PhyberSIM: a tool for the generation of ground truth to evaluate brain fiber clustering algorithms.

Diffusion Magnetic Resonance Imaging tractography is a non-invasive technique that produces a collection of streamlines representing the main white matter bundle trajectories. Methods, such as fiber clustering algorithms, are important in computational neuroscience and have been the basis of several white matter analysis methods and studies. Nevertheless, these clustering methods face the challenge of the absence of ground truth of white matter fibers, making their evaluation difficult. As an alternative solution, we present an innovative brain fiber bundle simulator that uses spline curves for fiber representation. The methodology uses a tubular model for the bundle simulation based on a bundle centroid and five radii along the bundle. The algorithm was tested by simulating 28 Deep White Matter atlas bundles, leading to low inter-bundle distances and high intersection percentages between the original and simulated bundles. To prove the utility of the simulator, we created three whole-brain datasets containing different numbers of fiber bundles to assess the quality performance of QuickBundles and Fast Fiber Clustering algorithms using five clustering metrics. Our results indicate that QuickBundles tends to split less and Fast Fiber Clustering tends to merge less, which is consistent with their expected behavior. The performance of both algorithms decreases when the number of bundles is increased due to higher bundle crossings. Additionally, the two algorithms exhibit robust behavior with input data permutation. To our knowledge, this is the first whole-brain fiber bundle simulator capable of assessing fiber clustering algorithms with realistic data.

Shifts in structural connectome organization in the limbic and sensory systems of patients with episodic migraine.

Migraine is a complex neurological condition characterized by recurrent headaches, which is often accompanied by various neurological symptoms. Magnetic resonance imaging (MRI) is a powerful tool for investigating whole-brain connectivity patterns; however, systematic assessment of structural connectome organization has rarely been performed. In the present study, we aimed to examine the changes in structural connectivity in patients with episodic migraines using diffusion MRI. First, we computed structural connectivity using diffusion MRI tractography, after which we applied dimensionality reduction techniques to the structural connectivity and generated three low-dimensional eigenvectors. We subsequently calculated the manifold eccentricity, defined as the Euclidean distance between each data point and the center of the data in the manifold space. We then compared the manifold eccentricity between patients with migraines and healthy controls, revealing significant between-group differences in the orbitofrontal cortex, temporal pole, and sensory/motor regions. Between-group differences in subcortico-cortical connectivity further revealed significant changes in the amygdala, accumbens, and caudate nuclei. Finally, supervised machine learning effectively classified patients with migraines and healthy controls using cortical and subcortical structural connectivity features, highlighting the importance of the orbitofrontal and sensory cortices, in addition to the caudate, in distinguishing between the groups. Our findings confirmed that episodic migraine is related to the structural connectome changes in the limbic and sensory systems, suggesting its potential utility as a diagnostic marker for migraine.

Tractometry of Human Visual White Matter Pathways in Health and Disease.

Diffusion-weighted MRI (dMRI) provides a unique non-invasive view of human brain tissue properties. The present review article focuses on tractometry analysis methods that use dMRI to assess the properties of brain tissue within the long-range connections comprising brain networks. We focus specifically on the major white matter tracts that convey visual information. These connections are particularly important because vision provides rich information from the environment that supports a large range of daily life activities. Many of the diseases of the visual system are associated with advanced aging, and tractometry of the visual system is particularly important in the modern aging society. We provide an overview of the tractometry analysis pipeline, which includes a primer on dMRI data acquisition, voxelwise model fitting, tractography, recognition of white matter tracts, and calculation of tract tissue property profiles. We then review dMRI-based methods for analyzing visual white matter tracts: the optic nerve, optic tract, optic radiation, forceps major, and vertical occipital fasciculus. For each tract, we review background anatomical knowledge together with recent findings in tractometry studies on these tracts and their properties in relation to visual function and disease. Overall, we find that measurements of the brain's visual white matter are sensitive to a range of disorders and correlate with perceptual abilities. We highlight new and promising analysis methods, as well as some of the current barriers to progress toward integration of these methods into clinical practice. These barriers, such as variability in measurements between protocols and instruments, are targets for future development.

Clinical characteristics of post-stroke basal ganglia aphasia and the study of language-related white matter tracts based on diffusion spectrum imaging.

