Fractional Anisotropy Metrics Research Articles

Brain tissue integrity in neuromyelitis optica spectrum disorder through T1-w/T2-w ratio, MTR and DTI.

The presence of diffuse brain damage in normal-appearing white matter (NAWM) and gray matter (NAGM) in neuromyelitis optica spectrum disorder (NMOSD) remains controversial. We aimed to address this controversy by applying a multiparametric MRI approach. Additionally, the association between MRI metrics and clinical variables was explored. In this cross-sectional study, we prospectively evaluated aquaporin-4-IgG positive NMOSD patients and healthy controls (HC) matched for age and sex. The clinical variables of interest were collected for each participant. The mean values of T1-w/T2-w ratio, magnetization transfer ratio (MTR), fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) were obtained in NAWM, NAGM, as well as in global and hypointense lesion masks. Global lesions refer to those typically associated with aquaporin-4-IgG positive NMOSD. Hypointense lesions were defined as areas of hypointense signal in both T1-w and fluid-attenuated inversion recovery (FLAIR) images. In total, we included 105 participants (59 NMOSD patients and 46 HC). T1-w/T2-w ratio was lower in NAWM of NMOSD patients versus HC (1.83 ± 0.14 vs 1.89 ± 0.14; p = 0.029), while no significant differences were found in NAWM or NAGM across the other metrics: (p range: 0.079 to 0.973). Hypointense lesions showed lower T1-w/T2-w ratio, MTR, and FA, and higher diffusivity metrics as compared to global lesion masks (p < 0.001). T1-w/T2-w ratio in NAWM was inversely correlated with time to start immunosuppressive therapy (r = - 0.278; p = 0.036) and with MD (r = - 0.325; p = 0.014). Microstructural integrity loss seems to be confined to focal tissue damage in NMOSD. Decreased T1-w/T2-w ratio in NAWM may reflect subclinical water accumulation due to astrocyte and blood-brain barrier dysfunction. Hypointense lesions have shown a severe degree of microstructural damage.

MRI-based analysis of the microstructure of the thalamus and hypothalamus and functional connectivity between cortical networks in episodic cluster headache

BackgroundNeuroimaging studies have shown that hypothalamic/thalamic nuclei and other distant brain regions belonging to complex cerebral networks are involved in cluster headache (CH). However, the exact relationship between these areas, which may be dependent or independent, remains to be understood. We investigated differences in resting-state functional connectivity (FC) between brain networks and its relationship with the microstructure of the hypothalamus and thalamus in patients with episodic CH outside attacks and healthy controls (HCs).MethodsWe collected 3T MRI data from 26 patients with CH during the in-bout period outside the attacks and compared them with data from 20 HCs. From resting-state data we derived independent component (IC) networks. We calculated the fractional anisotropy (FA) and mean (MD), axial (AD), and radial (RD) diffusivity values of the hypothalamus and bilateral thalami and correlated them with resting-state IC Z-scores and CH clinical features.ResultsPatients with CH had less FC between the salience network (SN) and left executive control network (ECN) than HCs, but more FC between the default mode network and right ECN. Patients with CH showed lower FA and higher MD microstructural hypothalamic metrics than HCs. Patients with CH had a higher bilateral FA metric in the thalamus than HCs. The AD and RD diffusivity metrics of the hypothalamus were positively correlated with the disease history duration. We found no correlations between the hypothalamic and thalamic diffusivity metrics and the FC of the cortical networks.ConclusionOur findings presented the possibility of a correlation between the FC of the SN and the inability to switch between internalizing and externalizing brain activity during demanding cognitive tasks, such as recurring headaches. Moreover, we found differences in the thalamic and hypothalamic microstructures that may independently contribute to the pathophysiology of CH. These differences may reflect changes in directional organization, cell size, and density.

Language and the Cerebellum: Structural Connectivity to the Eloquent Brain.

