Hypoglycemia with intensive insulin therapy after cardiac surgery: predisposing factors and association with mortality.

BACKGROUND: Intensive insulin therapy has become a major therapeutic target in cardiac surgery patients. It has been associated, however, with an increased risk of hypoglycemia compared with conventional insulin therapy. Our study sought to identify the factors predisposing to hypoglycemia with intensive insulin therapy and investigate its effect on early clinical outcomes after cardiac surgery. METHODS: A concurrent cohort study of 2,538 consecutive patients undergoing cardiac surgery (coronary artery bypass grafting, valve, or bypass grafting and valve surgery) from January 2005 to March 2010 was carried out. Multivariable logistic regression analysis and propensity score matching were used (1) to identify the risk factors for developing hypoglycemia (blood glucose < 60 mg/dL) after cardiac surgery and (2) to compare major morbidity, operative mortality, and actuarial survival between patients in whom hypoglycemia developed (n = 77) and those in whom it did not (n = 2461). The propensity score-adjusted sample included 61 patients in whom hypoglycemia developed and 305 patients in whom it did not (1 to 5 matching). RESULTS: Risk factors for hypoglycemia included female gender (odds ratio [OR] = 2.3, 95% confidence intervals [CI] = 1.4-3.7; P < .001), diabetes (OR = 2.8, CI = 1.7-4.5; P < .001), hemodialysis (OR = 3.0, CI = 1.3-6.8; P = .009), intraoperative blood product transfusion (OR = 2.0, CI = 1.2-3.4; P = .010), and earlier date of surgery (years of surgery, 2005-2007; OR = 2.1, CI = 1.2-3.7; P = .007) . Hypoglycemia increased the risk for operative mortality in univariate (hypoglycemic 10% vs normoglycemic patients 2%; P < .001) but not in propensity score- adjusted analysis (OR= 2.5, 0.9-6.7; P = .11). The propensity score-adjusted analysis demonstrated a significant increase in hemorrhage-related reexploration (P = .048), pneumonia (P < .001), reintubation (P < .001), prolonged ventilatory support (P < .001), hospital length of stay (P < .001), and intensive care unit length of stay (P < .001) for the hypoglycemic compared with normoglycemic patients. Five-year actuarial survival was similar in the compared patient groups (hypoglycemic 75% vs normoglycemic 75%; P = .22). CONCLUSIONS: Hypoglycemia with intensive insulin therapy is independently associated with increased risk for respiratory complications and prolonged hospital and intensive care unit lengths of stay after cardiac surgery. In our study, hypoglycemia was not independently associated with increased risk of death.

Magnetic resonance spectroscopy of the cervical cord in amyotrophic lateral sclerosis.

The objective of this study was to use magnetic resonance spectroscopy (MRS) to compare metabolite ratios in the cervical spinal cord of ALS patients to healthy controls. Fourteen ALS patients and 16 controls were scanned using a 3T scanner. A rectangular voxel (8 × 5 × 35 mm) was placed along the main axis of the cord with the lower limit at the inferior aspect of the C2 vertebral body. MRS was performed with a point-resolved spectroscopy (PRESS) sequence. Water signals were suppressed using a three-pulse chemical shift selective (CHESS) saturation sequence. Relative concentrations of choline (Cho), creatine (Cr), myo-inositol (Myo), and NAA were computed from metabolite peaks. Differences in metabolite ratios between ALS patients and controls were assessed with a Wilcoxon rank-sum test. The relationship of metabolite ratios to clinical measures (ALSFRS-R and FVC) was determined by Pearson correlation. The NAA/Cr and NAA/Myo ratios were reduced by 40% and 38%, respectively, in ALS patients. The reduction in NAA/Myo and NAA/Cho correlated significantly with FVC, with correlation coefficients of 0.66 and 0.60, respectively. In conclusion, MR spectra can reliably be obtained from the cervical spinal cord in ALS. MRS of the cervical cord may be a useful biomarker of disease progression.

