SungWon Chung

Diffusion Tensor MR Imaging and Fiber Tractography: Theoretic Underpinnings

SUMMARY: In this article, the underlying theory of clinical diffusion MR imaging, including diffusion tensor imaging (DTI) and fiber tractography, is reviewed. First, a brief explanation of the basic physics of diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping is provided. This is followed by an overview of the additional information that can be derived from the diffusion tensor, including diffusion anisotropy, color-encoded fiber orientation maps, and 3D fiber tractography. This article provides the requisite background for the second article in this 2-part review to appear next month, which covers the major technical factors that affect image quality in diffusion MR imaging, including the acquisition sequence, magnet field strength, gradient amplitude and slew rate, and multichannel radio-frequency coils and parallel imaging. The emphasis is on optimizing these factors for state-of-the-art DWI and DTI based on the best available evidence in the literature.

Diffusion tensor MR imaging and fiber tractography: technical considerations.

SUMMARY:This second article of the 2-part review builds on the theoretic background provided by the first article to cover the major technical factors that affect image quality in diffusion imaging, including the acquisition sequence, magnet field strength, gradient amplitude, and slew rate as well as multichannel radio-frequency coils and parallel imaging. The sources of many common diffusion image artifacts are also explored in detail. The emphasis is on optimizing these technical factors for state-of-the-art diffusion-weighted imaging and diffusion tensor imaging (DTI) based on the best available evidence in the literature. An overview of current methods for quantitative analysis of DTI data and fiber tractography in clinical research is also provided.

Accuracy of diffusion tensor magnetic resonance imaging tractography assessed using intraoperative subcortical stimulation mapping and magnetic source imaging

OBJECT Resecting brain tumors involves the risk of damaging the descending motor pathway. Diffusion tensor (DT)-imaged fiber tracking is a noninvasive magnetic resonance (MR) technique that can delineate the subcortical course of the motor pathway. The goal of this study was to use intraoperative subcortical stimulation mapping of the motor tract and magnetic source imaging to validate the utility of DT-imaged fiber tracking as a tool for presurgical planning. METHODS Diffusion tensor-imaged fiber tracks of the motor tract were generated preoperatively in nine patients with gliomas. A mask of the resultant fiber tracks was overlaid on high-resolution T1- and T2-weighted anatomical MR images and used for stereotactic surgical navigation. Magnetic source imaging was performed in seven of the patients to identify functional somatosensory cortices. During resection, subcortical stimulation mapping of the motor pathway was performed within the white matter using a bipolar electrode. RESULTS A total of 16 subcortical motor stimulations were stereotactically identified in nine patients. The mean distance between the stimulation sites and the DT-imaged fiber tracks was 8.7 +/- 3.1 mm (+/- standard deviation). The measured distance between subcortical stimulation sites and DT-imaged fiber tracks combines tracking technique errors and all errors encountered with stereotactic navigation. CONCLUSIONS Fiber tracks delineated using DT imaging can be used to identify the motor tract in deep white matter and define a safety margin around the tract.

Probabilistic streamline q-ball tractography using the residual bootstrap.

Q-ball imaging has the ability to discriminate multiple intravoxel fiber populations within regions of complex white matter architecture. This information can be used for fiber tracking; however, diffusion MR is susceptible to noise and multiple other sources of uncertainty affecting the measured orientation of fiber bundles. The proposed residual bootstrap method utilizes a spherical harmonic representation for high angular resolution diffusion imaging (HARDI) data in order to estimate the uncertainty in multimodal q-ball reconstructions. The accuracy of the q-ball residual bootstrap technique was examined through simulation. The residual bootstrap method was then used in combination with q-ball imaging to construct a probabilistic streamline fiber tracking algorithm. The residual bootstrap q-ball fiber tracking algorithm is capable of following the corticospinal tract and corpus callosum through regions of crossing white matter tracts in the centrum semiovale. This fiber tracking algorithm is an improvement upon prior diffusion tensor methods and the q-ball data can be acquired in a clinically feasible time frame.

Comparison of bootstrap approaches for estimation of uncertainties of DTI parameters.

