Fiber Tracking Techniques Research Articles

Microstructure reconstruction using fiber tracking technique and pore-scale simulations of heterogeneous gas diffusion layer

Two challenging tasks in pore-scale modeling of a gas diffusion layer (GDL) are realistic microstructure reconstruction and stress-strain simulation to differentiate the heterogeneous materials. This study proposes a novel method for reconstructing a GDL using fiber tracking technique and pore-scale modeling to investigate its stress-strain and anisotropic transport properties. X-ray computed tomography, fiber tracking, and morphological processing techniques were employed to reconstruct a realistic GDL. Pore-scale modeling was performed to compute the stress-strain, gas diffusivity, and electrical-thermal conductivity at different compression ratios. The sensitivity of compression speed and Young's modulus were investigated to balance the accuracy and computing cost of stress-strain simulation. The results showed that Young's modulus of 1 GPa and compression speed of 3 m/s meet the requirements for both accuracy and computational cost. The reconstructed GDL showed good agreements with the experimental data when considering fibers' orientation, length, and curvature. It was found that the stress among fibers was approximately five times higher than binders. The anisotropic ratios of diffusivity and conductivity decreased from 1.35 to 1.25, and 15 to 5, respectively, as the compression ratio increased to 25%. This study can provide accurate predictions and guidelines for GDL design with low stress and high performance.

Thalamic Tumors in a Pediatric Population: Surgical Outcomes and Utilization of High-Definition Fiber Tractography and the Fiber Tracking Technique

Objective: This study aimed to assess the operability of thalamic tumors since they are generally considered to be inoperable and to have poor outcomes. Advancements in neuroimaging, neuronavigational technology, and intraoperative neurophysiological monitoring allow accurate planning and safe resection.Methods: Clinical data and reports of 10 pediatric patients with thalamic tumors were retrieved retrospectively. All 10 patients underwent surgical intervention. Diffusion tensor tractography (DTI) was used preoperatively to select the safest surgical route. Intraoperative MRI and postoperative MRI were used to evaluate the extent of resection.Results: There were three gross total resections (GTRs), two subtotal resections (STRs), two partial resections (PRs), and three biopsies. All patients had unilateral thalamic tumors. Different surgical approaches were used according to the relationship with the internal capsule and corticospinal tract and according to the preoperative DTI. Five patients had pilocytic astrocytoma, two had diffuse pediatric-type high-grade glioma, one had ganglioglioma, one had pediatric-type diffuse low-grade glioma, and one had atypical teratoid rhabdoid tumor (ATRT). The outcomes of low-grade tumors were favorable, especially for those who underwent resection, and those of high-grade tumors were poor regardless of the extent of resection.Conclusion: Our review shows that surgical resection of thalamic tumors can be done safely and offers favorable outcomes for patients with low-grade tumors, even without adjuvant therapy. Our study provides further evidence for thalamic tumors operability and safe resection.

Tracking the Corticospinal Tract in Patients With High-Grade Glioma: Clinical Evaluation of Multi-Level Fiber Tracking and Comparison to Conventional Deterministic Approaches.