Neurobiological models of receptive language have focused on the left-hemisphere perisylvian cortex with the assumption that the cerebellum supports peri-linguistic cognitive processes such as verbal working memory. The goal of this study was to identify language-sensitive regions of the cerebellum then map the structural connectivity profile of these regions. Functional imaging data and diffusion-weighted imaging data from the Human Connectome Project (HCP) were analyzed. We found that (a) working memory, motor activity, and language comprehension activated partially overlapping but mostly unique subregions of the cerebellum; (b) the linguistic portion of the cerebello-thalamo-cortical circuit was more extensive than the linguistic portion of the cortico-ponto-cerebellar tract; (c) there was a frontal-lobe bias in the connectivity from the cerebellum to the cerebrum; (d) there was some degree of specificity; and (e) for some cerebellar tracts, individual differences in picture identification ability covaried with fractional anisotropy metrics. These findings yield insights into the structural connectivity of the cerebellum as relates to the uniquely human process of language comprehension.

Corpus callosum damage in PSP and unsteady PD patients: A multimodal MRI study

IntroductionPostural instability (PI) is a common disabling symptom in Parkinson’s disease (PD) patients, but the brain alterations underlying this sign are not fully understood yet. This study aimed to investigate the association between PI and callosal damage in PD and progressive supranuclear palsy (PSP) patients, using multimodal MR imaging. MethodsOne-hundred and two PD patients stratified according to the presence/absence of PI (PD-steady N=58; PD-unsteady N=44), 69 PSP patients, and 38 healthy controls (HC) underwent structural and diffusion 3T brain MRI. Thickness, fractional anisotropy (FA) and mean diffusivity (MD) were calculated over 50 equidistant points covering the whole midsagittal profile of the corpus callosum (CC) and compared among groups. Associations between imaging metrics and postural instability score were investigated using linear regression. ResultsBoth PSP and PD-unsteady patient groups showed CC involvement in comparison with HC, while no difference was found between PD-steady patients and controls. The CC damage was more severe and widespread in PSP than in PD patients. The CC genu was the regions most damaged in PD-unsteady patients compared with PD-steady patients, showing significant microstructural alterations of MD and FA metrics. Linear regression analysis pointed at the MD in the CC genu as the main contributor to PI among the considered MRI metrics. ConclusionThis study identified callosal microstructural alterations associated with PI in unsteady PD and PSP patients, which provide new insights on PI pathophysiology and might serve as imaging biomarkers for assessing postural instability progression and treatment response.

Development and benchmarking diffusion magnetic resonance imaging analysis for integration into radiation treatment planning.

The rising promise in the utility of advanced multi-parametric magnetic resonance (MR) imaging in radiotherapy (RT) treatment planning creates a necessity for testing and enhancing the accuracy of quantitative imaging analysis. Standardizing the analysis of diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) to generate meaningful and reproducible apparent diffusion coefficient (ADC) and fractional anisotropy (FA) lays the requisite needed for clinical integration. The aim of the demonstrated work is to benchmark the generation of the ADC and FA parametric map analyses using integrated tools in a commercial treatment planning system against the currently used ones. Three software packages were used for generating ADC and FA maps in this study; one tool was developed within a commercial treatment planning system, another by the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library FSL (Analysis Group, FMRIB, Oxford, United Kingdom), and an in-house tool developed at the M.D. Anderson Cancer Center. The ADC and FA maps generated by all three packages for 35 subjects were subtracted from one another, and the standard deviation of the images' differences was used to compare the reproducibility. The reproducibility of the ADC maps was compared with the Quantitative Imaging Biomarkers Alliance (QIBA) protocol, while that of the FA maps was compared to data in published literature. Results show that the discrepancies between the ADC maps calculated for each patient using the three different software algorithms are less than 2% which meets the 3.6% recommended QIBA requirement. Except for a small number of isolated points, the majority of differences in FA maps for each patient produced by the three methods did not exceed 0.02 which is 10 times lower than the differences seen in healthy gray and white matter. The results were also compared to the maps generated by existing MR Imaging consoles and showed that the robustness of console generated ADC and FA maps is largely dependent on the correct application of scaling factors, that only if correctly placed; the differences between the three tested methods and the console generated values were within the recommended QIBA guidelines. Cross-comparison difference maps demonstrated that quantitative reproducibility of ADC and FA metrics generated using our tested commercial treatment planning system were comparable to in-house and established tools as benchmarks. This integrated approach facilitates the clinical utility of diffusion imaging in radiation treatment planning workflow.