BACKGROUND: Stroke often damages the basal ganglia, leading to atypical and transient aphasia, indicating that post-stroke basal ganglia aphasia (PSBGA) may be related to different anatomical structural damage and functional remodeling rehabilitation mechanisms. The basal ganglia contain dense white matter tracts (WMTs). Hence, damage to the functional tract may be an essential anatomical structural basis for the development of PSBGA. METHODS: We first analyzed the clinical characteristics of PSBGA in 28 patients and 15 healthy controls (HCs) using the Western Aphasia Battery and neuropsychological test batteries. Moreover, we investigated white matter injury during the acute stage using diffusion magnetic resonance imaging scans for differential tractography. Finally, we used multiple regression models in correlation tractography to analyze the relationship between various language functions and quantitative anisotropy (QA) of WMTs. RESULTS: Compared with HCs, patients with PSBGA showed lower scores for fluency, comprehension (auditory word recognition and sequential commands), naming (object naming and word fluency), reading comprehension of sentences, Mini-Mental State Examination, and Montreal Cognitive Assessment, along with increased scores in Hamilton Anxiety Scale-17 and Hamilton Depression Scale-17 within 7 days after stroke onset (P < 0.05). Differential tractography revealed that patients with PSBGA had damaged fibers, including in the body fibers of the corpus callosum, left cingulum bundles, left parietal aslant tracts, bilateral superior longitudinal fasciculus II, bilateral thalamic radiation tracts, left fornix, corpus callosum tapetum, and forceps major, compared with HCs (FDR < 0.02). Correlation tractography highlighted that better comprehension was correlated with a higher QA of the left inferior fronto-occipital fasciculus (IFOF), corpus callosum forceps minor, and left extreme capsule (FDR < 0.0083). Naming was positively associated with the QA of the left IFOF, forceps minor, left arcuate fasciculus, and uncinate fasciculus (UF) (FDR < 0.0083). Word fluency of naming was also positively associated with the QA of the forceps minor, left IFOF, and thalamic radiation tracts (FDR < 0.0083). Furthermore, reading was positively correlated with the QA of the forceps minor, left IFOF, and UF (FDR < 0.0083). CONCLUSION: PSBGA is primarily characterized by significantly impaired word fluency of naming and preserved repetition abilities, as well as emotional and cognitive dysfunction. Damaged limbic pathways, dorsally located tracts in the left hemisphere, and left basal ganglia pathways are involved in PSBGA pathogenesis. The results of connectometry analysis further refine the current functional localization model of higher-order neural networks associated with language functions.

Multimodal cross-examination of progressive apraxia of speech by diffusion tensor imaging-based tractography and Tau-PET scans.

Progressive apraxia of speech (PAOS) is a 4R tauopathy characterized by difficulties with motor speech planning. Neurodegeneration in PAOS targets the premotor cortex, particularly the supplementary motor area (SMA), with degeneration of white matter (WM) tracts connecting premotor and motor cortices and Broca's area observed on diffusion tensor imaging (DTI). We aimed to assess flortaucipir uptake across speech-language-related WM tracts identified using DTI tractography in PAOS. Twenty-two patients with PAOS and 26 matched healthy controls were recruited by the Neurodegenerative Research Group (NRG) and underwent MRI and flortaucipir-PET. The patient population included patients with primary progressive apraxia of speech (PPAOS) and non-fluent variant/agrammatic primary progressive aphasia (agPPA). Flortaucipir PET scans and DTI were coregistered using rigid registration with a mutual information cost function in subject space. Alignments between DTI and flortaucipir PET were inspected in all cases. Whole-brain tractography was calculated using deterministic algorithms by a tractography reconstruction tool (DSI-studio) and specific tracts were identified using an automatic fiber tracking atlas-based method. Fractional anisotropy (FA) and flortaucipir standardized uptake value ratios (SUVRs) were averaged across the frontal aslant tract, arcuate fasciculi, inferior frontal-occipital fasciculus, inferior and middle longitudinal fasciculi, as well as the SMA commissural fibers. Reduced FA (p < .0001) and elevated flortaucipir SUVR (p = .0012) were observed in PAOS cases compared to controls across all combined WM tracts. For flortaucipir SUVR, the greatest differentiation of PAOS from controls was achieved with the SMA commissural fibers (area under the receiver operator characteristic curve [AUROC] = 0.83), followed by the left arcuate fasciculus (AUROC = 0.75) and left frontal aslant tract (AUROC = 0.71). Our findings demonstrate that flortaucipir uptake is increased across WM tracts related to speech/language difficulties in PAOS.

