Tensor Metrics Research Articles

Mean kurtosis-Curve (MK-Curve) correction improves the test-retest reproducibility of diffusion kurtosis imaging at 3 T.

Diffusion kurtosis imaging (DKI) is applied to gain insights into the microstructural organization of brain tissues. However, the reproducibility of DKI outside brain white matter, particularly in combination with advanced estimation to remedy its noise sensitivity, remains poorly characterized. Therefore, in this study, we investigated the variability and reliability of DKI metrics while correcting implausible values with a fit method called mean kurtosis (MK)-Curve. A total of 10 volunteers (four women; age: 41.4 ± 9.6 years) were included and underwent two MRI examinations of the brain. The images were acquired on a clinical 3-T scanner and included a T1-weighted image and a diffusion sequence with multiple diffusion weightings suitable for DKI. Region of interest analysis of common kurtosis and tensor metrics derived with the MK-Curve DKI fit was performed, including intraclass correlation (ICC) and Bland-Altman (BA) plot statistics. A p value of less than 0.05 was considered statistically significant. The analyses showed good to excellent agreement of both kurtosis tensor- and diffusion tensor-derived MK-Curve-corrected metrics (ICC values: 0.77-0.98 and 0.87-0.98, respectively), with the exception of two DKI-derived metrics (axial kurtosis in the cortex: ICC = 0.68, and radial kurtosis in deep gray matter: ICC = 0.544). Non-MK-Curve-corrected kurtosis tensor-derived metrics ranged from 0.01 to 0.52 and diffusion tensor-derived metrics from 0.06 to 0.66, indicating poor to moderate reliability. No structural bias was observed in the BA plots for any of the diffusion metrics. In conclusion, MK-Curve-corrected DKI metrics of the human brain can be reliably acquired in white and gray matter at 3 T and DKI metrics have good to excellent agreement in a test-retest setting.

Axisymmetric diffusion kurtosis imaging with Rician bias correction: A simulation study.

To compare the estimation accuracy of axisymmetric diffusion kurtosis imaging (DKI) and standard DKI in combination with Rician bias correction (RBC). Axisymmetric DKI is more robust against noise-induced variation in the measured signal than standard DKI because of its reduced parameter space. However, its susceptibility to Rician noise bias at low signal-to-noise ratios (SNR) is unknown. Here, we investigate two main questions: first, does RBC improve estimation accuracy of axisymmetric DKI?; second, is estimation accuracy of axisymmetric DKI increased compared to standard DKI? Estimation accuracy was investigated on the five axisymmetric DKI tensor metrics (AxTM): the parallel and perpendicular diffusivity and kurtosis and mean of the kurtosis tensor, using a noise simulation study based on synthetic data of tissues with varying fiber alignment and in-vivo data focusing on white matter. RBC mainly increased accuracy for the parallel AxTM in tissues with highly to moderately aligned fibers. For the perpendicular AxTM, axisymmetric DKI without RBC performed slightly better than with RBC. However, the combination of axisymmetric DKI with RBC was the overall best performing algorithm across all five AxTM in white matter and axisymmetric DKI itself substantially improved accuracy in axisymmetric tissues with low fiber alignment. Combining axisymmetric DKI with RBC facilitates accurate DKI parameter estimation at unprecedented low SNRs ( ) in white matter, possibly making it a valuable tool for neuroscience and clinical research studies where scan time is a limited resource. The tools used here are available in the open-source ACID toolbox for SPM.

Simultaneous Acquisition of Diffusion Tensor and Dynamic Diffusion MRI.