Machine learning classification of chronic traumatic brain injury using diffusion tensor imaging and NODDI: A replication and extension study

Individuals with acute and chronic traumatic brain injury (TBI) are associated with unique white matter (WM) structural abnormalities, including fractional anisotropy (FA) differences. Our research group previously used FA as a feature in a linear support vector machine (SVM) pattern classifier, observing high classification between individuals with and without acute TBI (i.e., an area under the curve [AUC] value of 75.50%). However, it is not known whether FA could similarly classify between individuals with and without history of chronic TBI. Here, we attempted to replicate our previous work with a new sample, investigating whether FA could similarly classify between incarcerated men with (n = 80) and without (n = 80) self-reported history of chronic TBI. Additionally, given limitations associated with FA, including underestimation of FA values in WM tracts containing crossing fibers, we extended upon our previous study by incorporating neurite orientation dispersion and density imaging (NODDI) metrics, including orientation dispersion (ODI) and isotropic volume (Viso). A linear SVM based classification approach, similar to our previous study, was incorporated here to classify between individuals with and without self-reported chronic TBI using FA and NODDI metrics as separate features. Overall classification rates were similar when incorporating FA and NODDI ODI metrics as features (AUC: 82.50%). Additionally, NODDI-based metrics provided the highest sensitivity (ODI: 85.00%) and specificity (Viso: 82.50%) rates. The current study serves as a replication and extension of our previous study, observing that multiple diffusion MRI metrics can reliably classify between individuals with and without self-reported history of chronic TBI.

An aberrant hippocampal subregional network, rather than structure, characterizes major depressive disorder

BackgroundBehavioral and neuroimaging studies have implicated the hippocampus as a cardinal neural structure in major depressive disorder (MDD) pathogenesis. The hippocampal subregion-specific structural and functional abnormalities in MDD remain unknown. MethodsMultimodal magnetic resonance imaging (MRI) was acquired in 140 patients with MDD and 44 age- and sex-matched healthy controls (HCs). We quantified hippocampal subregional volumes and fractional anisotropy (FA) following a structural and diffusion MRI data analysis processing stream. Hippocampal subregional networks were established using seed-based functional connectivity (FC) analysis. Univariate analysis was used to investigate the differences between the two groups. Significant subfield metrics were correlated with depression severity. ResultsCompared with HCs, we did not find significant differences in subregional volumes or FA metrics in the MDD group. The MDD group exhibited a significantly weaker connectivity of the right hippocampal subregional networks with the temporal cortex (extending to the insula) and basal ganglia but showed increased connectivity of the right subiculum to the bilateral lingual gyrus. The FC between the right cornu ammonis 1 and right fusiform, between the right hippocampal amygdala transition area and the bilateral basal ganglia, were negatively correlated with depression severity (r = −0.224, p = 0.010; r = −0.196, p = 0.025, respectively) in the MDD group. LimitationsThis study did not consider the longitudinal changes in the structure and functional connectivity of the hippocampal subregion. ConclusionThese findings advance our understanding of the neurobiological basis of depression by identifying the hippocampal subregional structural and functional abnormalities.

Impact of white-matter mask selection on DTI histogram-based metrics as potential biomarkers in cerebral small vessel disease.

Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small vessel disease (SVD), but methods and results have varied across studies. This work aims to assess the impact of mask selection for extracting histogram-based metrics of fractional anisotropy (FA) and mean diffusivity (MD) on their sensitivity as SVD biomarkers. DTI data were collected from 17 SVD patients and 12 healthy controls. FA and MD maps were estimated; from these, histograms were computed on two whole-brain white-matter masks: normal-appearing white-matter (NAWM) and mean FA tract skeleton (TBSS). Histogram-based metrics (median, peak height, peak width, peak value) were extracted from the FA and MD maps. These were compared between groups and correlated with the patients' cognitive scores (executive function and processing speed). White-matter mask selection significantly impacted FA and MD histogram metrics. In particular, significant interactions were found between Mask and Group for FA peak height (p = 0.027), MD Median (p = 0.035) and MD peak width (p = 0.047); indicating that the mask used affected their ability to discriminate between groups. In fact, MD peak width showed a significant 8.8% increase in patients when using TBSS (p = 0.037), but not when using NAWM (p = 0.69). Moreover, the mask may have an effect on the correlations with cognitive measures. Nevertheless, MD peak width (TBSS: r = - 0.75, NAWM: r = - 0.71) and MD peak height (TBSS: r = 0.65, NAWM: r = 0.62) remained significantly correlated with executive function, regardless of the mask. The impact of the processing methodology, in particular the choice of white-matter mask, highlights the need for standardized MRI data-processing pipelines.

Trigeminal neuralgia diffusivities using Gaussian process classification and merged group tractography.

Imaging of trigeminal neuralgia (TN) has demonstrated key diffusion tensor imaging-based diffusivity alterations in the trigeminal nerve; however, imaging has primarily focused on the peripheral nerve segment because of previous limitations in reliably segmenting small fiber bundles across multiple subjects. We used Selective Automated Group Integrated Tractography to study 36 subjects with TN (right-sided pain) and 36 sex-matched controls to examine the trigeminal nerve (fifth cranial nerve [CN V]), pontine decussation (TPT), and thalamocortical fibers (S1). Gaussian process classifiers were trained by scrolling a moving window over CN V, TPT, and S1 tractography centroids. Fractional anisotropy (FA), generalized FA, radial diffusivity, axial diffusivity, and mean diffusivity metrics were evaluated for both groups, analyzing TN vs control groups and affected vs unaffected sides. Classifiers that performed at greater-than-or-equal-to 70% accuracy were included. Gaussian process classifier consistently demonstrated bilateral trigeminal changes, differentiating them from controls with an accuracy of 80%. Affected and unaffected sides could be differentiated from each other with 75% accuracy. Bilateral TPT could be distinguished from controls with at least 85% accuracy. TPT left-right classification achieved 98% accuracy. Bilateral S1 could be differentiated from controls, where the affected S1 radial diffusivity classifier achieved 87% accuracy. This is the first TN study that combines group-wise merged tractography, machine learning classification, and analysis of the complete trigeminal pathways from the peripheral fibers to S1 cortex. This analysis demonstrates that TN is characterized by bilateral abnormalities throughout the trigeminal pathway compared with controls and abnormalities between affected and unaffected sides. This full pathway tractography study of TN demonstrates bilateral changes throughout the trigeminal pathway and changes between affected and unaffected sides.

Sixto Obrador SENEC prize 2019: Utility of diffusion tensor imaging as a prognostic tool in moderate to severe traumatic brain injury. Part I. Analysis of DTI metrics performed during the early subacute stage

Background and objectivesTraumatic axonal injury (TAI) contributes significantly to mortality and morbidity after traumatic brain injury (TBI). Its identification is still a diagnostic challenge because of the limitations of conventional imaging techniques to characterized it. Diffusion tensor imaging (DTI) can indirectly identify areas of damaged white matter (WM) integrity by detecting water molecule diffusion alterations. Our main objective is to characterize the TAI using DTI at the early subacute stage in our series of moderate to severe TBI patients and to evaluate if there is a relationship between the information provided by the DTI and patient’s outcome. Materials and methodsWe have obtained DTI data from 217 patients with moderate to severe TBI acquired at a median of 19 days after TBI, and patient DTI metrics were compared with data obtained from 58 age-matched healthy controls. Region of interest (ROI) method was applied to obtain mean fractional anisotropy (FA) value in 28 WM fiber bundles susceptible to TAI. ResultsOur main results were that when we compared patients with controls, patients, regardless of TBI severity, showed significantly reduced mean FA in almost all ROI measured. We found statistically significant correlation between FA metrics and some clinical characteristics. Additionally, the FA values of the three portions of Corpus callosum, Cingulum and cerebral peduncles measured at the early subacute stage were highly associated with outcome assessed at hospital discharge and at 6 and 12 months after TBI. ConclusionsWe conclude that DTI is a useful tool to characterize TAI and the detection of FA reduction in the subacute stage after TBI is associated with long-term unfavorable outcome.

