Addressing the path-length-dependency confound in white matter tract segmentation.

We derive the Iterative Confidence Enhancement of Tractography (ICE-T) framework to address the problem of path-length dependency (PLD), the streamline dispersivity confound inherent to probabilistic tractography methods. We show that PLD can arise as a non-linear effect, compounded by tissue complexity, and therefore cannot be handled using linear correction methods. ICE-T is an easy-to-implement framework that acts as a wrapper around most probabilistic streamline tractography methods, iteratively growing the tractography seed regions. Tract networks segmented with ICE-T can subsequently be delineated with a global threshold, even from a single-voxel seed. We investigated ICE-T performance using ex vivo pig-brain datasets where true positives were known via in vivo tracers, and applied the derived ICE-T parameters to a human in vivo dataset. We examined the parameter space of ICE-T: the number of streamlines emitted per voxel, and a threshold applied at each iteration. As few as 20 streamlines per seed-voxel, and a robust range of ICE-T thresholds, were shown to sufficiently segment the desired tract network. Outside this range, the tract network either approximated the complete white-matter compartment (too low threshold) or failed to propagate through complex regions (too high threshold). The parameters were shown to be generalizable across seed regions. With ICE-T, the degree of both near-seed flare due to false positives, and of distal false negatives, are decreased when compared with thresholded probabilistic tractography without ICE-T. Since ICE-T only addresses PLD, the degree of remaining false-positives and false-negatives will consequently be mainly attributable to the particular tractography method employed. Given the benefits offered by ICE-T, we would suggest that future studies consider this or a similar approach when using tractography to provide tract segmentations for tract based analysis, or for brain network analysis.

Healthy aging attenuates task-related specialization in the human medial temporal lobe.

Recent research on aging has established important links between the neurobiology of normal aging and age-related decline in episodic memory, yet the exact nature of this relationship is still unknown. Functional neuroimaging of regions such as the medial temporal lobe (MTL) have produced conflicting findings. Using functional magnetic resonance imaging (fMRI), we have recently shown that young healthy individuals show a stronger activation of the MTL during encoding of objects as compared with encoding of positions. Using the same encoding task, the present study addressed the question whether this greater MTL activation during encoding of objects varies with age. Fifty-four healthy individuals aged between 18 and 81 years underwent functional magnetic resonance imaging while they encoded and subsequently made new-old judgments on objects and positions. Region of interest (ROI) analysis of task related changes in the blood oxygen level-dependent (BOLD) signal was performed in native space after correction for gender effects and individual differences in cerebral blood flow. The hippocampus, amygdala, and parahippocampal, perirhinal, entorhinal, and temporopolar cortices of right and left hemisphere were defined as ROIs. Aging had an adverse effect on memory performance that was similar for memorizing objects or positions. In left and right MTL, relatively greater activation for object stimuli was attenuated in older individuals. Age-related attenuation in content specificity was most prominent in the recognition stage. During recognition, the larger response to objects gradually decreased with age in all ROIs apart from left temporopolar and entorhinal cortex. An age-related attenuation was also present during encoding, but only in right parahippocampus and amygdala. Our results suggest that memory-related processing in the MTL becomes gradually less sensitive to content during normal aging.

Regional activation of the human medial temporal lobe during intentional encoding of objects and positions.

The medial temporal lobe (MTL) consists of several regions thought to be involved in learning and memory. However, the degree of functional specialization among these regions remains unclear. Previous studies have demonstrated effects of both content and processing stage, but findings have been inconsistent. In particular, studies have suggested that the perirhinal cortex is more involved in object processing than spatial processing, while other regions such as the parahippocampal cortex have been implicated in spatial processing. In this study, functional magnetic resonance imaging (fMRI) optimized for the MTL region was used to probe MTL activation during intentional encoding of object identities or positions. A region of interest analysis showed that object encoding evoked stronger activation than position encoding in bilateral perirhinal cortex, temporopolar cortex, parahippocampal cortex, hippocampus and amygdala. Results also indicate an unexpected significant correlation in activation level between anterior and posterior portions in both the left parahippocampal cortex and left hippocampus. Exploratory analysis did not show any regional content effects during preparation and rehearsal stages. These results provide additional evidence for functional specialization within the MTL, but were less clear regarding the specific nature of content specificity in these regions.

