Dataset Information

Whole brain approaches for identification of microstructural abnormalities in individual patients: comparison of techniques applied to mild traumatic brain injury.

ABSTRACT:

Purpose

Group-wise analyses of DTI in mTBI have demonstrated evidence of traumatic axonal injury (TAI), associated with adverse clinical outcomes. Although mTBI is likely to have a unique spatial pattern in each patient, group analyses implicitly assume that location of injury will be the same across patients. The purpose of this study was to optimize and validate a procedure for analysis of DTI images acquired in individual patients, which could detect inter-individual differences and be applied in the clinical setting, where patients must be assessed as individuals.

Materials and methods

After informed consent and in compliance with HIPAA, 34 mTBI patients and 42 normal subjects underwent 3.0 Tesla DTI. Four voxelwise assessment methods (standard Z-score, "one vs. many" t-test, Family-Wise Error Rate control using pseudo t-distribution, EZ-MAP) for use in individual patients, were applied to each patient's fractional anisotropy (FA) maps and tested for its ability to discriminate patients from controls. Receiver Operating Characteristic (ROC) analyses were used to define optimal thresholds (voxel-level significance and spatial extent) for reliable and robust detection of mTBI pathology.

Results

ROC analyses showed EZ-MAP (specificity 71%, sensitivity 71%), "one vs. many" t-test and standard Z-score (sensitivity 65%, specificity 76% for both methods) resulted in a significant area under the curve (AUC) score for discriminating mTBI patients from controls in terms of the total number of abnormal white matter voxels detected while the FWER test was not significant. EZ-MAP is demonstrated to be robust to assumptions of Gaussian behavior and may serve as an alternative to methods that require strict Gaussian assumptions.

Conclusion

EZ-MAP provides a robust approach for delineation of regional abnormal anisotropy in individual mTBI patients.

SUBMITTER: Kim N

PROVIDER: S-EPMC3608654 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

Whole brain approaches for identification of microstructural abnormalities in individual patients: comparison of techniques applied to mild traumatic brain injury.

Kim Namhee N Branch Craig A CA Kim Mimi M Lipton Michael L ML

PloS one 20130326 3

<h4>Purpose</h4>Group-wise analyses of DTI in mTBI have demonstrated evidence of traumatic axonal injury (TAI), associated with adverse clinical outcomes. Although mTBI is likely to have a unique spatial pattern in each patient, group analyses implicitly assume that location of injury will be the same across patients. The purpose of this study was to optimize and validate a procedure for analysis of DTI images acquired in individual patients, which could detect inter-individual differences and b ...[more]

PMID: 23555665

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Project description:BACKGROUND:Diffusion Tensor Imaging (DTI) studies of traumatic brain injury (TBI) have focused on alterations in microstructural features of deep white matter fibers (DWM), though post-mortem studies have demonstrated that injured axons are often observed at the gray-white matter interface where superficial white matter fibers (SWM) mediate local connectivity. OBJECTIVES:To examine microstructural alterations in SWM and DWM in youths with a history of mild TBI and examine the relationship between white matter alterations and attention. METHODS:Using DTIDWM fractional anisotropy (FA) and SWM FA in youths with mild TBI (TBI, n=63) were compared to typically developing and psychopathology matched control groups (n=63 each). Following tract-based spatial statistics, SWM FA was assessed by applying a probabilistic tractography derived SWM mask, and DWM FA was captured with a white matter fiber tract mask. Voxel-wise z-score calculations were used to derive a count of voxels with abnormally high and low FA for each participant. Analyses examined DWM and SWM FA differences between TBI and control groups, the relationship between attention and DWM and SWM FA and the relative susceptibility of SWM compared to DWM FA to alterations associated with mild TBI. RESULTS:Case-based comparisons revealed more voxels with low FA and fewer voxels with high FA in SWM in youths with mild TBI compared to both control groups. Equivalent comparisons in DWM revealed a similar pattern of results, however, no group differences for low FA in DWM were found between mild TBI and the control group with matched psychopathology. Slower processing speed on the attention task was correlated with the number of voxels with low FA in SWM in youths with mild TBI. CONCLUSIONS:Within a sample of youths with a history of mild TBI, this study identified abnormalities in SWM microstructure associated with processing speed. The majority of DTI studies of TBI have focused on long-range DWM fiber tracts, often overlooking the SWM fiber type.

Project description:The underlying pathophysiology of paediatric mild traumatic brain injury and the time-course for biological recovery remains widely debated, with clinical care principally informed by subjective self-report. Similarly, clinical evidence indicates that adolescence is a risk factor for prolonged recovery, but the impact of age-at-injury on biomarkers has not been determined in large, homogeneous samples. The current study collected diffusion MRI data in consecutively recruited patients (n = 203; 8-18 years old) and age and sex-matched healthy controls (n = 170) in a prospective cohort design. Patients were evaluated subacutely (1-11 days post-injury) as well as at 4 months post-injury (early chronic phase). Healthy participants were evaluated at similar times to control for neurodevelopment and practice effects. Clinical findings indicated persistent symptoms at 4 months for a significant minority of patients (22%), along with residual executive dysfunction and verbal memory deficits. Results indicated increased fractional anisotropy and reduced mean diffusivity for patients, with abnormalities persisting up to 4 months post-injury. Multicompartmental geometric models indicated that estimates of intracellular volume fractions were increased in patients, whereas estimates of free water fractions were decreased. Critically, unique areas of white matter pathology (increased free water fractions or increased neurite dispersion) were observed when standard assumptions regarding parallel diffusivity were altered in multicompartmental models to be more biologically plausible. Cross-validation analyses indicated that some diffusion findings were more reproducible when ∼70% of the total sample (142 patients, 119 controls) were used in analyses, highlighting the need for large-sample sizes to detect abnormalities. Supervised machine learning approaches (random forests) indicated that diffusion abnormalities increased overall diagnostic accuracy (patients versus controls) by ∼10% after controlling for current clinical gold standards, with each diffusion metric accounting for only a few unique percentage points. In summary, current results suggest that novel multicompartmental models are more sensitive to paediatric mild traumatic brain injury pathology, and that this sensitivity is increased when using parameters that more accurately reflect diffusion in healthy tissue. Results also indicate that diffusion data may be insufficient to achieve a high degree of objective diagnostic accuracy in patients when used in isolation, which is to be expected given known heterogeneities in pathophysiology, mechanism of injury and even criteria for diagnoses. Finally, current results indicate ongoing clinical and physiological recovery at 4 months post-injury.