While the diagnosis of high-grade glioma (HGG) is still associated with a considerably poor prognosis, neurosurgical tumor resection provides an opportunity for prolonged survival and improved quality of life for affected patients. However, successful tumor resection is dependent on a proper surgical planning to avoid surgery-induced functional deficits whilst achieving a maximum extent of resection (EOR). With diffusion magnetic resonance imaging (MRI) providing insight into individual white matter neuroanatomy, the challenge remains to disentangle that information as correctly and as completely as possible. In particular, due to the lack of sensitivity and accuracy, the clinical value of widely used diffusion tensor imaging (DTI)-based tractography is increasingly questioned. We evaluated whether the recently developed multi-level fiber tracking (MLFT) technique can improve tractography of the corticospinal tract (CST) in patients with motor-eloquent HGGs. Forty patients with therapy-naïve HGGs (mean age: 62.6 ± 13.4 years, 57.5% males) and preoperative diffusion MRI [repetition time (TR)/echo time (TE): 5000/78 ms, voxel size: 2x2x2 mm3, one volume at b=0 s/mm2, 32 volumes at b=1000 s/mm2] underwent reconstruction of the CST of the tumor-affected and unaffected hemispheres using MLFT in addition to deterministic DTI-based and deterministic constrained spherical deconvolution (CSD)-based fiber tractography. The brain stem was used as a seeding region, with a motor cortex mask serving as a target region for MLFT and a region of interest (ROI) for the other two algorithms. Application of the MLFT method substantially improved bundle reconstruction, leading to CST bundles with higher radial extent compared to the two other algorithms (delineation of CST fanning with a wider range; median radial extent for tumor-affected vs. unaffected hemisphere – DTI: 19.46° vs. 18.99°, p=0.8931; CSD: 30.54° vs. 27.63°, p=0.0546; MLFT: 81.17° vs. 74.59°, p=0.0134). In addition, reconstructions by MLFT and CSD-based tractography nearly completely included respective bundles derived from DTI-based tractography, which was however favorable for MLFT compared to CSD-based tractography (median coverage of the DTI-based CST for affected vs. unaffected hemispheres – CSD: 68.16% vs. 77.59%, p=0.0075; MLFT: 93.09% vs. 95.49%; p=0.0046). Thus, a more complete picture of the CST in patients with motor-eloquent HGGs might be achieved based on routinely acquired diffusion MRI data using MLFT.

Filtering in tractography using autoencoders (FINTA).

Current brain white matter fiber tracking techniques show a number of problems, including: generating large proportions of streamlines that do not accurately describe the underlying anatomy; extracting streamlines that are not supported by the underlying diffusion signal; and under-representing some fiber populations, among others. In this paper, we describe a novel autoencoder-based learning method to filter streamlines from diffusion MRI tractography, and hence, to obtain more reliable tractograms. Our method, dubbed FINTA (Filtering in Tractography using Autoencoders) uses raw, unlabeled tractograms to train the autoencoder, and to learn a robust representation of brain streamlines. Such an embedding is then used to filter undesired streamline samples using a nearest neighbor algorithm. Our experiments on both synthetic and in vivo human brain diffusion MRI tractography data obtain accuracy scores exceeding the 90% threshold on the test set. Results reveal that FINTA has a superior filtering performance compared to conventional, anatomy-based methods, and the RecoBundles state-of-the-art method. Additionally, we demonstrate that FINTA can be applied to partial tractograms without requiring changes to the framework. We also show that the proposed method generalizes well across different tracking methods and datasets, and shortens significantly the computation time for large (>1M streamlines) tractograms. Together, this work brings forward a new deep learning framework in tractography based on autoencoders, which offers a flexible and powerful method for white matter filtering and bundling that could enhance tractometry and connectivity analyses.

Age-Related Alterations in DTI Metrics in the Human Brain—Consequences for Age Correction

Background: Over the life span, the diffusion metrics in brain MRI show different, partly nonlinear changes. These age-dependent changes also seem to exhibit regional differences with respect to the brain anatomy. The age correction of a study cohort's diffusion metrics might thus require consideration of age-related factors.Methods: Diffusion tensor imaging data sets were acquired from 219 healthy participants at ages between 19 and 81 years. Fractional anisotropy (FA), mean diffusivity (MD), and axial and radial diffusivity (AD and RD, respectively) maps were analyzed by a tract of interest-based fiber tracking approach. To describe diffusion metrics as a function of the participant age, linear splines were used to perform curve fitting in 21 specific tract systems covering different functional areas and diffusion directions.Results: In the majority of tracts, an interpolation with a change of alteration rate during adult life described the diffusion properties more accurately than a linear model. Consequently, the diffusion properties remained relatively stable until a decrease (of FA) or increase (of MD, AD, and RD) started at a region-specific time point, whereas a uniform change of diffusion properties was observed only in a few tracts. Single tracts, e.g., located in the cerebellum, remained nearly unaltered throughout the ages between 19 and 81 years.Conclusions: Age corrections of diffusion properties should not be applied to all white matter regions and all age spans in the same way. Therefore, we propose three different approaches for age correction based on fiber tracking techniques, i.e., no correction for areas that do not experience age-related changes and two variants of an age correction depending on the age range of the cohort and the tracts considered.

