Diffusion tensor tractography in children with sensory processing disorder: Potentials for devising machine learning classifiers.
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ABSTRACT:
SUBMITTER: Payabvash S
PROVIDER: S-EPMC6488562 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Publications
Diffusion tensor tractography in children with sensory processing disorder: Potentials for devising machine learning classifiers.
Payabvash Seyedmehdi S Palacios Eva M EM Owen Julia P JP Wang Maxwell B MB Tavassoli Teresa T Gerdes Molly M Brandes-Aitken Anne A Marco Elysa J EJ Mukherjee Pratik P
NeuroImage. Clinical 20190424
The "sensory processing disorder" (SPD) refers to brain's inability to organize sensory input for appropriate use. In this study, we determined the diffusion tensor imaging (DTI) microstructural and connectivity correlates of SPD, and apply machine learning algorithms for identification of children with SPD based on DTI/tractography metrics. A total of 44 children with SPD and 41 typically developing children (TDC) were prospectively recruited and scanned. In addition to fractional anisotropy (F ...[more]
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Project description:BackgroundThe brainstem is the main region that innervates neurotransmitter release to the Hypothalamic-Pituitary Adrenal (HPA) axis and fronto-limbic circuits, two key brain circuits found to be dysfunctional in Major Depressive Disorder (MDD). However, the brainstem's role in MDD has only been evaluated in limited reports. Using Diffusion Tensor Imaging (DTI), we investigated whether major brainstem white matter tracts that relate to these two circuits differ in MDD patients compared to healthy controls.MethodsMDD patients (n = 95) and age- and gender-matched controls (n = 34) were assessed using probabilistic tractography of DTI to delineate three distinct brainstem tracts: the nigrostriatal tract (connecting brainstem to striatum), solitary tract (connecting brainstem to amygdala) and corticospinal tract (connecting brainstem to precentral cortex). Fractional anisotropy (FA) was used to measure the white matter integrity of these tracts, and measures were compared between MDD and control participants.ResultsMDD participants were characterized by a significant and specific decrease in white matter integrity of the right solitary tract (p<0.009 using independent t-test), which is a "bottom up" afferent pathway that connects the brainstem to the amygdala. This decrease was not related to symptom severity.ConclusionsThe results provide new evidence to suggest that structural connectivity between the brainstem and the amygdala is altered in MDD. These results are interesting in light of predominant theories regarding amygdala-mediated emotional reactivity observed in functional imaging studies of MDD. The characterization of altered white matter integrity in the solitary tract in MDD supports the possibility of dysfunctional brainstem-amygdala connectivity impacting vulnerable circuits in MDD.
| S-EPMC3897382 | biostudies-literature
Project description:The caudate nucleus has been thought to be involved in the control of motor commands by the cerebrum, and recent studies suggest that it may play a role in the control of attachment behavior, cognition, emotion, and mental functions. Implied by the basal ganglia's involvement in the execution, planning and control of movement, the caudate nucleus functions in a situation-dependent manner where processing of external stimuli is important on the basis of learning and memory. Sensory processing, which determines the response to external stimuli, has been shown to be related to various brain regions but it remains unknown how sensory processing is associated with the structure of the caudate nucleus and white matter microstructures of the caudate. Using four diffusion parameters derived from diffusion tensor imaging (DTI) (i.e., fractional anisotropy (FA), mean diffusivity (MD), axonal diffusivity (AD), and radial diffusivity (RD)) and the Adolescent/Adult Sensory Profile (AASP) questionnaire of 99 healthy subjects [42 males and 57 females; mean age:26.9 years, standard deviation 6.9], we investigated the relationship between white matter structure in the caudate nucleus and sensory processing. In consistent with what had been suggested by the results of previous studies, we found significant correlations between AD, MD and tactile sensation. Furthermore, we found a significant correlation between AD, MD and tactile sensory avoidance, the AASP sub-scores regarding the tactile senses. To the best of our knowledge, this is the first study to show that DTI diffusion parameters correlate with AASP scores in specific brain regions.