7T MRI probabilistic tractography-based evidence of decussation of the fibers between the lateral geniculate nucleus and the primary visual area.

BACKGROUND AND OBJECTIVES: Geniculocalcarine fibers are thought to be exclusively ipsilateral. However, recent findings challenged this belief, revealing bilateral recruiting responses in occipito-temporo-parietal regions upon unilateral stimulation of the lateral geniculate nucleus (LGN) in humans. This raised the intriguing possibility of bilateral projections to primary visual areas (V1). This study sought to explore the hypothetical decussation of the geniculocalcarine tract. METHODS: Forty healthy individuals' 7T MR images from the Human Connectome Project were examined. Employing MRtrix3 software with the constrained spherical deconvolution algorithm, scans were processed. LGN served as the seed region, and contralateral regions of interest - ROIs (splenium of the corpus callosum - SCC, posterior commissure, LGN, V1, pulvinar, and superior colliculus) were defined to reconstruct the hypothetical decussated fibers. Tractography included contralateral V1 as the target region in all segmentations, excluding ipsilateral V1 to eliminate fibers leading to or originating from this area. Additionally, a segmentation of the tract originating from LGN and projecting to the ipsilateral V1 was performed. Mean fraction anisotropy and mean diffusivity metrics were extracted from the density maps. RESULTS: Observations revealed a substantial volume of decussated fibers between LGN and contralateral V1 via the SCC, albeit much smaller than ipsilateral fibers. The volume of ipsilateral fibers was similar in both sides. Left LGN-originating decussated fibers were more than double those originating from the right LGN. Tract segmentation to other ROIs yielded no fibers. CONCLUSIONS: This study suggests a partial decussation of the fibers between LGN and V1, likely constituting the geniculocalcarine tract.

Diffusion tensor imaging and fiber tractography of the normal epididymis.

PURPOSE: To evaluate the feasibility of diffusion tensor imaging (DTI) and fiber tractography (FT) of the normal epididymis and to determine normative apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values. METHODS: Twenty-eight healthy volunteers underwent MRI of the scrotum, including DTI on a 3.0 T system. For each anatomic part of the epididymis (head, body and tail) free-hand regions of interest were drawn and the mean ADC and FA were measured by two radiologists in consensus. Parametric statistical tests were used to determine intersubject differences in ADC and FA between the anatomic parts of each normal epididymis and between bilateral epididymides. Fiber tracts of the epididymis were reconstructed using the MR Diffusion tool. RESULTS: The mean ADC and FA of the normal epididymis was 1.31 × 10-3 mm2/s and 0.20, respectively. No differences in ADC (p = 0.736) and FA (p = 0.628) between the anatomic parts of each normal epididymis were found. Differences (p = 0.020) were observed in FA of the body between the right and the left epididymis. FT showed the fiber tracts of the normal epididymis. Main study's limitations include the following: small number of participants with narrow age range, absence of histologic confirmation and lack of quantitative assessment of the FT reconstructions. CONCLUSION: DTI and FT of the normal epididymis is feasible and allow the noninvasive assessment of the structural and geometric organization of the organ.

Preoperative diffusion tensor imaging: Fiber-trajectory-distribution-based tractography to identify facial nerve in vestibular schwannoma.

PURPOSE: Tractography of the facial nerve based on diffusion MRI is instrumental before surgery for the resection of vestibular schwannoma, but no excellent methods usable for the suppression of motion and image noise have been proposed. The aim of this study was to effectively suppress noise and provide accurate facial nerve reconstruction by extend a fiber trajectory distribution function based on the fourth-order streamline differential equations. METHODS: Preoperative MRI from 33 patients with vestibular schwannoma who underwent surgical resection were utilized in this study. First, T1WI and T2WI were used to obtain mask images and regions of interest. Second, probabilistic tractography was employed to obtain the fibers representing the approximate facial nerve pathway, and these fibers were subsequently translated into orientation information for each voxel. Last, the voxel orientation information and the peaks of the fiber orientation distribution were combined to generate a fiber trajectory distribution function, which was used to parameterize the anatomical information. The parameters were determined by minimizing the cost between the trajectory of fibers and the estimated directions. RESULTS: Qualitative and visual analyses were used to compare facial nerve reconstruction with intraoperative recordings. Compared with other methods (SD_Stream, iFOD1, iFOD2, unscented Kalman filter, parallel transport tractography), the fiber-trajectory-distribution-based tractography provided the most accurate facial nerve reconstructions. CONCLUSION: The fiber-trajectory-distribution-based tractography can effectively suppress the effect of noise. It is a more valuable aid for surgeons before vestibular schwannoma resection, which may ultimately improve the postsurgical patient's outcome.

