Altered white matter connectivity of ventral language networks in autism spectrum disorder: An automated fiber quantification analysis with multi-site datasets.

Comprehension and pragmatic deficits are prevalent in autism spectrum disorder (ASD) and are potentially linked to altered connectivity in the ventral language networks. However, previous magnetic resonance imaging studies have not sufficiently explored the microstructural abnormalities in the ventral fiber tracts underlying comprehension dysfunction in ASD. Additionally, the precise locations of white matter (WM) changes in the long tracts of patients with ASD remain poorly understood. In the current study, we applied the automated fiber-tract quantification (AFQ) method to investigate the fine-grained WM properties of the ventral language pathway and their relationships with comprehension and symptom manifestation in ASD. The analysis included diffusion/T1 weighted imaging data of 83 individuals with ASD and 83 age-matched typically developing (TD) controls. Case-control comparisons were performed on the diffusion metrics of the ventral tracts at both the global and point-wise levels. We also explored correlations between diffusion metrics, comprehension performance, and ASD traits, and conducted subgroup analyses based on age range to examine developmental moderating effects. Individuals with ASD exhibited remarkable hypoconnectivity in the ventral tracts, particularly in the temporal portions of the left inferior longitudinal fasciculus (ILF) and the inferior fronto-occipital fasciculus (IFOF). These WM abnormalities were associated with poor comprehension and more severe ASD symptoms. Furthermore, WM alterations in the ventral tract and their correlation with comprehension dysfunction were more prominent in younger children with ASD than in adolescents. These findings indicate that WM disruptions in the temporal portions of the left ILF/IFOF are most notable in ASD, potentially constituting the core neurological underpinnings of comprehension and communication deficits in autism. Moreover, impaired WM connectivity and comprehension ability in patients with ASD appear to improve with age.

Microscopic fractional anisotropy outperforms multiple sclerosis lesion assessment and clinical outcome associations over standard fractional anisotropy tensor.

We aimed to compare the ability of diffusion tensor imaging and multi-compartment spherical mean technique to detect focal tissue damage and in distinguishing between different connectivity patterns associated with varying clinical outcomes in multiple sclerosis (MS). Seventy-six people diagnosed with MS were scanned using a SIEMENS Prisma Fit 3T magnetic resonance imaging (MRI), employing both conventional (T1w and fluid-attenuated inversion recovery) and advanced diffusion MRI sequences from which fractional anisotropy (FA) and microscopic FA (µFA) maps were generated. Using automated fiber quantification (AFQ), we assessed diffusion profiles across multiple white matter (WM) pathways to measure the sensitivity of anisotropy diffusion metrics in detecting localized tissue damage. In parallel, we analyzed structural brain connectivity in a specific patient cohort to fully grasp its relationships with cognitive and physical clinical outcomes. This evaluation comprehensively considered different patient categories, including cognitively preserved (CP), mild cognitive deficits (MCD), and cognitively impaired (CI) for cognitive assessment, as well as groups distinguished by physical impact: those with mild disability (Expanded Disability Status Scale [EDSS] <=3) and those with moderate-severe disability (EDSS >3). In our initial objective, we employed Ridge regression to forecast the presence of focal MS lesions, comparing the performance of µFA and FA. µFA exhibited a stronger association with tissue damage and a higher predictive precision for focal MS lesions across the tracts, achieving an R-squared value of .57, significantly outperforming the R-squared value of .24 for FA (p-value <.001). In structural connectivity, µFA exhibited more pronounced differences than FA in response to alteration in both cognitive and physical clinical scores in terms of effect size and number of connections. Regarding cognitive groups, FA differences between CP and MCD groups were limited to 0.5% of connections, mainly around the thalamus, while µFA revealed changes in 2.5% of connections. In the CP and CI group comparison, which have noticeable cognitive differences, the disparity was 5.6% for FA values and 32.5% for µFA. Similarly, µFA outperformed FA in detecting WM changes between the MCD and CI groups, with 5% versus 0.3% of connections, respectively. When analyzing structural connectivity between physical disability groups, µFA still demonstrated superior performance over FA, disclosing a 2.1% difference in connectivity between regions closely associated with physical disability in MS. In contrast, FA spotted a few regions, comprising only 0.6% of total connections. In summary, µFA emerged as a more effective tool than FA in predicting MS lesions and identifying structural changes across patients with different degrees of cognitive and global disability, offering deeper insights into the complexities of MS-related impairments.