What Can Be Learned from Diffusion Tensor Imaging from a Large Traumatic Brain Injury Cohort?: White Matter Integrity and Its Relationship with Outcome.

Traumatic axonal injury (TAI) contributes significantly to mortality and morbidity after traumatic brain injury (TBI), but its identification is still a diagnostic challenge because of the limitations of conventional imaging techniques to characterized it. Diffusion tensor imaging (DTI) can indirectly identify areas of damaged white matter (WM) integrity by detecting water molecule diffusion alterations. Therefore, DTI may improve detection and description of TAI lesions after TBI. We have obtained DTI data from 217 patients with moderate to severe TBI acquired at a median of 19 days after TBI, and patient DTI metrics were compared with data obtained from 58 age-matched healthy controls. Region of interest (ROI) method was applied to obtain mean fractional anisotropy (FA) value in 28 WM fiber bundles susceptible to TAI. Our main results were that when we compared patients with controls, patients, regardless of TBI severity, showed significantly reduced mean FA in almost all ROI measured. We found statistically significant correlation between FA metrics and some demographic, clinical, and conventional imaging characteristics. Additionally, these FA metrics were highly associated with outcome assessed at hospital discharge and at 6 and 12 months after TBI. We conclude that FA reduction in the subacute stage after TBI assessed by DTI may be a useful prognostic factor for long-term unfavorable outcome.

In vivo characterization of cortical and white matter neuroaxonal pathology in early multiple sclerosis.

Neuroaxonal pathology is a main determinant of disease progression in multiple sclerosis; however, its underlying pathophysiological mechanisms, including its link to inflammatory demyelination and temporal occurrence in the disease course are still unknown. We used ultra-high field (7 T), ultra-high gradient strength diffusion and T1/T2-weighted myelin-sensitive magnetic resonance imaging to characterize microstructural changes in myelin and neuroaxonal integrity in the cortex and white matter in early stage multiple sclerosis, their distribution in lesional and normal-appearing tissue, and their correlations with neurological disability. Twenty-six early stage multiple sclerosis subjects (disease duration ≤5 years) and 24 age-matched healthy controls underwent 7 T T2*-weighted imaging for cortical lesion segmentation and 3 T T1/T2-weighted myelin-sensitive imaging and neurite orientation dispersion and density imaging for assessing microstructural myelin, axonal and dendrite integrity in lesional and normal-appearing tissue of the cortex and the white matter. Conventional mean diffusivity and fractional anisotropy metrics were also assessed for comparison. Cortical lesions were identified in 92% of early multiple sclerosis subjects and they were characterized by lower intracellular volume fraction (P = 0.015 by paired t-test), lower myelin-sensitive contrast (P = 0.030 by related-samples Wilcoxon signed-rank test) and higher mean diffusivity (P = 0.022 by related-samples Wilcoxon signed-rank test) relative to the contralateral normal-appearing cortex. Similar findings were observed in white matter lesions relative to normal-appearing white matter (all P < 0.001), accompanied by an increased orientation dispersion (P < 0.001 by paired t-test) and lower fractional anisotropy (P < 0.001 by related-samples Wilcoxon signed-rank test) suggestive of less coherent underlying fibre orientation. Additionally, the normal-appearing white matter in multiple sclerosis subjects had diffusely lower intracellular volume fractions than the white matter in controls (P = 0.029 by unpaired t-test). Cortical thickness did not differ significantly between multiple sclerosis subjects and controls. Higher orientation dispersion in the left primary motor-somatosensory cortex was associated with increased Expanded Disability Status Scale scores in surface-based general linear modelling (P < 0.05). Microstructural pathology was frequent in early multiple sclerosis, and present mainly focally in cortical lesions, whereas more diffusely in white matter. These results suggest early demyelination with loss of cells and/or cell volumes in cortical and white matter lesions, with additional axonal dispersion in white matter lesions. In the cortex, focal lesion changes might precede diffuse atrophy with cortical thinning. Findings in the normal-appearing white matter reveal early axonal pathology outside inflammatory demyelinating lesions.

