Diffusion Magnetic Resonance Imaging Tractography Research Articles

Deep multimodal saliency parcellation of cerebellar pathways: Linking microstructure and individual function through explainable multitask learning.

Parcellation of human cerebellar pathways is essential for advancing our understanding of the human brain. Existing diffusion magnetic resonance imaging tractography parcellation methods have been successful in defining major cerebellar fibre tracts, while relying solely on fibre tract structure. However, each fibre tract may relay information related to multiple cognitive and motor functions of the cerebellum. Hence, it may be beneficial for parcellation to consider the potential importance of the fibre tracts for individual motor and cognitive functional performance measures. In this work, we propose a multimodal data-driven method for cerebellar pathway parcellation, which incorporates both measures of microstructure and connectivity, and measures of individual functional performance. Our method involves first training a multitask deep network to predict various cognitive and motor measures from a set of fibre tract structural features. The importance of each structural feature for predicting each functional measure is then computed, resulting in a set of structure-function saliency values that are clustered to parcellate cerebellar pathways. We refer to our method as Deep Multimodal Saliency Parcellation (DeepMSP), as it computes the saliency of structural measures for predicting cognitive and motor functional performance, with these saliencies being applied to the task of parcellation. Applying DeepMSP to a large-scale dataset from the Human Connectome Project Young Adult study (n = 1065), we found that it was feasible to identify multiple cerebellar pathway parcels with unique structure-function saliency patterns that were stable across training folds. We thoroughly experimented with all stages of the DeepMSP pipeline, including network selection, structure-function saliency representation, clustering algorithm, and cluster count. We found that a 1D convolutional neural network architecture and a transformer network architecture both performed comparably for the multitask prediction of endurance, strength, reading decoding, and vocabulary comprehension, with both architectures outperforming a fully connected network architecture. Quantitative experiments demonstrated that a proposed low-dimensional saliency representation with an explicit measure of motor versus cognitive category bias achieved the best parcellation results, while a parcel count of four was most successful according to standard cluster quality metrics. Our results suggested that motor and cognitive saliencies are distributed across the cerebellar white matter pathways. Inspection of the final k = 4 parcellation revealed that the highest-saliency parcel was most salient for the prediction of both motor and cognitive performance scores and included parts of the middle and superior cerebellar peduncles. Our proposed saliency-based parcellation framework, DeepMSP, enables multimodal, data-driven tractography parcellation. Through utilising both structural features and functional performance measures, this parcellation strategy may have the potential to enhance the study of structure-function relationships of the cerebellar pathways.

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.

MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline.

Large-scale diffusion MRI tractography remains a significant challenge. Users must orchestrate a complex sequence of instructions that requires many software packages with complex dependencies and high computational costs. We developed MaPPeRTrac, an edge-centric tractography pipeline that simplifies and accelerates this process in a wide range of high-performance computing (HPC) environments. It fully automates either probabilistic or deterministic tractography, starting from a subject's magnetic resonance imaging (MRI) data, including structural and diffusion MRI images, to the edge density image (EDI) of their structural connectomes. Dependencies are containerized with Singularity (now called Apptainer) and decoupled from code to enable rapid prototyping and modification. Data derivatives are organized with the Brain Imaging Data Structure (BIDS) to ensure that they are findable, accessible, interoperable, and reusable following FAIR principles. The pipeline takes full advantage of HPC resources using the Parsl parallel programming framework, resulting in the creation of connectome datasets of unprecedented size. MaPPeRTrac is publicly available and tested on commercial and scientific hardware, so it can accelerate brain connectome research for a broader user community. MaPPeRTrac is available at: https://github.com/LLNL/mappertrac .