Prospective study of cervical arthroplasty in 98 patients involved in 1 of 3 separate investigational device exemption studies from a single investigational site with a minimum 2-year follow-up. Clinical article.

OBJECT: Cervical total disc replacement (TDR) was developed to address some of the shortcomings associated with anterior cervical discectomy and fusion (ACDF) by preserving motion at the treated level. To establish an evidence-based rationale for cervical TDR to serve as a viable alternative to ACDF, cervical arthroplasty must establish equivalent or superior clinical outcomes while maintaining motion. The authors report on 98 patients from a single investigational site involved in 3 separate prospective, randomized, controlled investigational device exemption multicenter trials comparing cervical arthroplasty to ACDF with a 2-6-year follow-up. METHODS: Patients with 1- and 2-level cervical disc disease producing radiculopathy and/or myelopathy were randomized prospectively under 3 separate investigational device exemption pivotal trials to undergo ACDF with plate or artificial disc placement. The 3 arthroplasty systems evaluated were the Bryan cervical disc, Kineflex/C disc, and Discover cervical disc. The patients were evaluated with pre- and postoperative serial neurological examinations, radiographs, and clinical outcome indices at 1, 3, 6, 12, 24, 36, 48, and 60 months. RESULTS: Ninety-eight patients were treated at the authors' single investigational site. Fifty-seven of these patients underwent cervical arthroplasty and 41 underwent ACDF. A minimum 24-month follow-up was available for 90 patients (92%; 53 in the combined arthroplasty group and 37 in the combined ACDF group) with a follow-up duration ranging from 24 to 67 months (mean 38 months). Clinical success, defined as a composite measure consisting of 5 separate components, was significantly higher in the combined arthroplasty group (85%) compared with the combined ACDF group (70%; p = 0.035). The Neck Disability Index and visual analog scale patient self-report measures were evaluated at 3-24-months follow-up, and all groups showed excellent clinical outcomes. All groups (Bryan, Kineflex/C, Discover, and ACDF) showed statistically significant improvement from the preoperative period to a minimum 2-year follow-up (p < 0.0001). Overall, angular motion was improved by 0.91° in the combined arthroplasty group and reduced by 7.8° in the combined ACDF group (p < 0.0001). In the ACDF group there was a fusion rate of 97% (36 of 37 cases). In the arthroplasty group there was a 5.6% incidence of bridging heterotopic ossification (3 cases). There were a total of 4 reoperations (7.5%) in the combined arthroplasty group with 1 (1.9%) at the adjacent level. There were 3 reoperations (8.1%) in the ACDF group, all at the adjacent level. CONCLUSIONS: The prospective, intermediate-term (average follow-up > 3 years) results of cervical TDR at the authors' site are encouraging. Patients treated with the artificial discs showed significantly better clinical results, maintained motion at the treated level, and trended toward less adjacent-level disease.

Diffusion tensor imaging reveals regional differences in the cervical spinal cord in amyotrophic lateral sclerosis.

Therapeutic development in amyotrophic lateral sclerosis (ALS) is hampered by the lack of suitable biomarkers that might be sensitive to spatial and temporal patterns of neurodegeneration. Diffusion tensor imaging is a useful non-invasive tool that permits detection of microstructural tissue changes due, for example, to neurodegeneration. Even though the spinal cord bears the brunt of the disease process, diffusion tensor imaging has mainly been used to study white matter changes in the brain. The aim of this study was to examine the diffusion tensor imaging parameters of the cervical spinal cord (C1 through C6 segments) and brainstem (corticospinal tracts in the pyramids and pons) among ALS patients, to compare these to findings in age-matched healthy controls, and to correlate these differences with clinical measures of disease severity. Fractional anisotropy in the white matter of the cervical cord was 12% lower (p<0.01) in ALS patients (n=14) compared to age-matched healthy control subjects (n=15), and showed significant positive correlation with the average finger and foot tapping speed (r=0.61, p<0.05) in ALS patients. Radial diffusivity in the cervical cord was 15% higher (p<0.05) in ALS patients compared to healthy control subjects. Radial diffusivity in the white matter of the cervical cord was significantly correlated with clinical measures of disease severity such as forced vital capacity (FVC % predicted, r=-0.69, p<0.01), average finger and foot tapping speed from all four limbs (r=-0.59, p<0.05), and ALSFRS-R (r=-0.55, p<0.05) in ALS patients. There were no significant differences in mean diffusivity or axial diffusivity in the cervical spinal cord, or in any diffusion tensor imaging parameters measured in the brainstem. Analysis of diffusion tensor imaging parameters from individual cervical segments as well as profile plots along the length of the cervical cord showed larger differences in fractional anisotropy and radial diffusivity at more distal cervical segments, providing evidence that supports the "dying-back" hypothesis of neurodegeneration in ALS.