Bootstrap is an empirical non-parametric statistical technique based on data resampling that has been used to quantify uncertainties of diffusion tensor MRI (DTI) parameters, useful in tractography and in assessing DTI methods. The current bootstrap method (repetition bootstrap) used for DTI analysis performs resampling within the data sharing common diffusion gradients, requiring multiple acquisitions for each diffusion gradient. Recently, wild bootstrap was proposed that can be applied without multiple acquisitions. In this paper, two new approaches are introduced called residual bootstrap and repetition bootknife. We show that repetition bootknife corrects for the large bias present in the repetition bootstrap method and, therefore, better estimates the standard errors. Like wild bootstrap, residual bootstrap is applicable to single acquisition scheme, and both are based on regression residuals (called model-based resampling). Residual bootstrap is based on the assumption that non-constant variance of measured diffusion-attenuated signals can be modeled, which is actually the assumption behind the widely used weighted least squares solution of diffusion tensor. The performances of these bootstrap approaches were compared in terms of bias, variance, and overall error of bootstrap-estimated standard error by Monte Carlo simulation. We demonstrate that residual bootstrap has smaller biases and overall errors, which enables estimation of uncertainties with higher accuracy. Understanding the properties of these bootstrap procedures will help us to choose the optimal approach for estimating uncertainties that can benefit hypothesis testing based on DTI parameters, probabilistic fiber tracking, and optimizing DTI methods.

Connecting white matter injury and thalamic atrophy in clinically isolated syndromes

Previous studies suggest that thalamic degeneration is prominent in multiple sclerosis (MS) and even in pre-MS patients presenting with a clinically isolated syndrome (CIS). However, the relationships between white matter lesions and deep grey matter loss are not well understood. We analyzed the association between white matter lesions and the thalami in CIS patients to determine if connectivity is an important determinant. We studied 24 CIS patients and 18 normal controls with anatomical and diffusion tensor (DTI) MRI images. DTI fiber tracking was used to create probabilistic templates of the thalamocortical white matter and to define white matter connecting lesions and thalami. DTI metrics in the lesions and normal-appearing white matter (NAWM) regions were compared between CIS and controls, and correlated with thalamic volume changes estimated by voxel-based morphometry. There was 10 times higher density of lesions in thalamocortical compared to other brain white matter. Increased diffusivities and decreased fractional anisotropies were measured in the thalamocortical NAWM of CIS patients compared to controls. A step-wise regression analysis demonstrated that thalamocortical lesion volume and the mean diffusivity in track regions connecting lesion and thalami were significantly correlated with thalamic volumes in patients (Rsq=0.66, p<0.001), a finding not observed in regions outside the thalamocortical white matter. These results provide compelling evidence for a direct relationship between white matter lesions and thalamic atrophy in CIS patients.

Diffusion Tensor MR Imaging Tractography of the Pyramidal Tracts Correlates with Clinical Motor Function in Children with Congenital Hemiparesis

BACKGROUND AND PURPOSE: Children with congenital hemiparesis have greater asymmetry in diffusion parameters of the pyramidal tracts compared with control subjects. We hypothesized that the asymmetry correlates with the severity of hemiparesis and that diffusion metrics would be abnormal in the affected tracts and normal in the unaffected tracts. MATERIALS AND METHODS: Fifteen patients with congenital hemiparesis and 17 age-matched control subjects were studied with diffusion tensor MR imaging tractography. Hemipareses were scored as mild, moderate, or severe. We measured tract-specific diffusion parameters (fractional anisotropy, mean, and directional diffusion coefficients) of the pyramidal tracts. We compared tract-specific parameters and asymmetry between the right and left tracts of the differing severity groups and control subjects. RESULTS: We observed many different causes of congenital hemiparesis including venous infarction, arterial infarction, and polymicrogyria. Clinical severity of hemiparesis correlated with asymmetry in fractional anisotropy (P < .0001), transverse diffusivity (P < .0001), and mean diffusivity (P < .03). With increasing severity of hemiparesis, fractional anisotropy decreased (P < .0001) and transverse diffusivity (P < .0001) and mean diffusivity (P < .02) increased in the affected pyramidal tract compared with controls. Diffusion metrics in the unaffected tract were similar to those in the control subjects. CONCLUSION: Asymmetry in fractional anisotropy, transverse diffusivity, and mean diffusivity, as well as the degree of abnormality in the actual values of the affected pyramidal tracts themselves, correlates with the severity of motor dysfunction in infants and children with congenital hemiparesis from different causes. This suggests that abnormalities detected by diffusion tensor MR imaging tractography in the affected pyramidal tract are related to the functional ability of the affected pyramidal tract, regardless of the etiology of motor dysfunction.