Establishing connectivity through microdissections of midbrain stimulation-related neural circuits.

Comprehensive understanding of the neural circuits involving the ventral tegmental area is essential for elucidating the anatomo-functional mechanisms governing human behaviour as well as the therapeutic and adverse effects of deep brain stimulation for neuropsychiatric diseases. While the ventral tegmental area has been successfully targeted with deep brain stimulation for different neuropsychiatric diseases, the axonal connectivity of the region has not been fully understood. Here using fiber micro-dissections in human cadaveric hemispheres, population-based high-definition fiber tractography, and previously reported deep brain stimulation hotspots, we find that the ventral tegmental area participates in an intricate network involving the serotonergic pontine nuclei, basal ganglia, limbic system, basal forebrain, and prefrontal cortex, which is implicated in the treatment of obsessive-compulsive disorder, major depressive disorder, Alzheimer's disease, cluster headaches, and aggressive behaviors.

Differential tractography and whole brain connectometry in primary motor area gliomas resection: A feasibility study.

OBJECTIVE: Establish the evolution of the connectome before and after resection of motor area glioma using a comparison of connectome maps and high-definition differential tractography (DifT). METHODS: DifT was done using normalized quantitative anisotropy (NQA) with DSI Studio. The quantitative analysis involved obtaining mean NQA and fractional anisotropy (FA) values for the disrupted pathways tracing the corticospinal tract (CST), and white fiber network changes over time. RESULTS: We described the baseline tractography, DifT, and white matter network changes from two patients who underwent resection of an oligodendroglioma (Case 1) and an IDH mutant astrocytoma, grade 4 (Case 2). CASE 1: There was a slight decrease in the diffusion signal of the compromised CST in the immediate postop. The NQA and FA values increased at the 1-year follow-up (0.18 vs. 0.32 and 0.35 vs. 0.44, respectively). CASE 2: There was an important decrease in the immediate postop, followed by an increase in the follow-up. In the 1-year follow-up, the patient presented with radiation necrosis and tumor recurrence, increasing NQA from 0.18 in the preop to 0.29. Fiber network analysis: whole-brain connectome comparison demonstrated no significant changes in the immediate postop. However, in the 1-year follow up there was a notorious reorganization of the fibers in both cases, showing the decreased density of connections. CONCLUSIONS: Connectome studies and DifT constitute new potential tools to predict early reorganization changes in a patient's networks, showing the brain plasticity capacity, and helping to establish timelines for the progression of the tumor and treatment-induced changes.

Akinetic mutism and gait disturbance in a patient with delayed post-hypoxic leukoencephalopathy.

We report on a patient with delayed post-hypoxic leukoencephalopathy (DPHL) who showed akinetic mutism and gait disturbance, neural injuries that were demonstrated on diffusion tensor tractography (DTT). A patient was exposed to carbon monoxide (CO) and rapidly recovered; however, two weeks after onset, he began to show cognitive impairment and gait disturbance. At six weeks after CO exposure, he showed akinetic mutism and gait inability. DTT at 6-weeks post-exposure showed discontinuations in neural connectivities of the caudate nucleus to the medial prefrontal and orbitofrontal cortex in both hemispheres. In addition, the corticoreticulospinal tract revealed severe thinning in both hemispheres.

Assessment of U-Net in the segmentation of short tracts: Transferring to clinical MRI routine.

