Faculty Bibliography

Concentration of the neuronal marker, N-acetylaspartate (NAA), a quantitative metric for the health and density of neurons, is currently obtained by integration of the manually defined peak in whole-head proton (1 H)-MRS. Our goal was to develop a full spectral modeling approach for the automatic estimation of the whole-brain NAA concentration (WBNAA) and to compare the performance of this approach with a manual frequency-range peak integration approach previously employed. MRI and whole-head 1 H-MRS from 18 healthy young adults were examined. Non-localized, whole-head 1 H-MRS obtained at 3 T yielded the NAA peak area through both manually defined frequency-range integration and the new, full spectral simulation. The NAA peak area was converted into an absolute amount with phantom replacement and normalized for brain volume (segmented from T1 -weighted MRI) to yield WBNAA. A paired-sample t test was used to compare the means of the WBNAA paradigms and a likelihood ratio test used to compare their coefficients of variation. While the between-subject WBNAA means were nearly identical (12.8 +/- 2.5 mm for integration, 12.8 +/- 1.4 mm for spectral modeling), the latter's standard deviation was significantly smaller (by ~50%, p = 0.026). The within-subject variability was 11.7% (+/-1.3 mm) for integration versus 7.0% (+/-0.8 mm) for spectral modeling, i.e., a 40% improvement. The (quantifiable) quality of the modeling approach was high, as reflected by Cramer-Rao lower bounds below 0.1% and vanishingly small (experimental - fitted) residuals. Modeling of the whole-head 1 H-MRS increases WBNAA quantification reliability by reducing its variability, its susceptibility to operator bias and baseline roll, and by providing quality-control feedback. Together, these enhance the usefulness of the technique for monitoring the diffuse progression and treatment response of neurological disorders

OBJECTIVE: The purpose of this study was to develop an algorithm incorporating MRI metrics to classify patients with mild traumatic brain injury (mTBI) and controls. METHODS: This was an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant prospective study. We recruited patients with mTBI and healthy controls through the emergency department and general population. We acquired data on a 3.0T Siemens Trio magnet including conventional brain imaging, resting-state fMRI, diffusion-weighted imaging, and magnetic field correlation (MFC), and performed multifeature analysis using the following MRI metrics: mean kurtosis (MK) of thalamus, MFC of thalamus and frontal white matter, thalamocortical resting-state networks, and 5 regional gray matter and white matter volumes including the anterior cingulum and left frontal and temporal poles. Feature selection was performed using minimal-redundancy maximal-relevance. We used classifiers including support vector machine, naive Bayesian, Bayesian network, radial basis network, and multilayer perceptron to test maximal accuracy. RESULTS: We studied 24 patients with mTBI and 26 controls. Best single-feature classification uses thalamic MK yielding 74% accuracy. Multifeature analysis yields 80% accuracy using the full feature set, and up to 86% accuracy using minimal-redundancy maximal-relevance feature selection (MK thalamus, right anterior cingulate volume, thalamic thickness, thalamocortical resting-state network, thalamic microscopic MFC, and sex). CONCLUSION: Multifeature analysis using diffusion-weighted imaging, MFC, fMRI, and volumetrics may aid in the classification of patients with mTBI compared with controls based on optimal feature selection and classification methods. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that classification algorithms using multiple MRI features accurately identifies patients with mTBI as defined by American Congress of Rehabilitation Medicine criteria compared with healthy controls.

PURPOSE: To examine thalamic and cortical injuries using fractional amplitude of low-frequency fluctuations (fALFFs) and functional connectivity MRI (fcMRI) based on resting state (RS) and task-related fMRI in patients with mild traumatic brain injury (MTBI). MATERIALS AND METHODS: Twenty-seven patients and 27 age-matched controls were recruited. The 3 Tesla fMRI at RS and finger tapping task were used to assess fALFF and fcMRI patterns. fALFFs were computed with filtering (0.01-0.08 Hz) and scaling after preprocessing. fcMRI was performed using a standard seed-based correlation method, and delayed fcMRI (coherence) in frequency domain were also performed between thalamus and cortex. RESULTS: In comparison with controls, MTBI patients exhibited significantly decreased fALFFs in the thalamus (and frontal/temporal subsegments) and cortical frontal and temporal lobes; as well as decreased thalamo-thalamo and thalamo-frontal/ thalamo-temporal fcMRI at rest based on RS-fMRI (corrected P < 0.05). This thalamic and cortical disruption also existed at task-related condition in patients. CONCLUSION: The decreased fALFFs (i.e., lower neuronal activity) in the thalamus and its segments provide additional evidence of thalamic injury in patients with MTBI. Our findings of fALFFs and fcMRI changes during motor task and resting state may offer insights into the underlying cause and primary location of disrupted thalamo-cortical networks after MTBI. J. Magn. Reson. Imaging 2013. (c) 2013 Wiley Periodicals, Inc.

