Diffusion tensor imaging of the sural nerve in normal controls.

OBJECTIVE: To develop a diffusion tensor imaging (DTI) protocol for assessing the sural nerve in healthy subjects. METHODS: Sural nerves in 25 controls were imaged using DTI at 3T with 6, 15, and 32 gradient directions. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were computed from nerve regions of interest co-registered with T2-weighted images. RESULTS: Coronal images with 0.5(RL)× 2.0(FH)× 0.5(AP)mm(3) resolution successfully localized the sural nerve. FA maps showed less variability with 32 directions (0.559 ± 0.071) compared to 15(0.590 ± 0.080) and 6(0.659 ± 0.109). CONCLUSIONS: Our DTI protocol was effective in imaging sural nerves in controls to establish normative FA/ADC, with potential to be used non-invasively in diseased nerves of patients.

Retrospective estimation of the susceptibility driven field map for distortion correction in echo planar imaging.

Echo planar imaging (EPI) sequence used for acquiring functional MRI (fMRI) time series data provides the advantage of high temporal resolution, but also is highly sensitive to the magnetic field inhomogeneity resulting in geometric distortions. A static field-inhomogeneity map measured before or after the fMRI scan to correct for such distortions does not account for magnetic field changes due to the head motion during the time series acquisition. In practice, the field map dynamically changes with head motion during the scan and leads to variations in the geometric distortion. We model in this work the field inhomogeneity with the object and the scanner dependent terms. The object-specific term varies with the object's magnetic susceptibility and orientation, i.e., head position with respect to B0. Thus, the simple transformation of the acquired field may not yield an accurate field map. We assume that the scanner-specific field remains unchanged and independent of the head motion. Our approach in this study is to retrospectively estimate the object's magnetic susceptibility (chi) map from an observed high-resolution static field map using an estimator derived from a probability density function of non-uniform noise. This approach is capable of finding the susceptibility map regardless of the wrapping effect. A dynamic field map at each head position can be estimated by applying a rigid body transformation to the estimated chi-map and the 3-D susceptibility voxel convolution (SVC) which is a physics-based discrete convolution model for computing chi-induced field inhomogeneity.

Accelerated nonrigid intensity-based image registration using importance sampling.

Nonrigid image registration methods using intensity-based similarity metrics are becoming increasingly common tools to estimate many types of deformations. Nonrigid warps can be very flexible with a large number of parameters and gradient optimization schemes are widely used to estimate them. However, for large datasets, the computation of the gradient of the similarity metric with respect to these many parameters becomes very time consuming. Using a small random subset of image voxels to approximate the gradient can reduce computation time. This work focuses on the use of importance sampling to reduce the variance of this gradient approximation. The proposed importance sampling framework is based on an edge-dependent adaptive sampling distribution designed for use with intensity-based registration algorithms. We compare the performance of registration based on stochastic approximations with and without importance sampling to that using deterministic gradient descent. Empirical results, on simulated magnetic resonance brain data and real computed tomography inhale-exhale lung data from eight subjects, show that a combination of stochastic approximation methods and importance sampling accelerates the registration process while preserving accuracy.

Motion robust magnetic susceptibility and field inhomogeneity estimation using regularized image restoration techniques for fMRI.

In functional MRI, head motion may cause dynamic nonlinear field-inhomogeneity changes, especially with large out-of-plane rotations. This may lead to dynamic geometric distortion or blurring in the time series, which may reduce activation detection accuracy. The use of image registration to estimate dynamic field inhomogeneity maps from a static field map is not sufficient in the presence of such rotations. This paper introduces a retrospective approach to estimate magnetic susceptibility induced field maps of an object in motion, given a static susceptibility induced field map and the associated object motion parameters. It estimates a susceptibility map from a static field map using regularized image restoration techniques, and applies rigid body motion to the former. The dynamic field map is then computed using susceptibility voxel convolution. The method addresses field map changes due to out-of-plane rotations during time series acquisition and does not involve real time field map acquisitions.

Formulation of current density weighted indices for correspondence between functional MRI and electrocortical stimulation maps.

