Glioma: application of whole-tumor texture analysis of diffusion-weighted imaging for the evaluation of tumor heterogeneity

BACKGROUND AND PURPOSE

To apply a texture analysis of apparent diffusion coefficient (ADC) maps to evaluate glioma heterogeneity, which was correlated with tumor grade.

MATERIALS AND METHODS

Forty patients with glioma (WHO grade II (n = 8), grade III (n = 10) and grade IV (n = 22)) underwent diffusion-weighted imaging (DWI), and the corresponding ADC maps were obtained. Regions of interest containing the lesions were drawn on every section of the ADC map containing the tumor, and volume-based data of the entire tumor were constructed. Texture and first order features including entropy, skewness and kurtosis were derived from the ADC map using in-house software. A histogram analysis of the ADC map was also performed. The texture and histogram parameters were compared between low-grade and high-grade gliomas using an unpaired student's t-test. Additionally, a one-way analysis of variance analysis with a post-hoc test was performed to compare the parameters of each grade.

RESULTS

Entropy was observed to be significantly higher in high-grade gliomas than low-grade tumors (6.861±0.539 vs. 6.261±0.412, P  = 0.006). The fifth percentiles of the ADC cumulative histogram also showed a significant difference between high and low grade gliomas (836±235 vs. 1030±185, P = 0.037). Only entropy proved to be significantly different between grades III and IV (6.295±0.4963 vs. 7.119±0.3165, P<0.001). The diagnostic accuracy of ADC entropy was significantly higher than that of the fifth percentile of the ADC histogram (P = 0.0034) in distinguishing high- from low-grade glioma.

CONCLUSION

A texture analysis of the ADC map based on the entire tumor volume can be useful for evaluating glioma grade, which provides tumor heterogeneity.

The evolving role of diffusion magnetic resonance imaging in movement disorders

Significant advances have allowed diffusion magnetic resonance imaging (MRI) to evolve into a powerful tool in the field of movement disorders that can be used to study disease states and connectivity between brain regions. Diffusion MRI is a promising potential biomarker for Parkinson's disease and other forms of parkinsonism, and may allow the distinction of different forms of parkinsonism. Techniques such as tractography have contributed to our current thinking regarding the pathophysiology of dystonia and possible mechanisms of penetrance. Diffusion MRI measures could potentially assist in monitoring disease progression in Huntington's disease, and in uncovering the nature of the processes and structures involved the development of essential tremor. The ability to represent structural connectivity in vivo also makes diffusion MRI an ideal adjunctive tool for the surgical treatment of movement disorders. We review recent studies using diffusion MRI in movement disorders research and present the current state of the science as well as future directions.

Effect of patient sex on white matter alterations in unilateral medial temporal lobe epilepsy with hippocampal sclerosis assessed by diffusion tensor imaging

BACKGROUND AND PURPOSE

Studies shows ictal behavior and symptoms are affected by patient sex in temporal lobe epilepsy. The purpose of our study was to determine whether alterations in the WM as assessed by DTI display different patterns in male and female patients with unilateral HS.

MATERIALS AND METHODS

Patients with unilateral HS were categorized as women with right HS (n=12), men with right HS (n=10), women with left HS (n=12), and men with left HS (n=10). DTI of the brain along 64 noncollinear directions was obtained from 44 patients and 37 sex-matched control participants. We used TBSS to analyze whole-brain WM. Regions with significant changes of FA and MD, and their mean FA, MD, total number of significant voxels, and asymmetry indices were determined for each group.

RESULTS

All groups showed bilateral and extensive reductions of FA and elevated MD in the WM, more prominent ipsilateral to the affected hippocampus. The total number of voxels with decreased FA in patients compared with that of control participants was higher in women with right HS (24,727 vs 5,459) and in men with left HS (27,332 vs 14,013) than in their counterparts. Changes in MD associated with right HS were more extensive in both men and women (right vs left HS, women: 16,926 vs 5,458; men: 5,389 vs 4,764) than in those with left HS. In patients with right HS, the ipsilateral cingulum, uncinate fasciculus, internal and external capsules, and right acoustic radiation were involved extensively in women.

CONCLUSIONS

Women and men showed different patterns in extent of WM alterations associated with HS.