Dynamic diffusion magnetic resonance imaging (ddMRI) metrics can assess transient microstructural alterations in tissue diffusivity but requires additional scan time hindering its clinical application. To determine whether a diffusion gradient table can simultaneously acquire data to estimate dynamic and diffusion tensor imaging (DTI) metrics. Prospective. Seven healthy subjects, 39 epilepsy patients (15 female, 31 male, age ± 15). Two-dimensional diffusion MRI (b=1000 s/mm2 ) at a field strength of 3T. Sessions in healthy subjects-standard ddMRI (30 directions), standard DTI (15 and 30 directions), and nested cubes scans (15 and 30 directions). Sessions in epilepsy patients-two 30 direction (standard ddMRI, 10 nested cubes) or two 15 direction scans (standard DTI, 5 nested cubes). Fifteen direction DTI was repeated twice for within-session test-retest measurements in healthy subjects. Bland-Altman analysis computed bias and limits of agreement for DTI metrics using test-retest scans and standard 15 direction vs. 5 nested cubes scans. Intraclass correlation (ICC) analysis compared tensor metrics between 15 direction DTI scans (standard vs. 5 nested cubes) and the coefficients of variation (CoV) of trace and apparent diffusion coefficient (ADC) between 30 direction ddMRI scans (standard vs. 10 nested cubes). Bland-Altman and ICC analysis using a P-value of 0.05 for statistical significance. Correlations of mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were strong and significant in gray (ICC > 0.95) and white matter (ICC > 0.95) between standard vs. nested cubes DTI acquisitions. Correlation of white matter fractional anisotropy was also strong (ICC > 0.95) and significant. ICCs of the CoV of dynamic ADC measured using repeated cubes and nested cubes acquisitions were modest (ICC >0.60), but significant in gray matter. A nested cubes diffusion gradient table produces tensor-based and dynamic diffusion measurements in a single acquisition. 2 TECHNICAL EFFICACY: Stage 1.

Microstructural Alterations in Projection and Association Fibers in Neonatal Hypoxia-Ischemia.

Diffusion MRI (dMRI) is known to be sensitive to hypoxic-ischemic encephalopathy (HIE). However, existing dMRI studies used simple diffusion tensor metrics and focused only on a few selected cerebral regions, which cannot provide a comprehensive picture of microstructural injury. To systematically characterize the microstructural alterations in mild, moderate, and severe HIE neonates compared to healthy neonates with advanced dMRI using region of interest (ROI), tract, and fixel-based analyses. Prospective. A total of 42 neonates (24 males and 18 females). 3-T, diffusion-weighted echo-planar imaging. Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), fiber density (FD), fiber cross-section (FC), and fiber density and cross-section (FDC) were calculated in 40 ROIs and 6 tracts. Fixel-based analysis was performed to assess group differences in individual fiber components within a voxel (fixel). One-way analysis of covariance (ANCOVA) to compare dMRI metrics among severe/moderate/mild HIE and control groups and general linear model for fixel-wise group differences (age, sex, and body weight as covariates). Adjusted P value < 0.05 was considered statistically significant. For severe HIE, ROI-based analysis revealed widespread regions, including the deep nuclei and white matter with reduced FA, while in moderate injury, only FC was decreased around the posterior watershed zones. Tract-based analysis demonstrated significantly reduced FA, FD, and FC in the right inferior fronto-occipital fasciculus (IFOF), right inferior longitudinal fasciculus (ILF), and splenium of corpus callosum (SCC) in moderate HIE, and in right IFOF and left anterior thalamic radiation (ATR) in mild HIE. Correspondingly, we found altered fixels in the right middle-posterior IFOF and ILF, and in the central-to-right part of SCC in moderate HIE. For severe HIE, extensive microstructural injury was identified. For moderate-mild HIE, association fiber injury in posterior watershed area with a rightward lateralization was found. 1 TECHNICAL EFFICACY: Stage 3.

A groupwise registration and tractography framework for cardiac myofiber architecture description by diffusion MRI: An application to the ventricular junctions.

BackgroundKnowledge of the normal myocardial–myocyte orientation could theoretically allow the definition of relevant quantitative biomarkers in clinical routine to diagnose heart pathologies. A whole heart diffusion tensor template representative of the global myofiber organization over species is therefore crucial for comparisons across populations. In this study, we developed a groupwise registration and tractography framework to resolve the global myofiber arrangement of large mammalian sheep hearts. To demonstrate the potential application of the proposed method, a novel description of sub-regions in the intraventricular septum is presented.MethodsThree explanted sheep (ovine) hearts (size ~12×8×6 cm3, heart weight ~ 150 g) were perfused with contrast agent and fixative and imaged in a 9.4T magnet. A group-wise registration of high-resolution anatomical and diffusion-weighted images were performed to generate anatomical and diffusion tensor templates. Diffusion tensor metrics (eigenvalues, eigenvectors, fractional anisotropy …) were computed to provide a quantitative and spatially-resolved analysis of cardiac microstructure. Then tractography was performed using deterministic and probabilistic algorithms and used for different purposes: i) Visualization of myofiber architecture, ii) Segmentation of sub-area depicting the same fiber organization, iii) Seeding and Tract Editing. Finally, dissection was performed to confirm the existence of macroscopic structures identified in the diffusion tensor template.ResultsThe template creation takes advantage of high-resolution anatomical and diffusion-weighted images obtained at an isotropic resolution of 150 μm and 600 μm respectively, covering ventricles and atria and providing information on the normal myocardial architecture. The diffusion metric distributions from the template were found close to the one of the individual samples validating the registration procedure. Small new sub-regions exhibiting spatially sharp variations in fiber orientation close to the junctions of the septum and ventricles were identified. Each substructure was defined and represented using streamlines. The existence of a fiber-bundles in the posterior junction was validated by anatomical dissection. A complex structural organization of the anterior junction in comparison to the posterior junction was evidenced by the high-resolution acquisition.ConclusionsA new framework combining cardiac template generation and tractography was applied on the whole sheep heart. The framework can be used for anatomical investigation, characterization of microstructure and visualization of myofiber orientation across samples. Finally, a novel description of the ventricular junction in large mammalian sheep hearts was proposed.

