Generalized Fractional Anisotropy Research Articles

Diffusion spectrum imaging in patients with idiopathic normal pressure hydrocephalus: correlation with ventricular enlargement

BackgroundTo investigate the association between white matter changes and ventricular expansion in idiopathic normal pressure hydrocephalus (iNPH) based on diffusion spectrum imaging (DSI).MethodsWe included 32 patients with iNPH who underwent DSI using a 3T MRI scanner. The lateral ventricles were manually segmented, and ventricular volumes were measured. Two methods were utilised in the study: manual region-of-interest (ROI) delineation and tract diffusion profile analysis. General fractional anisotropy (GFA) and fractional anisotropy (FA) were extracted in different white matter regions, including the bilateral internal capsule (anterior and posterior limbs) and corpus callosum (body, genu, and splenium) with manual ROI delineation. The 18 main tracts in the brain of each patient were extracted; the diffusion metrics of 100 equidistant nodes on each fibre were calculated, and Spearman’s correlation coefficient was used to determine the correlation between diffusion measures and ventricular volume of iNPH patients.ResultsThe GFA and FA of all ROI showed no significant correlation with lateral ventricular volume. However, in the tract diffusion profile analysis, lateral ventricular volume was positively correlated with part of the cingulum bundle, left corticospinal tract, and bilateral thalamic radiation posterior, whereas it was negatively correlated with the bilateral cingulum parahippocampal (all p < 0.05).ConclusionsThe effect of ventricular enlargement in iNPH on some white matter fibre tracts around the ventricles was limited and polarizing, and most white matter fibre tract integrity changes were not associated with ventricular enlargement; this reflects that multiple pathological mechanisms may have been combined to cause white matter alterations in iNPH.

Life-course neighbourhood deprivation and brain structure in older adults: the Lothian Birth Cohort 1936.

Neighbourhood disadvantage may be associated with brain health but the importance of exposure at different stages of the life course is poorly understood. Utilising the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and local neuroimaging measures at age 73. A total of 689 participants had at least one valid brain measures (53% male); to maximise the sample size structural equation models with fullinformation maximum likelihood were conducted. Residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (β = -0.06; SE = 0.02; sample size[N] = 658; number of pairwise complete observations[n]=390), grey matter (β = -0.11; SE = 0.03; N = 658; n = 390), and normal-appearing white matter volumes (β = -0.07; SE = 0.03; N = 658; n = 390), thinner cortex (β = -0.14; SE = 0.06; N = 636; n = 379), and lower general white matter fractional anisotropy (β = -0.19; SE = 0.06; N = 665; n = 388). We also found some evidence on the accumulating impact of neighbourhood deprivation from birth to late adulthood on age 73 total brain (β = -0.06; SE = 0.02; N = 658; n = 276) and grey matter volumes (β = -0.10; SE = 0.04; N = 658; n = 276). Local analysis identified affected focal cortical areas and specific white matter tracts. Among individuals belonging to lower social classes, the brain-neighbourhood associations were particularly strong, with the impact of neighbourhood deprivation on total brain and grey matter volumes, and general white matter fractional anisotropy accumulating across the life course. Our findings suggest that living in deprived neighbourhoods across the life course, but especially in mid- to late adulthood, is associated with adverse brain morphologies, with lower social class amplifying the vulnerability.

Structural network disruption of corticothalamic pathways in cerebral small vessel disease