Genetic architecture of the structural connectome

Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these connections remains unclear. We perform genome-wide association studies of 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography of 26,333 UK Biobank participants, each representing the density of myelinated connections within or between a pair of cortical networks, subcortical structures or cortical hemispheres. We identify 30 independent genome-wide significant variants after Bonferroni correction for the number of measures studied (126 variants at nominal genome-wide significance) implicating genes involved in myelination (SEMA3A), neurite elongation and guidance (NUAK1, STRN, DPYSL2, EPHA3, SEMA3A, HGF, SHTN1), neural cell proliferation and differentiation (GMNC, CELF4, HGF), neuronal migration (CCDC88C), cytoskeletal organization (CTTNBP2, MAPT, DAAM1, MYO16, PLEC), and brain metal transport (SLC39A8). These variants have four broad patterns of spatial association with structural connectivity: some have disproportionately strong associations with corticothalamic connectivity, interhemispheric connectivity, or both, while others are more spatially diffuse. Structural connectivity measures are highly polygenic, with a median of 9.1 percent of common variants estimated to have non-zero effects on each measure, and exhibited signatures of negative selection. Structural connectivity measures have significant genetic correlations with a variety of neuropsychiatric and cognitive traits, indicating that connectivity-altering variants tend to influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in adult oligodendrocytes (as well as microglia, inhibitory neurons and astrocytes) and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. Our results indicate pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, and support the relevance of this genetic control to healthy brain function.

Diffusion Magnetic Resonance Imaging Tractography Guides Investigation of the Zona Incerta: A Novel Target for Deep Brain Stimulation

BackgroundThe zona incerta (ZI) is a subcortical structure primarily investigated in rodents that is implicated in various behaviors, ranging from motor control to survival-associated activities, partly due to its integration in multiple neural circuits. In the current study, we used diffusion magnetic resonance imaging tractography to segment the ZI and gain insight into its connectivity in various circuits in humans. MethodsWe performed probabilistic tractography in 7T diffusion MRI on 178 participants from the Human Connectome Project to validate the ZI’s anatomical subdivisions and their respective tracts. K-means clustering segmented the ZI based on each voxel’s connectivity profile. We further characterized the connections of each ZI subregion using probabilistic tractography with each subregion as a seed. ResultsWe identified 2 dominant clusters that delineated the whole ZI into rostral and caudal subregions. The caudal ZI primarily connected with motor regions, while the rostral ZI received a topographic distribution of projections from prefrontal areas, notably the anterior cingulate and medial prefrontal cortices. We generated a probabilistic ZI atlas that was registered to a patient-participant’s magnetic resonance imaging scan for placement of stereoencephalographic leads for electrophysiology-guided deep brain stimulation to treat their obsessive-compulsive disorder. Rostral ZI stimulation improved the patient’s core symptoms (mean improvement 21%). ConclusionsWe present a tractography-based atlas of the rostral and caudal ZI subregions constructed using high-resolution diffusion magnetic resonance imaging from 178 healthy participants. Our work provides an anatomical foundation to explore the rostral ZI as a novel target for deep brain stimulation to treat refractory obsessive-compulsive disorder and other disorders associated with dysfunctional reward circuitry.

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.

Dissection of the Temporofrontal Extreme Capsule Fasciculus Using Diffusion MRI Tractography and Association with Lexical Retrieval.

The well-known arcuate fasciculus that connects the posterior superior temporal region with the language production region in the ventrolateral frontal cortex constitutes the classic peri-Sylvian dorsal stream of language. A second temporofrontal white matter tract connects ventrally the anterior to intermediate lateral temporal cortex with frontal areas via the extreme capsule. This temporofrontal extreme capsule fasciculus (TFexcF) constitutes the ventral stream of language processing. The precise origin, course, and termination of this pathway has been examined in invasive tract tracing studies in macaque monkeys, but there have been no standard protocols for its reconstruction in the human brain using diffusion imaging tractography. Here we provide a protocol for the dissection of the TFexcF in vivo in the human brain using diffusion magnetic resonance imaging (MRI) tractography which provides a solid basis for exploring its functional role. A key finding of the current dissection protocol is the demonstration that the TFexcF is left hemisphere lateralized. Furthermore, using the present dissection protocol, we demonstrate that the TFexcF is related to lexical retrieval scores measured with the category fluency test, in contrast to the classical arcuate fasciculus (the dorsal language pathway) that was also dissected and was related to sentence repetition.