Accurately studying structural connectivity requires precise tract segmentation strategies. The U-Net network has been widely recognized for its exceptional capacity in image segmentation tasks and provides remarkable results in large tract segmentation when high-quality diffusion-weighted imaging (DWI) data are used. However, short tracts, which are associated with various neurological diseases, pose specific challenges, particularly when high-quality DWI data acquisition within clinical settings is concerned. Here, we aimed to evaluate the U-Net network ability to segment short tracts by using DWI data acquired in different experimental conditions. To this end, we conducted three types of training experiments involving 350 healthy subjects and 11 white matter tracts, including the anterior, posterior, and hippocampal commissure, fornix, and uncinated fasciculus. In the first experiment, the model was exclusively trained with high-quality data of the Human Connectome Project (HCP) dataset. The second experiment focused on images of healthy subjects acquired from a local hospital dataset, representing a typical clinical routine acquisition. In the third experiment, a hybrid training approach was employed, combining data of the HCP and local hospital datasets. Then, the best model was also tested in unseen DWIs of 10 epilepsy patients of the local hospital and 10 healthy subjects acquired on a scanner from another company. The outcomes of the third experiment demonstrated a notable enhancement in performance when contrasted with the preceding trials. Specifically, the short tracts within the local hospital dataset achieved Dice scores ranging between 0.60 and 0.65. Similar intervals were obtained with HCP data in the first experiment, and a substantial improvement compared to the scores between 0.37 and 0.50 obtained with the local hospital dataset at the same experiment. This improvement persisted when the method was applied to diverse scenarios, including different scanner acquisitions and epilepsy patients. These results indicate that combining datasets from different sources, coupled with resolution standardization strengthens the neural network ability to generalize predictions across a spectrum of datasets. Nevertheless, short tract segmentation performance is intricately linked to the training composition, to validation, and to testing data. Moreover, curved tracts have intricate structural nature, which adds complexities to their segmenting. Although the network training approach tested herein has provided promising results, caution must be taken when extrapolating its application to datasets acquired under distinct experimental conditions, even in the case of higher-quality data or analysis of long or short tracts.

Lumbosacral plexus and pudendal nerve magnetic resonance tractography: A systematic review of the clinical applications for pudendal neuralgia.

Diffusion tensor imaging (DTI) is commonly used to establish three-dimensional mapping of white-matter bundles in the supraspinal central nervous system. DTI has also been the subject of many studies on cranial and peripheral nerves. This non-invasive imaging technique enables virtual dissection of nerves in vivo and provides specific measurements of microstructural integrity. Adverse effects on the lumbosacral plexus may be traumatic, compressive, tumoral, or malformative and thus require dedicated treatment. DTI could lead to new perspectives in pudendal neuralgia diagnosis and management. We performed a systematic review of all articles or posters reporting results and protocols for lumbosacral plexus mapping using the DTI technique between January 2011 and December 2023. Twenty-nine articles published were included. Ten studies with a total of 351 participants were able to track the lumbosacral plexus in a physiological context and 19 studies with a total of 402 subjects tracked lumbosacral plexus in a pathological context. Tractography was performed on a 1.5T or 3T MRI system. DTI applied to the lumbosacral plexus and pudendal nerve is feasible but no microstructural normative value has been proposed for the pudendal nerve. The most frequently tracking parameters used in our review are: 3T MRI, b-value of 800 s/mm2, 33 directions, 3 × 3 × 3 mm3, AF threshold of 0.1, minimum fiber length of 10 mm, bending angle of 30°, and 3DT2 TSE anatomical resolution. Increased use of DTI could lead to new perspectives in the management of pudendal neuralgia due to entrapment syndrome, whether at the diagnostic, prognostic, or preoperative planning level. Prospective studies of healthy subjects and patients with the optimal acquisition parameters described above are needed to establish the accuracy of MR tractography for diagnosing pudendal neuralgia and other intrapelvic nerve entrapments.

Tracts in the limbic system show microstructural alterations post COVID-19 recovery.

Delirium, memory loss, attention deficit and fatigue are frequently reported by COVID survivors, yet the neurological pathways underlying these symptoms are not well understood. To study the possible mechanisms for these long-term sequelae after COVID-19 recovery, we investigated the microstructural properties of white matter in Indian cohorts of COVID-recovered patients and healthy controls. For the cross-sectional study presented here, we recruited 44 COVID-recovered patients and 29 healthy controls in New Delhi, India. Using deterministic whole-brain tractography on the acquired diffusion MRI scans, we traced 20 white matter tracts and compared fractional anisotropy, axial, mean and radial diffusivity between the cohorts. Our results revealed statistically significant differences (PFWE < 0.01) in the uncinate fasciculus, cingulum cingulate, cingulum hippocampus and arcuate fasciculus in COVID survivors, suggesting the presence of microstructural abnormalities. Additionally, in a subsequent subgroup analysis based on infection severity (healthy control, non-hospitalized patients and hospitalized patients), we observed a correlation between tract diffusion measures and COVID-19 infection severity. Although there were significant differences between healthy controls and infected groups, we found no significant differences between hospitalized and non-hospitalized COVID patients. Notably, the identified tracts are part of the limbic system and orbitofrontal cortex, indicating microstructural differences in neural circuits associated with memory and emotion. The observed white matter alterations in the limbic system resonate strongly with the functional deficits reported in Long COVID. Overall, our study provides additional evidence that damage to the limbic system could be a neuroimaging signature of Long COVID. The findings identify targets for follow-up studies investigating the long-term physiological and psychological impact of COVID-19.