Generalized fractional anisotropy (GFA) can eliminate the crossing fiber effect, which may be more reflective of brain tissue changes in patients with cerebral small vessel disease (CSVD). This study aimed to explore the alterations of structural networks based on GFA and its relationship with cognitive performance in CSVD patients. We recruited 50 CSVD patients which were divided into two groups: cognitive impairment (CSVD-CI) and normal cognition (CSVD-NC), and 22 healthy controls (HCs). All participants underwent the Montreal Cognitive Assessment (MoCA) and MRI examinations. The structural topological properties were compared among the three groups. The correlation between these structural alterations and MoCA was analyzed. Compared with HCs, significantly decreased nodal efficiency and connectivity were detected in the corticothalamic pathways in both patient groups, of which some were significantly decreased in CSVD-CIs compared with CSVD-NCs. Moreover, both patient groups exhibited global network disruption including decreased global efficiency and increased characteristic path length compared with HCs. Furthermore, the nodal efficiency in the right pallidum positively correlated with MoCA in CSVD-NCs controlling for nuisance variables (r = 0.471, p = 0.031). The alterations in corticothalamic pathways indicated that the brain structural network underwent extensive disruption, providing evidence for the consideration of CSVD as a global brain disease.

Basal Ganglia Compensatory White Matter Changes on DTI in Alzheimer's Disease.

The volume reduction of the gray matter structures in patients with Alzheimer's disease is often accompanied by an asymmetric increase in the number of white matter fibers located close to these structures. The present study aims to investigate the white matter structure changes in the motor basal ganglia in Alzheimer's disease patients compared to healthy controls using diffusion tensor imaging. The amounts of tracts, tract length, tract volume, quantitative anisotropy, and general fractional anisotropy were measured in ten patients with Alzheimer's disease and ten healthy controls. A significant decrease in the number of tracts and general fractional anisotropy was found in patients with Alzheimer's disease compared to controls in the right caudate nucleus, while an increase was found in the left and the right putamen. Further, a significant decrease in the structural volume of the left and the right putamen was observed. An increase in the white matter diffusion tensor imaging parameters in patients with Alzheimer's disease was observed only in the putamen bilaterally. The right caudate showed a decrease in both the diffusion tensor imaging parameters and the volume in Alzheimer's disease patients. The right pallidum showed an increase in the diffusion tensor imaging parameters but a decrease in volume in Alzheimer's disease patients.

Disrupted white matter network of brain structural connectomes in bipolar disorder patients revealed by q-ball imaging

BackgroundStructural and functional brain changes have been found to be associated with altered emotion and cognition in patients with bipolar disorder (BD). Widespread microstructural white matter abnormalities have been observed using traditional structural imaging in BD. q-Ball imaging (QBI) and graph theoretical analysis (GTA) improve the specificity and sensitivity and high accuracy of fiber tracking. We applied QBI and GTA to investigate and compare the structural connectivity alterations and network alterations in patients with and without BD. MethodsSixty-two patients with BD and 62 healthy controls (HCs) completed a MR scan. We evaluated the group differences in generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA) values by voxel-based statistical analysis with QBI. We also evaluated the group differences in topological parameters of GTA and subnetwork interconnections in network-based statistical analysis (NBS). ResultsThe QBI indices in the BD group were significantly lower than those in the HC group in the corpus callosum, cingulate gyrus, and caudate. The GTA indices indicated that the BD group demonstrated less global integration and higher local segregation than the HC group, but they retained small-world properties. NBS evaluation showed that the majority of the more connected subnetworks in BD occurred in thalamo-temporal/parietal connectivity. ConclusionOur findings supported white matter integrity with network alterations in BD.

Improving the brain image resolution of generalized q-sampling MRI revealed by a three-dimensional CNN-based method.

Understanding neural connections facilitates the neuroscience and cognitive behavioral research. There are many nerve fiber intersections in the brain that need to be observed, and the size is between 30 and 50 nanometers. Improving image resolution has become an important issue for mapping the neural connections non-invasively. Generalized q-sampling imaging (GQI) was used to reveal the fiber geometry of straight and crossing. In this work, we attempted to achieve super-resolution with a deep learning method on diffusion weighted imaging (DWI). A three-dimensional super-resolution convolutional neural network (3D SRCNN) was utilized to achieve super-resolution on DWI. Then, generalized fractional anisotropy (GFA), normalized quantitative anisotropy (NQA), and the isotropic value of the orientation distribution function (ISO) mapping were reconstructed using GQI with super-resolution DWI. We also reconstructed the orientation distribution function (ODF) of brain fibers using GQI. With the proposed super-resolution method, the reconstructed DWI was closer to the target image than the interpolation method. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were also significantly improved. The diffusion index mapping reconstructed by GQI also had higher performance. The ventricles and white matter regions were much clearer. This super-resolution method can assist in postprocessing low-resolution images. With SRCNN, high-resolution images can be effectively and accurately generated. The method can clearly reconstruct the intersection structure in the brain connectome and has the potential to accurately describe the fiber geometry on a subvoxel scale.

