Trigeminal neuralgia diffusivities using Gaussian process classification and merged group tractography.

ABSTRACT: Imaging of trigeminal neuralgia (TN) has demonstrated key diffusion tensor imaging-based diffusivity alterations in the trigeminal nerve; however, imaging has primarily focused on the peripheral nerve segment because of previous limitations in reliably segmenting small fiber bundles across multiple subjects. We used Selective Automated Group Integrated Tractography to study 36 subjects with TN (right-sided pain) and 36 sex-matched controls to examine the trigeminal nerve (fifth cranial nerve [CN V]), pontine decussation (TPT), and thalamocortical fibers (S1). Gaussian process classifiers were trained by scrolling a moving window over CN V, TPT, and S1 tractography centroids. Fractional anisotropy (FA), generalized FA, radial diffusivity, axial diffusivity, and mean diffusivity metrics were evaluated for both groups, analyzing TN vs control groups and affected vs unaffected sides. Classifiers that performed at greater-than-or-equal-to 70% accuracy were included. Gaussian process classifier consistently demonstrated bilateral trigeminal changes, differentiating them from controls with an accuracy of 80%. Affected and unaffected sides could be differentiated from each other with 75% accuracy. Bilateral TPT could be distinguished from controls with at least 85% accuracy. TPT left-right classification achieved 98% accuracy. Bilateral S1 could be differentiated from controls, where the affected S1 radial diffusivity classifier achieved 87% accuracy. This is the first TN study that combines group-wise merged tractography, machine learning classification, and analysis of the complete trigeminal pathways from the peripheral fibers to S1 cortex. This analysis demonstrates that TN is characterized by bilateral abnormalities throughout the trigeminal pathway compared with controls and abnormalities between affected and unaffected sides. This full pathway tractography study of TN demonstrates bilateral changes throughout the trigeminal pathway and changes between affected and unaffected sides.

Author Correction: The challenge of mapping the human connectome based on diffusion tractography.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Multivariate pattern classification of brain white matter connectivity predicts classic trigeminal neuralgia.

Trigeminal neuralgia (TN) is a severe form of chronic facial neuropathic pain. Increasing interest in the neuroimaging of pain has highlighted changes in the root entry zone in TN, but also group-level central nervous system gray and white matter (WM) abnormalities. Group differences in neuroimaging data are frequently evaluated with univariate statistics; however, this approach is limited because it is based on single, or clusters of, voxels. By contrast, multivariate pattern analyses consider all the model's neuroanatomical features to capture a specific distributed spatial pattern. This approach has potential use as a prediction tool at the individual level. We hypothesized that a multivariate pattern classification method can distinguish specific patterns of abnormal WM connectivity of classic TN from healthy controls (HCs). Diffusion-weighted scans in 23 right-sided TN and matched controls were processed to extract whole-brain interregional streamlines. We used a linear support vector machine algorithm to differentiate interregional normalized streamline count between TN and HC. This algorithm successfully differentiated between TN and HC with an accuracy of 88%. The structural pattern emphasized WM connectivity of regions that subserve sensory, affective, and cognitive dimensions of pain, including the insula, precuneus, inferior and superior parietal lobules, and inferior and medial orbital frontal gyri. Normalized streamline counts were associated with longer pain duration and WM metric abnormality between the connections. This study demonstrates that machine-learning algorithms can detect characteristic patterns of structural alterations in TN and highlights the role of structural brain imaging for identification of neuroanatomical features associated with neuropathic pain disorders.

The challenge of mapping the human connectome based on diffusion tractography.

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

Combined structural and functional patterns discriminating upper limb motor disability in multiple sclerosis using multivariate approaches.

A structural or functional pattern of neuroplasticity that could systematically discriminate between people with impaired and preserved motor performance could help us to understand the brain networks contributing to preservation or compensation of behavior in multiple sclerosis (MS). This study aimed to (1) investigate whether a machine learning-based technique could accurately classify MS participants into groups defined by upper extremity function (i.e. motor function preserved (MP) vs. motor function impaired (MI)) based on their regional grey matter measures (GMM, cortical thickness and deep grey matter volume) and inter-regional functional connection (FC), (2) investigate which features (GMM, FC, or GMM + FC) could classify groups more accurately, and (3) identify the multivariate patterns of GMM and FCs that are most discriminative between MP and MI participants, and between each of these groups and the healthy controls (HCs). With 26 MP, 25 MI, and 21 HCs (age and sex matched) underwent T1-weighted and resting-state functional MRI at 3 T, we applied support vector machine (SVM) based classification to learn discriminant functions indicating regions in which GMM or between which FCs were most discriminative between groups. This study demonstrates that there exist structural and FC patterns sufficient for correct classification of upper limb motor ability of people with MS. The classifier with GMM + FC features yielded the highest accuracy of 85.61 % (p < 0.001) to distinguish between the MS groups using leave-one-out cross-validation. It suggests that a machine-learning approach combining structural and functional features is useful for identifying the specific neural substrates that are necessary and sufficient to preserve motor function among people with MS.

