complex (e.g. crossing) WM fiber configurations and non-WM tissue, such as gray matter (GM) and cerebrospinal fluid. High angular resolution diffusion imaging methods have been developed to correctly characterize complex WM fiber configurations, but significant non-WM PVEs are also present in a large proportion of WM voxels. In constrained spherical deconvolution (CSD), the full fiber orientation distribution function (fODF) is deconvolved from clinically feasible DW data using a response function (RF) representing the signal of a single coherently oriented population of fibers. Non-WM PVEs cause a loss of precision in the detected fiber orientations and an emergence of false peaks in CSD, more prominently in voxels with GM PVEs. We propose a method, informed CSD (iCSD), to improve the estimation of fODFs under non-WM PVEs by modifying the RF to account for non-WM PVEs locally. In practice, the RF is modified based on tissue fractions estimated from high-resolution anatomical data. Results from simulation and in-vivo bootstrapping experiments demonstrate a significant improvement in the precision of the identified fiber orientations and in the number of false peaks detected under GM PVEs. Probabilistic whole brain tractography shows fiber density is increased in the major WM tracts and decreased in subcortical GM regions. The iCSD method significantly improves the fiber orientation estimation at the WM-GM interface, which is especially important in connectomics, where the connectivity between GM regions is analyzed. [ABSTRACT FROM AUTHOR]