Accelerating fibre orientation estimation from diffusion weighted magnetic resonance imaging using GPUs

With the performance of central processing units (CPUs) having effectively reached a limit, parallel processing offers an alternative for applications with high computational demands. Modern graphics processing units (GPUs) are massively parallel processors that can execute simultaneously thousands of light-weight processes. In this study, we propose and implement a parallel GPU-based design of a popular method that is used for the analysis of brain magnetic resonance imaging (MRI). More specifically, we are concerned with a model-based approach for extracting tissue structural information from diffusion-weighted (DW) MRI data. DW-MRI offers, through tractography approaches, the only way to study brain structural connectivity, non-invasively and in-vivo. We parallelise the Bayesian inference framework for the ball & stick model, as it is implemented in the tractography toolbox of the popular FSL software package (University of Oxford). For our implementation, we utilise the Compute Unified Device Architecture (CUDA) programming model. We show that the parameter estimation, performed through Markov Chain Monte Carlo (MCMC), is accelerated by at least two orders of magnitude, when comparing a single GPU with the respective sequential single-core CPU version. We also illustrate similar speed-up factors (up to 120x) when comparing a multi-GPU with a multi-CPU implementation.

Microstructural damage of the posterior corpus callosum contributes to the clinical severity of neglect

One theory to account for neglect symptoms in patients with right focal damage invokes a release of inhibition of the right parietal cortex over the left parieto-frontal circuits, by disconnection mechanism. This theory is supported by transcranial magnetic stimulation studies showing the existence of asymmetric inhibitory interactions between the left and right posterior parietal cortex, with a right hemispheric advantage. These inhibitory mechanisms are mediated by direct transcallosal projections located in the posterior portions of the corpus callosum. The current study, using diffusion imaging and tract-based spatial statistics (TBSS), aims at assessing, in a data-driven fashion, the contribution of structural disconnection between hemispheres in determining the presence and severity of neglect. Eleven patients with right acute stroke and 11 healthy matched controls underwent MRI at 3T, including diffusion imaging, and T1-weighted volumes. TBSS was modified to account for the presence of the lesion and used to assess the presence and extension of changes in diffusion indices of microscopic white matter integrity in the left hemisphere of patients compared to controls, and to investigate, by correlation analysis, whether this damage might account for the presence and severity of patients' neglect, as assessed by the Behavioural Inattention Test (BIT). None of the patients had any macroscopic abnormality in the left hemisphere; however, 3 cases were discarded due to image artefacts in the MRI data. Conversely, TBSS analysis revealed widespread changes in diffusion indices in most of their left hemisphere tracts, with a predominant involvement of the corpus callosum and its projections on the parietal white matter. A region of association between patients' scores at BIT and brain FA values was found in the posterior part of the corpus callosum. This study strongly supports the hypothesis of a major role of structural disconnection between the right and left parietal cortex in determining 'neglect'.

Fisher statistics for analysis of diffusion tensor directional information

A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (p<0.0005) differences were found that robustly confirmed observations that were suggested by visual inspection of directionally encoded color DTI maps. The Fisher approach is a potentially useful analysis tool that may extend the current capabilities of DTI investigation by providing a means of statistical comparison of tissue structural orientation.

Efficient and robust nonlocal means denoising of MR data based on salient features matching

The nonlocal means (NLM) filter has become a popular approach for denoising medical images due to its excellent performance. However, its heavy computational load has been an important shortcoming preventing its use. NLM works by averaging pixels in nonlocal vicinities, weighting them depending on their similarity with the pixel of interest. This similarity is assessed based on the squared difference between corresponding pixels inside local patches centered at the locations compared. Our proposal is to reduce the computational load of this comparison by checking only a subset of salient features associated to the pixels, which suffice to estimate the actual difference as computed in the original NLM approach. The speedup achieved with respect to the original implementation is over one order of magnitude, and, when compared to more recent NLM improvements for MRI denoising, our method is nearly twice as fast. At the same time, we evidence from both synthetic and in vivo experiments that computing of appropriate salient features make the estimation of NLM weights more robust to noise. Consequently, we are able to improve the outcomes achieved with recent state of the art techniques for a wide range of realistic Signal-to-Noise ratio scenarios like diffusion MRI. Finally, the statistical characterization of the features computed allows to get rid of some of the heuristics commonly used for parameter tuning.