A Neuroimaging Strategy for the Three-Dimensional in vivo Anatomical Visualization and Characterization of Insular Gyri.

BACKGROUND: Interest in the anatomy of the insula is driven by its multifunctionality and the need for accurate visualization for surgical purposes. Few in vivo studies of human insular anatomy have been conducted due to methodological and anatomical challenges. OBJECTIVE: We used brain cortical morphometry tools to accurately reconstruct insular topology and permit a detailed visualization of its gyri in 3 dimensions. METHODS: Sixty healthy subjects (33 females; 37.8 ± 12.8 years) underwent 3-tesla MRI scans. The strategy for characterizing the insula was: (1) create 3-dimensional (3-D) insula representations for visual analysis; (2) rate topological features using a gyral conspicuity index; (3) identify individual variations across subjects/between groups; (4) compare to prior findings. RESULTS: Insular reconstruction was achieved in 113/120 cases. The anterior short, posterior short, anterior long gyri and central sulcus were easily identified. In contrast, middle short (MSG), posterior long (PLG) and accessory gyri (AG) were highly variable. The MSG, but not the PLG or AG, was clearer in males and in the left hemisphere, suggesting sex- and laterality-related differences. CONCLUSIONS: A noninvasive in vivo 3-D visualization strategy revealed anatomical variations of the insula in a healthy cohort. This methodological approach can be adopted for broad clinical and/or research purposes.

Age-related changes in diffusion tensor imaging metrics of fornix subregions in healthy humans.

OBJECTIVE: White matter diffusivity measures of the fornix change with aging, which likely relates to changes in memory and cognition in older adults. Subregional variations in forniceal diffusivity may exist, given its heterogeneous anatomy and connectivity; however, these have not been closely examined in vivo. We examined diffusivity parameters (fractional anisotropy, FA; radial diffusivity, RD; axial diffusivity, AD) in forniceal subregions of healthy subjects and correlated them with age and hippocampal volume. METHODS: Diffusion-weighted imaging and streamline tractography of the fornix were performed on 20 healthy, right-handed females (23-66 years). Six anatomical subregions were defined: midline (body, column, precommissural fornix) or lateral (fimbria, crura, postcommissural fornix). Regression analysis was performed comparing diffusivities against age. Hippocampal and ventricular volumes were also compared. RESULTS: Diffusivity values revealed statistical changes with age in both midline and lateralized subregions. The fornix body and left crus showed age-related alterations in all metrics (FA, RD, AD), whereas only right crus FA was altered. There was no significant change in hippocampal volumes, suggesting that forniceal changes may precede hippocampal age-related changes. CONCLUSIONS: Age-related changes in fornix diffusivity measures appear subregion dependent and asymmetrical. Specific subregion diffusivity measures may be a more sensitive aging marker than hippocampal volume change.

Tractography delineates microstructural changes in the trigeminal nerve after focal radiosurgery for trigeminal neuralgia.