Microstructural alterations in association tracts and language abilities in schoolchildren born very preterm and with poor fetal growth

BackgroundPrematurity and perinatal risk factors may influence white matter microstructure. In turn, these maturational changes may influence language development in this high-risk population of children.ObjectiveTo evaluate differences in the microstructure of association tracts between preterm and term children and between preterm children with appropriate growth and those with fetal growth restriction and to study whether the diffusion tensor metrics of these tracts correlate with language abilities in schoolchildren with no severe neurological impairment.Materials and methodsThis study prospectively followed 56 very preterm children (mean gestational age: 28.7 weeks) and 21 age- and gender-matched term children who underwent diffusion tensor imaging at a mean age of 9 years. We used automated probabilistic tractography and measured fractional anisotropy in seven bilateral association tracts known to belong to the white matter language network. Both groups participated in language assessment using five standardised tests at the same age.ResultsPreterm children had lower fractional anisotropy in the right superior longitudinal fasciculus 1 compared to term children (P < 0.05). Preterm children with fetal growth restriction had lower fractional anisotropy in the left inferior longitudinal fasciculus compared to preterm children with appropriate fetal growth (P < 0.05). Fractional anisotropy in three dorsal tracts and in two dorsal and one ventral tract had a positive correlation with language assessments among preterm children and preterm children with fetal growth restriction, respectively (P < 0.05).ConclusionThere were some microstructural differences in language-related tracts between preterm and term children and between preterm children with appropriate and those with restricted fetal growth. Children with better language abilities had a higher fractional anisotropy in distinct white matter tracts.

Higher-order multi-shell diffusion measures complement tensor metrics and volume in gray matter when predicting age and cognition

Recent advances in diffusion-weighted imaging have enabled us to probe the microstructure of even gray matter non-invasively. However, these advanced multi-shell protocols are often not included in large-scale studies as they significantly increase scan time. In this study, we investigated whether one set of multi-shell diffusion metrics commonly used in gray matter (as derived from Neurite Orientation Dispersion and Density Imaging, NODDI) provide enough additional information over typical tensor and volume metrics to justify the increased acquisition time, using the cognitive aging framework in the human hippocampus as a testbed. We first demonstrated that NODDI metrics are robust and reliable by replicating previous findings from our lab in a larger population of 79 younger (20.41 ± 1.89 years, 46 females) and 75 older (73.56 ± 6.26 years, 45 females) adults, showing that these metrics in the hippocampal subfields are sensitive to age and memory performance. We then asked how these subfield specific hippocampal NODDI metrics compared with standard tensor metrics and volume in predicting age and memory ability. We discovered that both NODDI and tensor measures separately predicted age and cognition in comparable capacities. However, integrating these modalities together considerably increased the predictive power of our logistic models, indicating that NODDI and tensor measures may be capturing independent microstructural information. We use these findings to encourage neuroimaging data collection consortiums to include a multi-shell diffusion sequence in their protocols since existing NODDI measures (and potential future multi-shell measures) may be able to capture microstructural variance that is missed by traditional approaches, even in studies exclusively examining gray matter.