Differences in structural connectome organization across sleep quality

Sleep quality, which measures satisfaction with overall sleep, is an important factor affecting an individual's health. Although previous neuroimaging studies based on magnetic resonance imaging (MRI) have observed altered regional morphology and functional activation related to poor sleep quality, the impact of sleep quality on whole-brain structural connectome organization is relatively under-investigated. To address this gap, we utilized dimensionality reduction techniques to estimate low-dimensional eigenvectors of structural connectivity derived from diffusion MRI tractography, and assessed their associations with measures of sleep quality. We found significant effects in the unimodal association and limbic regions. Additionally, the meta-analytic cognitive decoding analysis revealed associations with negative terms, including nociceptive and pain. Our findings suggest a link between alterations in the whole-brain structural organization and sleep quality, providing insights into the relationship between sleep quality and brain structure.

Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods.

The corticospinal tract (CST) is a critically important white matter fiber tract in the human brain that enables control of voluntary movements of the body. The CST exhibits a somatotopic organization, which means that the motor neurons that control specific body parts are arranged in order within the CST. Diffusion magnetic resonance imaging (MRI) tractography is increasingly used to study the anatomy of the CST. However, despite many advances in tractography algorithms over the past decade, modern, state-of-the-art methods still face challenges. In this study, we compare the performance of six widely used tractography methods for reconstructing the CST and its somatotopic organization. These methods include constrained spherical deconvolution (CSD) based probabilistic (iFOD1) and deterministic (SD-Stream) methods, unscented Kalman filter (UKF) tractography methods including multi-fiber (UKF2T) and single-fiber (UKF1T) models, the generalized q-sampling imaging (GQI) based deterministic tractography method, and the TractSeg method. We investigate CST somatotopy by dividing the CST into four subdivisions per hemisphere that originate in the leg, trunk, hand, and face areas of the primary motor cortex. A quantitative and visual comparison is performed using diffusion MRI data (N = 100 subjects) from the Human Connectome Project. Quantitative evaluations include the reconstruction rate of the eight anatomical subdivisions, the percentage of streamlines in each subdivision, and the coverage of the white matter-gray matter (WM-GM) interface. CST somatotopy is further evaluated by comparing the percentage of streamlines in each subdivision to the cortical volumes for the leg, trunk, hand, and face areas. Overall, UKF2T has the highest reconstruction rate and cortical coverage. It is the only method with a significant positive correlation between the percentage of streamlines in each subdivision and the volume of the corresponding motor cortex. However, our experimental results show that all compared tractography methods are biased toward generating many trunk streamlines (ranging from 35.10% to 71.66% of total streamlines across methods). Furthermore, the coverage of the WM-GM interface in the largest motor area (face) is generally low (under 40%) for all compared tractography methods. Different tractography methods give conflicting results regarding the percentage of streamlines in each subdivision and the volume of the corresponding motor cortex, indicating that there is generally no clear relationship, and that reconstruction of CST somatotopy is still a large challenge. Overall, we conclude that while current tractography methods have made progress toward the well-known challenge of improving the reconstruction of the lateral projections of the CST, the overall problem of performing a comprehensive CST reconstruction, including clinically important projections in the lateral (hand and face areas) and medial portions (leg area), remains an important challenge for diffusion MRI tractography.

Advancements in Diffusion MRI Tractography for Neurosurgery.

Diffusion magnetic resonance imaging tractography is a noninvasive technique that enables the visualization and quantification of white matter tracts within the brain. It is extensively used in preoperative planning for brain tumors, epilepsy, and functional neurosurgical procedures such as deep brain stimulation. Over the past 25 years, significant advancements have been made in imaging acquisition, fiber direction estimation, and tracking methods, resulting in considerable improvements in tractography accuracy. The technique enables the mapping of functionally critical pathways around surgical sites to avoid permanent functional disability. When the limitations are adequately acknowledged and considered, tractography can serve as a valuable tool to safeguard critical white matter tracts and provides insight regarding changes in normal white matter and structural connectivity of the whole brain beyond local lesions. In functional neurosurgical procedures such as deep brain stimulation, it plays a significant role in optimizing stimulation sites and parameters to maximize therapeutic efficacy and can be used as a direct target for therapy. These insights can aid in patient risk stratification and prognosis. This article aims to discuss state-of-the-art tractography methodologies and their applications in preoperative planning and highlight the challenges and new prospects for the use of tractography in daily clinical practice.