The effectiveness of locoregional therapies versus supportive care in maintaining survival within the Milan criteria in patients with hepatocellular carcinoma.

PURPOSE: To compare survival after treatment with either locoregional therapy (LRT) or supportive care in patients with hepatocellular carcinoma (HCC) within the Milan criteria. MATERIALS AND METHODS: Patients with HCC who were classified within the Milan criteria (solitary HCC

Adaptive smoothing of high angular resolution diffusion-weighted imaging data by generalized cross-validation improves Q-ball orientation distribution function reconstruction.

Q-ball imaging (QBI) is a high angular resolution diffusion-weighted imaging (HARDI) technique for reconstructing the orientation distribution function (ODF). Some form of smoothing or regularization is typically required in the ODF reconstruction from low signal-to-noise ratio HARDI data. The amount of smoothing or regularization is usually set a priori at the discretion of the investigator. In this article, we apply an adaptive and objective means of smoothing the raw HARDI data using the smoothing splines on the sphere method with generalized cross-validation (GCV) to estimate the diffusivity profile in each voxel. Subsequently, we reconstruct the ODF, from the smoothed data, based on the Funk-Radon transform (FRT) used in QBI. The spline method was applied to both simulated data and in vivo human brain data. Simulated data show that the smoothing splines on the sphere method with GCV smoothing reduces the mean squared error in estimates of the ODF as compared with the standard analytical QBI approach. The human data demonstrate the utility of the method for estimating smooth ODFs.

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.

PURPOSE: 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). MATERIALS AND METHODS: This study was Health Insurance Portability and Accountability Act (HIPAA)-compliant and Institutional Review Board (IRB)-approved. As per institution standardized contrast-enhanced magnetic resonance imaging (MRI) protocols, patients on dialysis were imaged using either MH, between 2/2007 to 9/2008, or OM between 10/2003 and 1/2007. Rates of NSF were compared using 95% score-based confidence intervals (CI). The Wilcoxon rank sum test was used to test similarity/difference between contrast doses given to each patient group. RESULTS: Overall, 312 patients on dialysis received OM and eight (2.6%) developed NSF (95% CI: 1.30%-4.98%). In all, 784 patients on dialysis received MH at a mean cumulative dose of 0.11 mmol/kg (0.05-0.75 mmol/kg) and no cases of NSF were identified (upper 95% confidence bound of 0.45%). The mean cumulative dose of OM was 0.16 mmol/kg (0.1-0.9 mmol/kg) for all patients and 0.28 mmol/kg (0.1-0.8 mmol/kg) for the patients with NSF. The median OM dose was greater in patients who developed NSF (P = 0.03), and was greater than the median MH dose (P < 0.005). CONCLUSION: NSF incidence in at-risk patients receiving contrast-enhanced MRI can be reduced after changing contrast administration protocols that includes changing the type and dose of contrast agent.

Variability in tissue Doppler echocardiographic measures of dyssynchrony is reduced with use of a larger region of interest.