Analytic treatment of nuclear spin-lattice relaxation for diffusion in a cone model

We consider nuclear spin-lattice relaxation rate resulted from a diffusion equation for rotational wobbling in a cone. We show that the widespread point of view that there are no analytical expressions for correlation functions for wobbling in a cone model is invalid and prove that nuclear spin-lattice relaxation in this model is exactly tractable and amenable to full analytical description. The mechanism of relaxation is assumed to be due to dipole-dipole interaction of nuclear spins and is treated within the framework of the standard Bloemberger, Purcell, Pound-Solomon scheme. We consider the general case of arbitrary orientation of the cone axis relative the magnetic field. The BPP-Solomon scheme is shown to remain valid for systems with the distribution of the cone axes depending only on the tilt relative the magnetic field but otherwise being isotropic. We consider the case of random isotropic orientation of cone axes relative the magnetic field taking place in powders. Also we consider the cases of their predominant orientation along or opposite the magnetic field and that of their predominant orientation transverse to the magnetic field which may be relevant for, e.g., liquid crystals. Besides we treat in details the model case of the cone axis directed along the magnetic field. The latter provides direct comparison of the limiting case of our formulas with the textbook formulas for free isotropic rotational diffusion. The dependence of the spin-lattice relaxation rate on the cone half-width yields results similar to those predicted by the model-free approach.

Extremely efficient and deterministic approach to generating optimal ordering of diffusion MRI measurements

PURPOSE

Diffusion MRI measurements are typically acquired sequentially with unit gradient directions that are distributed uniformly on the unit sphere. The ordering of the gradient directions has significant effect on the quality of dMRI-derived quantities. Even though several methods have been proposed to generate optimal orderings of gradient directions, these methods are not widely used in clinical studies because of the two major problems. The first problem is that the existing methods for generating highly uniform and antipodally symmetric gradient directions are inefficient. The second problem is that the existing methods for generating optimal orderings of gradient directions are also highly inefficient. In this work, the authors propose two extremely efficient and deterministic methods to solve these two problems.

METHODS

The method for generating nearly uniform point set on the unit sphere (with antipodal symmetry) is based upon the notion that the spacing between two consecutive points on the same latitude should be equal to the spacing between two consecutive latitudes. The method for generating optimal ordering of diffusion gradient directions is based on the idea that each subset of incremental sample size, which is derived from the prescribed and full set of gradient directions, must be as uniform as possible in terms of the modified electrostatic energy designed for antipodally symmetric point set.

RESULTS

The proposed method outperformed the state-of-the-art method in terms of computational efficiency by about six orders of magnitude.

CONCLUSIONS

Two extremely efficient and deterministic methods have been developed for solving the problem of optimal ordering of diffusion gradient directions. The proposed strategy is also applicable to optimal view-ordering in three-dimensional radial MRI.

New MR imaging criteria with a diffusion-weighted sequence for the diagnosis of hepatocellular carcinoma in chronic liver diseases

BACKGROUND & AIMS

To propose MRI criteria with a diffusion-weighted imaging (DWI) sequence for the diagnosis of hepatocellular carcinoma (HCC).

METHODS

Patients, who underwent liver MRI with contrast-enhanced sequences and DWI between 2004 and 2008 and who had at least one confirmed HCC of at least 10mm, were included. Index diagnostic criteria were: (1) enhancement in the arterial-dominant phase and washout in the portal venous and/or equilibrium phases; (2) enhancement in the arterial-dominant phase and hyperintensity on DWI; (3) enhancement in the arterial-dominant phase and washout in the portal venous and/or equilibrium phases or hyperintensity on DWI. Two radiologists independently reviewed the corresponding sets of sequences (DWI alone; T1-weighted sequence before and after dynamic injection of gadolinium chelates; combined DWI-T1-weighted sequence). Inter-observer agreement and sensitivity were determined per nodule.