The organization of frontostriatal brain wiring in non-affective early psychosis compared with healthy subjects using a novel diffusion imaging fiber cluster analysis.

Alterations in brain connectivity may underlie neuropsychiatric conditions such as schizophrenia. We here assessed the degree of convergence of frontostriatal fiber projections in 56 young adult healthy controls (HCs) and 108 matched Early Psychosis-Non-Affective patients (EP-NAs) using our novel fiber cluster analysis of whole brain diffusion magnetic resonance imaging tractography. Using whole brain tractography and our fiber clustering methodology on harmonized diffusion magnetic resonance imaging data from the Human Connectome Project for Early Psychosis we identified 17 white matter fiber clusters that connect frontal cortex (FCtx) and caudate (Cd) per hemisphere in each group. To quantify the degree of convergence and, hence, topographical relationship of these fiber clusters, we measured the inter-cluster mean distances between the endpoints of the fiber clusters at the level of the FCtx and of the Cd, respectively. We found (1) in both groups, bilaterally, a non-linear relationship, yielding convex curves, between FCtx and Cd distances for FCtx-Cd connecting fiber clusters, driven by a cluster projecting from inferior frontal gyrus; however, in the right hemisphere, the convex curve was more flattened in EP-NAs; (2) that cluster pairs in the right (p = 0.03), but not left (p = 0.13), hemisphere were significantly more convergent in HCs vs EP-NAs; (3) in both groups, bilaterally, similar clusters projected significantly convergently to the Cd; and, (4) a significant group by fiber cluster pair interaction for 2 right hemisphere fiber clusters (numbers 5, 11; p = .00023; p = .00023) originating in selective PFC subregions. In both groups, we found the FCtx-Cd wiring pattern deviated from a strictly topographic relationship and that similar clusters projected significantly more convergently to the Cd. Interestingly, we also found a significantly more convergent pattern of connectivity in HCs in the right hemisphere and that 2 clusters from PFC subregions in the right hemisphere significantly differed in their pattern of connectivity between groups.

Deficits in naming pictures of objects are associated with glioma infiltration of the inferior longitudinal fasciculus: A study with diffusion MRI tractography, volumetric MRI, and neuropsychology.