OBJECTIVE: Accurate localization of functionally significant brain regions reduces risks of post-operative neurological deficits. The gold standard for presurgical brain mapping is subdural electrocortical stimulation (ECS), which is an open-cranium surgical procedure. Functional MRI (fMRI) may be a noninvasive alternative if it can be shown that fMRI and ECS maps are spatially consistent. We formulate new 3D current density weighted ECS-fMRI correspondence indices and illustrate their use on human data. METHODS: Current density maps were computed for simulated and human datasets by solving the electrostatic Laplace equation. The proposed indices were characterized and compared with fixed radii and Euclidean distance indices. RESULTS: Results from simulated datasets showed that the proposed indices quantify correspondence between fMRI and the ECS truth predictably, and provide conspicuous sensitivity increase from fixed radii indices, whereas Euclidean distances may not be suitable measures of the correspondence. CONCLUSIONS: The proposed indices reflect contextual information from surrounding electrodes and may be physiologically more meaningful in evaluating ECS-fMRI correspondence. SIGNIFICANCE: To identify safe limits of resection, an ECS map requires placement of electrodes on a patient's brain. Our proposed indices accurately quantify ECS-fMRI correspondence and may be used to evaluate fMRI as a noninvasive alternative for defining resection limits.

Spin saturation artifact correction using slice-to-volume registration motion estimates for fMRI time series.

Evaluation of functional magnetic resonance imaging (fMRI) as a reliable clinical imaging tool requires accurate assessment and correction of head motion artifacts. As the correction of bulk head motion is vital, the loss of signal strength from the confounding effect of head motion on spin magnetization may be an additional factor in activation analysis error. This study focuses on the evaluation and correction of the spin saturation artifact that occurs when parts of adjacent slices are selected due to changing head positions in single-shot multislice acquisitions. As a consequence of head movement, the acquired slices constituting a fMRI volume are no longer parallel to each other and the spin magnetization in fMRI voxels becomes dependent on head motion history. Motion corrections applying the same rigid motion estimates to all the slices in a volume may not be a reasonable approximation in cases where the magnitude of head motion exceeds a subvoxel range. For realistic ranges of motion in fMRI, an accurate estimate of rigid motion parameters for each echo planar imaging (EPI) slice is essential to correctly register voxel intensities. Previously we have implemented the map-slice-to-volume (MSV) motion correction method that maps each slice in a time series onto a reference anatomical volume, which proved to be effective in improving activation detection. To correctly evaluate the motion dependence of spin magnetization, each voxel is tracked with movement history that is available from MSV motion estimates. Relatively low in resolution, EPI voxels are composed of varying mixtures of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) and variations in the tissue composition give rise to voxel intensities that are functions of tissue T1 properties. We have developed a weighted-average spin saturation (WASS) correction method that can handle full rigid motion and account for the melange of different brain tissue isochromats at each EPI voxel location. We evaluated the effect of spin saturation artifacts and the performance of the WASS correction using simulated fMRI time series synthesized with known true activation, motion, and the associated spin saturation artifact. Two different ranges of head rotations, [-5,5] and [-2,2] deg, were introduced and the effect of the spin saturation artifact was quantified to show 18% and 13% reduction in activation detection rate, respectively. Following the MSV motion and WASS correction, results indicate that WASS correction can improve activation detection by 17% relative to MSV only correction.

Concurrent correction of geometric distortion and motion using the map-slice-to-volume method in echo-planar imaging.

The accuracy of measuring voxel intensity changes between stimulus and rest images in fMRI echo-planar imaging (EPI) data is severely degraded in the presence of head motion. In addition, EPI is sensitive to susceptibility-induced geometric distortions. Head motion causes image shifts and associated field map changes that induce different geometric distortion at different time points. Conventionally, geometric distortion is "corrected" with a static field map independently of image registration. That approach ignores all field map changes induced by head motion. This work evaluates the improved motion correction capability of mapping slice to volume with concurrent iterative field corrected reconstruction using updated field maps derived from an initial static field map that has been spatially transformed and resampled. It accounts for motion-induced field map changes for translational and in-plane rotation motion. The results from simulated EPI time series data, in which motion, image intensity and activation ground truths are available, show improved accuracy in image registration, field corrected image reconstruction and activation detection.

Comprehensive mathematical simulation of functional magnetic resonance imaging time series including motion-related image distortion and spin saturation effect.

There has been vast interest in determining the feasibility of functional magnetic resonance imaging (fMRI) as an accurate method of imaging brain function for patient evaluations. The assessment of fMRI as an accurate tool for activation localization largely depends on the software used to process the time series data. The performance evaluation of different analysis tools is not reliable unless truths in motion and activation are known. Lack of valid truths has been the limiting factor for comparisons of different algorithms. Until now, currently available phantom data do not include comprehensive accounts of head motion. While most fMRI studies assume no interslice motion during the time series acquisition in fMRI data acquired using a multislice and single-shot echo-planar imaging sequence, each slice is subject to a different set of motion parameters. In this study, in addition to known three-dimensional motion parameters applied to each slice, included in the time series computation are geometric distortion from field inhomogeneity and spin saturation effect as a result of out-of-plane head motion. We investigated the effect of these head motion-related artifacts and present a validation of the mapping slice-to-volume (MSV) algorithm for motion correction and activation detection against the known truths. MSV was evaluated, and showed better performance in comparison with other widely used fMRI data processing software, which corrects for head motion with a volume-to-volume realignment method. Furthermore, improvement in signal detection was observed with the implementation of the geometric distortion correction and spin saturation effect compensation features in MSV.