RESULTS

Ninety-one patients were included (109 HCCs). The sensitivity of conventional MRI criteria for the diagnosis of HCC was 59.6% for both radiologists. The sensitivity of enhancement in the arterial-dominant phase and hyperintensity on DWI was 77.1% or 76.1%, depending on the radiologist. The sensitivity of enhancement in the arterial-dominant phase and washout in the portal venous and/or equilibrium phases or hyperintensity on DWI was 84.4% or 85.3%, depending on the radiologist. The inter-observer agreement for the latter was very good (kappa coefficient 0.82). These results were consistent in HCCs smaller than 20mm.

CONCLUSIONS

The proposed criteria, based on the characteristics of lesions after gadolinium chelate administration and hyperintensity on DWI, significantly increased the sensitivity for the diagnosis of HCC compared to conventional criteria, regardless of tumor size.

³He lung morphometry technique: accuracy analysis and pulse sequence optimization

The (3)He lung morphometry technique (Yablonskiy et al., JAP, 2009), based on MRI measurements of hyperpolarized gas diffusion in lung airspaces, provides unique information on the lung microstructure at the alveolar level. 3D tomographic images of standard morphological parameters (mean airspace chord length, lung parenchyma surface-to-volume ratio, and the number of alveoli per unit lung volume) can be created from a rather short (several seconds) MRI scan. These parameters are most commonly used to characterize lung morphometry but were not previously available from in vivo studies. A background of the (3)He lung morphometry technique is based on a previously proposed model of lung acinar airways, treated as cylindrical passages of external radius R covered by alveolar sleeves of depth h, and on a theory of gas diffusion in these airways. The initial works approximated the acinar airways as very long cylinders, all with the same R and h. The present work aims at analyzing effects of realistic acinar airway structures, incorporating airway branching, physiological airway lengths, a physiological ratio of airway ducts and sacs, and distributions of R and h. By means of Monte-Carlo computer simulations, we demonstrate that our technique allows rather accurate measurements of geometrical and morphological parameters of acinar airways. In particular, the accuracy of determining one of the most important physiological parameter of lung parenchyma - surface-to-volume ratio - does not exceed several percent. Second, we analyze the effect of the susceptibility induced inhomogeneous magnetic field on the parameter estimate and demonstrate that this effect is rather negligible at B(0) ≤ 3T and becomes substantial only at higher B(0) Third, we theoretically derive an optimal choice of MR pulse sequence parameters, which should be used to acquire a series of diffusion-attenuated MR signals, allowing a substantial decrease in the acquisition time and improvement in accuracy of the results. It is demonstrated that the optimal choice represents three not equidistant b-values: b(1)=0, b(2)∼2 s/cm(2), b(3)∼8 s/cm(2).

Numerical simulations of short-mixing-time double-wave-vector diffusion-weighting experiments with multiple concatenations on whole-body MR systems

Double- or two-wave-vector diffusion-weighting experiments with short mixing times in which two diffusion-weighting periods are applied in direct succession, are a promising tool to estimate cell sizes in the living tissue. However, the underlying effect, a signal difference between parallel and antiparallel wave vector orientations, is considerably reduced for the long gradient pulses required on whole-body MR systems. Recently, it has been shown that multiple concatenations of the two wave vectors in a single acquisition can double the modulation amplitude if short gradient pulses are used. In this study, numerical simulations of such experiments were performed with parameters achievable with whole-body MR systems. It is shown that the theoretical model yields a good approximation of the signal behavior if an additional term describing free diffusion is included. More importantly, it is demonstrated that the shorter gradient pulses sufficient to achieve the desired diffusion weighting for multiple concatenations, increase the signal modulation considerably, e.g. by a factor of about five for five concatenations. Even at identical echo times, achieved by a shortened diffusion time, a moderate number of concatenations significantly improves the signal modulation. Thus, experiments on whole-body MR systems may benefit from multiple concatenations.