Corrigendum: A structural connectivity atlas of limbic brainstem nuclei.

[This corrects the article DOI: 10.3389/fnimg.2022.1009399.].

Short fiber bundle filtering and test-retest reproducibility of the Superficial White Matter.

In recent years, there has been a growing interest in studying the Superficial White Matter (SWM). The SWM consists of short association fibers connecting near giry of the cortex, with a complex organization due to their close relationship with the cortical folding patterns. Therefore, their segmentation from dMRI tractography datasets requires dedicated methodologies to identify the main fiber bundle shape and deal with spurious fibers. This paper presents an enhanced short fiber bundle segmentation based on a SWM bundle atlas and the filtering of noisy fibers. The method was tuned and evaluated over HCP test-retest probabilistic tractography datasets (44 subjects). We propose four fiber bundle filters to remove spurious fibers. Furthermore, we include the identification of the main fiber fascicle to obtain well-defined fiber bundles. First, we identified four main bundle shapes in the SWM atlas, and performed a filter tuning in a subset of 28 subjects. The filter based on the Convex Hull provided the highest similarity between corresponding test-retest fiber bundles. Subsequently, we applied the best filter in the 16 remaining subjects for all atlas bundles, showing that filtered fiber bundles significantly improve test-retest reproducibility indices when removing between ten and twenty percent of the fibers. Additionally, we applied the bundle segmentation with and without filtering to the ABIDE-II database. The fiber bundle filtering allowed us to obtain a higher number of bundles with significant differences in fractional anisotropy, mean diffusivity, and radial diffusivity of Autism Spectrum Disorder patients relative to controls.

Ultrahigh field diffusion magnetic resonance imaging uncovers intriguing microstructural changes in the adult zebrafish brain caused by Toll-like receptor 2 genomic deletion.

Toll-like receptor 2 (TLR2) belongs to the TLR protein family that plays an important role in the immune and inflammation response system. While TLR2 is predominantly expressed in immune cells, its expression has also been detected in the brain, specifically in microglia and astrocytes. Recent studies indicate that genomic deletion of TLR2 can result in impaired neurobehavioural function. It is currently not clear if the genomic deletion of TLR2 leads to any alterations in the microstructural features of the brain. In the current study, we noninvasively assess microstructural changes in the brain of TLR2-deficient (tlr2-/-) zebrafish using state-of-the art magnetic resonance imaging (MRI) methods at ultrahigh magnetic field strength (17.6 T). A significant increase in cortical thickness and an overall trend towards increased brain volumes were observed in young tlr2-/- zebrafish. An elevated T2 relaxation time and significantly reduced apparent diffusion coefficient (ADC) unveil brain-wide microstructural alterations, potentially indicative of cytotoxic oedema and astrogliosis in the tlr2-/- zebrafish. Multicomponent analysis of the ADC diffusivity signal by the phasor approach shows an increase in the slow ADC component associated with restricted diffusion. Diffusion tensor imaging and diffusion kurtosis imaging analysis revealed diminished diffusivity and enhanced kurtosis in various white matter tracks in tlr2-/- compared with control zebrafish, identifying the microstructural underpinnings associated with compromised white matter integrity and axonal degeneration. Taken together, our findings demonstrate that the genomic deletion of TLR2 results in severe alterations to the microstructural features of the zebrafish brain. This study also highlights the potential of ultrahigh field diffusion MRI techniques in discerning exceptionally fine microstructural details within the small zebrafish brain, offering potential for investigating microstructural changes in zebrafish models of various brain diseases.

Structural and functional connectivity in hydrocephalus: a scoping review.