Fixel based analysis of white matter alterations in early stage cerebral small vessel disease

Cerebral small vessel disease (CSVD) is a common cause of morbidity and cognitive decline in the elderly population. However, characterizing the disease pathophysiology and its association with potential clinical sequelae in early stages is less well explored. We applied fixel-based analysis (FBA), a novel framework of investigating microstructural white matter integrity by diffusion-weighted imaging, to data of 921 participants of the Hamburg City Health Study, comprising middle-aged individuals with increased cerebrovascular risk in early stages of CSVD. In individuals in the highest quartile of white matter hyperintensity loads (n = 232, median age 63 years; IQR 15.3 years), FBA detected significantly reduced axonal density and increased atrophy of transcallosal fiber tracts, the bilateral superior longitudinal fasciculus, and corticospinal tracts compared to participants in the lowest quartile of white matter hyperintensities (n = 228, mean age 55 years; IQR 10 years). Analysis of all participants (N = 921) demonstrated a significant association between reduced fiber density and worse executive functions operationalized by the Trail Making Test. Findings were confirmed by complementary analysis of diffusion tensor metrics.

Prenatal depression exposure alters white matter integrity and neurodevelopment in early childhood

Prenatal exposure to maternal depression increases the risk for onset of emotional and behavioral disorders in children. We investigated the effects of exposure to prenatal depression on white matter microstructural integrity at birth and at 2-3 years, and associated neurodevelopment. Diffusion-weighted images were acquired for children of the Drakenstein Child Health Study at 2-4 weeks postpartum (n=70, 47% boys) and at 2-3 years of age (n=60, 58% boys). Tract-Based Spatial Statistics was used to compare, using an ROI based approach, diffusion tensor metrics across groups defined by presence (>19 on Beck’s Depression Inventory and/or >12 on the Edinburgh Postnatal Depression Scale) or absence (below depression thresholds) of depression, and associations with neurodevelopmental measures at age 2-3 years were determined. We did not detect group differences in white matter integrity at neonatal age, but at 2-3 years, children in the exposed group demonstrated higher fractional anisotropy, and lower mean and radial diffusivity in association tracts compared to controls. This was notable in the sagittal stratum (radial diffusivity: p<0.01). Altered white matter integrity metrics were also observed in projection tracts, including the corona radiata, which associated with cognitive and motor outcomes in exposed 2-3-year-olds (p<0.05). Our findings of widespread white matter alterations in 2-3-year-old children with prenatal exposure to depression are consistent with previous findings, as well as with neuroimaging findings in adults with major depression. Further, we identified novel associations of altered white matter integrity with cognitive development in depression-exposed children, suggesting that these neuroimaging findings may have early functional impact.

White matter diffusivity and its correlations to state measures of psychopathology in male refugees with posttraumatic stress disorder

Post-traumatic stress disorder (PTSD) is a heterogenous condition and the underlying neurobiology is still poorly understood. In this study, we tested the hypothesis that PTSD is associated with microstructural changes in white matter (WM) fibre tracts that connect regions involved in emotional processing, memory, attention, and language. Furthermore, we examined how different response patterns to individualized trauma-provoking stimuli related to underlying WM microstructure. Sixty-nine trauma-affected male refugees with PTSD (N = 38) or without PTSD (N = 31) underwent clinical assessments and diffusion-weighted magnetic resonance imaging (DWI) of the whole brain at 3 Tesla. Diffusion tensor metrics were computed from DWI data and used to characterize regional white-matter microstructure. An automated tract segmentation method was used to extract diffusion tensor metrics from subject-based reconstructions of tract segments (ROI), including uncinate fasciculus (UF), cingulum bundle (CB), superior longitudinal fasciculus (SLF) in three subdivisions (SLF I - III), and fibre bundles connecting orbito-frontal cortex to striatum (OF-ST). Outside the scanner we obtained measures of immediate (state) arousal, avoidance and dissociation symptoms assessed in response to auditory exposure to a personal traumatic memory. Using mean FA of the middle part of each ROI, mixed ANOVA revealed a significant interaction between group, ROI and hemisphere. Post-hoc comparisons showed that, relative to refugees without PTSD, refugees with PTSD had lower FA in right CB, left SLF-I, bilateral OF-ST and bilateral SLF-II. Mean FA scaled negatively with avoidance in right CB while mean FA in bilateral UF scaled positively with individual scores reflecting dissociation symptoms. The results support a pathophysiological model of PTSD that implicates limbic structures, prefrontal cortex and striatum. The results also emphasize the need to consider PTSD’s multifaceted manifestations when searching for functional-structural relationships.