P11 Comparison of different fibertracking techniques to delineate the dentate-rubro-thalamic tract

P11 Comparison of different fibertracking techniques to delineate the dentate-rubro-thalamic tract

Test-retest reliability of Diffusion Tensor Imaging metrics in neonates

Diffusion tensor imaging (DTI) has been widely used in children and adults to study the microstructural features of the brain. Its use in neonate brains has been limited. Neonate brains are almost completely unmyelinated, and this together with the tendency for babies to move during a scanning session may affect the reliability of the measurements. Here we divided a 96 direction acquisition into three segments, and analysed the intra scan test-retest reliability for pairs of segments. Each segment was subjected to a rigorous quality control, and from the surviving data we chose 25 diffusion encoding directions from each segment, and assessed the pairwise reliability of the most common DTI metrics. This pairwise reliability was assessed for data from 86 infants. We used tract-based spatial statistics (TBSS), voxelwise and ROI analysis schemes, to see potential differential effects of analysis strategy and post processing on the obtained DTI metrics. We found that intra class correlation coefficient (ICC) values were generally high (ICC > 0.80). Residual motion in the data, after quality control, was not found to associate with the diffusion metrics. The results indicate that DTI metrics from neonate data can be reliable, even at relatively low angular resolution that are common for neonate scans. The results lend confidence to the use of neonate DTI data in cross sectional and longitudinal analyses in brain white matter skeleton. Future studies should assess the reliability of fiber tracking techniques in neonate data.

Prediction of pituitary stalk position in pituitary adenomas by visualization of the hypothalamo-hypophyseal tract using diffusion tensor imaging tractography.

The preservation of pituitary stalk during surgery is very important for neurosurgeons. Sometimes, it is hard to identify the pituitary stalk in the operation. The hypothalamo-hypophyseal tract (HHT) projects through the pituitary stalk to the posterior pituitary gland. If the HHT can be identified, the position of pituitary stalk will be visualized. The diffusion tensor imaging (DTI) fiber tracking technique has been widely used for the quantitative assessment of the white matter integrity and thus may be suitable for the evaluation of the HHT.DTI was used to track the HHT in 11 patients with pituitary adenoma, and the location of the tract was compared with the pituitary stalk of postoperative image in those patients.The fiber tracking and 3D visualization of the HHT were successfully carried out in all 11 patients. Comparison between the tract and pituitary stalk of postoperative magnetic resonance imaging (MRI) was carried out in 9 patients. The results revealed that the position of tract was consistent with the pituitary stalk of postoperative MRI image in 8 patients (88.9%). The properties of tract showed that the median number of tract was 5.18 ± 7.00, the median fractional anisotropy (FA) was 0.14 ± 0.04, and the median length was 28.81 ± 7.94 mm.HHT can be tracked and visualized with the DTI-FT technique. It will be helpful to identify the location of pituitary stalk preoperatively.