Atypical development in white matter microstructures in ADHD: A longitudinal diffusion imaging study.

In cross-sectional studies, alterations in white matter microstructure are evident in children with attention-deficit/hyperactivity disorder (ADHD) but not so prominent in adults with ADHD compared to typically-developing controls (TDC). Moreover, the developmental trajectories of white matter microstructures in ADHD are unclear, given the limited longitudinal imaging studies that characterize developmental changes in ADHD vs. TDC. This longitudinal study acquired diffusion spectrum imaging (DSI) at two time points. The sample included 55 participants with ADHD and 61 TDC. The enrollment/first DSI age ranged from 7 to 18 years, with a five-year mean follow-up time. We examined time-by-diagnosis interaction on the generalized fractional anisotropy (GFA) of 45 white matter tracts, adjusting for confounding factors and correcting for multiple comparisons. We also tested whether the longitudinal changes of microstructures were associated with ADHD symptoms and attention performance in a computerized continuous performance test. Participants with ADHD showed more rapid development of GFA in the arcuate fasciculus, superior longitudinal fasciculus, frontal aslant tract, cingulum, inferior fronto-occipital fasciculus (IFOF), frontostriatal tract connecting the prefrontal cortex (FS-PFC), thalamic radiation, corticospinal tract, and corpus callosum. Within participants with ADHD, more rapid GFA increases in cingulum and FS-PFC were associated with slower decreases in inattention symptoms. In addition, in all participants, more rapid GFA increases in cingulum and IFOF were associated with greater improvement in attention performance. Our findings suggest atypical developmental trajectories of white matter tracts in ADHD, characterized by normalization and possible compensatory neuroplastic processes with age from childhood to early adulthood.

HIV peripheral neuropathy‐related degeneration of white matter tracts to sensorimotor cortex

Human immunodeficiency virus-associated distal sensory polyneuropathy (HIV-DSP) affects up to 50% of people with HIV and is associated with depression, unemployment, and generally worsened quality of life. Previous work on the cortical mechanism of HIV neuropathy found decreased gray matter volume in the bilateral midbrain, thalamus, and posterior cingulate cortex, but structural connectivity in this context remains under-studied. Here we examine alterations in white matter microstructure using diffusion imaging, hypothesizing that cortical white matter degeneration would be observed in continuation of the peripheral white matter atrophy previously observed in HIV-DSP. Male HIV seropositive patients (n = 57) experiencing varying degrees of HIV neuropathy underwent single-shell diffusion tensor imaging with 51 sampling directions. The scans were pooled using tractography and connectometry to create a quantitative map of white matter tract integrity, measured in generalized fractional anisotropy (GFA). The relationship between GFA and neuropathy severity was evaluated with linear regression. Correction for multiple comparisons was done using false discovery rate (FDR), a statistical method commonly used in genomics and imaging to minimize false positives when thousands of individual comparisons are made. Neuropathy severity was associated with decreased GFA along thalamocortical radiations leading along the lateral thalamus to sensorimotor cortex, with r = -0.405 (p < 0.001; FDR), as well as with the superior bilateral cingulum (r = -0.346 (p < 0.05; FDR)). Among a population of HIV neuropathy patients, greater neuropathy severity was correlated with lower white matter integrity running from midbrain to somatosensory cortex. This suggests ascending deafferentation extending from damaged peripheral nerves further downstream than seen previously, into the axons of third-order neurons. There is also evidence of cingulum degeneration, implying some more complex mechanism beyond the ascending atrophy observed here.