Association between segmental alterations of white matter bundles and cognitive performance in first-episode, treatment-naïve young adults with major depressive disorder.

BACKGROUND: Cumulative evidence has consistently shown that white matter (WM) disruption is associated with cognitive decline in geriatric depression. However, limited research has been conducted on the correlation between these lesions and cognitive performance in untreated young adults with major depressive disorder (MDD), particularly with the specific segmental alterations of the fibers. METHOD: Diffusion tensor images were performed on 60 first-episode, treatment-naïve young adult patients with MDD and 54 matched healthy controls (HCs). Automated fiber quantification was applied to calculate the tract profiles of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) to evaluate the WM microstructural organization. Correlation analysis was performed to find the associations between the diffusion properties and cognitive performance. RESULTS: Compared with HCs, patients with MDD exhibited predominantly different diffusion properties in bilateral uncinate fasciculus (UF), corticospinal tracts (CSTs), left superior longitudinal fasciculus and anterior thalamic radiation. The FA of the temporal cortex portion of right UF was positively correlated with working memory. The MD of the temporal component of left UF was negatively correlated with working memory and positively correlated with symptom severity. Additionally, a positive correlation between the MD of left CST and the psychomotor speed, negative correlation between the MD of left CST and the executive functions and complex attentional processes were observed. CONCLUSIONS: Our study validated the alterations in spatial localization of WM microstructure and its correlations with cognitive performance in first-episode, treatment-naïve young adults with MDD. This study added to the knowledge of the neuropathological basis of MDD.

Exploring the Structural Plasticity Mechanism of Corticospinal Tract during Stroke Rehabilitation Based Automated Fiber Quantification Tractography.

BACKGROUND: Corticospinal tract (CST) is the principal motor pathway; we aim to explore the structural plasticity mechanism in CST during stroke rehabilitation. METHODS: A total of 25 patients underwent diffusion tensor imaging before rehabilitation (T1), 1-month post-rehabilitation (T2), 2 months post-rehabilitation (T3), and 1-year post-discharge (T4). The CST was segmented, and fractional anisotropy (FA), axial diffusion (AD), mean diffusivity (MD), and radial diffusivity (RD) were determined using automated fiber quantification tractography. Baseline level of laterality index (LI) and motor function for correlation analysis. RESULTS: The FA values of all segments in the ipsilesional CST (IL-CST) were lower compared with normal CST. Repeated measures analysis of variance showed time-related effects on FA, AD, and MD of the IL-CST, and there were similar dynamic trends in these 3 parameters. At T1, FA, AD, and MD values of the mid-upper segments of IL-CST (around the core lesions) were the lowest; at T2 and T3, values for the mid-lower segments were lower than those at T1, while the values for the mid-upper segments gradually increased; at T4, the values for almost entire IL-CST were higher than before. The highest LI was observed at T2, with a predominance in contralesional CST. The LIs for the FA and AD at T1 were positively correlated with the change rate of motor function. CONCLUSIONS: IL-CST showed aggravation followed by improvement from around the lesion to the distal end. Balance of interhemispheric CST may be closely related to motor function, and LIs for FA and AD may have predictive value for mild-to-moderate stroke rehabilitation. Clinical Trial Registration. URL: http://www.chictr.org.cn; Unique Identifier: ChiCTR1800019474.

Exploring subtypes of multiple sclerosis through unsupervised machine learning of automated fiber quantification.