It has been suggested that the inferior longitudinal fasciculus (ILF) may play an important role in several aspects of language processing such as visual object recognition, visual memory, lexical retrieval, reading, and specifically, in naming visual stimuli. In particular, the ILF appears to convey visual information from the occipital lobe to the anterior temporal lobe (ATL). However, direct evidence proving the essential role of the ILF in language and semantics remains limited and controversial. The first aim of this study was to prove that patients with a brain glioma damaging the left ILF would be selectively impaired in picture naming of objects; the second aim was to prove that patients with glioma infiltrating the ATL would not be impaired due to functional reorganization of the lexical retrieval network elicited by the tumor. We evaluated 48 right-handed patients with neuropsychological testing and magnetic resonance imaging (MRI) before and after surgery for resection of a glioma infiltrating aspects of the left temporal, occipital, and/or parietal lobes; diffusion tensor imaging (DTI) was acquired preoperatively in all patients. Damage to the ILF, inferior frontal occipital fasciculus (IFOF), uncinate fasciculus (UF), arcuate fasciculus (AF), and associated cortical regions was assessed by means of preoperative tractography and pre-/pos-toperative MRI volumetry. The association of fascicles damage with patients' performance in picture naming and three additional cognitive tasks, namely, verbal fluency (two verbal non-visual tasks) and the Trail Making Test (a visual attentional task), was evaluated. Nine patients were impaired in the naming test before surgery. ILF damage was demonstrated with tractography in six (67%) of these patients. The odds of having an ILF damage was 6.35 (95% CI: 1.27-34.92) times higher among patients with naming deficit than among those without it. The ILF was the only fascicle to be significantly associated with naming deficit when all the fascicles were considered together, achieving an adjusted odds ratio of 15.73 (95% CI: 2.30-178.16, p = .010). Tumor infiltration of temporal and occipital cortices did not contribute to increase the odd of having a naming deficit. ILF damage was found to be selectively associated with picture naming deficit and not with lexical retrieval assessed by means of verbal fluency. Early after surgery, 29 patients were impaired in naming objects. The association of naming deficit with percentage of ILF resection (assessed by 3D-MRI) was confirmed (beta = -56.78 ± 20.34, p = .008) through a robust multiple linear regression model; no significant association was found with damage of IFOF, UF or AF. Crucially, postoperative neuropsychological evaluation showed that naming scores of patients with tumor infiltration of the anterior temporal cortex were not significantly associated with the percentage of ILF damage (rho = .180, p > .999), while such association was significant in patients without ATL infiltration (rho = -.556, p = .004). The ILF is selectively involved in picture naming of objects; however, the naming deficits are less severe in patients with glioma infiltration of the ATL probably due to release of an alternative route that may involve the posterior segment of the AF. The left ILF, connecting the extrastriatal visual cortex to the anterior region of the temporal lobe, is crucial for lexical retrieval on visual stimulus, such as in picture naming. However, when the ATL is also damaged, an alternative route is released and the performance improves.

135. A Diffusion Magnetic Resonance Imaging Tractography Study of Frontostriatal Brain Wiring Organization in Early Psychosis Affective Subjects and in Healthy Controls

135. A Diffusion Magnetic Resonance Imaging Tractography Study of Frontostriatal Brain Wiring Organization in Early Psychosis Affective Subjects and in Healthy Controls

Neural Correlates of Formal Thought Disorder Dimensions in Psychosis.

Formal thought disorder (FTD) is a core symptom of psychosis, but its neural correlates remain poorly understood. This study tested whether four FTD dimensions differ in their association with brain perfusion and brain structure. This cross-sectional study investigated 110 patients with schizophrenia spectrum disorders using 3T magnetic resonance imaging (MRI). The Thought and Language Disorder scale (TALD) was utilized, which comprises four subscales: Objective Positive (OP), Objective Negative (ON), Subjective Positive (SP), and Subjective Negative (SN). Resting-state cerebral blood flow (rsCBF), cortical thickness (CortTh), gray matter volume (GMV), and diffusion MRI tractography were tested for associations with TALD subscales controlling for age, medication, total intracranial volume, and for variance of the 3 other TALD subscales. Following Bonferroni correction, the FTD dimensions presented distinct neural correlates. OP scores were associated with increased rsCBF and increased GMV in the right cerebellum lingual gyrus. Higher SP scores were linked to increased GMV in bilateral prefrontal cortex. In contrast, ON was associated with increased GMV in the right premotor cortex. At more liberal statistical thresholds, higher SP was associated with increased CortTh in the right inferior frontal gyrus, whereas SN scores were linked to decreased GMV in the right prefrontal lobe, the left inferior temporal gyrus, and the left supplementary motor area. Unadjusted analyses mostly corroborated these findings. These findings stress the heterogeneity in FTD, suggesting distinct neural patterns for specific FTD experiences. In sum, FTD in psychosis may require distinct treatment strategies and further mechanistic investigations on single-item levels.