Brain white matter correlates of learning ankle tracking using a wearable device: importance of the superior longitudinal fasciculus II

BackgroundWearable devices have been found effective in training ankle control in patients with neurological diseases. However, the neural mechanisms associated with using wearable devices for ankle training remain largely unexplored. This study aimed to investigate the ankle tracking performance and brain white matter changes associated with ankle tracking learning using a wearable-device system and the behavior–brain structure relationships in middle-aged and older adults.MethodsTwenty-six middle-aged and older adults (48–75 years) participated in this study. Participants underwent 5-day ankle tracking learning with their non-dominant foot using a custom-built ankle tracking system equipped with a wearable sensor and a sensor-computer interface for real-time visual feedback and data acquisition. Repeated and random sequences of target tracking trajectories were both used for learning and testing. Ankle tracking performance, calculated as the root-mean-squared-error (RMSE) between the target and actual ankle trajectories, and brain diffusion spectrum MR images were acquired at baseline and retention tests. The general fractional anisotropy (GFA) values of eight brain white matter tracts of interest were calculated to indicate their integrity. Two-way (Sex × Time) mixed repeated measures ANOVA procedures were used to investigate Sex and Time effects on RMSE and GFA. Correlations between changes in RMSE and those in GFA were analyzed, controlling for age and sex.ResultsAfter learning, both male and female participants reduced the RMSE of tracking repeated and random sequences (both p < 0.001). Among the eight fiber tracts, the right superior longitudinal fasciculus II (R SLF II) was the only one which showed both increased GFA (p = 0.039) after learning and predictive power of reductions in RMSE for random sequence tracking with its changes in GFA [β = 0.514, R2 change = 0.259, p = 0.008].ConclusionsOur findings implied that interactive tracking movement learning using wearable sensors may place high demands on the attention, sensory feedback integration, and sensorimotor transformation functions of the brain. Therefore, the SLF II, which is known to perform these brain functions, showed corresponding neural plasticity after such learning, and its plasticity also predicted the behavioral gains. The SLF II appears to be a very important anatomical neural correlate involved in such learning paradigms.

The Effects of Nicotine and Cannabis Co-Use During Late Adolescence on White Matter Fiber Tract Microstructure

Co-use of cannabis and nicotine and tobacco products (NTPs) in adolescence/young adulthood is common and associated with worse outcomes than the use of either substance in isolation. Despite this, little is known about the unique contributions of co-use to neurostructural microstructure during this neurodevelopmentally important period. This study sought to investigate the interactive effects of nicotine and cannabis co-use on white matter fiber tract microstructure in emerging adulthood. A total of 111 late adolescent (16-22 years old) nicotine (NTP; n = 55, all past-year cannabis users) and non-nicotine users (non-NTP; n = 56, 61% reporting cannabis use in the past year) completed demographic and clinical interviews and a neuroimaging session comprising anatomical and diffusion-weighted imaging scans. Group connectometry analysis identified white matter tracts significantly associated with the interaction between nicotine group and past-year cannabis use according to generalized fractional anisotropy (GFA). Nicotine Group × Cannabis Use interactions were observed in the right and left cingulum and left fornix tracts (false discovery rate = 0.053), where greater cannabis use was associated with increased GFA in the cingulum and left fornix, but only when co-used with nicotine. This report represents the first group connectometry analysis in late adolescent/young adult cannabis and/or NTP users. Results suggest that co-use of cannabis and NTPs results in a structurally distinct white matter phenotype as compared with cannabis use only, although to what extent this may change over time with more chronic nicotine and cannabis use remains to be examined in future work.