Deep medullary veins are associated with widespread brain structural abnormalities

Our aim is to investigate the association of cerebral deep medullary veins (DMVs) with white matter microstructural integrity and regional brain atrophy in MRI. In a community-based cohort of 979 participants (mean age 55.4 years), DMVs were identified on susceptibility-weighted imaging. Brain structural measurements including gray matter and hippocampus volumes, as well as diffusion tensor metrics, were evaluated. The mean (SD)number of DMVs was 19.0 (1.7). A fewer number of DMVs was related to lower fractional anisotropy and higher mean diffusivity in multiple voxels on the white matter skeleton (threshold-free cluster enhancement corrected p < 0.05, adjusted for age and sex). Also, fewer DMVs were significantly related to a lower gray matter fraction and a hippocampal fraction (0.10 and 0.11 per DMV, respectively; SE, 0.03 for both; p < 0.001 for both). A significant correlation between DMVs’ reduction and cortical atrophy was observed in the bilateral occipital lobes, temporal lobes, hippocampus, and frontal lobes (p < 0.001, adjusted for age, sex, and total intracranial volume). Our results provided evidence that cerebral small venules disease play a role in brain parenchymal lesions and neurodegenerative processes.

MRI Correlates of Ototoxicity in the Auditory Pathway in Children Treated for Medulloblastoma.

To assess diffusion and perfusion changes of the auditory pathway in pediatric medulloblastoma patients exposed to ototoxic therapies. Retrospective cohort study. A single academic tertiary children's hospital. Twenty pediatric medulloblastoma patients (13 men; mean age 12.0 ± 4.8 yr) treated with platinum-based chemotherapy with or without radiation and 18 age-and-sex matched controls were included. Ototoxicity scores were determined using Chang Ototoxicity Grading Scale. Three Tesla magnetic resonance was used for diffusion tensor and arterial spin labeling perfusion imaging. Quantitative diffusion tensor metrics were extracted from the Heschl's gyrus, auditory radiation, and inferior colliculus. Arterial spin labeling perfusion of the Heschl's gyrus was also examined. Nine patients had clinically significant hearing loss, or Chang grades more than or equal to 2a; 11 patients had mild/no hearing loss, or Chang grades less than 2a. The clinically significant hearing loss group showed reduced mean diffusivity in the Heschl's gyrus (p = 0.018) and auditory radiation (p = 0.037), and decreased perfusion in the Heschl's gyrus (p = 0.001). Mild/no hearing loss group showed reduced mean diffusivity (p = 0.036) in Heschl's gyrus only, with a decrease in perfusion (p = 0.008). There were no differences between groups in the inferior colliculus. There was no difference in fractional anisotropy between patients exposed to ototoxic therapies and controls. Patients exposed to ototoxic therapies demonstrated microstructural and physiological alteration of the auditory pathway. The present study shows proof-of-concept use of diffusion tensor imaging to gauge ototoxicity along the auditory pathway. Future larger cohort studies are needed to assess significance of changes in diffusion tensor imaging longitudinally, and the relationship between these changes and hearing loss severity and longitudinal changes of the developing auditory white matter.

Mapping white matter maturational processes and degrees on neonates by diffusion kurtosis imaging with multiparametric analysis.

White matter maturation has been characterized by diffusion tensor (DT) metrics. However, maturational processes and degrees are not fully investigated due to limitations of univariate approaches and limited specificity/sensitivity. Diffusion kurtosis imaging (DKI) provides kurtosis tensor (KT) and white matter tract integrity (WMTI) metrics, besides DT metrics. Therefore, we tried to investigate performances of DKI with the multiparametric analysis in characterizing white matter maturation. Developmental changes in metrics were investigated by using tract‐based spatial statistics and the region of interest analysis on 50 neonates with postmenstrual age (PMA) from 37.43 to 43.57 weeks. Changes in metrics were combined into various patterns to reveal different maturational processes. Mahalanobis distance based on DT metrics (D M,DT) and that combing DT and KT metrics (D M,DT‐KT) were computed, separately. Performances of D M,DT‐KT and D M,DT were compared in revealing correlations with PMA and the neurobehavioral score. Compared with DT metrics, WMTI metrics demonstrated additional changing patterns. Furthermore, variations of D M,DT‐KT across regions were in agreement with the maturational sequence. Additionally, D M,DT‐KT demonstrated stronger negative correlations with PMA and the neurobehavioral score in more regions than D M,DT. Results suggest that DKI with the multiparametric analysis benefits the understanding of white matter maturational processes and degrees on neonates.