Exploring the ventral white matter language network in bimodal and unimodal bilinguals

We used diffusion magnetic resonance imaging tractography to investigate the effect of language modality on the anatomy of the ventral white matter language network by comparing unimodal (Italian/English) and bimodal bilinguals (Italian/Italian Sign Language). We extracted the diffusion tractography measures of the Inferior Longitudinal fasciculus (ILF), Uncinate fasciculus (UF) and Inferior Fronto-Occipital fasciculus (IFOF) and we correlated them with the degree of bilingualism and the individual performance in fluency tasks. For both groups of bilinguals, the microstructural properties of the right ILF were correlated with individual level of proficiency in L2, confirming the involvement of this tract in bilingualism. In addition, we found that the degree of left lateralization of the ILF predicted the performance in semantic fluency in L1. The microstructural properties of the right UF correlated with performance in phonological fluency in L1, only for bimodal bilinguals. Overall, the pattern shows both similarities and differences between the two groups of bilinguals.

In-vivo data-driven parcellation of Heschl’s gyrus using structural connectivity

The human auditory cortex around Heschl’s gyrus (HG) exhibits diverging patterns across individuals owing to the heterogeneity of its substructures. In this study, we investigated the subregions of the human auditory cortex using data-driven machine-learning techniques at the individual level and assessed their structural and functional profiles. We studied an openly accessible large dataset of the Human Connectome Project and identified the subregions of the HG in humans using data-driven clustering techniques with individually calculated imaging features of cortical folding and structural connectivity information obtained via diffusion magnetic resonance imaging tractography. We characterized the structural and functional profiles of each HG subregion according to the cortical morphology, microstructure, and functional connectivity at rest. We found three subregions. The first subregion (HG1) occupied the central portion of HG, the second subregion (HG2) occupied the medial-posterior-superior part of HG, and the third subregion (HG3) occupied the lateral-anterior-inferior part of HG. The HG3 exhibited strong structural and functional connectivity to the association and paralimbic areas, and the HG1 exhibited a higher myelin density and larger cortical thickness than other subregions. A functional gradient analysis revealed a gradual axis expanding from the HG2 to the HG3. Our findings clarify the individually varying structural and functional organization of human HG subregions and provide insights into the substructures of the human auditory cortex.

Automated quantification of brain connectivity in Alzheimer's disease using ClusterMetric

Diffusion magnetic resonance imaging tractography allows investigating brain structural connections in a noninvasive way and has been widely used for understanding neurological disease. Quantification of brain connectivity along with its length by dividing a fiber bundle into multiple segments (node) is a powerful approach to assess biological properties, which is termed as tractometry. However, current tractometry methods face challenges in node identification along with the length of complex bundles whose morphology is difficult to summarize. In addition, the anatomic measure reflecting the macroscopic fiber cross-section has not been followed in previous tractometry. In this paper, we propose an automated fiber bundle quantification, which we refer to as ClusterMetric. The ClusterMetric uses a data-driven approach to identify fiber clusters corresponding to subdivisions of the white matter anatomy and identify consistent space nodes along the length of clusters across individuals. The proposed method is demonstrated by applicating to our collected dataset including 23 Alzheimer's disease (AD) patients and 22 healthy controls (HCs) and a public dataset of ADNI including 53 AD patients and 85 HCs. The altered white matter tracts in AD group are observed using both datasets, which involve several major fiber tracts including the corpus callosum, corona-radiata-frontal, arcuate fasciculus, inferior occipito-frontal fasciculus, uncinate fasciculus, thalamo-frontal, superior longitudinal fasciculus, inferior cerebellar peduncle, cingulum bundle, and extreme capsule. These fiber clusters represent the white matter connections that could be most affected in AD, suggesting the ability of our method in identifying potential abnormalities specific to local regions within a fiber cluster.

Alterations of white matter tracts and topological properties of structural networks in hemifacial spasm.

