Fractional Anisotropy Measures Research Articles

Unsupervised neurobiology-driven stratification of clinical heterogeneity in depression

IntroductionOne of the main obstacles in providing effective treatments for major depressive disorder (MDD) is clinical heterogeneity, whose neurobiological correlates are not clearly defined. A biologically meaningful stratification of depressed patients is needed to promote tailored diagnostic procedures.ObjectivesUsing structural data, we performed an unsupervised clustering to define clinically meaningful clusters of depressed patients.MethodsT1-weighted and diffusion tensor images were obtained from 102 MDD patients. In 64 patients, clinical symptoms, number of stressful life events, severity and exposure to adverse childhood experiences were evaluated using the Beck Depression Inventory (BDI), Schedule of Recent Experiences (SRE), Risky Family Questionnaire (RFQ), and Childhood Trauma Questionnaire (CTQ). Clustering analyses were performed with extracted tract-based fractional anisotropy (TBSS, FSL), cortical thickness, surface area, and regional measures of grey matter volumes (CAT12). Gaussian mixture model was implemented for clustering, considering Support Vector Machine (SVM) as classifier. A 10x2 repeated cross-validation with grid search was performed for hyperparameters tuning and clusters’ stability. The optimal number of clusters was determined by normalized stability, Akaike and Bayesian information criterion. Analyses were adjusted for total intracranial volume, age, and sex. The clinical relevance of the identified clusters was assessed through MANOVA, considering domains of clinical scales as dependent variables and clusters’ labels as fixed factors. Discriminant analysis was subsequently performed to assess the discriminative power of these variables.ResultsCross-validated clustering approach identified 2 highly stable clusters (normalized stability=0.316, AIC=-80292.48, BIC=351329.16). MANOVA showed a significant between-clusters difference in clinical scales scores (p=0.038). Discriminant analysis distinguished the two clusters with an accuracy of 78.1%, with BDI behavioural and CTQ minimisation/denial domains showing the highest discriminant values (0.325 and 0.313).ConclusionsOur results defined two biologically informed clusters of MDD patients associated with childhood trauma and specific clinical profiles, which may assist in targeting effective interventions and treatments.Disclosure of InterestNone Declared

Predicting Suicide Attempts among Major Depressive Disorder Patients with Structural Neuroimaging: A Machine Learning Approach

IntroductionEvery year at least one million people die by suicide, with major depressive disorder (MDD) being one of the major causes of suicide deaths. Current suicide risk assessments rely on subjective information, are time consuming, low predictive, and poorly reliable. Thus, finding objective biomarkers of suicidality is crucial to move clinical practice towards a precision psychiatry framework, enhancing suicide risk detection and prevention for MDD.ObjectivesThe present study aimed at applying machine learning (ML) algorithms on both grey matter and white-matter voxel-wise data to discriminate MDD suicide attempters (SA) from non-attempters (nSA).Methods91 currently depressed MDD patients (24 SA, 67 nSA) underwent a structural MRI session. T1-weighted images and diffusion tensor imaging scans were respectively pre-processed using Computational Atlas Toolbox 12 (CAT12) and spatial tract-based statistics (TBSS) on FSL, to obtain both voxel-based morphometry (VBM) and fractional anisotropy (FA) measures. Three classification models were built, entering whole-brain VBM and FA maps alone into a Support Vector Machine (SVM) and combining both modalities into a Multiple Kernel Learning (MKL) algorithm. All models were trained through a 5-fold nested cross-validation with subsampling to calculate reliable estimates of balanced accuracy, specificity, sensitivity, and area under the receiver operator curve (AUC).ResultsModels’ performances are summarized in Table 1.Table 1.Models’ performances.Input featuresAlgorithmSpecificitySensitivityBalanced accuracyAUCVBMSVM55.00%50.00%52.50%0.55FASVM72.00%54.00%63.00%0.62VBM and FAMKL68.00%54.00%61.00%0.58Abbreviations: AUC, area under the receiver operator curve; FA, fractional anisotropy; VBM, voxel-based morphometry.ConclusionsOverall, although overcoming the random classification accuracy (i.e., 50%), performances of all models classifying SA and nSA MDD patients were moderate, possibly due to the imbalanced numerosity of classes, with SVM on FA reaching the highest accuracy. Thus, future studies may enlarge the sample and add different features (e.g., functional neuroimaging data) to develop an objective and reliable predictive model to assess and hence prevent suicide risk among MDD patients.Disclosure of InterestNone Declared

Abstract P307: Elevated Blood Pressure Accelerates White Matter Brain Aging in Late Middle-Aged Women: A Mendelian Randomization Study in UK Biobank