Altered White-matter Tract Property in Adults with Attention-deficit Hyperactivity Disorder

Although altered microstructure properties of white-matter tracts have been reported in children with attention-deficit/hyperactivity disorder (ADHD), findings from relatively few adult ADHD studies are inconsistent. This study aims to examine microstructural property over the whole brain in adults with ADHD and explore structural connectivities. Sixty-four medication-naïve adults with ADHD and 81 healthy adults received diffusion spectrum imaging. Generalized fractional anisotropy (GFA), an index indicating microstructural property, was calculated stepwise among 76 white-matter tracts. With the threshold-free clustering weighted method, the segments with the largest group difference were selected, and mean GFA (mGFA) values were calculated. Adults with ADHD had increased mGFA values in the segments located in the left frontal aslant tract, the right inferior longitudinal fasciculus, and the left perpendicular fasciculus, and reduced mGFA values in the segments located in the right superior longitudinal fasciculus (SLF) I, the left SLF II, the right frontostriatal tracts from dorsolateral prefrontal cortex and the ventrolateral prefrontal cortex, the right medial lemniscus, the right inferior thalamic radiation to the auditory cortex, and the callosal fibers. Additionally, the mGFA value of the right SLF I segment was associated with hyperactivity-impulsivity symptoms. Our findings suggest that white-matter tracts with altered microstructure properties are located within the attention networks, fronto-striato-thalamocortical regions, and those associated with attention and visual perception in adults with ADHD.

Quantification of changes in white matter tract fibers in idiopathic normal pressure hydrocephalus based on diffusion spectrum imaging

PurposePatients with idiopathic normal pressure hydrocephalus (iNPH) present white-matter abnormalities. The analytical methods described to date only measure mean diffusion parameter alterations of iNPH-specific brain regions or in a certain fasciculus. This study quantitatively analyzed whether iNPH-tract abnormalities are confined to specific sections or involve entire fibers based on diffusion spectrum imaging (DSI). MethodTwenty-two patients with iNPH and 20 normally aging subjects were included. The 18 main tracts in the brain of each subject were extracted, and the diffusion parameters of 100 equidistant nodes on each fiber were calculated to quantitatively evaluate integrity changes in different regions along these tracts. Two diffusion metrics were measured, i.e., general fractional anisotropy (GFA) and fractional anisotropy (FA). ResultsCompared to normally aging (P < 0.05), in iNPH, the GFA and FA of the left uncinate fasciculus and FA of the bilateral superior longitudinal fasciculus 1 were reduced in areas where the entire fiber was involved (%nodes with significant differences > 90%). Most other fasciculi detected presented GFA or FA alterations limited to specific regions. Increased and decreased GFA or FA co-occurred in different sections of the same fibers, including the corticospinal tract and left thalamic radiation posterior in iNPH. ConclusionsFew iNPH fibers presented diffusion abnormalities involving nearly all tracts. Most fiber abnormalities in iNPH were confined to specific areas, and different parts of the same fasciculus showed diverse diffusion alterations in few cases. This DSI-based tract analysis provided detailed information on iNPH white-matter changes.

Trigeminal Nerve White Matter Fiber Abnormalities in Primary Trigeminal Neuralgia: A Diffusion Spectrum Imaging Study

ObjectiveDiffusion spectrum imaging (DSI) was used to quantitatively study the changes in the trigeminal cistern segment in patients with trigeminal neuralgia (TN) and to further explore the value of acquiring DSI data from patients with TN.MethodsTo achieve high-resolution fiber tracking, 60 patients with TN and 35 healthy controls (HCs) were scanned with conventional magnetic resonance imaging (MRI) and DSI. The patients and the members of the control group were compared within and between groups. The correlations between quantitative parameters of DSI and the visual analog scale (VAS), and symptom duration and responsible vessel types were analyzed.ResultsCompared with unaffected side of patients in the TN group, the affected side showed significantly decreased quantitative anisotropy (QA) (p < 0.001), fractional anisotropy (FA) (p = 0.001), and general FA (GFA) (p < 0.001). The unaffected side exhibited significantly decreased QA (p + 0.001), FA (p = 0.001), and GFA (p < 0.001) and significantly increased axial diffusivity (AD) (p = 0.036) compared with the affected side of patients in the TN group and the average values of HCs. There were significantly decreased QA (p = 0.046) and FA (p = 0.008) between the unaffected side of patients and the average values of HCs. GFA can evidently distinguish arteries, veins, and features of unaffected side in TN patients.ConclusionUsing high-resolution fiber tracking technology, DSI can provide quantitative information that can be used to detect the integrity of trigeminal white matter in patients with TN and can improve the understanding of the disease mechanism.