FV 9 Diffusion tensor imaging in pure lower motor neuron disease

Criteria for assessing upper motor neuron pathology in lower motor neuron disease (LMND) still remain a major issue in clinical diagnosis. This study was designed to investigate patients with the clinical diagnosis of adult pure LMND by use of whole-brain based diffusion tensor imaging (DTI) in order to delineate alterations of corticoefferent pathways in vivo. Comparison of fractional anisotropy (FA) maps was performed by whole brain-based spatial statistics for 37 LMND patients vs. 53 matched controls to detect white matter structural alterations. LMND patients were clinically differentiated in fast and slow progressors. Tract specific alterations were investigated by fiber tracking techniques according to the staging hypothesis for amyotrophic lateral sclerosis (ALS). The analysis of white matter structural connectivity demonstrated widespread and characteristic patterns of alterations in patients with LMND, predominantly along the corticospinal tract (CST), with multiple clusters of regional FA reductions in the motor system at p < 0.05 (corrected for multiple comparisons). Fast progressing LMND showed substantial CST involvement, while slow progressors showed less CST alterations. In the tract-specific analysis according to the ALS-staging pattern (Kassubek et al., 2014), fast progressing LMND showed significant alterations of ALS-related tract systems (Müller et al., xxxx) beyond the CST compared to slow progressors and controls. In clinically pure LMND patients, the involvement of corticoefferent tracts was demonstrated, in particular along the CST, supporting the hypothesis that LMND is a phenotypical variant of ALS. This finding suggests to treat these patients like ALS, including the opportunity to participate in clinical trials.

Group comparison of cortical fiber connectivity map: An application between post-stroke patients and healthy subjects

Structural connectome measurement combined with diffusion magnetic resonance imaging (MRI) and tractography allows generation of a whole-brain connectome. However, current cortical structural connectivity (SC) measurements have not been well combined with the vertex-wise multi-subjects statistical analysis. The aim of this study was to examine the feasibility of using group comparison vertex-wise analysis for cortical SC measurement. A fiber connectivity density (FiCD) method based on a combination of a diffusion fiber tracking technique and cortical surface-based analysis was used to measure the whole-brain cortical SC map (FiCD map). A public MRI dataset (GigaDB) was employed to evaluate the reproducibility of the FiCD method. For group comparison, 14 post-stroke patients (mean age, 68.36±7.33y) and 19 healthy participants (mean age, 66.84±8.58y) had FiCD measurement. The intergroup comparison of the FiCD map was performed using vertex-wise multi-subject statistical analysis. Reliability testing showed the mean intra- and inter-subject FiCD variability was 3.51±2.12% and 19.44±4.79%, respectively. The group comparison of the whole-brain FiCD identified cortical regions with altered FiCD values, and there was a spatial consistency between the cortical clusters with low FiCD values and the subcortical lesions of patients. This study demonstrated the feasibility of vertex-wise group comparison for evaluating cortical fiber connectivity density. The FiCD method has good intra- and inter-individual reproducibility, and accurately reflects the affected cortical regions in post-stroke patients. This method may be helpful for neuroscience research.

Corticoefferent pathways in pure lower motor neuron disease: a diffusion tensor imaging study

Criteria for assessing upper motor neuron pathology in lower motor neuron disease (LMND) still remain major issues in clinical diagnosis. This study was designed to investigate patients with the clinical diagnosis of adult pure LMND by use of whole brain based diffusion tensor imaging (DTI) to delineate alterations of corticoefferent pathways in vivo. Comparison of fractional anisotropy (FA) maps was performed by whole brain-based spatial statistics for 37 LMND patients vs. 53 matched controls to detect white matter structural alterations. LMND patients were clinically differentiated in fast and slow progressors. Furthermore, tract specific alterations were investigated by fiber tracking techniques according to the staging hypothesis for amyotrophic lateral sclerosis (ALS). The analysis of white matter structural connectivity demonstrated widespread and characteristic patterns of alterations in patients with LMND, predominantly along the corticospinal tract (CST), with multiple clusters of regional FA reductions in the motor system at p<0.05 (corrected for multiple comparisons). Fast progressing LMND showed substantial CST involvement, while slow progressors showed less CST alterations. In the tract-specific analysis according to the ALS-staging pattern as suggested by Braak, fast progressing LMND showed significant alterations of ALS-related tract systems beyond the CST compared to slow progressors and controls. In clinically pure LMND patients, the involvement of corticoefferent fibers was demonstrated, in particular along the CST, supporting the hypothesis that LMND is a phenotypical variant of ALS. This finding suggests to treat these patients like ALS, including the opportunity to participate in clinical trials.