Background: Elevated blood pressure (BP) is a modifiable risk factor associated with cognitive impairment and cerebrovascular diseases. However, the causal effect of BP on white matter (WM) brain aging remains unclear. In this study, we hypothesize that increasing BP will accelerate WM brain aging. Methods: In our study, we focused on N=219,968 non-pregnant, family-unrelated individuals of European ancestry who had genotype data and two non-null clinical BP measurements available (99,532 male and 120,436 female, age range: 40-69, 16,901 have neuroimaging data available) collected from UK Biobank (UKBB). In the current study, we adopted a chronological age-adjusted brain age metric, Brain Age Gap (BAG), as the outcome variable to measure the brain aging status. As a first step, we applied machine learning method to establish the model to compute BAG based on fractional anisotropy (FA) measurements derived from structural neuroimaging data among a group of subjects without hypertension (N=7,728). The established model will be applied to calculate WM BAG in other subjects with or without hypertension. We then performed association analysis as well as a two-sample Mendelian Randomization (MR) analysis to estimate the causal effect of BP on WM BAG in the whole population and subgroups stratified by gender and age brackets . In the first sample with genotype and BP data but no WM FA data (N=20,3067), we tested the genetic-exposure association and identified relevant genetic variants as instrumental variables. In the second non-overlapping sample with genotype, BP, and WM FA data, we tested the genetic-outcome association (N=8,822). The causal effect of BP on WM BAG is estimated by using a generalized version of the inverse-variance weighted (IVW) approach. Results: The non-hypertension group and females had younger brains (WM BAG) across all the year cycles than the hypertension group by 0.3098 year and males by 1.2666 years, respectively, both p <0.0001. The association analysis revealed that both Diastolic Blood Pressure (DBP) and Systolic Blood Pressure (SBP) had a stronger significant relationship with WM BAG among females (βSBP=0.0149; βDBP=0.0233), 50-59 aged group (βSBP=0.0163; βDBP=0.0259), and 60-69 aged group (βSBP=0.0086; βDBP=0.0147), all p < 0.0001. The MR analyses showed that DBP had a significant causal effect on WM BAG among females aged 50-59 (β=0.0720, p=0.0243) and females aged 60-69 (β=0.1000, p=0.0085). We only observed SBP had a marginal causal effect (0.05<p<0.1) among males aged 50-59 (β= -0.0458), females aged 40-49 (β= -0.0446) and aged 50-59 (β=0.0326). Conclusion: Hypertension and genetic predisposition to higher BP can accelerate WM brain aging specifically targeting at late middle-aged women, providing insights on planning effective control of BP for women in this age group.

Identifying subcortical connectivity during brain tumor surgery: a multimodal study.

Bipolar direct electrical stimulation (DES) of an awake patient is the reference technique for identifying brain structures to achieve maximal safe tumor resection. Unfortunately, DES cannot be performed in all cases. Alternative surgical tools are, therefore, needed to aid identification of subcortical connectivity during brain tumor removal. In this pilot study, we sought to (i) evaluate the combined use of evoked potential (EP) and tractography for identification of white matter (WM) tracts under the functional control of DES, and (ii) provide clues to the electrophysiological effects of bipolar stimulation on neural pathways. We included 12 patients (mean age of 38.4years) who had had a dMRI-based tractography and a functional brain mapping under awake craniotomy for brain tumor removal. Electrophysiological recordings of subcortical evoked potentials (SCEPs) were acquired during bipolar low frequency (2Hz) stimulation of the WM functional sites identified during brain mapping. SCEPs were successfully triggered in 11 out of 12 patients. The median length of the stimulated fibers was 43.24 ± 19.55mm, belonging to tracts of median lengths of 89.84 ± 24.65mm. The electrophysiological (delay, amplitude, and speed of propagation) and structural (number and lengths of streamlines, and mean fractional anisotropy) measures were correlated. In our experimental conditions, SCEPs were essentially limited to a subpart of the bundles, suggesting a selectivity of action of the DES on the brain networks. Correlations between functional, structural, and electrophysiological measures portend the combined use of EPs and tractography as a potential intraoperative tool to achieve maximum safe resection in brain tumor surgery.

Diffusion tensor imaging analysis of the corpus callosum in children with high-risk autism spectrum disorder.

Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that begins in early infancy and childhood and is characterized by impaired social communication and repetitive stereotyped behaviors. The purpose of this study was to examine the development of the corpus callosum and its relationship to neurobehavior in young children with high-risk (HR) ASD using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Twenty-one children with HR-ASD who visited Anhui Children's Hospital between January 2020 and December 2021 were selected as the study group, while 19 matched children with normal development during the same time were adopted as the control group. Cranial MRI+DTI were performed for all of the enrolled children and fractional anisotropy (FA) measurements were taken in each region of the corpus callosum. The FA values in all regions of the corpus callosum were higher in the study group than in the control group (0.417 ± 0.016 vs. 0.412 ± 0.02 in the corpus callosum knee, 0.439 ± 0.018 vs. 0.431 ± 0.023 in the corpus callosum body, and 0.446 ± 0.017 vs. 0.434 ± 0.019 in the splenium of corpus callosum [SCC]), where the difference in the FA in the SCC was statistically significant between the two groups (P< 0.05). There was a positive correlation between the FA in the corpus callosum knee and speech scores in the neuropsychological development of the study group (P< 0.05). There was a premature development tendency for corpus callosum myelination in young children with HR-ASD, and the developmental tendency was visible in the SCC. There was also a positive relationship between corpus callosum knee development and language function.