Abstract Mild traumatic brain injury (mTBI), although often presenting without the gross structural abnormalities seen in more severe forms of brain trauma, can nonetheless result in lingering cognitive and behavioral problems along with subtle alterations in brain structure and function. Repeated injuries are associated with brain atrophy and dementia in the form of chronic traumatic encephalopathy (CTE). The mechanisms underlying these dysfunctions are poorly understood. There is a growing body of evidence that brain iron is abnormal after TBI, and brain iron has also been implicated in a host of neurodegenerative disorders. The purpose of this article is to review evidence about the function of iron in the pathophysiology of mTBI and the role that advanced imaging modalities can play in further elucidating said function. MRI techniques sensitive to field inhomogeneities provide supporting evidence for both deep gray matter non-heme iron accumulation as well as focal microhemorrhage resulting from mTBI. In addition, there is evidence that iron may contribute to pathology after mTBI through a number of mechanisms, including generation of reactive oxygen species (ROS), exacerbation of oxidative stress from other sources, and encouragement of tau phosphorylation and the formation of neurofibrillary tangles. Finally, recent animal studies suggest that iron may serve as a therapeutic target in mitigating the effects of mTBI. However, research on the presence and role of iron in mTBI and CTE is still relatively sparse, and further work is necessary to elucidate issues such as the sources of increased iron and the chain of secondary injury.

OBJECTIVE: To obtain quantitative neurometabolite measurements, specifically myoinositol (mI) and glutamate plus glutamine (Glx), markers of glial and neuronal excitation, in deep gray matter structures after mild traumatic brain injury (mTBI) using proton magnetic resonance spectroscopy (1H-MRS) and to compare these measurements against normal healthy control subjects. METHODS: This study approved by the institutional review board is Health Insurance Portability and Accountability Act compliant. T1-weighted MRI and multi-voxel 1H-MRS imaging were acquired at 3 tesla from 26 patients with mTBI an average of 22 days postinjury and from 13 age-matched healthy controls. Two-way analysis of variance was used to compare patients and controls for mean N-acetylaspartate, choline, creatine (Cr), Glx, and mI levels as well as the respective ratios to Cr within the caudate, globus pallidus, putamen, and thalamus. RESULTS: Quantitative putaminal mI was higher in patients with mTBI compared with controls (p = 0.02). Quantitative neurometabolite ratios of putaminal mI and Glx relative to Cr, mI/Cr, and Glx/Cr were also higher among patients with mTBI compared with controls (p = 0.01 and 0.02, respectively). No other differences in neurometabolite levels or ratios were observed in any other brain region evaluated. CONCLUSION: Increased putaminal mI, mI/Cr, and Glx/Cr in patients after mTBI compared with control subjects supports the notion of a complex glial and excitatory response to injury without concomitant neuronal loss, evidenced by preserved N-acetylaspartate levels in this region.

Objective. To compare periventricular lesions in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOsd). Materials and Methods. Sagittal and axial fluid attenuated inversion recovery (FLAIR) sequences of 20 NMOsd and 40 group frequency-matched MS patients were evaluated by two neuroradiologists. On axial FLAIR, periventricular area was characterized as free of lesions/smooth-bordered ("type A") or jagged-bordered ("type B") pattern. On sagittal FLAIR, the images were evaluated for presence of "Dawson's fingers." Results. Type A pattern was observed in 80% of NMOsd patients by Reader 1 and 85% by Reader 2 but only in 5% MS patients by either Reader. Type B was seen in 15% NMOsd patients by Reader 1 and 20% by Reader 2 and in 95% MS patients by either Reader. Dawson's fingers were observed in no NMOsd patients by Reader 1 and 5% by Reader 2. In MS, Dawson's fingers were seen in 92.5% patients by Reader 1 and 77.5% by Reader 2. The differences in periventricular patterns and Dawson's finger detection between NMOsd and MS were highly significant (P < 0.001). Conclusions. Dawson's fingers and "jagged-bordered" periventricular hyperintensities are typical of MS and almost never seen in NMOsd, which suggests a practical method for differentiating the two diseases.