Optimizing the treatment of hydrocephalus remains a major challenge in adult and pediatric neurosurgery. Currently, clinical treatment relies heavily on anatomic imaging of ventricular size and clinical presentation. The emergence of functional and structural brain connectivity imaging has provided the basis for a new paradigm in the management of hydrocephalus. Here we review the pertinent advances in this field. Following PRISMA-ScR guidelines for scoping reviews, we searched PubMed for relevant literature from 1994 to April 2023 using hydrocephalus and MRI-related terms. Included articles reported original MRI data on human subjects with hydrocephalus, while excluding non-English or pre-1994 publications that didn't match the study framework. The review identified 44 studies that investigated functional and/or structural connectivity using various MRI techniques across different hydrocephalus populations. While there is significant heterogeneity in imaging technology and connectivity analysis, there is broad consensus in the literature that 1) hydrocephalus is associated with disruption of functional and structural connectivity, 2) this disruption in cerebral connectivity can be further associated with neurologic compromise 3) timely treatment of hydrocephalus restores both cerebral connectivity and neurologic compromise. The robustness and consistency of these findings vary as a function of patient age, hydrocephalus etiology, and the connectivity region of interest studied. Functional and structural brain connectivity imaging shows potential as an imaging biomarker that may facilitate optimization of hydrocephalus treatment. Future research should focus on standardizing regions of interest as well as identifying connectivity analysis most pertinent to clinical outcome.

The effect of spinal correction surgery on the tractography data of the pain pathway in scoliosis patients: a preliminary report.

STUDY DESIGN: Cross-sectional study. OBJECTIVE: Pain in individuals with opered scoliosis is usually evaluated with a postural analysis or questionnaire. In this study, we evaluated pain in individuals with scoliosis who underwent spinal correction surgery by tractography and compared it with individuals with non-opered scoliosis and healthy individuals. DESIGN: Fifteen healthy individuals, 15 non-operated scoliosis patients and 15 operated scoliosis patients were included in the study. METHODS: All female participants in this prospectively planned study used their right hand as the dominant hand. Bilateral tractography analysis of the pain pathways was performed with DSI Studio software using brain magnetic resonance images (MRI) of the participants. Statistical analysis of the study was performed with IBM SPSS 23.0 and p<0.05 values were considered significant. RESULTS: It was observed that the tractography values of the operated scoliosis group were similar to the control group (p˃0.05). In the non-operated scoliosis group, tractography findings related to nerve conduction velocity such as fiber count, fiber ratio and axial diffusivity (AD) were found to be higher than the other two groups (p<0.05). Fractional anisotropy (FA) values of the unoperated scoliosis group were significantly different between the pain pathways projected from the right/left side of the body (p<0.05). CONCLUSION: The fact that the pain path tractography values of patients with scoliosis who underwent surgery were similar to those of healthy individuals may be evidence of decreased pain sensation reaching the brain. Surgery may be a good choice in the treatment of pain in patients with scoliosis.

Anat-SFSeg: Anatomically-guided superficial fiber segmentation with point-cloud deep learning.

Diffusion magnetic resonance imaging (dMRI) tractography is a critical technique to map the brain's structural connectivity. Accurate segmentation of white matter, particularly the superficial white matter (SWM), is essential for neuroscience and clinical research. However, it is challenging to segment SWM due to the short adjacent gyri connection in a U-shaped pattern. In this work, we propose an Anatomically-guided Superficial Fiber Segmentation (Anat-SFSeg) framework to improve the performance on SWM segmentation. The framework consists of a unique fiber anatomical descriptor (named FiberAnatMap) and a deep learning network based on point-cloud data. The spatial coordinates of fibers represented as point clouds, as well as the anatomical features at both the individual and group levels, are fed into a neural network. The network is trained on Human Connectome Project (HCP) datasets and tested on the subjects with a range of cognitive impairment levels. One new metric named fiber anatomical region proportion (FARP), quantifies the ratio of fibers in the defined brain regions and enables the comparison with other methods. Another metric named anatomical region fiber count (ARFC), represents the average fiber number in each cluster for the assessment of inter-subject differences. The experimental results demonstrate that Anat-SFSeg achieves the highest accuracy on HCP datasets and exhibits great generalization on clinical datasets. Diffusion tensor metrics and ARFC show disorder severity associated alterations in patients with Alzheimer's disease (AD) and mild cognitive impairments (MCI). Correlations with cognitive grades show that these metrics are potential neuroimaging biomarkers for AD. Furthermore, Anat-SFSeg could be utilized to explore other neurodegenerative, neurodevelopmental or psychiatric disorders.