Porcine Model of the Growing Spinal Cord—Changes in Diffusion Tensor Imaging Parameters

Diffusion tensor imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique that has promising applications for the objective assessment of the microstructure of the spinal cord. This study aimed to verify the parameters obtained using DTI change during the growth process. We also wanted to identify if the DTI values change on the course of the spinal cord. The model organism was a healthy growing porcine spinal cord (19 pigs, Polish White, weight 24-120 kg, mean 48 kg, median 48 kg, age 2.5-11 months, mean 5 months, median 5.5 months). DTI parameters were measured in three weight groups: up to 29 kg (five pigs), 30-59 kg (six pigs), and from 60 kg up (eight pigs). DTI was performed with a 1.5 Tesla magnetic resonance scanner (Philips, Ingenia). Image post-processing was done using the Fiber Track package (Philips Ingenia workstation) by manually drawing the regions of interest (nine ROIs). The measurements were recorded for three sections: the cervical, thoracolumbar and lumbar segments of the spinal cord at the C4/C5, Th13/L1, and L4/L5 vertebrae levels. In each case, one segment was measured cranially and one caudally from the above-mentioned places. The values of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were obtained for each ROIs and compared. It is shown that there is a correlation between age, weight gain, and change in FA and ADC parameters. Moreover, it is noted that, with increasing weight and age, the FA parameter increases and ADC decreases, whereas the FA and ADC measurement values did not significantly change between the three sections of the spinal cord. These findings could be useful in determining the reference values for the undamaged spinal cords of animals and growing humans.

Reliability of Functional and Diffusion MR Imaging Near Cerebral Cavernous Malformations.

Surgical resection of cerebral cavernous malformations close to eloquent regions frequently uses fMRI and DTI for surgical planning to best preserve neurologic function. This study investigates the reliability of fMRI and DTI near cerebral cavernous malformations. Consecutive patients with cerebral cavernous malformations undergoing presurgical fMRI and DTI mapping were identified. Each cerebral cavernous malformation was hand-contoured; 2 sequential 4-mm expansion shells (S1 and S2) were created, generating 2 ROIs and 2 contralateral controls. Fractional anisotropy and regional homogeneity measurements were then extracted from each ROI and compared with the contralateral controls. Reliability, accuracy, and precision were compared as appropriate. Fifty-four patients were identified and included. Errors of fractional anisotropy were significantly lower than those of regional homogeneity in S1 and S2 (P < .001), suggesting that fractional anisotropy is more reliable than regional homogeneity near cerebral cavernous malformations. Proximity to cerebral cavernous malformations worsened the reliability of regional homogeneity (S1 versus S2, P < .001), but not fractional anisotropy (P = .24). While fractional anisotropy was not significantly biased in any ROI (P > .05), regional homogeneity was biased toward lower signals in S1 and S2 (P < .05), an effect that was attenuated with distance from cerebral cavernous malformations (P < .05). Fractional anisotropy measurements were also more precise than regional homogeneity in S1 and S2 (P < .001 for both). Our findings suggest that hemosiderin-rich lesions such as cerebral cavernous malformations may lead to artifactual depression of fMRI signals and that clinicians and surgeons should interpret fMRI studies near cerebral cavernous malformations with caution. While fMRI is considerably affected by cerebral cavernous malformation-related artifacts, DTI appears to be relatively unaffected and remains a reliable imaging technique near cerebral cavernous malformations.

Diffusion tensor imaging derived metrics in high grade glioma and brain metastasis differentiation

Background: Pretreatment differentiation between glioblastoma and metastasis is a frequently encountered dilemma in neurosurgical practice. Distinction is required for precise planning of resection or radiotherapy, and also for defining further diagnostic procedures. Morphology and spectroscopy imaging features are not specific and frequently overlap. This limitation of magnetic resonance imaging and magnetic resonance spectroscopy was the reason to initiate this study. The aim of the present study was to determine whether the dataset of diffusion tensor imaging metrics contains information which may be used for the distinction between primary and secondary intra-axial neoplasms. Methods: Two diffusion tensor imaging parameters were measured in 81 patients with an expansive, ring-enhancing, intra-axial lesion on standard magnetic resonance imaging (1.5 T system). All tumors were histologically verified glioblastoma or secondary deposit. For qualitative analysis, two regions of interest were defined: intratumoral and immediate peritumoral region (locations 1 and 2, respectively). Fractional anisotropy and mean difusivity values of both groups were compared. Additional test was performed to determine if there was a significant difference in mean values between two locations. Results: A statistically significant difference was found in fractional anisotropy values among two locations, with decreasing values in the direction of neoplastic infiltration, although such difference was not observed in fractional anisotropy values in the group with secondary tumors. Mean difusivity values did not appear helpful in differentiation between these two entities. In both groups there was no significant difference in mean difusivity values, neither in intratumoral nor in peritumoral location. Conclusion: The results of our study justify associating the diffusion tensor imaging technique to conventional morphologic magnetic resonance imaging as an additional diagnostic tool for the distinction between primary and secondary intra-axial lesions. Quantitative analysis of diffusion tensor imaging metric, in particular measurement of fractional anisotropy in peritumoral edema facilitates accurate diagnosis.