PURPOSE: This study aimed to subtype multiple sclerosis (MS) patients using unsupervised machine learning on white matter (WM) fiber tracts and investigate the implications for cognitive function and disability outcomes. MATERIALS AND METHODS: We utilized the automated fiber quantification (AFQ) method to extract 18 WM fiber tracts from the imaging data of 103 MS patients in total. Unsupervised machine learning techniques were applied to conduct cluster analysis and identify distinct subtypes. Clinical and diffusion tensor imaging (DTI) metrics were compared among the subtypes, and survival analysis was conducted to examine disability progression and cognitive impairment. RESULTS: The clustering analysis revealed three distinct subtypes with variations in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Significant differences were observed in clinical and DTI metrics among the subtypes. Subtype 3 showed the fastest disability progression and cognitive decline, while Subtype 2 exhibited a slower rate, and Subtype 1 fell in between. CONCLUSIONS: Subtyping MS based on WM fiber tracts using unsupervised machine learning identified distinct subtypes with significant cognitive and disability differences. WM abnormalities may serve as biomarkers for predicting disease outcomes, enabling personalized treatment strategies and prognostic predictions for MS patients.

Brain white matter microstructural alterations in patients with systemic lupus erythematosus: an automated fiber quantification study.

This study aimed to identify damaged segments of brain white matter fiber tracts in patients with systemic lupus erythematosus (SLE) using diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ), and analyze their relationship with cognitive impairment. Clinical and imaging data for 39 female patients with SLE and for 44 female healthy controls (HCs) were collected. AFQ was used to track whole-brain white matter tracts in each participant, and each tract was segmented into 100 equally spaced nodes. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated at each node. Correlations were also explored between DTI metrics in the damaged segments of white matter fiber tracts and neuropsychological test scores of patients with SLE. Compared with HCs, SLE patients exhibited significantly lower FA values, and significantly higher MD, AD, RD values in many white matter tracts (all P < 0.05, false discovery rate-corrected). FA values in nodes 97-100 of the left inferior fronto-occipital fasciculus (IFOF) positively correlated with the mini-mental state examination score. AFQ enables precise and accurate identification of damage to white matter fiber tracts in brains of patients with SLE. FA values in the left IFOF correlate with cognitive impairment in SLE.

Aberrant white matter microstructure detected by automatic fiber quantification in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease.

BACKGROUND AND OBJECTIVES: Myelin oligodendrocyte glycoprotein antibody-associated diseases (MOGAD) is an idiopathic inflammatory demyelinating disorder in children, for which the precise damage patterns of the white matter (WM) fibers remain unclear. Herein, we utilized diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ) to identify patterns of fiber damage and to investigate the clinical significance of MOGAD-affected fiber tracts. METHODS: A total of 28 children with MOGAD and 31 healthy controls were included in this study. The AFQ approach was employed to track WM fiber with 100 equidistant nodes defined along each tract for statistical analysis of DTI metrics in both the entire and nodal manner. The feature selection method was used to further screen significantly aberrant DTI metrics of the affected fiber tracts or segments for eight common machine learning (ML) to evaluate their potential in identifying MOGAD. These metrics were then correlated with clinical scales to assess their potential as imaging biomarkers. RESULTS: In the entire manner, significantly reduced fractional anisotropy (FA) was shown in the left anterior thalamic radiation, arcuate fasciculus, and the posterior and anterior forceps of corpus callosum in MOGAD (all p < 0.05). In the nodal manner, significant DTI metrics alterations were widely observed across 37 segments in 10 fiber tracts (all p < 0.05), mainly characterized by decreased FA and increased radial diffusivity (RD). Among them, 14 DTI metrics in seven fiber tracts were selected as important features to establish ML models, and satisfactory discrimination of MOGAD was obtained in all models (all AUC > 0.85), with the best performance in the logistic regression model (AUC = 0.952). For those features, the FA of left cingulum cingulate and the RD of right inferior frontal-occipital fasciculus were negatively and positively correlated with the expanded disability status scale (r = -0.54, p = 0.014; r = 0.43, p = 0.03), respectively. CONCLUSION: Pediatric MOGAD exhibits extensive WM fiber tract aberration detected by AFQ. Certain fiber tracts exhibit specific patterns of DTI metrics that hold promising potential as biomarkers.