Loss and dispersion of superficial white matter in Alzheimer's disease: a diffusion MRI study.

Pathological cerebral white matter changes in Alzheimer’s disease have been shown using diffusion tensor imaging. Superficial white matter changes are relatively understudied despite their importance in cortico-cortical connections. Measuring superficial white matter degeneration using diffusion tensor imaging is challenging due to its complex organizational structure and proximity to the cortex. To overcome this, we investigated diffusion MRI changes in young-onset Alzheimer’s disease using standard diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging to distinguish between disease-related changes that are degenerative (e.g. loss of myelinated fibres) and organizational (e.g. increased fibre dispersion). Twenty-nine young-onset Alzheimer’s disease patients and 22 healthy controls had both single-shell and multi-shell diffusion MRI. We calculated fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index and tissue fraction (1-free water fraction). Diffusion metrics were sampled in 15 a priori regions of interest at four points along the cortical profile: cortical grey matter, grey/white boundary, superficial white matter (1 mm below grey/white boundary) and superficial/deeper white matter (2 mm below grey/white boundary). To estimate cross-sectional group differences, we used average marginal effects from linear mixed effect models of participants’ diffusion metrics along the cortical profile. The superficial white matter of young-onset Alzheimer’s disease individuals had lower neurite density index compared to controls in five regions (superior and inferior parietal, precuneus, entorhinal and parahippocampus) (all P < 0.05), and higher orientation dispersion index in three regions (fusiform, entorhinal and parahippocampus) (all P < 0.05). Young-onset Alzheimer’s disease individuals had lower fractional anisotropy in the entorhinal and parahippocampus regions (both P < 0.05) and higher fractional anisotropy within the postcentral region (P < 0.05). Mean diffusivity was higher in the young-onset Alzheimer’s disease group in the parahippocampal region (P < 0.05) and lower in the postcentral, precentral and superior temporal regions (all P < 0.05). In the overlying grey matter, disease-related changes were largely consistent with superficial white matter findings when using neurite density index and fractional anisotropy, but appeared at odds with orientation dispersion and mean diffusivity. Tissue fraction was significantly lower across all grey matter regions in young-onset Alzheimer’s disease individuals (all P < 0.001) but group differences reduced in magnitude and coverage when moving towards the superficial white matter. These results show that microstructural changes occur within superficial white matter and along the cortical profile in individuals with young-onset Alzheimer’s disease. Lower neurite density and higher orientation dispersion suggests underlying fibres undergo neurodegeneration and organizational changes, two effects previously indiscernible using standard diffusion tensor metrics in superficial white matter.

Role of regional diffusion tensor imaging (DTI)-derived tensor metrics in the evaluation of intracranial gliomas and its histopathological correlation

BackgroundThe imaging of brain tumours has significantly improved with the use of advanced magnetic resonance (MR) techniques like diffusion tensor imaging (DTI). This study was conducted to analyse the utility of DTI-derived tensor metrics in the evaluation of intracranial gliomas with histopathological correlation and further adoption of these image-data analyses in clinical setting. MethodsA total of 50 patients with suspected diagnosis of intracranial gliomas underwent DTI along with conventional MR examination. The study correlated various DTI parameters in the enhancing part of the tumour and the peritumoral region with the histopathological grades of the intracranial gliomas. ResultsThe study revealed higher values of Cl (linear anisotropy), Cp (planar anisotropy), AD (axial diffusivity), FA (fractional anisotropy) and RA (relative anisotropy) and lower values of Cs (spherical anisotropy), MD (mean diffusivity) and RD (radial diffusivity) in the enhancing part of the tumour in case of high-grade gliomas. However, in the peritumoral region, the values of Cl, Cp, AD, FA and RA were less whereas values of Cs, MD and RD were more in high-grade gliomas than in the low-grade gliomas. The various cutoff values of these DTI-derived tensor metrics were found to be statistically significant. ConclusionDTI-derived tensor metrics can be a valuable tool in differentiation between high-grade and low-grade gliomas which might be accepted in clinical practice in near future.