Diffusion Tensor MRI of Brain in Healthy Adult Population: Normative Fractional Anisotropy Values at 3 Tesla MRI

Introduction: Diffusion Tensor Imaging (DTI) technique and its clinical application are increasing in clinical routine practice, still very less normative data is available. Awareness regarding regional differences in Fractional Anisotropy (FA) measurements is very important when routinely DTI is used in clinical Magnetic Resonance Imaging (MRI). Aim: To determine the normative FA values data at 3 Tesla (3T) MRI and to determine the degradation of FA values in various regions of brain values with age. Materials and Methods: This cross-sectional study involved a total of 52 participants without any abnormal findings ( presence of tumour, stroke, infarct, degeneration, etc) and whose brain scanning was performed at 3T MRI, in the Department of Radiodiagnosis, Shree Krishna Hospital, and Pramukhswami Medical College, Karamsad, Anand, Gujarat, India. A DTI protocol was set for the healthy patient’s brain scanning. The colour-coded DTI brain images were postprocessed carefully to draw a circular Region of Interest (ROI) in the required areas of white matter and FA values were noted. Descriptive statistics were used to find out the normative data in 11 regions of the brain on right and left side. Pearson correlation was used to check the correlation of FA values with age. Results: There were 52 patients in the present study, with a male to female ratio of 1.7:1 and a mean age of 52 years. The highest FA values were observed in the splenium (0.809), genu (0.767), the body of the corpus callosum (0.627), and the posterior limb of the internal capsule (0.721), rest areas showed moderate to low FA values. Pearson correlation was used to find the variation in the FA values with age in three age groups 18-40, 41-60 and &gt;60 years, where moderate changes in FA values with age were seen in a few regions of the brain such as genu (right side) with p-value=0.003 and foramen magnum at CVJ level (right side) with a p-value of 0.001. Conclusion: Generally, FA values intend to change with the presence of multiple tract areas, field strength, coil sensitivity, and partial volume averaging. FA values were also found to be affected with respect to increasing age.

Differentiation of high grade glioma and solitary brain metastases by measuring relative cerebral blood volume and fractional anisotropy: a systematic review and meta-analysis of MRI diagnostic test accuracy studies.

This study aims to research the efficacy of MRI (I) for differentiating high-grade glioma (HGG) (P) with solitary brain metastasis (SBM) (C) by creating a combination of relative cerebral blood volume (rCBV) (O) and fractional anisotropy (FA) (O) in patients with intracerebral tumors. Searches were conducted on September 2021 with no publication date restriction, using an electronic search for related articles published in English, from PubMed (1994 to September 2021), Scopus (1977 to September 2021), Web of Science (1985 to September 2021), and Cochrane (1997 to September 2021). A total of 1056 studies were found, with 23 used for qualitative and quantitative data synthesis. Inclusion criteria were: patients diagnosed with HGG and SBM without age, sex, or race restriction; MRI examination of rCBV and FA; reliable histopathological diagnostic method as the gold-standard for all conditions of interest; observational and clinical studies. Newcastle-Ottawa quality assessment Scale (NOS) and Cochrane risk of bias tool (ROB) for observational and clinical trial studies were managed to appraise the quality of individual studies included. Data extraction results were managed using Mendeley and Excel, pooling data synthesis was completed using the Review Manager 5.4 software with random effect model to discriminate HGG and SBM, and divided into four subgroups. There were 23 studies included with a total sample size of 597 HGG patients and 373 control groups/SBM. The analysis was categorized into four subgroups: (1) the subgroup with rCBV values in the central area of the tumor/intratumoral (399 HGG and 232 SBM) shows that HGG patients are not significantly different from SBM/controls group (SMD [95% CI] = -0.27 [-0.66, 0.13]), 2) the subgroup with rCBV values in the peritumoral area (452 HGG and 274 SBM) shows that HGG patients are significantly higher than SBM (SMD [95% CI] = -1.23 [-1.45 to -1.01]), (3) the subgroup with FA values in the central area of the tumor (249 HGG and 156 SBM) shows that HGG patients are significantly higher than SBM (SMD [95% CI] = - 0.44 [-0.84,-0.04]), furthermore (4) the subgroup with FA values in the peritumoral area (261 HGG and 168 SBM) shows that the HGG patients are significantly higher than the SBM (SMD [95% CI] = -0.59 [-1.02,-0.16]). Combining rCBV and FA measurements in the peritumoral region and FA in the intratumoral region increase the accuracy of MRI examination to differentiate between HGG and SBM patients effectively. Confidence in the accuracy of our results may be influenced by major interstudy heterogeneity. Whereas the I2 for the rCBV in the intratumoral subgroup was 80%, I2 for the rCBV in the peritumoral subgroup was 39%, and I2 for the FA in the intratumoral subgroup was 69%, and I2 for the FA in the peritumoral subgroup was 74%. The predefined accurate search criteria, and precise selection and evaluation of methodological quality for included studies, strengthen this studyOur study has no funder, no conflict of interest, and followed an established PROSPERO protocol (ID: CRD42021279106). The combination of rCBV and FA measurements' results is promising in differentiating HGG and SBM.