Segmentation of the Cingulum Bundle in the Human Brain: A New Perspective Based on DSI Tractography and Fiber Dissection Study.

The cingulum bundle (CB) is a critical white matter fiber tract in the brain, which forms connections between the frontal lobe, parietal lobe and temporal lobe. In non-human primates, the CB is actually divided into distinct subcomponents on the basis of corticocortical connections. However, at present, no study has verified similar distinct subdivisions in the human brain. In this study, we reconstructed these distinct subdivisions in the human brain, and determined their exact cortical connections using high definition fiber tracking (HDFT) technique on 10 healthy adults and a 488-subject template from the Human Connectome Project (HCP-488). Fiber dissections were performed to verify tractography results. Five CB segments were identified. CB-I ran from the subrostral areas to the precuneus and splenium, encircling the corpus callosum (CC). CB-II arched around the splenium and extended anteriorly above the CC to the medial aspect of the superior frontal gyrus (SFG). CB-III connected the superior parietal lobule (SPL) and precuneus with the medial aspect of the SFG. CB-IV was a relatively minor subcomponent from the SPL and precuneus to the frontal region. CB-V, the para-hippocampal cingulum, stemmed from the medial temporal lobe and fanned out to the occipital lobes. Our findings not only provide a more accurate and detailed description on the associated architecture of the subcomponents within the CB, but also offer new insights into the functional role of the CB in the human brain.

Magnetic resonance imaging DTI-FT study on schizophrenic patients with typical negative first symptoms.

Magnetic resonance imaging (MRI) with diffusion-tensor imaging (DTI) together with a white matter fiber tracking (FT) technique was used to assess different brain white matter structures and functionalities in schizophrenic patients with typical first negative symptoms. In total, 30 schizophrenic patients with typical first negative symptoms, comprising an observation group were paired 1:1 according to gender, age, right-handedness, and education, with 30 healthy individuals in a control group. Individuals in each group underwent routine MRI and DTI examination of the brain, and diffusion-tensor tractography (DTT) data were obtained through whole brain analysis based on voxel and tractography. The results were expressed by fractional anisotropy (FA) values. The schizophrenic patients were evaluated using a positive and negative symptom scale (PANSS) as well as a Global Assessment Scale (GAS). The results of the study showed that routine MRIs identified no differences between the two groups. However, compared with the control group, the FA values obtained by DTT from the deep left prefrontal cortex, the right deep temporal lobe, the white matter of the inferior frontal gyrus and part of the corpus callosum were significantly lower in the observation group (P<0.05). The PANSS positive scale value in the observation group averaged 7.7±1.5, and the negative scale averaged 46.6±5.9, while the general psychopathology scale averaged 65.4±10.3, and GAS averaged 53.8±19.2. The Pearson statistical analysis, the left deep prefrontal cortex, the right deep temporal lobe, the white matter of the inferior frontal gyrus and the FA value of part of the corpus callosum in the observation group was negatively correlated with the negative scale (P<0.05), and positively correlated with GAS (P<0.05). In conclusion, a decrease in the FA values of the left deep prefrontal cortex, the right deep temporal lobe, the white matter of the inferior frontal gyrus and part of the corpus callosum may be associated with schizophrenia with typical first negative symptoms and the application of MRI DTI-FT can improve diagnostic accuracy.

Fiber tracking: A qualitative and quantitative comparison between four different software tools on the reconstruction of major white matter tracts

