John D. Carew

Hierarchical clustering to measure connectivity in fMRI resting-state data

Low frequency oscillations, which are temporally correlated in functionally related brain regions, characterize the mammalian brain, even when no explicit cognitive tasks are performed. Functional connectivity MR imaging is used to map regions of the resting brain showing synchronous, regional and slow fluctuations in cerebral blood flow and oxygenation. In this study, we use a hierarchical clustering method to detect similarities of low-frequency fluctuations. We describe one measure of correlations in the low frequency range for classification of resting-state fMRI data. Furthermore, we investigate the contribution of motion and hardware instabilities to resting-state correlations and provide a method to reduce artifacts. For all cortical regions studied and clusters obtained, we quantify the degree of contamination of functional connectivity maps by the respiratory and cardiac cycle. Results indicate that patterns of functional connectivity can be obtained with hierarchical clustering that resemble known neuronal connections. The corresponding voxel time series do not show significant correlations in the respiratory or cardiac frequency band.

Diffusion tensor MRI in temporal lobe epilepsy

The purpose of this study was to investigate the diffusion characteristics of white matter in patients with focal temporal lobe epilepsy (TLE). Diffusion tensor imaging (DTI) was applied to patients and normal controls. Rotationally invariant mean diffusivity and diffusion anisotropy maps were calculated for all subjects. Comparisons between the two groups were performed for several white matter structures. Mean diffusivity and diffusion anisotropy of each selected structure were tested for correlations with age at onset and duration of epilepsy. Significantly lower diffusion anisotropy, and higher diffusivity in directions perpendicular to the axons, was detected in several white matter structures of the patients when compared to the controls. These structures were not located in the temporal lobes. No significant difference in mean diffusivity was detected between the selected structures from the two groups. Diffusion anisotropy was significantly correlated with age at onset of epilepsy in the posterior corpus callosum. Duration of epilepsy was not significantly correlated with the diffusion indices from any of the selected structures. The results of this study suggest that diffusion anisotropy may reveal abnormalities in patients with focal TLE. In addition, these abnormal changes are not necessarily restricted to the temporal lobes but might extend in other brain regions as well. Furthermore, the age at onset of epilepsy may be an important factor in determining the extent of the effect of epilepsy on white matter.

Diagnostic value of high-resolution MR imaging in giant cell arteritis.

BACKGROUND AND PURPOSE: Clinical indications of giant cell arteritis may be unspecific, and noninvasive diagnosis is often difficult. This study investigated the hypothesis that high-resolution MR imaging of the superficial cranial arteries is a noninvasive imaging technique that can detect the occurrence of giant cell arteritis. MATERIALS AND METHODS: Contrast-enhanced, high-resolution MR imaging was performed on 64 consecutive patients with suspected giant cell arteritis. Mural thickness, lumen diameter, and a mural contrast enhancement score were assessed with T1-weighted spin-echo images with submillimeter in-plane spatial resolution. The final rheumatologists diagnosis according to the clinical criteria of the American College of Rheumatology including laboratory tests and results of temporal artery biopsies from 32 patients was used as a “gold standard” for the evaluation of the MR imaging findings. RESULTS: All of the examinations provided diagnostic image quality. Evaluation of the mural inflammatory MR imaging signs for diagnosing vasculitis resulted in a sensitivity of 80.6% and a specificity of 97.0%. In comparison, histology results alone showed a sensitivity of 77.8% and specificity of 100%. The mean wall thickness increased significantly from 0.39 mm (±0.18 mm) to 0.74 mm (±0.32 mm; P < .001), and the lumen diameter decreased significantly from 0.84 mm (±0.29 mm) to 0.65 mm (±0.38 mm; P < .05) for patients with giant cell arteritis. CONCLUSION: Contrast-enhanced, high-resolution MR imaging allows noninvasive assessment of mural inflammation in giant cell arteritis with good diagnostic certainty. Measures of mural thickening and contrast enhancement can be obtained in these small vessels and provide valuable vasculitic MR imaging findings.

Utility of axial and radial diffusivity from diffusion tensor MRI as markers of neurodegeneration in amyotrophic lateral sclerosis.

OBJECTIVE To investigate changes in the diffusion tensor imaging measures, axial diffusivity and radial diffusivity, in addition to the more commonly used fractional anisotropy and mean diffusivity, in patients with amyotrophic lateral sclerosis (ALS) using the voxel-based statistical analysis tool, tract based spatial statistics. METHODS We studied 12 patients with ALS and 19 normal controls using diffusion tensor imaging; tract based spatial statistics was applied to study changes in fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity values in brain white matter tracts. ALS patients were evaluated using clinical examination, administration of the revised ALS functional rating scale and measurement of the forced vital capacity. RESULTS In ALS patients, we found significant increases in axial diffusivity, radial diffusivity, and mean diffusivity and significant decreases in fractional anisotropy. Increases in axial diffusivity and radial diffusivity were more widespread and more prominent in the corticospinal tract than the decreases in fractional anisotropy. The decreases in fractional anisotropy were evident only in the corona radiata and genu of the corpus callosum. CONCLUSION In ALS, axial diffusivity and radial diffusivity may be useful diffusion tensor imaging-derived indices to consider in addition to fractional anisotropy and mean diffusivity to aid in demonstrating neurodegenerative changes.

Decreased incidence of NSF in patients on dialysis after changing gadolinium contrast-enhanced MRI protocols.

To retrospectively determine the incidence of nephrogenic systemic fibrosis (NSF) in patients on dialysis administered either a lower dose high‐relaxivity linear gadolinium‐chelate, gadobenate dimeglumine (MultiHance, MH), compared to a standard dose linear gadolinium chelate, gadodiamide (Omniscan, OM).