Project description:Blast-related traumatic brain injury (TBI) has been a common injury among returning troops due to the widespread use of improvised explosive devices in the Iraq and Afghanistan Wars. As most of the TBIs sustained are in the mild range, brain changes may not be detected by standard clinical imaging techniques such as CT. Furthermore, the functional significance of these types of injuries is currently being debated. However, accumulating evidence suggests that diffusion tensor imaging (DTI) is sensitive to subtle white matter abnormalities and may be especially useful in detecting mild TBI (mTBI). The primary aim of this study was to use DTI to characterize the nature of white matter abnormalities following blast-related mTBI, and in particular, examine the extent to which mTBI-related white matter abnormalities are region-specific or spatially heterogeneous. In addition, we examined whether mTBI with loss of consciousness (LOC) was associated with more extensive white matter abnormality than mTBI without LOC, as well as the potential moderating effect of number of blast exposures. A second aim was to examine the relationship between white matter integrity and neurocognitive function. Finally, a third aim was to examine the contribution of PTSD symptom severity to observed white matter alterations. One hundred fourteen OEF/OIF veterans underwent DTI and neuropsychological examination and were divided into three groups including a control group, blast-related mTBI without LOC (mTBI - LOC) group, and blast-related mTBI with LOC (mTBI + LOC) group. Hierarchical regression models were used to examine the extent to which mTBI and PTSD predicted white matter abnormalities using two approaches: 1) a region-specific analysis and 2) a measure of spatial heterogeneity. Neurocognitive composite scores were calculated for executive functions, attention, memory, and psychomotor speed. Results showed that blast-related mTBI + LOC was associated with greater odds of having spatially heterogeneous white matter abnormalities. Region-specific reduction in fractional anisotropy (FA) in the left retrolenticular part of the internal capsule was observed in the mTBI + LOC group as the number of blast exposures increased. A mediation analysis revealed that mTBI + LOC indirectly influenced verbal memory performance through its effect on white matter integrity. PTSD was not associated with spatially heterogeneous white matter abnormalities. However, there was a suggestion that at higher levels of PTSD symptom severity, LOC was associated with reduced FA in the left retrolenticular part of the internal capsule. These results support postmortem reports of diffuse axonal injury following mTBI and suggest that injuries with LOC involvement may be particularly detrimental to white matter integrity. Furthermore, these results suggest that LOC-associated white matter abnormalities in turn influence neurocognitive function.

Project description:Dynamic Functional Connectivity (DFC) analysis is a promising approach for the characterization of brain electrophysiological activity. In this study, we investigated abnormal alterations due to mild Traumatic Brain Injury (mTBI) using DFC of the source reconstructed magnetoencephalographic (MEG) resting-state recordings. Brain activity in several well-known frequency bands was first reconstructed using beamforming of the MEG data to determine ninety anatomical brain regions of interest. A DFC graph was formulated using the imaginary part of phase-locking values, which were obtained from 30 mTBI patients and 50 healthy controls (HC). Subsequently, we estimated normalized Laplacian transformations of individual, statistically and topologically filtered quasi-static graphs. The corresponding eigenvalues of each node synchronization were then computed and through the neural-gas algorithm, we quantized the evolution of the eigenvalues resulting in distinct network microstates (NMstates). The discrimination level between the two groups was assessed using an iterative cross-validation classification scheme with features either the NMstates in each frequency band, or the combination of the so-called chronnectomics (flexibility index, occupancy time of NMstate, and Dwell time) with the complexity index over the evolution of the NMstates across all frequency bands. Classification performance based on chronnectomics showed 80% accuracy, 99% sensitivity, and 49% specificity. However, performance was much higher (accuracy: 91-97%, sensitivity: 100%, and specificity: 77-93%) when focusing on the microstates. Exploring the mean node degree within and between brain anatomical networks (default mode network, frontoparietal, occipital, cingulo-opercular, and sensorimotor), a reduced pattern occurred from lower to higher frequency bands, with statistically significant stronger degrees for the HC than the mTBI group. A higher entropic profile on the temporal evolution of the modularity index was observed for both NMstates for the mTBI group across frequencies. A significant difference in the flexibility index was observed between the two groups for the ? frequency band. The latter finding may support a central role of the thalamus impairment in mTBI. The current study considers a complete set of frequency-dependent connectomic markers of mTBI-caused alterations in brain connectivity that potentially could serve as markers to assess the return of an injured subject back to normality.

Dataset Information

Whole brain approaches for identification of microstructural abnormalities in individual patients: comparison of techniques applied to mild traumatic brain injury.

Purpose

Materials and methods

Results

Conclusion

Publications

Whole brain approaches for identification of microstructural abnormalities in individual patients: comparison of techniques applied to mild traumatic brain injury.

Similar Datasets

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