PURPOSE: Focal radiosurgery is a common treatment modality for trigeminal neuralgia (TN), a neuropathic facial pain condition. Assessment of treatment effectiveness is primarily clinical, given the paucity of investigational tools to assess trigeminal nerve changes. Since diffusion tensor imaging (DTI) provides information on white matter microstructure, we explored the feasibility of trigeminal nerve tractography and assessment of DTI parameters to study microstructural changes after treatment. We hypothesized that trigeminal tractography provides more information than 2D-MR imaging, allowing detection of unique, focal changes in the target area after radiosurgery. Changes in specific diffusivities may provide insight into the mechanism of action of radiosurgery on the trigeminal nerve. METHODS AND MATERIALS: Five TN patients (4 females, 1 male, average age 67 years) treated with Gamma Knife radiosurgery, 80 Gy/100% isodose line underwent 3Tesla MR trigeminal nerve tractography before and sequentially up to fourteen months after treatment. Fractional anisotropy (FA), radial (RD) and axial (AD) diffusivities were calculated for the radiosurgical target area defined as the region-of-interest. Areas outside target and the contralateral nerve served as controls. RESULTS: Trigeminal tractography accurately detected the radiosurgical target. Radiosurgery resulted in 47% drop in FA values at the target with no significant change in FA outside the target, demonstrating highly focal changes after treatment. RD but not AD changed markedly, suggesting that radiosurgery primarily affects myelin. Tractography was more sensitive than conventional gadolinium-enhanced post-treatment MR, since FA changes were detected regardless of trigeminal nerve enhancement. In subjects with long term follow-up, recovery of FA/RD correlated with pain recurrence. CONCLUSIONS: DTI parameters accurately detect the effects of focal radiosurgery on the trigeminal nerve, serving as an in vivo imaging tool to study TN. This study is a proof of principle for further assessment of DTI parameters to understand the pathophysiology of TN and treatment effects.

Three-dimensional in vivo modeling of vestibular schwannomas and surrounding cranial nerves with diffusion imaging tractography.

BACKGROUND: Preservation of cranial nerves (CNs) is of paramount concern in the treatment of vestibular schwannomas, particularly in large tumors with thinned and distorted CN fibers. However, imaging of the CN fibers surrounding vestibular schwannomas has been limited with 2-dimensional imaging alone. OBJECTIVE: To assess whether tractography of the CN combined with anatomic magnetic resonance imaging of the tumor can provide superior 3-dimensional (3D) visualization of tumor/CN complexes. METHODS: Magnetic resonance imaging at 3 T, including diffusion tensor imaging and anatomic images, were analyzed in 3 subjects with vestibular schwannomas using 3D Slicer software. The diffusion tensor images were used to track the courses of trigeminal, abducens, facial, and vestibulocochlear nerves. The anatomic images were used to model the 3D volume reconstruction of the tumor. The 2 sets of images were then superimposed through the use of linear registration. RESULTS: Combined 3D tumor modeling and CN tractography can effectively and consistently reconstruct the 3D spatial relationship of CN/tumor complexes and allows superior visualization compared with 2-dimensional imaging. Lateral and superior distortion of the trigeminal nerve was observed in all cases. The position of the facial nerve was primarily anteriorly and inferiorly. The gasserian ganglion and early postganglionic branches could also be visualized. CONCLUSION: Tractography and anatomic imaging were successfully combined to demonstrate the precise location of surrounding CN fibers. This technique can be useful in both neuronavigation and radiosurgical planning. Because knowledge of the course of these fibers is of important clinical interest, implementation of this technique may help decrease injury to CNs during treatment of these lesions.

In vivo visualization of cranial nerve pathways in humans using diffusion-based tractography.

OBJECTIVE: Diffusion-based tractography has emerged as a powerful technique for 3-dimensional tract reconstruction and imaging of white matter fibers; however, tractography of the cranial nerves has not been well studied. In particular, the feasibility of tractography of the individual cranial nerves has not been previously assessed. METHODS: 3-Tesla magnetic resonance imaging scans, including anatomic magnetic resonance images and diffusion tensor images, were used for this study. Tractography of the cranial nerves was performed using 3D Slicer software. The reconstructed 3-dimensional tracts were overlaid onto anatomic images for determination of location and course of intracranial fibers. RESULTS: Detailed tractography of the cranial nerves was obtained, although not all cranial nerves were imaged with similar anatomic fidelity. Some tracts were imaged in great detail (cranial nerves II, III, and V). Tractography of the optic apparatus allowed tracing from the optic nerve to the occipital lobe, including Meyer's loop. Trigeminal tractography allowed visualization of the gasserian ganglion as well as postganglionic fibers. Tractography of cranial nerve III shows the course of the fibers through the midbrain. Lower cranial nerves (cranial nerves IX, XI, and XII) could not be imaged well. CONCLUSION: Tractography of the cranial nerves is feasible, although technical improvements are necessary to improve the tract reconstruction of the lower cranial nerves. Detailed assessment of anatomy and the ability of overlaying the tracts onto anatomic magnetic resonance imaging scans is essential, particularly in the posterior fossa, to ensure that the tracts have been reconstructed with anatomic fidelity.