| S-EPMC10085014 | biostudies-literature
Project description:BackgroundDiffusion tensor imaging (DTI) infers the trajectory and location of large white matter tracts by measuring the anisotropic diffusion of water. DTI data may then be analyzed and presented as tractography for visualization of the tracts in 3 dimensions. Despite the important information contained in tractography images, usefulness for neurosurgical planning has been limited by the inability to define which are critical structures within the mass of demonstrated fibers and to clarify their relationship to the tumor.ObjectiveTo develop a method to allow the interactive querying of tractography data sets for surgical planning and to provide a working software package for the research community.MethodsThe tool was implemented within an open source software project. Echo-planar DTI at 3 T was performed on 5 patients, followed by tensor calculation. Software was developed that allowed the placement of a dynamic seed point for local selection of fibers and for fiber display around a segmented structure, both with tunable parameters. A neurosurgeon was trained in the use of software in < 1 hour and used it to review cases.ResultsTracts near tumor and critical structures were interactively visualized in 3 dimensions to determine spatial relationships to lesion. Tracts were selected using 3 methods: anatomical and functional magnetic resonance imaging-defined regions of interest, distance from the segmented tumor volume, and dynamic seed-point spheres.ConclusionInteractive tractography successfully enabled inspection of white matter structures that were in proximity to lesions, critical structures, and functional cortical areas, allowing the surgeon to explore the relationships between them.
| S-EPMC3112275 | biostudies-literature
Project description:Diffusion tensor tractography is increasingly used to examine structural connectivity in the brain in various conditions, but its test-retest reliability is understudied. The main purposes of this study were to evaluate 1) the reliability of quantitative measurements of diffusion tensor tractography and 2) the effect on reliability of the number of gradient sampling directions and scan repetition. Images were acquired from ten healthy participants. Ten fiber regions of nine major fiber tracts were reconstructed and quantified using six fiber variables. Intra- and inter-session reliabilities were estimated using intraclass correlation coefficient (ICC) and coefficient of variation (CV), and were compared to pinpoint major error sources. Additional pairwise comparisons were made between the reliability of images with 30 directions and NEX 2 (DTI30-2), 30 directions and NEX 1 (DTI30-1), and 15 directions and NEX 2 (DTI15-2) to determine whether increasing gradient directions and scan repetition improved reliability. Of the 60 tractography measurements, 43 showed intersession CV ? 10%, ICC ? .70, or both for DTI30-2, 40 measurements for DTI30-1, and 37 for DTI15-2. Most of the reliable measurements were associated with the tracts corpus callosum, cingulum, cerebral peduncular fibers, uncinate fasciculus, and arcuate fasciculus. These reliable measurements included factional anisotropy (FA) and mean diffusivity of all 10 fiber regions. Intersession reliability was significantly worse than intra-session reliability for FA, mean length, and tract volume measurements from DTI15-2, indicating that the combination of MRI signal variation and physiological noise/change over time was the major error source for this sequence. Increasing the number of gradient directions from 15 to 30 while controlling the scan time, significantly affected values for all six variables and reduced intersession variability for mean length and tract volume measurements. Additionally, while increasing scan repetition from 1 to 2 had no significant effect on the reliability for DTI with 30 directions, this significantly reduced the upward bias in FA values from all 10 fiber regions and fiber count, mean length, and tract volume measurements from 5 to 7 fiber regions. In conclusion, diffusion tensor tractography provided many measurements with high test-retest reliability across different fiber variables and various fiber tracts even for images with 15 directions (NEX 2). Increasing the number of gradient directions from 15 to 30 with equivalent scan time reduced variability whereas increasing repetition from 1 to 2 for 30-direction DTI improved the accuracy of tractography measurements.
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Project description:Diffusion-tensor MRI fiber tractography has been used to reconstruct skeletal muscle architecture, but remains a specialized technique using custom-written data processing routines. In this work, we describe the public release of a software toolbox having the following design objectives: accomplish the pre-processing tasks of file input, image registration, denoising, and diffusion-tensor calculation; allow muscle-specific methods for defining seed points; make fiber-tract architectural measurements referenced to tendinous structures; visualize fiber tracts and other muscle structures of interest; analyze the goodness of outcomes; and provide a programming structure that allows the addition of new capabilities in future versions. The proper function of the code was verified using simulated datasets. The toolbox capabilities for characterizing human muscle structure in vivo were demonstrated in a case study. These capabilities included measurements of muscle morphology; contractile and non-contractile tissue volumes; fiber-tract length, pennation angle, curvature; and the physiological cross-sectional area,. The free public release of this software is a first step in creating of a community of users who use these tools in studies of muscle physiology and biomechanics. Users may further contribute to code development. Along with simulated and actual datasets for benchmarking, these tools will further create mechanisms for enhancing scientific rigor and developing and validating new code features. Planned future developments include additional options for image pre-processing, development of a graphical user interface, analysis of architectural patterns during muscle contraction, and integration of functional imaging data.