Reproduced correlations between integrity of white matter tracts and self-reported anxiety

Diffusion tensor imaging (DTI) allows us to evaluate the structural properties of white matter tracts which are associated with trait anxiety. However, in recent DTI studies of anxiety, research was focused mainly on selected white matter tracts, e.g. the uncinate fasciculus. At the same time, whole-brain structural connectivity has been rarely investigated in non-clinical populations. The present study aimed to explore correlations between white matter tract characteristics evaluated with the generalized fractional anisotropy (GFA) measure and state and trait anxiety inventory (STAI) scores at the whole-brain scale using the connectometry approach. In addition, we conducted psychological testing twice and examined the within-study reproducibility of these correlations. The results indicate reproduced correlations between both trait and state anxiety scores and GFA in the corpus callosum and association fibers predominantly in the right hemisphere, including the inferior, superior, and inferior fronto-occipital fasciculus, and cingulum bundle. The associations with state anxiety are the same as with trait anxiety except for the negative one with GFA in the left cingulum. The findings point to the role of the integrity of these white matter tracts in susceptibility to high trait and state anxiety. The defined local connectome correlations with anxiety ratings could serve as targets for anxiety disorders preventive diagnostics.

Assessment of Disrupted Brain Structural Connectome in Depressive Patients With Suicidal Ideation Using Generalized Q-Sampling MRI.

Suicide is one of the leading causes of mortality worldwide. Various factors could lead to suicidal ideation (SI), while depression is the predominant cause among all mental disorders. Studies have shown that alterations in brain structures and networks may be highly associated with suicidality. This study investigated both neurological structural variations and network alterations in depressed patients with suicidal ideation by using generalized q-sampling imaging (GQI) and Graph Theoretical Analysis (GTA). This study recruited 155 participants and divided them into three groups: 44 depressed patients with suicidal ideation (SI+; 20 males and 24 females with mean age = 42, SD = 12), 56 depressed patients without suicidal ideation (Depressed; 24 males and 32 females with mean age = 45, SD = 11) and 55 healthy controls (HC; nine males and 46 females with mean age = 39, SD = 11). Both the generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA) values were evaluated in a voxel-based statistical analysis by GQI. We analyzed different topological parameters in the graph theoretical analysis and the subnetwork interconnections in the Network-based Statistical (NBS) analysis. In the voxel-based statistical analysis, both the GFA and NQA values in the SI+ group were generally lower than those in the Depressed and HC groups in the corpus callosum and cingulate gyrus. Furthermore, we found that the SI+ group demonstrated higher global integration and lower local segregation among the three groups of participants. In the network-based statistical analysis, we discovered that the SI+ group had stronger connections of subnetworks in the frontal lobe than the HC group. We found significant structural differences in depressed patients with suicidal ideation compared to depressed patients without suicidal ideation and healthy controls and we also found several network alterations among these groups of participants, which indicated that white matter integrity and network alterations are associated with patients with depression as well as suicidal ideation.

Prenatal Exposure to Endocrine-Disrupting Chemicals and Subsequent Brain Structure Changes Revealed by Voxel-Based Morphometry and Generalized Q-Sampling MRI.