Evaluating the accuracy and precision of a two-compartment Kärger model using Monte Carlo simulations

Specific parameters of the neuronal tissue microstructure, such as axonal diameters, membrane permeability and intracellular water fractions are assessable using diffusion MRI. These parameters are commonly estimated using analytical models, which may introduce bias in the estimated parameters due to the approximations made when deriving the models. As an alternative to using analytical models, a database of signal curves generated by fast Monte Carlo simulations can be employed. Simulated diffusion MRI measurements were generated and evaluated using the two-compartment Kärger model as well as the simulation model based on a database containing signal curves from approximately 60000 simulations performed with different combinations of microstructural parameters. A protocol based on a pulsed gradient spin echo sequence with diffusion times of 30 and 60 ms and with gradient amplitudes obtainable with a clinical MRI scanner was employed for the investigations. When using the analytical model, a major negative bias (up to approximately 25%) in the estimated intracellular volume fraction was observed for short exchange times, while almost no bias was seen for the simulation model. In general, the simulation model improved the accuracy of the estimated parameters as compared to the analytical model, except for the exchange time parameter.

Double-wave-vector diffusion-weighting experiments with multiple concatenations at long mixing times

MR sequences where two diffusion-weighting periods are applied successively in a single acquisition seem to be a promising tool for the investigation of tissue structure on a microscopic level such as the characterization of the compartment size or eccentricity measures of pores. However, the application of such double-wave-vector (DWV) experiments on whole-body MR systems is hampered by the long gradient pulses required that have been shown to reduce the signal modulation. In this work, it is demonstrated that involving multiple concatenations of the two diffusion-weighting periods can ameliorate this problem in experiments with long mixing times between the two wave vectors. The recently presented tensor equation is extended to multiple concatenations. As confirmed by Monte-Carlo simulations, this model shows a good approximation of the signals observed for typical whole-body gradient pulse durations and the derived anisotropy measures are obtained with good accuracy. Most importantly, the signal modulation is increased with multiple concatenations because shorter gradient pulses can be used to achieve the desired diffusion-weighting. Thus, the multiple concatenation approach may help to improve the applicability and reliability of DWV measurements with long mixing times on standard whole-body MR systems.

About the origins of NMR diffusion-weighting induced by frequency-swept pulses

In the present work, the non-linear phase dispersion induced by slice selective frequency-swept pulses is analyzed, in order to assess NMR signal attenuation due to molecular diffusion during such pulses. In particular, theoretical considerations show that diffusion-weighting can be calculated based on the non-linear phase spatial derivative (i.e. the phase gradient), and that the phase of B(1) field at the instant of the flip does not contribute to phase scrambling and diffusion-weighting, yielding a simple analytical expressions. The theory is validated by confrontation with numerical simulations of the Bloch equations including diffusion, performed for a pair of hyperbolic secant pulses and a pair of CHIRP pulses. The simple though general conceptual framework developed here should be useful for the understanding and the exact calculation of diffusion-weighting in NMR sequences using frequency-swept pulses.

Identical, but not the same: intra-site and inter-site reproducibility of fractional anisotropy measures on two 3.0T scanners

Diffusion Tensor Imaging (DTI) is being increasingly used to assess white matter integrity and it is therefore paramount to address the test–retest reliability of DTI measures. In this study we assessed inter- and intra-site reproducibility of two nominally identical 3 T scanners at different sites in nine healthy controls using a DTI protocol representative of typical current “best practice” including cardiac gating, a multichannel head coil, parallel imaging and optimized diffusion gradient parameters. We calculated coefficients of variation (CV) and intraclass correlation coefficients (ICC) of fractional anisotropy (FA) measures for the whole brain, for three regions of interest (ROI) and for three tracts derived from these ROI by probabilistic tracking. We assessed the impact of affine, nonlinear and template based methods for spatially aligning FA maps on the reproducibility. The intra-site CV for FA ranged from 0.8% to 3.0% with ICC from 0.90 to 0.99, while the inter-site CV ranged from 1.0% to 4.1% with ICC of 0.82 to 0.99. Nonlinear image coregistration improved reproducibility compared to affine coregistration. Normalization to template space reduced the between-subject variation, resulting in lower ICC values and indicating a possibly reduced sensitivity. CV from probabilistic tractography were about 50% higher than for the corresponding seed ROI.

Reproducibility maps of the whole scan volume showed a low variation of less than 5% in the major white matter tracts but higher variations of 10–15% in gray matter regions.