| S-EPMC9673086 | biostudies-literature
Project description:IntroductionCortico-cortical evoked potentials (CCEPs) are utilized to identify effective networks in the human brain. Following single-pulse electrical stimulation of cortical electrodes, evoked responses are recorded from distant cortical areas. A negative deflection (N1) which occurs 10-50 ms post-stimulus is considered to be a marker for direct cortico-cortical connectivity. However, with CCEPs alone it is not possible to observe the white matter pathways that conduct the signal or accurately predict N1 amplitude and latency at downstream recoding sites. Here, we develop a new approach, termed "dynamic tractography," which integrates CCEP data with diffusion-weighted imaging (DWI) data collected from the same patients. This innovative method allows greater insights into cortico-cortical networks than provided by each method alone and may improve the understanding of large-scale networks that support cognitive functions. The dynamic tractography model produces several fundamental hypotheses which we investigate: 1) DWI-based pathlength predicts N1 latency; 2) DWI-based pathlength negatively predicts N1 voltage; and 3) fractional anisotropy (FA) along the white matter path predicts N1 propagation velocity.MethodsTwenty-three neurosurgical patients with drug-resistant epilepsy underwent both extraoperative CCEP recordings and preoperative DWI scans. Subdural grids of 3 mm diameter electrodes were used for stimulation and recording, with 98-128 eligible electrodes per patient. CCEPs were elicited by trains of 1 Hz stimuli with an intensity of 5 mA and recorded at a sample rate of 1 kHz. N1 peak and latency were defined as the maximum of a negative deflection within 10-50 ms post-stimulus with a z-score > 5 relative to baseline. Electrodes and DWI were coregistered to construct electrode connectomes for white matter quantification.ResultsClinical variables (age, sex, number of anti-epileptic drugs, handedness, and stimulated hemisphere) did not correlate with the key outcome measures (N1 peak amplitude, latency, velocity, or DWI pathlength). All subjects and electrodes were therefore pooled into a group-level analysis to determine overall patterns. As hypothesized, DWI path length positively predicted N1 latency (R2 = 0.81, β = 1.51, p = 4.76e-16) and negatively predicted N1 voltage (R2 = 0.79, β = -0.094, p = 9.30e-15), while FA predicted N1 propagation velocity (R2 = 0.35, β = 48.0, p = 0.001).ConclusionWe have demonstrated that the strength and timing of the CCEP N1 is dependent on the properties of the underlying white matter network. Integrated CCEP and DWI visualization allows robust localization of intact axonal pathways which effectively interconnect eloquent cortex.
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Project description:Left unilateral neglect, a dramatic condition which impairs awareness of left-sided events, has been classically reported after right hemisphere cortical lesions involving the inferior parietal region. More recently, the involvement of long range white matter tracts has been highlighted, consistent with the idea that awareness of events occurring in space depends on the coordinated activity of anatomically distributed brain regions. Damage to the superior longitudinal fasciculus (SLF), linking parietal to frontal cortical regions, or to the inferior longitudinal fasciculus (ILF), connecting occipital and temporal lobes, has been described in neglect patients. In this study, four right-handed patients with right hemisphere strokes underwent a high definition anatomical MRI with diffusion tensor imaging (DTI) sequences and a pencil and paper neglect battery of tests. We used DTI tractography to visualise the SLF, ILF and the inferior fronto-occipital fasciculus (IFOF), a pathway running the depth of the temporal lobe, not hitherto associated with neglect. Two patients with cortical involvement of the inferior parietal and superior temporal regions, but intact and symmetrical fasciculi, showed no signs of neglect. The other two patients with signs of left neglect had superficial damage to the inferior parietal cortex and white matter damage involving the IFOF. These findings suggest that superficial damage to the inferior parietal cortex per se may not be sufficient to produce visual neglect. In some cases, a lesion to the direct connections between ventral occipital and frontal regions (ie, IFOF) may contribute to the manifestation of neglect by impairing the top down modulation of visual areas from the frontal cortex.
| S-EPMC2386830 | biostudies-literature
Project description:Evaluation of brainstem pathways with diffusion tensor imaging (DTI) and tractography may provide insights into pathophysiologies associated with dysfunction of key brainstem circuits. However, identification of these tracts has been elusive, with relatively few in vivo human studies to date. In this paper we proposed an automated approach for reconstructing nine brainstem fiber trajectories of pathways that might be involved in pain modulation. We first performed native-space manual tractography of these fiber tracts in a small normative cohort of participants and confirmed the anatomical precision of the results using existing anatomical literature. Second, region-of-interest pairs were manually defined at each extracted fiber's termini and nonlinearly warped to a standard anatomical brain template to create an atlas of the region-of-interest pairs. The resulting atlas was then transformed non-linearly into the native space of 17 veteran patients' brains for automated brainstem tractography. Lastly, we assessed the relationships between the integrity levels of the obtained fiber bundles and pain severity levels. Fractional anisotropy (FA) measures derived using automated tractography reflected the respective tracts' FA levels obtained via manual tractography. A significant inverse relationship between FA and pain levels was detected within the automatically derived dorsal and medial longitudinal fasciculi of the brainstem. This study demonstrates the feasibility of DTI in exploring brainstem circuitries involved in pain processing. In this context, the described automated approach is a viable alternative to the time-consuming manual tractography. The physiological and functional relevance of the measures derived from automated tractography is evidenced by their relationships with individual pain severities.