Diffusion Tensor Imaging in Syringomyelia Secondary to Chiari Malformation in Cavalier King Charles Spaniel—A Preliminary Study

Syringomyelia secondary to Chiari-like malformation (so-called CM-SM syndrome) is a common disorder in Cavalier King Charles Spaniels (CKCS) that is diagnosed using standard structural MRI, though imaging findings often do not correlate with the severity of clinical symptoms. Diffusion tensor imaging (DTI) is a technique that defines subtle microstructural changes in the course of many brain and spinal cord diseases, that are not visible on standard MRI. The aim of the study was to identify the correlation between the presence of clinical symptoms and DTI parameters, such as apparent diffusion coefficient (ADC) and fractional anisotropy (FA) within the spinal cord in the course of CM-SM. Study subjects included 18 dogs, CKCS with MRI-confirmed SM (SM group), and 12 CKCS dogs without SM (non-SM group). The SM group was divided into SM-symptomatic group (n = 8) and SM-asymptomatic group, n = 10). All dogs underwent same clinical and neurological assessment followed by MRI examination. All MRI studies were performed on a 1.5T MRI scanner. The MRI spine protocol included: transverse and sagittal T2-weighted images followed by DTI performed in the sagittal plane. The measurements of FA and ADC values were performed manually using the region of interest (ROI) method at the level of three intervertebral discs between C1 and C4. Notable differences in age and body weight were found. No significant differences in FA and ADC values between the SM and non-SM groups were found, but between non-SM, SM-asymptomatic and SM-symptomatic groups significant differences were found in ADC values in all three ROIs and in FA values in ROI-1 and ROI-3. SM-symptomatic dogs compared to non-SM, showed decreased FA value in ROI-1 and ROI-3 also increased ADC value in ROI-1, ROI-2 and ROI-3. SM-symptomatic dogs compared to SM-asymptomatic showed also decreased FA value in ROI-1 and ROI-3, and also increased ADC value in ROI-1, ROI-2 and ROI-3. The results suggest that the values of DTI parameters correlate with the severity of clinical symptoms in the course of CM-SM in animals. The use of DTI evaluation of CM-SM patients carries a potential value as a clinically relevant protocol for an objective assessment of the spinal cord.

Executive Functions and Episodic Memory are Associated with Extracellular White Matter Microstructure in Early Old Age

AbstractBackgroundCortical surface area, cortical thickness, and hippocampal volume are well‐studied in relation to later life cognitive impairments and AD. Fewer studies have investigated how white mater microstructure relates to cognition in late life. Existing work has focused on fractional anisotropy (FA) and mean diffusivity (MD) measures that are thought to capture demyelination and axonal degradation and relate to cognitive decline in normal aging and AD. However, these measures are susceptible to partial volume effects. Here, we evaluated whether executive function and memory are associated with FA and MD after deploying a free‐water (FW) elimination post‐processing method that separates fluid (FW) from tissue (FW‐corrected FA and MD).MethodWe examined 489 non‐demented men in the Vietnam Era Twin Study of Aging (VETSA) at mean age 68. Executive function was based on 6 tasks spanning inhibition, shifting, and working memory. Memory was based on 7 subtests from the Logical Memory, Visual Reproductions, and California Verbal Learning tests. Analyses focused on 11 cortical white matter tracts across three metrics: FW, FW‐corrected FA, and FW‐corrected MD. Analyses controlled for age, scanner, diabetes, hypertension, race, and ethnicity. We used false discovery rate to account for multiple testing.ResultBetter executive functioning was associated with lower FW across all 11 tracts. Better memory was associated with lower FW in 3 tracts: the superior longitudinal fasciculus (SLF) and two sections of the inferior frontal gyrus (opercularis and triangularis). Despite widespread differences with FW, there was only one significant association with intracellular metrics (executive function and FW‐corrected FA in the SLF). Finally, indicators of cognitive reserve (education or general cognitive ability assessed in early adulthood) did not moderate these associations between cognition and white matter microstructure.ConclusionOur findings leveraged a post‐processing method that separates extracellular fluid (FW) from intracellular tissue (FA, MD). We found that cognitive abilities in early old age are associated primarily with extracellular white matter microstructure (FW), which demonstrated global associations with executive function. Finally, there was no evidence that indicators of cognitive reserve influenced the strength of the association between cognition and white matter, at least in this sample of non‐demented men.

Associations among executive function Abilities, free Water, and white matter microstructure in early old age

BackgroundStudies have investigated white matter microstructure in relation to late-life cognitive impairments, with fractional anisotropy (FA) and mean diffusivity (MD) measures thought to capture demyelination and axonal degradation. However, new post-processing methods allow isolation of free water (FW), which captures extracellular fluid contributions such as atrophy and neuroinflammation, from tissue components. FW also appears to be highly relevant to late-life cognitive impairment. Here, we evaluated whether executive functions are associated with FW, and FA and MD corrected for FW (FAFWcorr and MDFWcorr). MethodWe examined 489 non-demented men in the Vietnam Era Twin Study of Aging (VETSA) at mean age 68. Two latent factors capturing ‘common executive function’ and ‘working-memory specific’ processes were estimated based on 6 tasks. Analyses focused on 11 cortical white matter tracts across three metrics: FW, FAFWcorr, and MDFWcorr. ResultsBetter ‘common executive function’ was associated with lower FW across 9 of the 11 tracts. There were no significant associations with intracellular metrics after false discovery rate correction. Effects also appeared driven by individuals with MCI (13.7% of the sample). Working memory-specific tasks showed some associations with FAFWcorr, including the triangularis portion of the inferior frontal gyrus. There was no evidence that cognitive reserve (i.e., general cognitive ability assessed in early adulthood) moderated these associations between executive function and FW or FA. DiscussionExecutive function abilities in early old age are associated primarily with extracellular fluid (FW) as opposed to white matter (FAFWcorr or MDFWcorr). Moderation analyses suggested cognitive reserve does not play a strong role in these associations, at least in this sample of non-demented men.