One of the two scanners showed better intra-site reproducibility, while the intra-site CV for both scanners was significantly better than inter-site CV. However, when using nonlinear coregistration of FA maps, the average inter-site CV was below 2%. There was a consistent inter-site bias, FA values on site 2 were 1.0–1.5% lower than on site 1. Correction for this bias with a global scaling factor reduced the inter-site CV to the range of intra-site CV. Our results are encouraging for multi-centre DTI studies in larger populations, but also illustrate the importance of the image processing pipeline for reproducibility.

Extension of the double-wave-vector diffusion-weighting experiment to multiple concatenations

Experiments involving two diffusion-weightings in a single acquisition, so-called double- or two-wave-vector experiments, have recently been applied to measure the microscopic anisotropy in macroscopically isotropic samples or to estimate pore or compartment sizes. These informations are derived from the signal modulation observed when varying the wave vectors' orientations. However, the modulation amplitude can be small and, for short mixing times between the two diffusion-weightings, decays with increased gradient pulse lengths which hampers its detectability on whole-body MR systems. Here, an approach is investigated that involves multiple concatenations of the two diffusion-weightings in a single experiment. The theoretical framework for double-wave-vector experiments of fully restricted diffusion is adapted and the corresponding tensor approach recently presented for short mixing times extended and compared to numerical simulations. It is shown that for short mixing times (i) the extended tensor approach well describes the signal behavior observed for multiple concatenations and (ii) the relative amplitude of the signal modulation increases with the number of concatenations. Thus, the presented extension of the double-wave-vector experiment may help to improve the detectability of the signal modulations observed for short mixing times, in particular on whole-body MR systems with their limited gradient amplitudes.

3T MR imaging of postoperative recurrent middle ear cholesteatomas: value of periodically rotated overlapping parallel lines with enhanced reconstruction diffusion-weighted MR imaging

BACKGROUND AND PURPOSE

MR diagnostic of postoperative recurrent cholesteatomas is difficult. Our purpose was to compare multishot fast spin-echo periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) diffusion-weighted MR imaging (DWI) with array spatial sensitivity encoding technique (ASSET) single-shot echo-planar DWI and late postgadolinium T1-weighted MR imaging for the detection of postoperative recurrent middle ear cholesteatomas with a 3T imaging unit.

MATERIALS AND METHODS

Thirty-five patients with suggested postoperative recurrent middle ear cholesteatoma underwent 3T MR imaging with PROPELLER DWI, ASSET echo-planar DWI, and late postgadolinium T1-weighted MR imaging. Three radiologists (2 seniors, 1 fellow) analyzed unlabeled images for visualization of recurrence. Interobserver and intraobserver agreement was assessed by using the Cohen kappa statistic test. Sensitivity, specificity, and predictive value were assessed for the 3 observers.

RESULTS

Nineteen recurrent cholesteatomas were diagnosed. PROPELLER interobserver agreement was very good (1, 0.89, 0.89) among the 3 observers. Intraobserver agreement between PROPELLER and T1-weighted imaging was very good to moderate (0.88, 0.57, 0.58). PROPELLER DWI provided less interobserver variability than other sequences, and the best sensitivity, specificity, and predictive value.

CONCLUSIONS

On a 3T imaging unit, multishot fast spin-echo PROPELLER DWI allows an easier detection of postoperative recurrent middle ear cholesteatoma than T1-weighted imaging by reducing artifacts and by its better contrast. DWI with PROPELLER is diagnostically robust and accurate.

A geometric flow-based approach for diffusion tensor image segmentation

Diffusion tensor magnetic resonance imaging (DT-MRI, shortened as DTI) produces, from a set of diffusion-weighted magnetic resonance images, tensor-valued images where each voxel is assigned a 3x3 symmetric, positive-definite matrix. This tensor is simply the covariance matrix of a local Gaussian process with zero mean, modelling the average motion of water molecules. We propose a three-dimensional geometric flow-based model to segment the main core of cerebral white matter fibre tracts from DTI. The segmentation is carried out with a front propagation algorithm. The front is a three-dimensional surface that evolves along its normal direction with speed that is proportional to a linear combination of two measures: a similarity measure and a consistency measure. The similarity measure computes the similarity of the diffusion tensors at a voxel and its neighbouring voxels along the normal to the front; the consistency measure is able to speed up the propagation at locations where the evolving front is more consistent with the diffusion tensor field, to remove noise effect to some extent, and thus to improve results. We validate the proposed model and compare it with some other methods using synthetic and human brain DTI data; experimental results indicate that the proposed model improves the accuracy and efficiency in segmentation.