Previous studies have indicated that prenatal exposure to endocrine-disrupting chemicals (EDCs) can cause adverse neuropsychiatric disorders in children and adolescents. This study aimed to determine the association between the concentrations of prenatal EDCs and brain structure changes in teenagers by using MRI. We recruited 49 mother–child pairs during the third trimester of pregnancy, and collected and examined the concentration of EDCs—including phthalate esters, perfluorochemicals (PFCs), and heavy metals (lead, arsenic, cadmium, and mercury)—in maternal urine and/or serum. MRI voxel-based morphometry (VBM) and generalized q-sampling imaging (GQI) mapping—including generalized fractional anisotropy (GFA), normalized quantitative anisotropy (NQA), and the isotropic value of the orientation distribution function (ISO)—were obtained in teenagers 13–16 years of age in order to find the association between maternal EDC concentrations and possible brain structure alterations in the teenagers’ brains. We found that there are several specific vulnerable brain areas/structures associated with prenatal exposure to EDCs, including decreased focal brain volume, primarily in the frontal lobe; high frontoparietal lobe, temporooccipital lobe and cerebellum; and white matter structural alterations, which showed a negative association with GFA/NQA and a positive association with ISO, primarily in the corpus callosum, external and internal capsules, corona radiata, superior fronto-occipital fasciculus, and superior longitudinal fasciculus. Prenatal exposure to EDCs may be associated with specific brain structure alterations in teenagers.

White matter microstructural integrity correlates of emotion dysregulation in children with ADHD: A diffusion imaging tractography study

BackgroundEmotion dysregulation (ED) is prevalent in youths with attention-deficit hyperactivity disorder (ADHD) and causes more social impairment and poor adaptive function. Alterations in the integrity of white matter (WM) tracts might have important implications for affective processing related to ED. However, little is known about the WM correlates underpinning ED in ADHD. MethodsUsing diffusion spectrum image tractography, we obtained generalized fractional anisotropy (GFA) values of 76 WM tracts in 77 children with ADHD and 105 typically developing controls (TDC). ED severity was defined by the dysregulation profile from the child behavior checklist. Canonical correlation analysis (CCA) was performed to identify modes that relate WM microstructural property to ED severity and cognitive measures. ResultsThe application of CCA identified one significant mode (r = 0.638, FWE-corrected p = 0.046) of interdependencies between WM property patterns and diagnosis, ADHD total symptom levels, dysregulation by diagnosis interaction, and full-scale intellectual quotient (FIQ). GFA values of 19 WM tracts that were linked to affective-processing, sensory-processing and integration, and cognitive control circuitry were positively correlated with ED severity in TDC but negatively correlated with ED severity in ADHD. ADHD symptom severity and diagnosis were negatively associated with the GFA patterns of this set of tract bundles. In contrast, FIQ was positively correlated with this set of tract bundles. ConclusionsThis study used the CCA to show that children with ADHD and TDC had distinct multivariate associations between ED severity (diagnosis by ED interaction) and microstructural property in a set of WM tracts. These tracts interconnect the cortical regions that are principally involved in emotion processing, integration, and cognitive control in multiple brain systems. The WM microstructure integrity impairment might be an essential correlate of emotion dysregulation in ADHD.

Mapping Brain Microstructure and Network Alterations in Depressive Patients with Suicide Attempts Using Generalized Q-Sampling MRI

Depressive disorder is one of the leading causes of disability worldwide, with a high prevalence and chronic course. Depressive disorder carries an increased risk of suicide. Alterations in brain structure and networks may play an important role in suicidality among depressed patients. Diffusion magnetic resonance imaging (MRI) is a noninvasive method to map white-matter fiber orientations and provide quantitative parameters. This study investigated the neurological structural differences and network alterations in depressed patients with suicide attempts by using generalized q-sampling imaging (GQI). Our study recruited 155 participants and assigned them into three groups: 44 depressed patients with a history of suicide attempts (SA), 56 depressed patients without a history of suicide attempts (D) and 55 healthy controls (HC). We used the GQI to analyze the generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA) values in voxel-based statistical analysis, topological parameters in graph theoretical analysis and subnetwork connectivity in network-based statistical analysis. GFA indicates the measurement of neural anisotropy and represents white-matter integrity; NQA indicates the amount of anisotropic spins that diffuse along fiber orientations and represents white-matter compactness. In the voxel-based statistical analysis, we found lower GFA and NQA values in the SA group than in the D and HC groups and lower GFA and NQA values in the D group than in the HC group. In the graph theoretical analysis, the SA group demonstrated higher local segregation and lower global integration among the three groups. In the network-based statistical analysis, the SA group showed stronger subnetwork connections in the frontal and parietal lobes, and the D group showed stronger subnetwork connections in the parietal lobe than the HC group. Alternations were found in the structural differences and network measurements in healthy controls and depressed patients with and without a history of suicide attempt.