Diffusion-weighted imaging of the fetal brain in vivo

A method of performing diffusion‐weighted imaging (DWI) and diffusion tensor imaging (DTI) of the fetal brain in utero is proposed. The major difficulty of performing diffusion imaging in utero is the presence of motion. By modifying conventional single‐shot spin‐echo echo‐planar DWI with a short repetition time sequence, a sequence that performs DWI and DTI within a breath‐hold of the mother (13 sec and 18 sec, respectively) was devised. T1 weighting caused by the use of short repetition times is compensated by interspersing diffusion imaging with additional b=0 image acquisitions. In utero fetal brain DWI and DTI were performed using this sequence. Quantitative analysis revealed minimal differences in the obtained apparent diffusion coefficient (ADC; directionally averaged ADC) values when using this sequence. The method can be readily implemented in a clinical setting and is especially useful when scanning mothers who cannot tolerate lengthier breath‐holds. Magn Reson Med, 2007.

Whole brain voxel-wise analysis of single-subject serial DTI by permutation testing.

Diffusion tensor MRI (DTI) has been widely used to investigate brain microstructural changes in pathological conditions as well as for normal development and aging. In particular, longitudinal changes are vital to the understanding of progression but these studies are typically designed for specific regions of interest. To analyze changes in these regions traditional statistical methods are often employed to elucidate group differences which are measured against the variability found in a control cohort. However, in some cases, rather than collecting multiple subjects into two groups, it is necessary and more informative to analyze the data for individual subjects. There is also a need for understanding changes in a single subject without prior information regarding the spatial distribution of the pathology, but no formal statistical framework exists for these voxel-wise analyses of DTI. In this study, we present PERVADE (permutation voxel-wise analysis of diffusion estimates), a whole brain analysis method for detecting localized FA changes between two separate points in time of any given subject, without any prior hypothesis about where changes might occur. Exploiting the nature of DTI that it is calculated from multiple diffusion-weighted images of each region, permutation testing, a non-parametric hypothesis testing technique, was modified for the analysis of serial DTI data and implemented for voxel-wise hypothesis tests of diffusion metric changes, as well as for suprathreshold cluster analysis to correct for multiple comparisons. We describe PERVADE in detail and present results from Monte Carlo simulation supporting the validity of the technique as well as illustrative examples from a healthy subject and patients in the early stages of multiple sclerosis.

Bootstrap quantification of cardiac pulsation artifact in DTI

While several studies have shown the benefit of cardiac gating in diffusion MRI with single-shot EPI acquisition, cardiac gating is still not commonly used. This is probably because it requires additional time and many investigators may not be convinced that cardiac gating is worth the extra effort. Here, we tested a clinically feasible protocol with a minimal increase in scan time, and quantified the effect of cardiac gating under partial or full Fourier acquisition. Eight volunteers were scanned on a 3 T scanner with a SENSE 8-channel head coil. Diffusion-weighted, single-shot spin-echo EPI images were acquired along 32 gradient directions, with or without cardiac gating and with partial or full Fourier acquisition. Vectorcardiography (VCG) was used to trigger acquisition at a minimum delay (30 ms). The uncertainties of DTI derived parameters were estimated using residual bootstrap. With partial Fourier, cardiac gating reduced the uncertainties, and better efficiency in reducing DTI parameter variability was also achieved even allowing for the increase in total scan time. For full Fourier acquisition, minimum time gating slightly decreased the uncertainties but the efficiency was worse. A minimum trigger delay might not be the optimal scheme to avoid the majority of systole but it allows clinically acceptable scan times. We have demonstrated that cardiac gating, especially of partial Fourier acquisitions, can reduce the uncertainties of DTI derived parameters in a time-efficient manner.