Alterations in white matter fiber tracts and their correlation with flying cadet behavior.

An increasing number of studies have shown that flight training alters the human brain structure; however, most studies have focused on gray matter, and the exploration of white matter structure has been largely neglected. This study aimed to investigate the changes in white matter structure induced by flight training and estimate the correlation between such changes and psychomotor and flight performance. Diffusion tensor imaging data were obtained from 25 flying cadets and 24 general college students. Data were collected in 2019 and 2022 and analyzed using automated fiber quantification. This study found no significant changes in the flight group in 2019. However, in 2022, the flight group exhibited significant alterations in the diffusion tensor imaging of the right anterior thalamic radiation, left cingulum cingulate, bilateral superior longitudinal fasciculus, and left arcuate fasciculus. These changes occurred within local nodes of the fiber tracts. In addition, we found that changes in fiber tracts in the 2022 flight group were correlated with the reaction time of the psychomotor test task and flight duration. These findings may help improve flight training programs and provide new ideas for the selection of excellent pilots.

Segmental disturbance of white matter microstructure in predicting mild cognitive impairment in idiopathic Parkinson's disease: An individualized study based on automated fiber quantification tractography.

PURPOSE: The neurobiological mechanisms and an early identification of MCI in idiopathic Parkinson's disease (IPD) remain unclear. To investigate the abnormalities of types of white matter (WM) fiber tracts segmentally and establish reliable indicator in IPD-MCI. METHODS: Forty IPD with normal cognition (IPD-NCI), thirty IPD-MCI, and thirty healthy controls were included. Automated fiber quantification was applied to extract the fractional anisotropy (FA) and mean diffusivity (MD) values at 100 locations along the major fibers. Partial correlation was performed between diffusion values and cognitive performance. Furthermore, machine learning analyses were conducted to determine the imaging biomarker of MCI. Permutation tests were performed to evaluate the pointwise differences under the FWE correction. RESULTS: IPD-MCI had similar but more severe and widespread WM degeneration in the association, projection, and commissural fibers compared with IPD-NCI. Meanwhile, IPD-MCI showed distinct degeneration pattern in the association fibers. The FA of the anterior segment of right inferior fronto-occipital fasciculus (IFOF) was positively correlated with MoCA (P < 0.05) and executive function (P < 0.05). The MD of the middle and posterior segment of left superior longitudinal fasciculus (SLF) was negatively correlated with MoCA P < 0.05), executive (P < 0.05), visuospatial function (P < 0.05). Furthermore, the AUC of support vector machine model was 0.80 in the validation dataset. The FA of anterior segment of right IFOF contribute the most. CONCLUSION: This study demonstrated that regional tract-specific microstructural degeneration, especially the association fibers, can be used to predict MCI in IPD. Especially, the right IFOF may be a significant imaging biomarker in predicting IPD with MCI.

Microstructure abnormalities of the diffusion quantities in children with attention-deficit/hyperactivity disorder: an AFQ and TBSS study.