BACKGROUND: Doppler tissue imaging (DTI)-based dyssynchrony parameters failed to predict response to cardiac resynchronization therapy (CRT) in the multicenter Predictors of Response to Cardiac Resynchronization Therapy (PROSPECT) trial. Large variability during the interpretation of DTI data was one of several factors thought to contribute to this failure. In this study, the authors hypothesized that using larger regions of interest (ROIs) to generate velocity curves from Doppler tissue images would significantly reduce the variability of DTI dyssynchrony parameters. METHODS: The variability of 3 ROI sizes (6 x 6, 18 x 6, and 30 x 6 mm) was compared in 30 patients undergoing CRT. Variability due to manual ROI placement was determined for each ROI size by placing 3 ROIs in each myocardial segment, 6mm apart from one another. Thus, 3 velocity curves were generated for each segment and each ROI size. Four published dyssynchrony parameters were calculated from all permutations of the 3 ROI positions per segment. A mean modified coefficient of variation was calculated for each parameter and ROI size. RESULTS: The 6 x 6 mm ROI had a mean coefficient of variation of 27%. The 18 x 6 and 30 x 6 mm ROIs had significantly lower coefficients of variation (17% and 14%, respectively) than the 6 x 6 mm ROI (P < .01 for both). The 30 x 6 mm ROI also reduced the diagnostic inconsistency of dyssynchrony parameters by 44% (P = .024) compared with the 6 x 6 mm ROI. CONCLUSION: Using a 30 x 6 mm ROI instead of a 6 x 6 mm ROI to quantify tissue Doppler dyssynchrony reduces variability by 47% and diagnostic inconsistency by 44%. The authors recommend using a 30 x 6 mm ROI in future trials to minimize variability.

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-alpha. 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.

A tractography comparison between turboprop and spin-echo echo-planar diffusion tensor imaging.

The development of accurate, non-invasive methods for mapping white matter fiber-tracts is of critical importance. However, fiber-tracking is typically performed on diffusion tensor imaging (DTI) data obtained with echo-planar-based imaging techniques (EPI), which suffer from susceptibility-related image artifacts, and image warping due to eddy-currents. Thus, a number of white matter fiber-bundles mapped using EPI-based DTI data are distorted and/or terminated early. This severely limits the clinical potential of fiber-tracking. In contrast, Turboprop-MRI provides images with significantly fewer susceptibility and eddy-current-related artifacts than EPI. The purpose of this work was to compare fiber-tracking results obtained from DTI data acquired with Turboprop-DTI and EPI-based DTI. It was shown that, in brain regions near magnetic field inhomogeneities, white matter fiber-bundles obtained with EPI-based DTI were distorted and/or partially detected, when magnetic susceptibility-induced distortions were not corrected. After correction, residual distortions were still present and several fiber-tracts remained partially detected. In contrast, when using Turboprop-DTI data, all traced fiber-tracts were in agreement with known anatomy. The inter-session reproducibility of tractography results was higher for Turboprop than EPI-based DTI data in regions near field inhomogeneities. Thus, Turboprop may be a more appropriate DTI data acquisition technique for tracing white matter fibers near regions with significant magnetic susceptibility differences, as well as in longitudinal studies of such fibers. However, the intra-session reproducibility of tractography results was higher for EPI-based than Turboprop DTI data. Thus, EPI-based DTI may be more advantageous for tracing fibers minimally affected by field inhomogeneities.

A unifying theoretical and algorithmic framework for least squares methods of estimation in diffusion tensor imaging.

A unifying theoretical and algorithmic framework for diffusion tensor estimation is presented. Theoretical connections among the least squares (LS) methods, (linear least squares (LLS), weighted linear least squares (WLLS), nonlinear least squares (NLS) and their constrained counterparts), are established through their respective objective functions, and higher order derivatives of these objective functions, i.e., Hessian matrices. These theoretical connections provide new insights in designing efficient algorithms for NLS and constrained NLS (CNLS) estimation. Here, we propose novel algorithms of full Newton-type for the NLS and CNLS estimations, which are evaluated with Monte Carlo simulations and compared with the commonly used Levenberg-Marquardt method. The proposed methods have a lower percent of relative error in estimating the trace and lower reduced chi2 value than those of the Levenberg-Marquardt method. These results also demonstrate that the accuracy of an estimate, particularly in a nonlinear estimation problem, is greatly affected by the Hessian matrix. In other words, the accuracy of a nonlinear estimation is algorithm-dependent. Further, this study shows that the noise variance in diffusion weighted signals is orientation dependent when signal-to-noise ratio (SNR) is low (

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.