PurposeDiffusion tensor imaging (DTI) enables in vivo reconstruction of white matter (WM) pathways. Considering the emergence of numerous models and fiber tracking techniques, we herein aimed to compare, both quantitatively and qualitatively, the fiber tracking results of four DTI software (Brainance, Philips FiberTrak, DSI Studio, NordicICE) on the reconstruction of representative WM tracts. Materials and methodsTen healthy participants underwent 30-directional diffusion tensor imaging on a 3T-Philips Achieva TX MR-scanner. All data were analyzed by two independent sites of experienced raters with the aforementioned software and the following WM tracts were reconstructed: corticospinal tract (CST); forceps major (Fmajor); forceps minor (Fminor); cingulum bundle (CB); superior longitudinal fasciculus (SLF); inferior fronto-occipital fasciculus (IFOF). Visual inspection of the resulted tracts and statistical analysis (inter-rater and betweensoftware agreement; paired t-test) on fractional anisotropy (FA), axial and radial diffusivity (Daxial, Dradial) were applied for qualitative and quantitative evaluation of DTI software results. ResultsQualitative evaluation of the extracted tracts confirmed anatomical landmarks at least for the core part of each tract, even though differences in the number of fibers extracted and the whole tract were evident, especially for the CST, Fmajor, Fminor and SLF. Descriptive values did not deviate from the expected range of values for healthy adult population. Substantial inter-rater agreement (intraclass correlation coefficient [ICC], Bland-Altman analysis) was found for all tracts (ICC; FA: 0.839–0.989, Daxial: 0.704–0.991, Dradial: 0.972–0.993). Low agreement for FA, Daxial and Dradial (ICC; Bland-Altman analysis) and significant paired t-test differences (p<0.05) were detected regarding between-software agreement. ConclusionsQualitative comparison of four different DTI software in addition to substantial inter-rater but poor between-software agreement highlight the differences on existing fiber tracking methodologies and several particularities of each WM tract, further supporting the need for further study in both clinical and research settings.

In vivo visualization of the facial nerve in patients with acoustic neuroma using diffusion tensor imaging-based fiber tracking.

OBJECTIVE Preoperative determination of the facial nerve (FN) course is essential to preserving its function. Neither regular preoperative imaging examination nor intraoperative electrophysiological monitoring is able to determine the exact position of the FN. The diffusion tensor imaging-based fiber tracking (DTI-FT) technique has been widely used for the preoperative noninvasive visualization of the neural fasciculus in the white matter of brain. However, further studies are required to establish its role in the preoperative visualization of the FN in acoustic neuroma surgery. The object of this study is to evaluate the feasibility of using DTI-FT to visualize the FN. METHODS Data from 15 patients with acoustic neuromas were collected using 3-T MRI. The visualized FN course and its position relative to the tumors were determined using DTI-FT with 3D Slicer software. The preoperative visualization results of FN tracking were verified using microscopic observation and electrophysiological monitoring during microsurgery. RESULTS Preoperative visualization of the FN using DTI-FT was observed in 93.3% of the patients. However, in 92.9% of the patients, the FN visualization results were consistent with the actual surgery. CONCLUSIONS DTI-FT, in combination with intraoperative FN electrophysiological monitoring, demonstrated improved FN preservation in patients with acoustic neuroma. FN visualization mainly included the facial-vestibular nerve complex of the FN and vestibular nerve.

DTI Image Registration under Probabilistic Fiber Bundles Tractography Learning.

Diffusion Tensor Imaging (DTI) image registration is an essential step for diffusion tensor image analysis. Most of the fiber bundle based registration algorithms use deterministic fiber tracking technique to get the white matter fiber bundles, which will be affected by the noise and volume. In order to overcome the above problem, we proposed a Diffusion Tensor Imaging image registration method under probabilistic fiber bundles tractography learning. Probabilistic tractography technique can more reasonably trace to the structure of the nerve fibers. The residual error estimation step in active sample selection learning is improved by modifying the residual error model using finite sample set. The calculated deformation field is then registered on the DTI images. The results of our proposed registration method are compared with 6 state-of-the-art DTI image registration methods under visualization and 3 quantitative evaluation standards. The experimental results show that our proposed method has a good comprehensive performance.

Incorporating priors for EEG source imaging and connectivity analysis.