Objective: To explore the specific alterations of white matter microstructure in children with attention-deficit/hyperactivity disorder (ADHD) by automated fiber quantification (AFQ) and tract-based spatial statistics (TBSS), and to analyze the correlation between white matter abnormality and impairment of executive function. Methods: In this prospective study, a total of twenty-seven patients diagnosed with ADHD (20 males, 7 females; mean age of 8.89 ± 1.67 years) and twenty-two healthy control (HC) individuals (11 males, 11 females, mean age of 9.82 ± 2.13 years) were included. All participants were scanned with diffusion kurtosis imaging (DKI) and assessed for executive functions. AFQ and TBSS analysis methods were used to investigate the white matter fiber impairment of ADHD patients, respectively. Axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD) and fractional anisotropy (FA) of 17 fiber properties were calculated using the AFQ. The mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), mean diffusivity (MDDKI), axial diffusivity (ADDKI), radial diffusivity (RDDKI) and fractional anisotropy (FADKI) of DKI and AD, RD, MD, and FA of diffusion tensor imaging (DTI) assessed the integrity of the white matter based on TBSS. Partial correlation analyses were conducted to evaluate the correlation between white matter abnormalities and clinical test scores in ADHD while taking age, gender, and education years into account. The analyses were all family-wise error rate (FWE) corrected. Results: ADHD patients performed worse on the Behavior Rating Inventory of Executive Function (BRIEF) test (p < 0.05). Minor variances existed in gender and age between ADHD and HC, but these variances did not yield statistically significant distinctions. There were no significant differences in TBSS for DKI and DTI parameters (p > 0.05, TFCE-corrected). Compared to HC volunteers, the mean AD value of right cingulum bundle (CB_R) fiber tract showed a significantly higher level in ADHD patients following the correction of FWE. As a result of the point-wise comparison between groups, significant alterations (FWE correction, p < 0.05) were mainly located in AD (nodes 36-38, nodes 83-97) and MD (nodes 92-95) of CB_R. There was no significant correlation between white matter diffusion parameters and clinical test scores in ADHD while taking age, gender, and education years into account. Conclusion: The AFQ method can detect ADHD white matter abnormalities in a specific location with greater sensitivity, and the CB_R played a critical role. Our findings may be helpful in further studying the relationship between focal white matter abnormalities and ADHD.

Abnormal white matter along fibers by automated fiber quantification in patients undergoing hemodialysis.

BACKGROUND: Abnormal white matter has been reported in patients with end-stage renal disease (ESRD). However, few studies have investigated the relationship between specific damage segments and cognition in ESRD. This study aimed to delineate white matter alterations in ESRD and its relationship with cognition. METHODS: A total of 36 patients undergoing hemodialysis and 25 healthy controls underwent diffusion tensor imaging (DTI) and a series of neuropsychiatric tests. Automated fiber quantification was used to extract distinct DTI indices, and the relationship between the specific segment of the white matter and clinical properties was investigated. Furthermore, a support vector machine was applied to differentiate patients with ESRD from healthy controls. RESULTS: Fractional anisotropy values decreased in multiple fiber bundles, including bilateral thalamic radiata, cingulum cingulate, inferior fronto-occipital fasciculus (IFOF), uncinate, Callosum_Forceps_Major/Callosum_Forceps_Minor (CFMaj/CFMin), and left uncinate from the tract level in patients with ESRD. Specific damaged segments were detected in 8 fiber bundles, including bilateral thalamic radiation, cingulum cingulate, IFOF, CFMin, and left corticospinal tract. Few alterations in these fiber bundles were correlated with cognition impairment and hemoglobin levels. The tract profiles of the left thalamic radiata and left cingulum cingulate could be used to differentiate hemodialysis patients from healthy controls, with an accuracy of 76.9% and 67.6%, respectively. CONCLUSIONS: This study revealed white matter damage in hemodialysis patients. This damage occurred in specific segments of the tract, especially in the left thalamic radiata and left cingulum cingulate, which might become a new biomarker for patients with ESRD and cognition impairment.

White matter microstructural abnormalities in individuals with attenuated positive symptom syndromes.

White matter (WM) microstructural alterations have been extensively studied in patients with psychosis, but research on the microstructure of WM in individuals with attenuated positive symptom syndrome (APSS) is currently limited. To improve the understanding of the neuropathology in APSS, this study investigated the WM of individuals with APSS using diffusion tensor and T1-weighted imaging. Automated fiber quantification was used to calculate the diffusion index values along the trajectories of 20 major fiber tracts in 42 individuals with APSS and 51 age-and sex-matched healthy control (HC) individuals. The diffusion index values in each of fiber tracts were compared node-by-node between the 2 groups. Compared with the HC group, the APSS group showed differences in the diffusion index values in partial segments of the callosum forceps minor, left and right cingulum cingulate, inferior fronto-occipital fasciculus, right corticospinal tract, left superior longitudinal fasciculus, and arcuate fasciculus. Notably, in the APSS group positive associations were found between the axial diffusivity values of the partial nodes of the left and right cingulum cingulate and the current Global Assessment of Functioning scores, as well as between the axial diffusivity values of the partial nodes of the right corticospinal tract and negative symptoms scores and reasoning and problem-solving scores. These findings suggest that individuals with APSS exhibit reduced WM integrity or possible impaired myelin in certain segments of WM tracts involved in the frontal- and limbic-cortical connections. Additionally, abnormal WM tracts appear to be associated with impaired general function and neurocognitive function. This study provides important new insights into the neurobiology of APSS and highlights potential targets for future intervention and treatment.