Generalized q‐sampling imaging‐based fiber tracking measures of white matter tracts in cognitive impairment

AbstractBackgroundDiffusion magnetic resonance imaging (dMRI) is a non‐invasive technique for exploring white matter fiber organization of the brain. As traditional diffusion tensor imaging (DTI) methods may provide inaccurate descriptions of local crossing, kissing and diverging fibers, we examined generalized q‐sampling imaging (GQI), a novel method providing better directional and quantitative information using dMRI data from community‐dwelling older adults.MethodWe examined baseline dMRI data from 227 adults aged 71±8 on average from the Wake Forest Alzheimer’s Disease Research Center’s Clinical Core, who had baseline and year‐1 follow‐up global Clinical Dementia Rating (CDR) score of 0 (indicates normal cognitive function) and 0.5 (akin to mild cognitive impairment [MCI]). The primary outcome measure was cognitive migration status determined by CDR increase/decrease between baseline and follow‐up (mean difference=13.9 months), shown in Figure. We performed atlas‐based fiber tracking analysis using GQI in DSI Studio to generate normalized quantitative anisotropy (NQA), DTI fractional anisotropy (DTI_FA) and restricted diffusion (RDI) measures in several AD‐related white matter (WM) tracts: Corpus Callosum (CC), Fornix, Cingulum bundle/Parahippocampal tracts (CFP; CP; CPP), Uncinate Fasciculus (UF), Superior Longitudinal Fasciculus (SLF) and Inferior Fronto‐Occipital Fasciculus (IFOF). We performed multinomial logistic regression (MLR) models adjusted for age, sex, and education, using cognitive migration status as the outcome, and standardized GQI‐based diffusion indices sNQA, sRDI, and sDTI_FA as predictors.ResultTable 1 lists the baseline demographics and biomarker characteristics for cognitive migration groups. MLR results in Table 2 show significant associations between diffusion indices and tracts for outcome 4 (Reversion) in reference to outcome 1 (stability of normal cognition). Decrease in sNQA in bilateral CP and right Fornix was significantly associated with higher odds of Reversion relative to the reference. Increase in sDTI_FA in left IFOF was associated with higher odds of reversion relative to reference. Decrease in sRDI in bilateral CFP, CPP, Fornix and UF and right CP was associated with higher reversion relative to reference.ConclusionIn early trajectories of cognitive impairment, RDI may be a sensitive diffusion marker for cognitive reversion in several AD‐related WM tracts. Future work will validate these markers in other cognitive migration groups (negative migration and MCI stability).

White matter microstructure and sleep-wake disturbances in individuals at ultra-high risk of psychosis.

White matter changes in individuals at ultra-high risk for psychosis (UHR) may be involved in the transition to psychosis. Sleep-wake disturbances commonly precede the first psychotic episode and predict development of psychosis. We examined associations between white matter microstructure and sleep-wake disturbances in UHR individuals compared to healthy controls (HC), as well as explored the confounding effect of medication, substance use, and level of psychopathology. Sixty-four UHR individuals and 35 HC underwent clinical interviews and diffusion weighted imaging. Group differences on global and callosal mean fractional anisotropy (FA) was tested using general linear modeling. Sleep-wake disturbances were evaluated using the subjective measures disturbed sleep index (DSI) and disturbed awakening index (AWI) from the Karolinska Sleep Questionnaire, supported by objective sleep measures from one-night actigraphy. The primary analyses comprised partial correlation analyses between global FA/callosal FA and sleep-wake measures. Secondary analyses investigated multivariate patterns of covariance between measures of sleep-wake disturbances and FA in 48 white matter regions of interest using partial least square correlations. Ultra-high risk for psychosis individuals displayed lower global FA (F = 14.56, p < 0.001) and lower callosal FA (F = 11.34, p = 0.001) compared to HC. Subjective sleep-wake disturbances were significantly higher among the UHR individuals (DSI: F = 27.59, p < 0.001, AWI: F = 36.42, p < 0.001). Lower callosal FA was correlated with increased wake after sleep onset (r = -0.34, p = 0.011) and increased sleep fragmentation index (r = -0.31, p = 0.019) in UHR individuals. Multivariate analyses identified a pattern of covariance in regional FA which were associated with DSI and AWI in UHR individuals (p = 0.028), but not in HC. Substance use, sleep medication and antipsychotic medication did not significantly confound these associations. The association with objective sleep-wake measures was sustained when controlling for level of depressive and UHR symptoms, but symptom level confounded the covariation between FA and subjective sleep-wake measures in the multivariate analyses. Compromised callosal microstructure in UHR individuals was related to objectively observed disruptions in sleep-wake functioning. Lower FA in ventrally located regions was associated with subjectively measured sleep-wake disturbances and was partly explained by psychopathology. These findings call for further investigation of sleep disturbances as a potential treatment target.