Diffusion Spectrum Imaging of Corticospinal Tracts in Idiopathic Normal Pressure Hydrocephalus.

Purpose: The purpose of this study was to measure the diffusion spectrum imaging (DSI) parameters of corticospinal tracts (CSTs) and evaluate diffusional changes in CSTs in patients with idiopathic normal pressure hydrocephalus (iNPH) by DSI.Methods: Twenty-three iNPH patients and twenty-one healthy controls (HCs) were involved in this study. Brain DSI data for all participants were collected through the same MR scanning procedure. The diffusion parameters measured and analyzed included quantitative anisotropy (QA), the isotropic diffusion component (ISO), general fractional anisotropy (GFA), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of corticospinal tracts.Results: The QA and ISO values of corticospinal tracts in iNPH patients were significantly lower than those in HCs (PLQA = 0.008, PRQA = 0.016, PLISO = 0.024, PRISO = 0.016). The mean MD, AD, and RD values in iNPH patients were significantly higher than those in HCs (PMD = 0.032, PAD = 0.032, PRD = 0.048,). No significant differences in GFA and FA values were noted between iNPH patients and HCs.Conclusion: Decreased QA and ISO values of corticospinal tracts were found in iNPH patients. Quantitative CST evaluation using DSI may lead to information that can improve the present understanding of the disease mechanism.

Convolutional Neural Network–Based Deep Learning Model for Predicting Differential Suicidality in Depressive Patients Using Brain Generalized q-Sampling Imaging

Suicide is a priority health problem. Suicide assessment depends on imperfect clinician assessment with minimal ability to predict the risk of suicide. Machine learning/deep learning provides an opportunity to detect an individual at risk of suicide to a greater extent than clinician assessment. The present study aimed to use deep learning of structural magnetic resonance imaging (MRI) to create an algorithm for detecting suicidal ideation and suicidal attempts. We recruited 4 groups comprising a total of 186 participants: 33 depressive patients with suicide attempt (SA), 41 depressive patients with suicidal ideation (SI), 54 depressive patients without suicidal thoughts (DP), and 58 healthy controls (HCs). The confirmation of depressive disorder, SA and SI was based on psychiatrists' diagnosis and Mini-International Neuropsychiatric Interview (MINI) interviews. In the generalized q-sampling imaging (GQI) dataset, indices of generalized fractional anisotropy (GFA), the isotropic value of the orientation distribution function (ISO), and normalized quantitative anisotropy (NQA) were separately trained in convolutional neural network (CNN)-based deep learning and DenseNet models. From the results of 5-fold cross-validation, the best accuracies of the CNN classifier for predicting SA, SI, and DP against HCs were 0.916, 0.792, and 0.589, respectively. In SA-ISO, DenseNet outperformed the simple CNNs with a best accuracy from 5-fold cross-validation of 0.937. In SA-NQA, the best accuracy was 0.915. The results showed that a deep learning method based on structural MRI can effectively detect individuals at different levels of suicide risk, from depression to suicidal ideation and attempted suicide. Further studies from different populations, larger sample sizes, and prospective follow-up studies are warranted to confirm the utility of deep learning methods for suicide prevention and intervention.