Abnormal focal segments in left uncinate fasciculus in adults with obsessive-compulsive disorder.

Background: Although the specific role of the uncinate fasciculus (UF) in emotional processing in patients with obsessive-compulsive disorder (OCD) has been investigated, the exact focal abnormalities in the UF have not been identified. The aim of the current study was to identify focal abnormalities in the white matter (WM) microstructure of the UF and to determine the associations between clinical features and structural neural substrates. Methods: In total, 71 drug-naïve patients with OCD and 81 age- and sex-matched healthy controls (HCs) were included. Automated fiber quantification (AFQ), a tract-based quantitative approach, was adopted to measure alterations in diffusion parameters, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD), along the trajectory of the UF. Additionally, we utilized partial correlation analyses to explore the relationship between the altered diffusion parameters and clinical characteristics. Results: OCD patients showed significantly higher FA and lower RD at the level of the temporal and insular portions in the left UF than HCs. In the insular segments of the left UF, increased FA was positively correlated with the Hamilton Anxiety Scale (HAMA) score, while decreased RD was negatively correlated with the duration of illness. Conclusion: We observed specific focal abnormalities in the left UF in adult patients with OCD. Correlations with measures of anxiety and duration of illness underscore the functional importance of the insular portion of left UF disturbance in OCD patients.

Altered microstructural pattern of the cortex and basal forebrain cholinergic system in wilson's disease: an automated fiber quantification tractography study.

Basal forebrain (BF) cholinergic projection neurons form a highly extensive input to the cortex. Failure of BF cholinergic circuits is responsible for the cognitive impairment associated with Wilson's disease (WD), but whether and how the microstructural changes in fiber projections between the BF and cerebral cortex influence prospective memory (PM) remain poorly understood. We collected diffusion tensor imaging (DTI) data from 21 neurological WD individuals and 26 healthy controls (HCs). The experiment reconstructed the probabilistic streamlined tractography of 18 white matter tracts using an automated fiber quantification (AFQ) toolkit. Tract properties (FA, MD, RD, and AD) were computed for 100 points along each tract for each participant, and the differences between the groups were examined. Subsequently, correlation analysis was performed to evaluate whether abnormal microstructural white matter integrity measures correlate with PM performance. Additional investigations used a tract-based spatial statistics (TBSS) approach to identify regions with altered white matter structure between groups and verify the reliability of the AFQ results. The highest nonoverlapping DTI-related differences were detected in the anterior thalamic radiation (ATR), corticospinal tract (CST), corpus callosum, association fibers, and limbic system fibers. Additionally, PM parameters of the patient group were highly correlated with white matter microstructure changes in the inferior longitudinal fasciculus. Our study highlights that the performance of projections between cholinergic input and output areas-the cerebral cortex and BF-may serve as neural biomarkers of PM and disease prognosis.

Segmental Abnormalities of White Matter Microstructure in Primary Hypothyroidism Identified by Automated Fiber Quantification.