White matter microstructure predicts cognitive training-induced improvements in attention and executive functioning in schizophrenia

We examined the relationship between white matter microstructure in schizophrenia using diffusion tensor imaging (DTI) and cognitive improvements induced by 70h (~16weeks) of cognitive training. We measured anatomical connectivity in 48 patients with schizophrenia (SZ) and 28 healthy control participants (HC) at baseline, and then examined the relationship between anatomical connectivity at baseline and training-induced cognitive gains in 30 SZ who performed diffusion imaging after completing 70h of training. Compared with healthy control participants, individuals with schizophrenia showed reduced white matter integrity at baseline, as indexed by fractional anisotropy metrics, in bilateral posterior corona radiata, bilateral retrolenticular internal capsules, bilateral posterior thalamic radiation, left anterior corona radiata, left superior longitudinal fasciculus, left sagittal stratum, right cerebral peduncle and the genu and splenium of the corpus callosum. After training, schizophrenia participants showed significant gains in attention/vigilance, speed of processing, verbal learning, visual learning and executive functioning. White matter integrity within the right fronto-occipital fasciculus predicted training-induced improvements in attention/vigilance, while white matter integrity within the right corticospinal tract and bilateral medial lemnisci predicted cognitive training-induced improvements in executive functioning, areas that did not show white matter tract deficits at baseline. These findings suggest that preserved white matter integrity connecting long-range prefrontal-thalamic-sensorimotor areas may be an important determinant for training-induced neurocognitive plasticity.

Local Fractional Anisotropy Is Reduced in Areas with Tumor Recurrence in Glioblastoma

Purpose To analyze if fractional anisotropy (FA) in nonenhancing peritumoral regions (NEPTRs) at baseline is associated with later tumor recurrence in glioblastoma. Materials and Methods Ethical approval was obtained for this retrospective, HIPAA-compliant study. FA was measured in 70 patients with glioblastoma in five regions of interest (ROIs) per patient in the NEPTR at preoperative magnetic resonance (MR) imaging with (166 regions) or without (184 regions) local contrast-enhancing tumor recurrence at follow-up MR imaging (median, 7.3 months; range, 0.9-46.6 months). ROIs were classified according to their location (white matter, cortex, fiber tracts, basal ganglia). Ratio of FA in the ROI of the NEPTR to that in the contralateral side (FAcontra) and to that in the internal capsule (FAint) was calculated. A generalized linear mixed model was performed. Ten-fold cross-validation was used for the receiver operating characteristics (ROC) analysis. Results FAcontra and FAint were significantly lower in regions with later tumor recurrence than in regions without (median FAcontra: 0.29 [interquartile range {IR}, 0.22-0.36] vs 0.46 [IR, 0.38-0.57]; median FAint: 0.20 [IR, 0.16-0.24] vs 0.29 [IR, 0.22-0.36], respectively). ROC analysis revealed an area under the ROC curve of 0.893 for FAcontra and of 0.815 for FAint, resulting in respective sensitivity and specificity of 85.5% and 84.2% for FAcontra and 86.7% and 66.8% for FAint. Conclusion Local tumor recurrence in the NEPTR may be predicted by FA metrics at baseline in patients with glioblastoma. This might be important for surgery or radiation planning. © RSNA, 2016 Online supplemental material is available for this article.