Hemifacial spasm (HFS) is characterized by involuntary and paroxysmal muscle contractions on the hemiface. It is generally believed that HFS is caused by neurovascular compression at the root exit zone of the facial nerve. In recent years, the structural alterations of brains with HFS have aroused growing concern. However, little attention has been directed towards the possible involvement of specific white matter (WM) tracts and the topological properties of structural networks in HFS. In the present study, diffusion magnetic resonance imaging tractography was utilized to construct structural networks and perform tractometric analysis. The diffusion tensor imaging scalar parameters along with the WM tracts, and the topological parameters of global networks and subnetworks, were assessed in 62 HFS patients and 57 demographically matched healthy controls (HCs). Moreover, we investigated the correlation of these parameters with disease-clinical-level (DCL) and disease-duration-time (DDT) of HFS patients. Compared with HCs, HFS patients had additional hub regions including the amygdala, ventromedial putamen, lateral occipital cortex, and rostral cuneus gyrus. Furthermore, HFS patients showed significant alternations with specific topological properties in some structural subnetworks, including the limbic, default mode, dorsal attention, somato-motor, and control networks, as well as diffusion properties in some WM tracts, including the superior longitudinal fasciculus, cingulum bundle, thalamo-frontal, and corpus callosum. These subnetworks and tracts were associated with the regulation of emotion, motor function, vision, and attention. Notably, we also found that the parameters with subnetworks and tracts exhibited correlations with DCL and DDT. In addition to corroborating previous findings in HFS, this study demonstrates the changed microstructures in specific locations along with the fiber tracts and changed topological properties in structural subnetworks.

Mapping Motor Pathways in Parkinson's Disease Patients with Subthalamic Deep Brain Stimulator: A Diffusion MRI Tractography Study.

IntroductionThis study assessed the safety of postoperative diffusion tensor imaging (DTI) with on-state deep brain stimulation (DBS) and the feasibility of reconstruction of the white matter tracts in the vicinity of the stimulation site of the subthalamic nucleus (STN). The association between the impact of DBS on the nigrostriatal pathway (NSP) and the treatment effect on motor symptoms in Parkinson’s disease (PD) was then evaluated.MethodsThirty-one PD patients implanted with STN-DBS (mean age: 66 years; 25 male) were scanned on a 1.5-T magnetic resonance imaging (MRI) scanner using the DTI sequence with DBS on. Twenty-three of them were scanned a second time with DBS off. The NSP, dentato-rubro-thalamic tract (DRTT), and hyperdirect pathway (HDP) were generated using both deterministic and probabilistic tractography methods. The DBS-on-state and off-state tractography results were validated and compared. Afterward, the relationships between the characteristics of the reconstructed white matter tracts and the clinical assessment of PD symptoms and the DBS effect were further examined.ResultsNo adverse events related to DTI were identified in either the DBS-on-state or off-state. Overall, the NSP was best reconstructed, followed by the DRTT and HDP, using the probabilistic tractography method. The connection probability of the left NSP was significantly lower than that of the right side (p < 0.05), and a negative correlation (r = −0.39, p = 0.042) was identified between the preoperative symptom severity in the medication-on state and the connection probability of the left NSP in the DBS-on-state images. Furthermore, the distance from the estimated left-side volume of tissue activated (VTA) by STN-DBS to the ipsilateral NSP was significantly shorter in the DBS-responsive group compared to the DBS-non-responsive group (p = 0.046).ConclusionsDTI scanning is safe and delineation of white matter pathway is feasible for PD patients implanted with the DBS device. Postoperative DTI is a useful technique to strengthen our current understanding of the therapeutic effect of DBS for PD and has the potential to refine target selection strategies for brain stimulation.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40120-022-00331-1.

Corticospinal excitability and conductivity are related to the anatomy of the corticospinal tract.

Probing the brain structure-function relationship is at the heart of modern neuroscientific explorations, enabled by recent advances in brain mapping techniques. This study aimed to explore the anatomical blueprint of corticospinal excitability and shed light on the structure-function relationship within the human motor system. Using diffusion magnetic resonance imaging tractography, based on the spherical deconvolution approach, and transcranial magnetic stimulation (TMS), we show that anatomical inter-individual variability of the corticospinal tract (CST) modulates the corticospinal excitability and conductivity. Our findings show for the first time the relationship between increased corticospinal excitability and conductivity in individuals with a bigger CST (i.e., number of streamlines), as well as increased corticospinal microstructural organization (i.e., fractional anisotropy). These findings can have important implications for the understanding of the neuroanatomical basis of TMS as well as the study of the human motor system in both health and disease.