INTRODUCTION: Hypothyroidism leads to impaired white matter (WM) integrity, associated with cognitive/neuropsychiatric dysfunction. However, the specific segmental abnormalities of the fibers remain unexplored. Therefore, this study aimed to investigate whether the damage of the WM is limited to a specific segment or the entire bundle via diffusion metrics using automated fiber quantification. METHODS: A cross-sectional study was conducted on 31 hypothyroid patients and 28 healthy controls. Thyroid-related hormone levels, cognitive/neuropsychiatric function, and diffusion tensor image data were collected and analyzed. Correlation and random forest analyses were also performed. RESULTS: The mean fractional anisotropy (FA) values were reduced at the fiber tract level. The mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values were increased in several fiber tracts, i.e., cingulum cingulate (CC), anterior forceps of corpus callosum (CCF_A). Significant correlations were found between cognitive function and diffusion indicators such as the FA value of the left corticospinal tract and arcuate fasciculus (AF), the MD value of left CC, the RD value of left AF, the AD value of left CC, and CCF_A. The widespread microstructure disruption was spread on multiple specific segments of different tracts at the point-wise level. The random forest revealed that the accuracy of recognizing hypothyroid patients was 82.5%, with the anterior component of CCF_A having the most significant contribution. CONCLUSION: WM microstructural integrity impairments were found in multi-segments of the multiple fiber bundles in hypothyroidism, which might be a potential mechanism of the underlying neurocognitive decline and cerebral impairment. The CCF_A might serve as a neuro biomarker for early warning of cerebral impairment in hypothyroidism.

Neuroimaging mechanisms in short-term heroin- and methamphetamine-abstinent users: Similarities and differences.

Heroin and methamphetamine cause great damage to individuals and society. However, numerous withdrawal mechanisms remain unidentified. In this study, 19 heroin short-term abstinent (HSTA) patients, 20 methamphetamine short-term abstinent (MSTA) patients, and 27 healthy controls (HCs) were scanned using multimodal magnetic resonance imaging. Degraded nodes of fiber tracts were identified using automated fiber quantification. Voxel- and surface-based morphometric measurements were performed to determine the gray matter volume and cortical thickness. The MSTA and HSTA groups had abnormal diffusion metrics in a variety of bilateral corticospinal tract (CST) and left superior longitudinal tract (SLT) nodes compared with the HC group. The MSTA patients reported more severely disrupted diffusion metrics in certain nodes of the bilateral anterior thalamic radiation and left inferior fronto-occipital tract than the HSTA patients. The MSTA and HSTA groups exhibited identical cortical damage in the fusiform and superior temporal gyri, as well as in the superior frontal gyrus, posterior cerebellum, and precentral gyrus. Extensive differences in gray matter lesions were observed between the MSTA and HSTA groups. Neuroimaging mechanisms of short-term abstinence may aid in the development of rehabilitation strategies.

Altered MRI Diffusion Properties of the White Matter Tracts Connecting Frontal and Thalamic Brain Regions in First-Episode, Drug-Naïve Patients With Postpartum Depression.

BACKGROUND: Although progress has been made in exploring postpartum depression (PPD), the involvement of cerebral structure connectivity in PPD patients keeps unclear. PURPOSE: To explore structural connectivity alternations in mothers with PPD, diffusion tensor imaging (DTI) and automated fiber quantification (AFQ) were used to calculate brain white matter microstructure properties. STUDY TYPE: Cross-sectional. POPULATION: A total of 51 women with first-episode, treatment-näive PPD, and 49 matched healthy postpartum women (HPW) controls. FIELD STRENGTH: A 3.0 T; single-shot echo-planar imaging sequence. ASSESSMENT: DTI measurements of fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) were obtained for 18 specific white matter tracts. The relationship between PDD symptoms, hormone levels, and postpartum days was also investigated. STATISTICAL TESTS: Two sample t test and Pearson's correlation analysis. The analysis was performed by using a permutation-based multiple-comparison correction approach, with the threshold of P < 0.05 (family wise error corrected [FWE-corrected]) separately across the four different outcome measures. RESULTS: Women with PPD showed significantly increased FA and AD in right anterior thalamic radiation (ATR) tract and significantly increased FA and significantly reduced RD in the cingulum tract, compared to women without PPD. The RD values of right cingulum were significantly positively correlated with postpartum days in HPW (r = 0.39). There were no significant relationships between brain measures and hormone levels in either patients or controls. DATA CONCLUSIONS: DTI measures have revealed altered integrity in the white matter of the cortical-thalamic circuits in women with PPD compared to HPW. Damage to these circuits may be a structural basis for the impaired emotional regulation and blunted mother-infant bonding in mothers with PPD and a potential target for the development of new treatments. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Aberrant white matter microstructure evaluation by automated fiber quantification in typhoon-related post-traumatic stress disorder.