Altered cingulate white matter connectivity in panic disorder patients

OBJECTIVE

Functional imaging studies of panic disorder subjects suggest an increased activation of the cingulate regions of the brain. Aim of the current study was to explore the white matter connectivity differences between subjects with panic disorder and healthy comparison subjects.

METHOD

Structural white matter connectivity, as determined from fractional anisotropy (FA) values obtained by diffusion tensor imaging, was assessed for anterior and posterior cingulate regions in 24 panic disorder patients and 24 age and sex-matched healthy comparison subjects.

RESULTS

Subjects with panic disorder exhibited significantly greater FA values in left anterior and right posterior cingulate regions (by 13.3% and 19.6%, respectively) relative to comparison subjects. White matter connectivity for these two cingulate regions was also positively correlated with clinical severity, as determined by Panic Disorder Severity Scale. FA values in left anterior cingulate region negatively correlated with the time of Trail Making Tests and positively with Digit Symbol Substitution Test.

CONCLUSIONS

Findings suggest a potential 'enhancement' in white matter connectivity in left anterior and right posterior cingulate regions in panic disorder, and that these changes may play an important role in mediating clinical symptoms of panic disorder.

Altered resting-state functional connectivity and anatomical connectivity of hippocampus in schizophrenia

Hippocampus has been implicated in participating in the pathophysiology of schizophrenia. However, the functional and anatomical connectivities between hippocampus and other regions are rarely concurrently investigated in schizophrenia. In the present study, both functional magnetic resonance imaging (fMRI) during rest and diffusion tensor imaging (DTI) were performed on 17 patients with paranoid schizophrenia and 14 healthy subjects. Resting-state functional connectivities of the bilateral hippocampi were separately analyzed by selecting the anterior hippocampus as region of interest. The fornix body was reconstructed by diffusion tensor tractography, and the integrity of this tract was evaluated using fractional anisotropy (FA). In patients with schizophrenia, the bilateral hippocampi showed reduced functional connectivities to some regions which have been reported to be involved in episodic memory, such as posterior cingulate cortex, extrastriate cortex, medial prefrontal cortex, and parahippocampus gyrus. We speculated that these reduced connectivity may reflect the disconnectivity within a neural network related to the anterior hippocampus in schizophrenia. Meanwhile the mean FA of the fornix body was significantly reduced in patients, indicating the damage in the hippocampal anatomical connectivity in schizophrenia. The concurrence of the functional disconnectivity and damaged anatomical connectivity between the hippocampus and other regions in schizophrenia suggest that the functional-anatomical relationship need to be further investigated.

Diffusion-based magnetic resonance imaging and tractography in epilepsy

Diffusion-based imaging is an advanced MRI technique that is sensitive to the movement of water molecules, providing additional information on the micro-structural arrangement of tissue. Qualitative and quantitative analysis of peri, post and interictal diffusion images can aid the localization of seizure foci. Diffusion tensor tractography is an extension of diffusion-based imaging, and can provide additional information about white matter pathways. Both techniques are able to increase understanding of the effects of epilepsy on the structural organization of the brain, and can be used to optimize presurgical planning of patients with epilepsy. This review focuses on the basis, applications, limitations, and future directions of diffusion imaging in epilepsy. Literature search strategy: We searched Pubmed using the terms "diffusion MRI or diffusion tensor MRI or tractography and epilepsy."

K-space and image space combination for motion artifact correction in multicoil multishot diffusion weighted imaging

Motion during diffusion encodings leads to phase errors in different shots of a multishot acquisition. Phase differences in k-space data among shots result in phase cancellation artifacts in the reconstructed image. Due to aliasing of the phase from under-sampled regions of the shot, correction of the phase error using direct low-resolution phase subtraction is incomplete. We introduce a new k-space and image-space combination (KICT) method for motion artifacts cancellation that avoids incomplete phase error correction. Further, the method preserves the phase of the object, which is important for parallel imaging applications.