Long-term global and regional brain volume changes following severe traumatic brain injury: a longitudinal study with clinical correlates.

Traumatic brain injury (TBI) results in neurodegenerative changes that progress for months, perhaps even years post-injury. However, there is little information on the spatial distribution and the clinical significance of this late atrophy. In 24 patients who had sustained severe TBI we acquired 3D T1-weighted MRIs about 8 weeks and 12 months post-injury. For comparison, 14 healthy controls with similar distribution of age, gender and education were scanned with a similar time interval. For each subject, longitudinal atrophy was estimated using SIENA, and atrophy occurring before the first scan time point using SIENAX. Regional distribution of atrophy was evaluated using tensor-based morphometry (TBM). At the first scan time point, brain parenchymal volume was reduced by mean 8.4% in patients as compared to controls. During the scan interval, patients exhibited continued atrophy with percent brain volume change (%BVC) ranging between -0.6% and -9.4% (mean -4.0%). %BVC correlated significantly with injury severity, functional status at both scans, and with 1-year outcome. Moreover, %BVC improved prediction of long-term functional status over and above what could be predicted using functional status at approximately 8 weeks. In patients as compared to controls, TBM (permutation test, FDR 0.05) revealed a large coherent cluster of significant atrophy in the brain stem and cerebellar peduncles extending bilaterally through the thalamus, internal and external capsules, putamen, inferior and superior longitudinal fasciculus, corpus callosum and corona radiata. This indicates that the long-term atrophy is attributable to consequences of traumatic axonal injury. Despite progressive atrophy, remarkable clinical improvement occurred in most patients.

Diffusion tensor imaging during recovery from severe traumatic brain injury and relation to clinical outcome: a longitudinal study.

Diffusion tensor imaging (DTI) has been proposed as a sensitive biomarker of traumatic white matter injury, which could potentially serve as a tool for prognostic assessment and for studying microstructural changes during recovery from traumatic brain injury (TBI). However, there is a lack of longitudinal studies on TBI that follow DTI changes over time and correlate findings with long-term clinical outcome. We performed a prospective longitudinal study of 30 adult patients admitted for subacute rehabilitation following severe traumatic brain injury. DTI and conventional MRI were acquired at mean 8 weeks (5-11 weeks), and repeated in 23 of the patients at mean 12 months (9-15 months) post-trauma. Using a region-of-interest-based approach, DTI parameters were compared to those of healthy matched controls, scanned during the same time period and rescanned with a similar interval as that of patients. At the initial scan, fractional anisotropy was reduced in all the investigated white matter regions in patients compared to controls (P

Slice profile optimization in arterial spin labeling using presaturation and optimized RF pulses.

OBJECTIVE: An important source of error in arterial spin labeling (ASL) is incomplete static tissue subtraction due to imperfect slice profiles. This effect can be reduced by saturating the spins in the imaging area prior to labeling. In this study, the use of optimized presaturation is compared with the use of optimized RF pulses for minimizing this error. MATERIALS AND METHODS: Different methods for optimizing presaturation were simulated by numerical solution of the Bloch equation. Presaturation was optimized by changing the number of presaturation pulses, their position in the pulse sequence and the area of the crusher gradients following each saturation pulse. It was also investigated whether the use of optimized presaturation could reduce the tag gap needed to ensure complete static tissue subtraction. Simulation results were verified using phantom and in vivo studies at 3T. RESULTS: In proximal inversion with control for off-resonance effects, optimized presaturation could reduce the necessary tag gap to 15% of the imaging slab for experiments using standard RF pulses, while c-FOCI RF pulses could reduce it to 11%. In flow-sensitive alternating inversion recovery, a single presaturation pulse could reduce the inversion width to 122% of the imaging slab and neither multiple presaturation pulses nor optimized RF pulses could reduce it further. CONCLUSION: Optimized presaturation can reduce the necessary inversion width to the same level as if using optimized RF pulses and can, therefore, be used to optimize ASL sensitivity. Furthermore, optimized presaturation can reduce the B(1)-dependent sensitivity in static tissue subtraction.