Super typhoons can lead to post-traumatic stress disorder (PTSD), which can adversely affect a person's mental health after a disaster. Neuroimaging studies suggest that patients with PTSD may have post-exposure abnormalities of the white matter. However, little is known about these defects, if they are localized to specific regions of the white matter fibers, or whether they may be potential biomarkers for PTSD. Typhoon survivors with PTSD (n = 27), trauma-exposed controls (TEC) (n = 33), and healthy controls (HCs) (n = 30) were enrolled. We used automated fiber quantification (AFQ) to process the participants' DTI and compared diffusion metrics among the three groups. To evaluate diagnostic value, we used support vector machine (SVM) and a random forest (RF) classifier to build a machine learning model. White matter fiber segmentation between the three groups was found to be statistically significant for the fractional anisotropy (FA) value of the right anterior thalamic radiation (ATR) (26-50 nodes) and right uncinate fasciculus (UF) (60-72 nodes) (FDR correction, p < 0.05). By analyzing the characteristics of the machine learning model, the two most important variables were the right ATR and right UF for differentiating PTSD and trauma-exposed controls (TEC) from the healthy controls (HC). In addition, the left cingulum cingulate and left UF were the most critical variables in the differentiation of PTSD and TEC. AFQ with machine learning can localize abnormalities in specific regions of white matter fibers. These regions may be used as a diagnostic biomarker for PTSD.

Mapping white matter structural and network alterations in betel quid-dependent chewers using high angular resolution diffusion imaging.

Background: To evaluate brain white matter diffusion characteristics and anatomical network alterations in betel quid dependence (BQD) chewers using high angular resolution diffusion imaging (HARDI). Methods: The current study recruited 53 BQD chewers and 37 healthy controls (HC) in two groups. We explored regional diffusion metrics alternations in the BQD group compared with the HC group using automated fiber quantification (AFQ). We further employed the white matter (WM) anatomical network of HARDI to explore connectivity alterations in BQD chewers using graph theory. Results: BQD chewers presented significantly lower FA values in the left and right cingulum cingulate, the left and right thalamic radiation, and the right uncinate. The BQD has a significantly higher RD value in the right uncinate fasciculus than the HC group. At the global WM anatomical network level, global network efficiency (p = 0.008) was poorer and Lp (p = 0.016) was greater in the BQD group. At the nodal WM anatomical network level, nodal efficiency (p < 0.05) was lower in the BQD group. Conclusion: Our findings provide novel morphometric evidence that brain structural changes in BQD are characterized by white matter diffusivity and anatomical network connectivity among regions of the brain, potentially leading to the enhanced reward system and impaired inhibitory control.

Altered White Matter Microstructure in Herpes Zoster and Postherpetic Neuralgia Determined by Automated Fiber Quantification.

This study aimed to explore changes in the white matter microstructure in herpes zoster (HZ) and postherpetic neuralgia (PHN) patients and to estimate the correlation of these changes with clinical data. Diffusion tensor imaging (DTI) data were collected from 33 HZ patients, 32 PHN patients, and 35 well-matched healthy controls (HCs). Subsequently, these data were analyzed by automated fiber quantification (AFQ) to accurately locate alterations in the white matter microstructure. Compared with HCs, HZ and PHN patients both showed a wide range of changes in the diffusion properties of fiber tracts. HZ patients exhibited changes primarily in the left superior longitudinal fasciculus (SLF), whereas PHN patients predominantly exhibited changes in the left inferior fronto-occipital fasciculus. The bilateral SLF and the left corticospinal tract were altered in the PHN patients compared with HZ patients. In addition, PHN patients showed a trend toward more expansive white matter alterations compared with those observed in HZ patients; additionally, in PHN patients, changes in the left cingulum cingulate were significantly correlated with changes in emotion and the duration of disease. These findings may help to elucidate the transformation from HZ to PHN and provide new ideas regarding the reasons for intractable neuropathic pain in PHN.