| S-EPMC7028272 | biostudies-literature
Project description:Background and purposePatients with craniosynostosis syndromes caused by mutations in FGFR-2, FGFR-3, and TWIST1 genes are characterized by having prematurely fused skull sutures and skull base synchondroses, which result in a skull deformity and are accompanied by brain anomalies, including altered white matter microarchitecture. In this study, the reliability and reproducibility of DTI fiber tractography was investigated in these patients. The outcomes were compared with those of controls.Materials and methodsDTI datasets were acquired with a 1.5T MR imaging system with 25 diffusion gradient orientations (voxel size = 1.8 × 1.8 × 3.0 mm(3), b-value = 1000 s/mm(2)). White matter tracts studied included the following: corpus callosum, cingulate gyrus, fornix, corticospinal tracts, and medial cerebellar peduncle. Tract pathways were reconstructed with ExploreDTI in 58 surgically treated patients with craniosynostosis syndromes and 7 controls (age range, 6-18 years).ResultsBecause of the brain deformity and abnormal ventricular shape and size, DTI fiber tractography was challenging to perform in patients with craniosynostosis syndromes. To provide reliable tracts, we adapted standard tracking protocols. Fractional anisotropy was equal to that in controls (0.44 versus 0.45 ± 0.02, P = .536), whereas mean, axial, and radial diffusivity parameters of the mean white matter were increased in patients with craniosynostosis syndromes (P < .001). No craniosynostosis syndrome-specific difference in DTI properties was seen for any of the fiber tracts studied in this work.ConclusionsPerforming DTI fiber tractography in patients with craniosynostosis syndromes was difficult due to partial volume effects caused by an anisotropic voxel size and deformed brain structures. Although these patients have a normal fiber organization, increased diffusivity parameters suggest abnormal microstructural tissue properties of the investigated white matter tracts.
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Project description:Advanced brain imaging of neonatal macrostructure and microstructure, which has prognosticating importance, is more frequently being incorporated into multi-center trials of neonatal neuroprotection. Multicenter neuroimaging studies, designed to overcome small sample sized clinical cohorts, are essential but lead to increased technical variability. Few harmonization techniques have been developed for neonatal brain microstructural (diffusion tensor) analysis. The work presented here aims to remedy two common problems that exist with the current state of the art approaches: 1) variance in scanner and protocol in data collection can limit the researcher's ability to harmonize data acquired under different conditions or using different clinical populations. 2) The general lack of objective guidelines for dealing with anatomically abnormal anatomy and pathology. Often, subjects are excluded due to subjective criteria, or due to pathology that could be informative to the final analysis, leading to the loss of reproducibility and statistical power. This proves to be a barrier in the analysis of large multi-center studies and is a particularly salient problem given the relative scarcity of neonatal imaging data. We provide an objective, data-driven, and semi-automated neonatal processing pipeline designed to harmonize compartmentalized variant data acquired under different parameters. This is done by first implementing a search space reduction step of extracting the along-tract diffusivity values along each tract of interest, rather than performing whole-brain harmonization. This is followed by a data-driven outlier detection step, with the purpose of removing unwanted noise and outliers from the final harmonization. We then use an empirical Bayes harmonization algorithm performed at the along-tract level, with the output being a lower dimensional space but still spatially informative. After applying our pipeline to this large multi-site dataset of neonates and infants with congenital heart disease (n= 398 subjects recruited across 4 centers, with a total of n=763 MRI pre-operative/post-operative time points), we show that infants with single ventricle cardiac physiology demonstrate greater white matter microstructural alterations compared to infants with bi-ventricular heart disease, supporting what has previously been shown in literature. Our method is an open-source pipeline for delineating white matter tracts in subject space but provides the necessary modular components for performing atlas space analysis. As such, we validate and introduce Diffusion Imaging of Neonates by Group Organization (DINGO), a high-level, semi-automated framework that can facilitate harmonization of subject-space tractography generated from diffusion tensor imaging acquired across varying scanners, institutions, and clinical populations. Datasets acquired using varying protocols or cohorts are compartmentalized into subsets, where a cohort-specific template is generated, allowing for the propagation of the tractography mask set with higher spatial specificity. Taken together, this pipeline can reduce multi-scanner technical variability which can confound important biological variability in relation to neonatal brain microstructure.
| S-EPMC9575513 | biostudies-literature