Assessing a standardised approach to measuring corticospinal integrity after stroke with DTI

The structural integrity of the corticospinal tract (CST) after stroke is closely linked to the degree of motor impairment. Simple and reliable methods of assessing white matter integrity within the CST would facilitate the use of this measure in routine clinical practice. Commonly, diffusion tensor imaging is used to measure voxel-wise fractional anisotropy (FA) in a variety of regions of interest (ROIs) representing the CST. Several methods are currently in use with no consensus about which approach is best. ROIs are usually either the whole CST or the posterior limb of the internal capsule (PLIC). These are created manually on brain images or with reference to an individual's CST determined by tractography. Once the ROI has been defined, the FA can be reported as an absolute measure from the ipsilesional side or as a ratio in comparison to the contralesional side. Both corticospinal tracking and manual ROI definition in individual stroke patients are time consuming and subject to bias. Here, we investigated whether using a CST template derived from healthy volunteers was a feasible method for defining the appropriate ROI within which to measure changes in FA. We reconstructed the CST connecting the primary motor cortex to the ipsilateral pons in 23 age-matched control subjects and 21 stroke patients. An average healthy CST template was created from the 23 control subjects. For each patient, FA values were then calculated for both the template CST and for their own CST. We compared patients' FA metrics between the two tracts by considering four measures (FA in the ipsilesional side, FA in the contralesional side, FA ratio of the ipsilesional side to the contralesional side and FA asymmetry between the two sides) and in two tract-based ROIs (whole tract and tract section traversing the PLIC). There were no significant differences in FA metrics for either method, except for contralesional FA. Furthermore, we found that FA metrics relating to CST damage all correlated with motor ability post-stroke equally well. These results suggest that the healthy CST template could be a surrogate structure for defining tract-based ROIs with which to measure stroke patients' FA metrics, avoiding the necessity for CST tracking in individual patients. CST template-based automated quantification of structural integrity would greatly facilitate implementation of practical clinical applications of diffusion tensor imaging.

Diffusion tensor imaging tractography parameters of limbic system bundles in temporal lobe epilepsy patients

To investigate changes in diffusion tensor imaging (DTI) measures in limbic system white matter of patients with temporal lobe epilepsy (TLE) using diffusion tensor tractography. DTI metrics including fractional anisotropy (FA), λ1, λ2, λ3, and trace (Tr) coefficients were obtained from tractography for bilateral fornix, superior and inferior cingulum fibers in 18 patients and 10 healthy controls. Hippocampal signal-to-noise ratio (SNR) quantitative analysis was performed in order to confirm the magnetic resonance imaging (MRI) hippocampal lesion presence or absence in TLE patients. Nine patients presented unilateral hippocampal sclerosis (TLE+HS) and nine patients had no signal abnormalities on conventional MRI (TLE-HS). On the ipsilateral seizure side, all three investigated tracts showed significant DTI indices abnormalities in both patient groups when compared with controls, most marked on the inferior cingulum. Contralateral to the seizure side, the three tracts presented significant DTI parameters in only the TLE+HS group when compared with controls. The DTI abnormalities found in the TLE-HS group may suggest that in the inferior cingulum the structural integrity is more affected than in the fornix or superior cingulum white matter bundles. The eigenvalues taken separately add complementary information to the FA and Tr metrics and may be useful indices in better understanding the architectural reorganization of limbic system tracts in TLE patients without HS.

Diffusion tensor quantification of the human midsagittal corpus callosum subdivisions across the lifespan

The midsagittal corpus callosum (CC) cross-sectional area subdivisions have been used as early and sensitive markers of human brain white matter connectivity, development, natural aging and disease. Despite the simplicity and conspicuity of the appearance of the CC on anatomical magnetic resonance imaging (MRI), the published quantitative MRI literature on its regional sex and age trajectories are contradictory. The availability of noninvasive quantitative methods to assess the CC regions across the human lifespan would help clarify its contribution to behavior and cognition. In this report, we extended the utility of a recently described semi-automated diffusion tensor imaging (DTI) tissue segmentation method to utilize the high orientation contrast of the CC on DTI. Using optimized DTI methods on a cohort of 121 right-handed children and adults aged 6–68 years, we examined the CC areas and corresponding DTI metrics of the different functionally specialized sectors of the CC. Both the area and fractional anisotropy metrics followed inverted U-shaped curves, while the mean and radial diffusivities followed U-curves reflecting white matter progressive and regressive myelination dynamics that continue into young adulthood.