Neurite orientation dispersion and density imaging reveals white matter microstructural alterations in adults with autism

BackgroundEvidences suggesting the association between behavioral anomalies in autism and white matter (WM) microstructural alterations are increasing. Diffusion tensor imaging (DTI) is widely used to infer tissue microstructure. However, due to its lack of specificity, the underlying pathology of reported differences in DTI measures in autism remains poorly understood. Herein, we applied neurite orientation dispersion and density imaging (NODDI) to quantify and define more specific causes of WM microstructural changes associated with autism in adults.MethodsNODDI (neurite density index [NDI], orientation dispersion index, and isotropic volume fraction [ISOVF]) and DTI (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity, and radial diffusivity [RD]) measures were compared between autism (N = 26; 19 males and 7 females; 32.93 ± 9.24 years old) and age- and sex-matched typically developing (TD; N = 25; 17 males and 8 females; 34.43 ± 9.02 years old) groups using tract-based spatial statistics and region-of-interest analyses. Linear discriminant analysis using leave-one-out cross-validation (LDA-LOOCV) was also performed to assess the discriminative power of diffusion measures in autism and TD.ResultsSignificantly lower NDI and higher ISOVF, suggestive of decreased neurite density and increased extracellular free-water, respectively, were demonstrated in the autism group compared with the TD group, mainly in commissural and long-range association tracts, but with distinct predominant sides. Consistent with previous reports, the autism group showed lower FA and higher MD and RD when compared with TD group. Notably, LDA-LOOCV suggests that NDI and ISOVF have relatively higher accuracy (82%) and specificity (NDI, 84%; ISOVF, 88%) compared with that of FA, MD, and RD (accuracy, 67–73%; specificity, 68–80%).LimitationsThe absence of histopathological confirmation limit the interpretation of our findings.ConclusionsOur results suggest that NODDI measures might be useful as imaging biomarkers to diagnose autism in adults and assess its behavioral characteristics. Furthermore, NODDI allows interpretation of previous findings on changes in WM diffusion tensor metrics in individuals with autism.

Diffusivity Metrics Three Months After Upfront Gamma Knife Radiosurgery for Trigeminal Neuralgia May Be Correlated with Pain Relief

Gamma Knife radiosurgery (GKRS) is a safe and effective treatment option for trigeminal neuralgia (TN). However, there is no objective, noninvasive tool to identify nonresponders or late responders to GKRS and to facilitate longitudinal patient management. We hypothesized that diffusivity metrics obtained 3 months after GKRS may correlate with response to treatment. Sixteen patients with TN treated with GKRS underwent preprocedural and 3-month postprocedural 3-T magnetic resonance imaging of the brain. Diffusion tensor metrics of axial diffusivity, radial diffusivity, and fractional anisotropy were extracted from the pontine segments, the root entry zones, and the distal cisternal segments of both trigeminal nerves. Diffusivity metrics at the 3-month post-GKRS time point were compared with pain relief at last follow-up. Favorable response to GKRS was defined as pain intensity of I-III on the Barrow Neurological Institute scale. The median clinical follow-up was 11 months (range 3-18 months). Patients with favorable response to GKRS at last follow-up had lower mean fractional anisotropy values at the pontine segment (P= 0.04) and increased mean radial diffusivity values at the root entry zones (P= 0.032) of the treated trigeminal nerve on the 3-month diffusion tensor imaging sequences as compared with the nonresponders. Diffusivity metrics changes on the treated trigeminal nerve at the 3-month time point after GKRS for TN correlated with pain relief at last follow-up. Further, well-designed studies are warranted to establish the clinical application of diffusion tensor imaging as a noninvasive, prognostic tool in patients with TN managed with GKRS.

Brainstem damage is associated with poorer sleep quality and increased pain in gulf war illness veterans