Investigation of anomalous estimates of tensor-derived quantities in diffusion tensor imaging.

The diffusion tensor is typically assumed to be positive definite. However, noise in the measurements may cause the eigenvalues of the tensor estimate to be negative, thereby violating this assumption. Negative eigenvalues in diffusion tensor imaging (DTI) data occur predominately in regions of high anisotropy and may cause the fractional anisotropy (FA) to exceed unity. Two constrained least squares methods for eliminating negative eigenvalues are explored. These methods, the constrained linear least squares method (CLLS) and the constrained nonlinear least squares method (CNLS), are compared with other commonly used algebraic constrained methods. The CLLS tensor estimator can be shown to be equivalent to the linear least squares (LLS) tensor estimator when the LLS tensor estimate is positive definite. Similarly, the CNLS tensor estimator can be shown to be equivalent to the nonlinear least squares (NLS) tensor estimator when the NLS tensor estimate is positive definite. The constrained least squares methods for eliminating negative eigenvalues are evaluated with both simulations and in vivo human brain DTI data. Simulation results show that the CNLS method is, in terms of mean squared error for estimating trace and FA, the most effective method for correcting negative eigenvalues. Magn Reson Med, 2006. Published 2006 Wiley‐Liss, Inc.

Hemispheric asymmetry in supplementary motor area connectivity during unilateral finger movements.

Studies of unilateral finger movement in right-handed subjects have shown asymmetrical patterns of activation in primary motor cortex. Some studies have measured a similar asymmetry in the supplementary motor area (SMA), but others have not. To shed more light on the symmetry of function in the SMA, we used path analysis of functional MRI data to investigate effective connectivity during a unilateral finger movement task. We observed a slight asymmetry in task activation: left SMA was equally active during movement of either hand, while right SMA was more active for left-hand movement, suggesting a dominant role of left SMA. In addition, we tested for a corresponding asymmetry in the influence of SMA on sensorimotor cortex (SMC) using a path model based on the well-established principle that SMA is involved in motor control and SMC in execution. We observed that the influence of left SMA on left SMC increased during right-hand movement, and the influence of left SMA on right SMC increased during left-hand movement. However, there was no significant hand-dependent change in the influences of the right SMA. This asymmetry in connectivity implies that left SMA does play a dominant role in unilateral movements of either hand in right handers. The experiment also provides a basis for further studies of motor system connectivity in healthy or patient populations.

Independent component analysis applied to diffusion tensor MRI.

The accuracy of the outcome in a diffusion tensor imaging (DTI) experiment depends on the acquisition scheme as well as the postprocessing methods used. In the present study, the DTI results acquired after applying different combinations of diffusion‐weighted (DW) gradient orientations were initially compared. Then, spatially independent component analysis (ICA) was applied to the T2 and DW images. In all cases a single component was detected that was similar to the map of the trace of the diffusion tensor, but contained a reduced amount of noise. Furthermore, when no correction for eddy current artifacts was used in the image acquisition scheme, the effects of eddy currents were separated by ICA into independent components. After these components were removed, conventional estimation of the diffusion tensor was performed on the modified data. No artifact was contained in the final rotationally invariant scalar quantities that describe the intrinsic diffusion properties. Additionally, independent components that mapped major white matter fiber tracts in the human brain were identified. Finally, the noise included in the original T2 and DW images was also separated by ICA into independent components. These components were subsequently removed and a reduction of noise in the final DTI results was achieved. Magn Reson Med 47:354–363, 2002.

Cytokeratin 18, a marker of cell death, is increased in children with suspected nonalcoholic fatty liver disease.

Objectives: Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disease associated with obesity, and is now the most common liver disease in the United States. Cytokeratin 18 (CK18) is an intracellular protein released into the blood by both necrosis and apoptosis of hepatocytes. Levels of CK18 have not been reported previously in children with NAFLD. Methods: In a cross-sectional analysis of 62 children (28 normal weight, 14 obese, and 20 suspected NAFLD), we measured CK18 levels as well as alanine aminotransferase, fasting glucose, fasting insulin, and tumor necrosis factor-α. Results: CK18 was significantly elevated in the children with suspected NAFLD compared with obese controls and normal weight controls (median = 424 U/L compared with 243 and 214 respectively, P < 0.001). In multiple logistic regression analysis, CK18 was the best single predictor of suspected NAFLD (prediction accuracy = 84.1%). Conclusions: CK18 is elevated in children with suspected NAFLD and should be investigated as a potential diagnostic marker of NAFLD.

Optimal spline smoothing of fMRI time series by generalized cross-validation.

Linear parametric regression models of fMRI time series have correlated residuals. One approach to address this problem is to condition the autocorrelation structure by temporal smoothing. Smoothing splines with the degree of smoothing selected by generalized cross-validation (GCV-spline) provide a method to find an optimal smoother for an fMRI time series. The purpose of this study was to determine if GCV-spline of fMRI time series yields unbiased variance estimates of linear regression model parameters. GCV-spline was evaluated with a real fMRI data set and bias of the variance estimator was computed for simulated time series with autocorrelation structures derived from fMRI data. This study only considered fMRI experimental designs of boxcar type. The results from the real data suggest that GCV-spline determines appropriate amounts of smoothing. The simulations show that the variance estimates are, on average, unbiased. The unbiased variance estimates come at some cost to signal detection efficiency. This study demonstrates that GCV-spline is an appropriate method for smoothing fMRI time series.