Fractional anisotropy values of brain matter among healthy children: cohort study

INTRODUCTION: Diffusion-tensor magnetic resonance imaging (DT-MRI) is currently a well studied and applied in clinical practice technique. An important advantage of this technique is the measurement of fractional anisotropy (FA) values, which make it possible to quantify changes in brain matter. The authors are aware of publications on the study of FА values among children in small groups including only a part of ages. This work presents study of FA among large amount of examined children and notes values of FA for most of the significant structures of the brain in subjects from 4 months to 18 years of age.OBJECTIVE: Analysis of the FА values of the anatomical structures of the brain in children of different age groups who did not reveal changes in the brain matter during multiparametric MRI, in order to further study the processes of development and myelination of brain structures, as well as the use of these values in clinical practice as reference values in the analysis of pathology.MATERIALS AND METHODS: 153 patients aged from 4 months to 18 years were examined. MRI of brain was performed on the recommendation of the attending physician in accordance with clinical indications in case of suspected infection in the paranasal sinuses and neurological complaints, without focal symptoms. Distribution of examined children by age groups was: up to 1 year (infant age) — 6 children (3.9%); from 1 year to 3 years (early childhood) — 14 children (9.15%); from 3 to 7 years old (preschool age) — 39 children (25.5%); older than 7 years (school age and older) — 94 children (61.45%). Distribution of the examined by gender: male children — 82 (53.6%); female — 71 (46.4%). DT-MRI was applied to all patients with measurement of diffusion in 15 directions, and then FА values were measured in 21 areas of the white and gray matter of the brain. The regions of interest (ROI) were arranged in accordance with the zones of the ASPECTS and PC-ASPECTS scales adapted for the purposes of this study. Statistics: processing of the received data was carried out using application programs: Microsoft Excel, Statistica 10 with an assessment of the normality of the distribution of values and the use of parametric and nonparametric criteria.RESULTS: The highest mean numerical values of FA for all groups of children were found in the white matter along neural pathways: 0.66±0.04 for the internal capsule; 0.68±0.05 — in the white matter of the midbrain; 0.64±0.08 — at the level of the pons; 0.69±0.04 — in the cerebellar peduncles. The FA indices in the white matter of other anatomical regions are slightly lower: 0.50±0.08 — for white matter at the M4 level according to ASPECTS; 0.52±0.08 — in the occipital lobe at the level of the basal ganglia; 0.54±0.05 — in the temporal lobe. The lowest FA values appeared in the gray matter: 0.16±0.04 — in the caudate nucleus; 0.12±0.04 — in the gray matter at the M4 level according to ASPECTS. The most pronounced differences in FA in children of early childhood and school age appeared in the ROI located in the white matter of the cerebral cortex: in the area of M5 0.46±0.05 versus 0.54±0.05, respectively; in the area of M1 0.43±0.06 versus 0.51±0.06, respectively. At the same time, differences in FA in children of early childhood and school age in ROI located in the white matter at the level of stem structures are less pronounced: at the level of the pons 0.6±0.07 versus 0.64±0.07, respectively; at the level of the cerebellar peduncles 0.68±0.04 versus 0.69±0.04, respectively. These numerical indicators illustrate and additionally confirm the known ideas about the development and formation of neural pathways and about the processes of their myelination. They also reflect the known data on the structural and functional differences between the gray and white matter of the brain. A significant increase of the FА values in children older than 7 years was determined in comparison with groups of younger children in the white matter of the cortical structures of the brain. At the same time, there are no significant age-related differences of FА in the region of brainstem. It was also found that in preschoolers, compared with children from 1 to 3 years old, white matter FА increases in the region of the caudate nucleus and midbrain.CONCLUSION: The obtained normative values of FА can later be widely used in clinical practice as reference ones when performing DT-MRI and assessing neuroinfectious and other pathological changes in the brain matter in children. The revealed differences in age groups indicate an earlier development of brainstem structures, while the subcortical-cortical areas of the cerebral hemispheres develop and myelinate over a longer time.

MRI Clustering Reveals Three ALS Subtypes With Unique Neurodegeneration Patterns.