Electroencephalography source imaging (ESI) is a useful technique to localize the generators from a given scalp electric measurement and to investigate the temporal dynamics of the large-scale neural circuits. By introducing reasonable priors from other modalities, ESI reveals the most probable sources and communication structures at every moment in time. Here, we review the available priors from such techniques as magnetic resonance imaging (MRI), functional MRI (fMRI), and positron emission tomography (PET). The modality's specific contribution is analyzed from the perspective of source reconstruction. For spatial priors, EEG-correlated fMRI, temporally coherent networks (TCNs) and resting-state fMRI are systematically introduced in the ESI. Moreover, the fiber tracking (diffusion tensor imaging, DTI) and neuro-stimulation techniques (transcranial magnetic stimulation, TMS) are also introduced as the potential priors, which can help to draw inferences about the neuroelectric connectivity in the source space. We conclude that combining EEG source imaging with other complementary modalities is a promising approach toward the study of brain networks in cognitive and clinical neurosciences.

Diffusion tensor imaging of periventricular leukomalacia – Initial experience

Aim of the studyTo investigate the role of MR diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) in the assessment of altered major white matter fibers in preterm infants and children with PVL. Patients and methodsWe used diffusion tensor imaging to evaluate the major white matter tract fibers in 15 children with periventricular leukomalacia in correlation with cognitive and motor disability. Mean age of the patients was 28.5months (range: 9–84months). 5 normal control children were recruited (mean age: 21.4, range: 11–60months). MR imaging was obtained by using a 1.5-T, whole-body scanner. DTI was acquired after the routine sequences. Then, data post-processing and fiber-tracking method was applied. ResultsThis study demonstrated the existence of the WM tract injury in PVL patients using the DTI tractography approach in correlation with neurodevelopmental delay in patients with various degrees of cognitive and motor impairment. Compared with the normal control group, the following abnormalities were detected on qualitative analysis of the white matter tracts. Corticospinal tractsDecreased volume and cross-sectional area on the affected side. Ascending sensorimotor tractsThinning of sensory fiber tracts and posterior thalamic radiations. Commissural and association tractsSignificant damage of the callosal fibers was reported in cases with partial agenesis of the corpus callosum. ConclusionDTI proved to be a promising noninvasive method for assessing the severity of white matter tract injury in patients with PVL. This is owing to the capability of fiber-tracking techniques to provide more information for understanding the pathophysiologic features of sensorimotor and cognitive disability associated with PVL. This will allow for the early intervention and initiation of rehabilitation programs aiming for minimizing the associated neurological deficit.

COMMIT: Convex optimization modeling for microstructure informed tractography.

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

The Dentate Nucleus and Its Projection System in the Human Cerebellum

Neurosurgical management of cerebellar lesions remains challenging. Thus, it is important to have sound knowledge of the microsurgical anatomy of the cerebellum and dentate nucleus (DN) and to define different types of exposure in a variety of surgical interventions. To examine the anatomy of the DN from a neurosurgical viewpoint using fiber tracking techniques. Ten formalin-fixed human hemispheres were dissected with the Ludwig and Klingler fiber dissection technique under × 6 to × 40 magnification. Anatomic images were created with 3-dimensional diffusion tensor imaging. The relationships of the DN to tentorium and suboccipital and lateral surfaces of the cerebellum and its spatial positioning relative to different surgical approaches in the cerebellum and fourth ventricle were examined. The fiber tracts terminating at and surrounding the DN were defined. The DN is at greater risk of being injured in the transvermian and supratonsillar approaches to the cerebellum and fourth ventricle, with lesser risk in the telovelar and subtonsillar approaches. Superior approaches are safer compared with other approaches. The DN represents an important anatomic structure in surgical interventions involving the posterior fossa, particularly in the elderly because of the common occurrence of atrophy-related problems in this age group. Functionally and anatomically, the DN is closely related to the superior and middle cerebellar peduncles. The inferior cerebellar peduncle poses positional risks because it follows an anterior and superior course relative to the DN. The telovelar approach is a safer procedure for interventions involving the pathological lesions of the fourth ventricle floor.