AimsGulf War Illness (GWI) is manifested as multiple chronic symptoms, including chronic pain, chronic fatigue, sleep problems, neuropsychiatric disorders, respiratory, gastrointestinal, and skin problems. No single target tissue or unifying pathogenic process has been identified that accounts for this variety of symptoms. The brainstem has been suspected to contribute to this multiple symptomatology. The aim of this study was to assess the role of the brainstem in chronic sleep problems and pain in GWI veterans. Materials and methodsWe enrolled 90 veterans (Age = 50 ± 5, 87% Male) who were deployed to the 1990–91 Gulf War and presented with GWI symptoms. Sleep quality was evaluated using the global Pittsburgh Sleep Quality Index. Pain intensities were obtained with the Brief Pain Inventory sum score. Volumes in cortical, subcortical, brainstem, and brainstem subregions and diffusion tensor metrics in 10 bilateral brainstem tracts were tested for correlations with symptom measures. Key findingsPoorer sleep quality was significantly correlated with atrophy of the whole brainstem and brainstem subregions (including midbrain, pons, medulla). Poorer sleep quality also significantly correlated with lower fractional anisotropy in the nigrostriatal tract, medial forebrain tract, and the dorsal longitudinal fasciculus. There was a significant correlation between increased pain intensity and decreased fractional anisotropy in the dorsal longitudinal fasciculus. These correlations were not altered after controlling for age, sex, total intracranial volumes, or additional factors, e.g., depression and neurological conditions. SignificanceThese findings suggest that the brainstem plays an important role in the aberrant neuromodulation of sleep and pain symptoms in GWI.

Progressive microstructural alterations in subcortical nuclei in Parkinson's disease: A diffusion magnetic resonance imaging study

ObjectivesTo explore the microstructural alterations in subcortical nuclei in Parkinson's disease (PD) at different stages with diffusion kurtosis imaging (DKI) and tensor imaging and to test the performance of diffusion metrics in identifying PD. Methods108 PD patients (64 patients in early-stage PD group (EPD) and 44 patients in moderate-late-stage PD group (MLPD)) and 64 healthy controls (HC) were included. Tensor and kurtosis metrics in the subcortical nuclei were compared. Partial correlation was used to correlate the diffusion metrics and Unified Parkinson's Disease Rating Scale part-III (UPDRS-III) score. Logistic regression and receiver operating characteristic analysis were applied to test the diagnostic performance of the diffusion metrics. ResultsCompared with HC, both EPD and MLPD patients showed higher fractional anisotropy and axial diffusivity, lower mean kurtosis (MK) and axial kurtosis in substantia nigra, lower MK and radial kurtosis (RK) in globus pallidus (GP) and thalamus (all p < 0.05). Compared with EPD, MLPD patients showed lower MK and RK in GP and thalamus (all p < 0.05). MK and RK in GP and thalamus were negatively correlated with UPDRS-III score (all p < 0.01). The logistic regression model combining kurtosis and tensor metrics showed the best performance in diagnosing PD, EPD, and MLPD (areas under curve were 0.817, 0.769, and 0.914, respectively). ConclusionsPD has progressive microstructural alterations in the subcortical nuclei. DKI is sensitive to detect microstructural alterations in GP and thalamus during PD progression. Combining kurtosis and tensor metrics can achieve a good performance in diagnosing PD.

Anterior cingulate cortex metabolites and white matter microstructure: a multimodal study of emergent alcohol use disorder.

Multimodal imaging is increasingly used to address neuropathology associated with alcohol use disorder (AUD). Few studies have investigated relationships between metabolite concentrations and white matter (WM) integrity; currently, there are no such data in AUD. In this preliminary study, we used complementary neuroimaging techniques, magnetic resonance spectroscopy (MRS), and diffusion weighted imaging (DWI), to study AUD neurophysiology. We tested for relationships between metabolites in the dorsal anterior cingulate cortex (dACC) and adjacent WM microstructure in young adult AUD and control (CON) subjects. Sixteen AUD and fourteen CON underwent whole-brain DWI and MRS of the dACC. Outcomes were dACC metabolites, and diffusion tensor metrics of dACC-adjacent WM. Multiple linear regression terms included WM region, group, and region × group for prediction of dACC metabolites. dACC myo-inositol was positively correlated with axial diffusivity in the left anterior corona radiata (p < 0.0001) in CON but not AUD (group effect: p < 0.001; region × group: p < 0.001; Bonferroni-corrected). In the bilateral anterior corona radiata and right genu of the corpus callosum, glutamate was negatively related to mean diffusivity in AUD, but not CON subjects (all model terms: p < 0.05, uncorrected). In AUD subjects, dACC glutamate was negatively correlated with AUD symptom severity. This is likely the first integrative study of cortical metabolites and WM integrity in young individuals with AUD. Differential relationships between dACC metabolites and adjacent WM tract integrity in AUD could represent early consequences of hazardous drinking, and/or novel biomarkers of early-stage AUD. Additional studies are required to replicate these findings, and to determine the behavioral relevance of these results.