The purpose of this study was to identify subtypes of amyotrophic lateral sclerosis (ALS) by comparing patterns of neurodegeneration using brain magnetic resonance imaging (MRI) and explore their phenotypes. We performed T1-weighted and diffusion tensor imaging in 488 clinically well-characterized patients with ALS and 338 control subjects. Measurements of whole-brain cortical thickness and white matter connectome fractional anisotropy were adjusted for disease-unrelated variation. A probabilistic network-based clustering algorithm was used to divide patients into subgroups of similar neurodegeneration patterns. Clinical characteristics and cognitive profiles were assessed for each subgroup. In total, 512 follow-up scans were used to validate clustering results longitudinally. The clustering algorithm divided patients with ALS into 3 subgroups of 187, 163, and 138 patients. All subgroups displayed involvement of the precentral gyrus and are characterized, respectively, by (1) pure motor involvement (pure motor cluster [PM]), (2) orbitofrontal and temporal involvement (frontotemporal cluster [FT]), and (3) involvement of the posterior cingulate cortex, parietal white matter, temporal operculum, and cerebellum (cingulate-parietal-temporal cluster [CPT]). These subgroups had significantly distinct clinical profiles regarding male-to-female ratio, age at symptom onset, and frequency of bulbar symptom onset. FT and CPT revealed higher rates of cognitive impairment on the Edinburgh cognitive and behavioral ALS screen (ECAS). Longitudinally, clustering remained stable: at 90.4% of their follow-up visits, patients clustered in the same subgroup as their baseline visit. ALS can manifest itself in 3 main patterns of cerebral neurodegeneration, each associated with distinct clinical characteristics and cognitive profiles. Besides the pure motor and frontotemporal dementia (FTD)-like variants of ALS, a new neuroimaging phenotype has emerged, characterized by posterior cingulate, parietal, temporal, and cerebellar involvement. ANN NEUROL 2022;92:1030-1045.

Brain structure and episodic learning rate in cognitively healthy ageing

Memory normally declines with ageing and these age-related cognitive changes are associated with changes in brain structure. Episodic memory retrieval has been widely studied during ageing, whereas learning has received less attention. Here we examined the neural correlates of episodic learning rate in ageing. Our study sample consisted of 982 cognitively healthy female and male older participants from the Vallecas Project cohort, without a clinical diagnosis of mild cognitive impairment or dementia. The learning rate across the three consecutive recall trials of the verbal memory task (Free and Cued Selective Reminding Test) recall trials was used as a predictor of grey matter (GM) using voxel-based morphometry, and WM microstructure using tract-based spatial statistics on fractional anisotropy (FA) and mean diffusivity (MD) measures. Immediate Recall improved by 1.4 items per trial on average, and this episodic learning rate was faster in women and negatively associated with age. Structurally, hippocampal and anterior thalamic GM volume correlated positively with learning rate. Learning also correlated with the integrity of WM microstructure (high FA and low MD) in an extensive network of tracts including bilateral anterior thalamic radiation, fornix, and long-range tracts. These results suggest that episodic learning rate is associated with key anatomical structures for memory functioning, motivating further exploration of the differential diagnostic properties between episodic learning rate and retrieval in ageing.

White matter integrity and key structures affected in Alzheimer's disease characterized by diffusion tensor imaging.

White matter (WM) degeneration is suggested to predict the early signs of Alzheimer's disease (AD). The exact structural regions of brain circuitry involved are not known. This study aims to examine the associations between WM tract integrity, represented by the diffusion tensor imaging (DTI) measures, and AD diagnosis and to denote the key substrates in predicting AD. It included DTI measures of mean diffusivity (MD), fractional anisotropy, radial diffusivity and axial diffusivity of 18 main WM tracts in 84 non-Hispanic white participants from the Alzheimer's Disease Neuroimaging Initiative dataset. The multivariable general linear model was used to examine the association of AD diagnosis with each DTI measure adjusting for age, gender and education. The corpus callosum, fornix, cingulum hippocampus, uncinate fasciculus, sagittal striatum, left posterior thalamic radiation and fornix-stria terminalis showed significant increases in MD, radial and axial diffusivity, whereas the splenium of corpus callosum and the fornix showed significant decreases in fractional anisotropy among AD patients. Variable cluster analysis identified that hippocampus volume, mini-mental state examination (MMSE), cingulate gyrus/hippocampus, inferior fronto-occipital fasciculus and uncinate fasciculus are highly correlated in one cluster with MD measures. In conclusion, there were significant differences in DTI measures between the brain WM of AD patients and controls. Age is the risk factor associated with AD, not gender or education. Right cingulum gyrus and right uncinate fasciculus are particularly affected, correlating well with a cognitive test MMSE and MD measures for dementia in AD patients and could be a region of focus for AD staging.

Purkinje cell vulnerability induced by diffuse traumatic brain injury is linked to disruption of long-range neuronal circuits

Cerebellar dysfunction is commonly observed following traumatic brain injury (TBI). While direct impact to the cerebellum by TBI is rare, cerebellar pathology may be caused by indirect injury via cortico-cerebellar pathways. To address the hypothesis that degeneration of Purkinje cells (PCs), which constitute the sole output from the cerebellum, is linked to long-range axonal injury and demyelination, we used the central fluid percussion injury (cFPI) model of widespread traumatic axonal injury in mice. Compared to controls, TBI resulted in early PC loss accompanied by alterations in the size of pinceau synapses and levels of non-phosphorylated neurofilament in PCs. A combination of vDISCO tissue clearing technique and immunohistochemistry for vesicular glutamate transporter type 2 show that diffuse TBI decreased mossy and climbing fiber synapses on PCs. At 2 days post-injury, numerous axonal varicosities were found in the cerebellum supported by fractional anisotropy measurements using 9.4 T MRI. The disruption and demyelination of the cortico-cerebellar circuits was associated with poor performance of brain-injured mice in the beam-walk test. Despite a lack of direct input from the injury site to the cerebellum, these findings argue for novel long-range mechanisms causing Purkinje cell injury that likely contribute to cerebellar dysfunction after TBI.