Independent component analysis applied to self-paced functional MR imaging paradigms.

Self-paced functional MR imaging (fMRI) paradigms, in which the task timing is determined by the subject's performance, can offer several advantages over commonly applied paradigms with predetermined stimulus timing. Independent component analysis (ICA) does not require specification of a timed response function, and could be an advantageous method of deriving results from fMRI data sets with varying response timings and durations. In this study normal volunteers (N = 10) each performed two self-paced fMRI motor and arithmetic paradigms. Individual data sets were analyzed with the Infomax spatial ICA algorithm. Conventional regression analysis was performed for comparison purposes. Spatial ICA effectively produced task-related components from each of the self-paced data sets, even in a few cases where regression analysis yielded non-specific functional maps. For the motor paradigm, these components consistently mapped to primary motor areas. ICA of the arithmetic paradigm yielded multiple task-related components that variably mapped to regions of parietal and frontal lobes. Regression analysis generally yielded similar spatial maps. The multiple task-related ICA components that were sometimes produced from each self-paced data set can be challenging to identify and evaluate for significance. These preliminary results indicate that ICA is useful as an exploratory and complementary method to conventional regression analysis for fMRI of self-paced paradigms.

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.

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.

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.

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 MR imaging in diffuse axonal injury.

BACKGROUND AND PURPOSE: Disruption of the cytoskeletal network and axonal membranes characterizes diffuse axonal injury (DAI) in the first few hours after traumatic brain injury. Histologic abnormalities seen in DAI hypothetically decrease the diffusion along axons and increase the diffusion in directions perpendicular to them. DAI therefore is hypothetically associated in the short term with decreased diffusion anisotropy. We tested this hypothesis by measuring the diffusion characteristics of traumatized brain tissue with use of diffusion tensor MR imaging. METHODS: Five patients with mild traumatic brain injuries and 10 control subjects were studied with CT, conventional MR imaging, and diffusion tensor imaging. All patients were examined within 24 hours of injury. In each participant, diffusion tensor indices from homologous normal-appearing white matter regions of both hemispheres were compared. These indices were also compared between homologous regions of each patient and the control group. In two patients, diffusion tensor images from the immediate post-trauma period were compared with those at 1 month follow-up. RESULTS: Patients displayed significant reduction of diffusion anisotropy in several regions compared with the homologous ones in the contralateral hemisphere. Such differences were not observed in the control subjects. Significant reduction of diffusion anisotropy was also detected when diffusion tensor results from the patients were compared with those of the controls. This reduction was often less evident 1 month after injury. CONCLUSION: White matter regions with reduced anisotropy are detected in the first 24 hours after traumatic brain injury. Therefore, diffusion tensor imaging may be a powerful technique for in vivo detection of DAI.

Characterizing instantaneous phase relationships in whole-brain fMRI activation data.

Typically, fMRI data is processed in the time domain with linear methods such as regression and correlation analysis. We propose that the theory of phase synchronization may be used to more completely understand the dynamics of interacting systems, and can be applied to fMRI data as a novel method of detecting activation. Generalized synchronization is a phenomenon that occurs when there is a nonlinear functional relationship present between two or more coupled, oscillatory systems, whereas phase synchronization is defined as the locking of the phases while the amplitudes may vary. In this study, we developed an application of phase synchronization analysis that is appropriate for fMRI data, in which the phase locking condition is investigated between a voxel time series and the reference function of the task performed. A synchronization index is calculated to quantify the level of phase locking, and a nonparametric permutation test is used to determine the statistical significance of the results. We performed the phase synchronization analysis on the data from five volunteers for an event-related finger-tapping task. Functional maps were created that provide information on the interrelations between the instantaneous phases of the reference function and the voxel time series in a whole-brain fMRI activation data set. We conclude that this method of analysis is useful for revealing additional information on the complex nature of the fMRI time series.