Noninvasive measurements of regional cerebral perfusion in preterm and term neonates by magnetic resonance arterial spin labeling.

Magnetic resonance arterial spin labeling (ASL) at 3 Tesla has been investigated as a quantitative technique for measuring regional cerebral perfusion (RCP) in newborn infants. RCP values were measured in 49 healthy neonates: 32 preterm infants born before 34 wk of gestation and 17 term-born neonates. Examinations were performed on unsedated infants at postmenstrual age of 39-40 wk in both groups. Due to motion, reliable data were obtained from 23 preterm and 6 term infants. Perfusion in the basal ganglia (39 and 30 mL/100 g/min for preterm and term neonates, respectively) was significantly higher (p < 0.0001) than in cortical gray matter (19 and 16 mL/100 g/min) and white matter (15 and 10 mL/100 g/min), both in preterm neonates at term-equivalent age and in term neonates. Perfusion was significantly higher (p = 0.01) in the preterm group than in the term infants, indicating that RCP may be influenced by developmental and postnatal ages. This study demonstrates, for the first time, that noninvasive ASL at 3T may be used to measure RCP in healthy unsedated preterm and term neonates. ASL is, therefore, a viable tool that will allow serial studies of RCP in high-risk neonates.

Non-white noise in fMRI: does modelling have an impact?

The sources of non-white noise in Blood Oxygenation Level Dependent (BOLD) functional magnetic resonance imaging (fMRI) are many. Familiar sources include low-frequency drift due to hardware imperfections, oscillatory noise due to respiration and cardiac pulsation and residual movement artefacts not accounted for by rigid body registration. These contributions give rise to temporal autocorrelation in the residuals of the fMRI signal and invalidate the statistical analysis as the errors are no longer independent. The low-frequency drift is often removed by high-pass filtering, and other effects are typically modelled as an autoregressive (AR) process. In this paper, we propose an alternative approach: Nuisance Variable Regression (NVR). By inclusion of confounding effects in a general linear model (GLM), we first confirm that the spatial distribution of the various fMRI noise sources is similar to what has already been described in the literature. Subsequently, we demonstrate, using diagnostic statistics, that removal of these contributions reduces first and higher order autocorrelation as well as non-normality in the residuals, thereby improving the validity of the drawn inferences. In addition, we also compare the performance of the NVR method to the whitening approach implemented in SPM2.

Hypercapnic normalization of BOLD fMRI: comparison across field strengths and pulse sequences.

The blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal response to neural stimulation is influenced by many factors that are unrelated to the stimulus. These factors are physiological, such as the resting venous cerebral blood volume (CBV(v)) and vessel size, as well as experimental, such as pulse sequence and static magnetic field strength (B(0)). Thus, it is difficult to compare task-induced fMRI signals across subjects, field strengths, and pulse sequences. This problem can be overcome by normalizing the neural activity-induced BOLD fMRI response by a global hypercapnia-induced BOLD signal. To demonstrate the effectiveness of the BOLD normalization approach, gradient-echo BOLD fMRI at 1.5, 4, and 7 T and spin-echo BOLD fMRI at 4 T were performed in human subjects. For neural stimulation, subjects performed sequential finger movements at 2 Hz, while for global stimulation, subjects breathed a 5% CO(2) gas mixture. Under all conditions, voxels containing primarily large veins and those containing primarily active tissue (i.e., capillaries and small veins) showed distinguishable behavior after hypercapnic normalization. This allowed functional activity to be more accurately localized and quantified based on changes in venous blood oxygenation alone. The normalized BOLD signal induced by the motor task was consistent across different magnetic fields and pulse sequences, and corresponded well with cerebral blood flow measurements. Our data suggest that the hypercapnic normalization approach can improve the spatial specificity and interpretation of BOLD signals, allowing comparison of BOLD signals across subjects, field strengths, and pulse sequences. A theoretical framework for this method is provided.