Zero and first-order phase shift correction for field map estimation with dual-echo GRE using bipolar gradients.

A simple phase error correction technique used for field map estimation with a generally available dual-echo gradient-echo (GRE) sequence is presented. Magnetic field inhomogeneity maps estimated using two separate GRE volume acquisitions at different echo times are prone to dynamic motion errors between acquisitions. By using the dual-echo sequence, the data are collected during two back-to-back readout gradients in opposite polarity after a single radio frequency pulse, and interecho motion artifacts and alignment errors in field map estimation can be factored out. Residual phase error from the asymmetric readout pulses is modeled as an affine term in the readout direction. Results from phantom and human data suggest that the first-order phase correction term stays constant over time and, hence, can be applied to different data acquired with the same protocol over time. The zero-order phase correction term may change with time and is estimated empirically for different scans.

Improved map-slice-to-volume motion correction with B0 inhomogeneity correction: validation of activation detection algorithms using ROC curve analyses.

Head motion is a significant source of error in fMRI activation detection and a common approach is to apply 3D volumetric rigid body motion correction techniques. However, in 2D multislice fMRI, each slice may have a distinct set of motion parameters due to inter-slice motion. Here, we apply an automated mutual information based slice-to-volume rigid body registration technique on time series data synthesized from a T2 MRI brain dataset with simulated motion, functional activation, noise and geometric distortion. The map-slice-to-volume (MSV) technique was previously applied to patient data without ground truths for motion and activation regions. In this study, the activation images and area under the receiver operating characteristic curves for various time series datasets indicate that the MSV registration improves the activation detection capability when compared to results obtained from Statistical Parametric Mapping (SPM). The effect of temporal median filtering of motion parameters on activation detection performance was also investigated.

Evaluation of (E)-2'-deoxy-2'-(fluoromethylene)cytidine on the 9L rat brain tumor model using MRI.

(E)-2'-deoxy-2'-(fluoromethylene)cytidine (FMdC), was evaluated as a potential treatment for malignant gliomas using the rat 9L brain tumor model. FMdC was shown to be an effective inhibitor of cell proliferation in cultured 9L cells with an EC(50) of 40 ng/ml. In vitro studies also revealed that this compound significantly inhibited incorporation of [(3)H]thymidine in 9L cells. In vivo therapeutic efficacy of FMdC was evaluated in rats harboring intracerebral 9L tumors which were treated daily with 15 mg/kg, i.p. Treatment response was quantified from changes in tumor growth rates as assessed from sequential magnetic resonance imaging (MRI) tumor volume measurements. In vivo tumor cell kill in individual animals was calculated by fitting tumor volume data with an iterative computer routine. It was estimated that therapeutically responsive rats treated with FMdC daily produced a >/= 0.1 log kill per therapeutic dose which resulted in a significant reduction in tumor growth rate. In addition, localized (1)H-MRS of intracerebral 9L tumors revealed changes in metabolite levels which correlated with therapeutic response. These results provide evidence supporting the use of FMdC in clinical trials for the treatment of malignant gliomas and reveals that MR can play an important role in the pre-clinical evaluation of novel compounds using orthotopic tumor models.

Magnetic Resonance Imaging and Spectroscopy: Application to Experimental Neuro-Oncology.

The development and use of animal brain tumor models over the past 25 years has helped to advance our understanding of both tumor biology and the effectiveness of new therapeutic approaches. The application of MRI and MRS as noninvasive tools for in vivo studies of intracerebral tumor models provides unique possibilities for furthering our knowledge of brain cancer. This article provides a brief background of traditional techniques used to evaluate growth and treatment efficacy in rodent brain tumor models and overviews the use of MR for quantitating intracerebral tumor growth kinetics and therapeutic response of experimental brain tumors from work conducted in this laboratory. The application of MRI and MRS in rodent brain tumor models for evaluation of novel therapeutic approaches, including gene transfer technology, is discussed. Finally, initial results with diffusion MRI for monitoring the treatment of brain tumors is introduced.