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Nan-Kuei Chen

Publications and source records attributed to Nan-Kuei Chen.

7 recordsLinked to original sources

76-space analysis of grey matter diffusivity: methods and applications.

Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) allow in vivo investigation of molecular motion of tissue water at a microscopic level in cerebral gray matter (GM) and white matter (WM). DWI/DTI measure of water diffusion has been proven to be invaluable for the study of many neurodegenerative diseases (e.g., Alzheimer's disease and Creutzfeldt-Jakob disease) that predominantly involve GM. Thus, quantitative analysis of GM diffusivity is of scientific interest and is promised to have a clinical impact on the investigation of normal brain aging and neuropathology. In this paper, we propose an automated framework for analysis of GM diffusivity in 76 standard anatomic subdivisions of gray matter to facilitate studies of neurodegenerative and other gray matter neurological diseases. The computational framework includes three enabling technologies: (1) automatic parcellation of structural MRI GM into 76 precisely defined neuroanatomic subregions ("76-space"), (2) automated segmentation of GM, WM and CSF based on DTI data, and (3) automatic measurement of the average apparent diffusion coefficient (ADC) in each segmented GM subregion. We evaluate and validate this computational framework for 76-space GM diffusivity analysis using data from normal volunteers and from patients with Creutzfeldt-Jakob disease.

Adult↗

Computation of transmitted and received B1 fields in magnetic resonance imaging.

Computation of B1 fields is a key issue for determination and correction of intensity nonuniformity in magnetic resonance images. This paper presents a new method for computing transmitted and received B1 fields. Our method combines a modified MRI acquisition protocol and an estimation technique based on the Levenberg-Marquardt algorithm and spatial filtering. It enables accurate estimation of transmitted and received B1 fields for both homogeneous and heterogeneous objects. The method is validated using numerical simulations and experimental data from phantom and human scans. The experimental results are in agreement with theoretical expectations.

Algorithms↗

Functional MRI using regularized parallel imaging acquisition.

Parallel MRI techniques reconstruct full-FOV images from undersampled k-space data by using the uncorrelated information from RF array coil elements. One disadvantage of parallel MRI is that the image signal-to-noise ratio (SNR) is degraded because of the reduced data samples and the spatially correlated nature of multiple RF receivers. Regularization has been proposed to mitigate the SNR loss originating due to the latter reason. Since it is necessary to utilize static prior to regularization, the dynamic contrast-to-noise ratio (CNR) in parallel MRI will be affected. In this paper we investigate the CNR of regularized sensitivity encoding (SENSE) acquisitions. We propose to implement regularized parallel MRI acquisitions in functional MRI (fMRI) experiments by incorporating the prior from combined segmented echo-planar imaging (EPI) acquisition into SENSE reconstructions. We investigated the impact of regularization on the CNR by performing parametric simulations at various BOLD contrasts, acceleration rates, and sizes of the active brain areas. As quantified by receiver operating characteristic (ROC) analysis, the simulations suggest that the detection power of SENSE fMRI can be improved by regularized reconstructions, compared to unregularized reconstructions. Human motor and visual fMRI data acquired at different field strengths and array coils also demonstrate that regularized SENSE improves the detection of functionally active brain regions.

Brain Mapping↗

PROPELLER EPI: an MRI technique suitable for diffusion tensor imaging at high field strength with reduced geometric distortions.

A technique suitable for diffusion tensor imaging (DTI) at high field strengths is presented in this work. The method is based on a periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) k-space trajectory using EPI as the signal readout module, and hence is dubbed PROPELLER EPI. The implementation of PROPELLER EPI included a series of correction schemes to reduce possible errors associated with the intrinsically higher sensitivity of EPI to off-resonance effects. Experimental results on a 3.0 Tesla MR system showed that the PROPELLER EPI images exhibit substantially reduced geometric distortions compared with single-shot EPI, at a much lower RF specific absorption rate (SAR) than the original version of the PROPELLER fast spin-echo (FSE) technique. For DTI, the self-navigated phase-correction capability of the PROPELLER EPI sequence was shown to be effective for in vivo imaging. A higher signal-to-noise ratio (SNR) compared to single-shot EPI at an identical total scan time was achieved, which is advantageous for routine DTI applications in clinical practice.

Algorithms↗

76-space analysis of grey matter diffusivity: methods and applications.

Diffusion Weighted Imaging (DWI) and Diffusion Tensor Imaging (DTI) are widely used in the study and diagnosis of neurological diseases involving the White Matter (WM). However, many neurological and neurodegenerative diseases (e.g., Alzheimer's disease and Creutzfeldt-Jakob disease) are generally considered to involve the Grey Matter (GM). Investigation of GM diffusivity of normal aging and pathological brains has both scientific significance and clinical applications. Most of previous research reports on quantification of GM diffusivity were based on the manually labeled Region of Interests (ROI) analysis of specific neuroanatomic regions. The well-known drawbacks of ROI analysis include inter-rater variations, irreproducible results, tediousness, and requirement of a priori definition of interested regions. In this paper, we present a new framework of automated 76-space analysis of GM diffusivity using DWI/DTI. The framework will be evaluated using clinical data, and applied for study of normal brain, Creutzfeldt-Jakob disease and Schizophrenia.

Algorithms↗

Brain-computer interface using fMRI: spatial navigation by thoughts.

A brain-computer interface (BCI) is a way of conveying an individual's thoughts to control computer or electromechanical hardware. Capitalizing on the ability to characterize brain activity in a reproducible manner, we explored the possibility of using real-time fMRI to interpret the spatial distribution of brain function as BCI commands. Using a high-field (3T) MRI scanner, brain activities associated with four distinct covert functional tasks were detected and subsequently translated into predetermined computer commands for moving four directional cursors. The proposed fMRI-BCI method allowed volunteer subjects to navigate through a simple 2D maze solely through their thought processes.

Adult↗

Selection of voxel size and slice orientation for fMRI in the presence of susceptibility field gradients: application to imaging of the amygdala.

The impact of voxel geometry on the blood oxygenation level-dependent (BOLD) signal detectability in the presence of field inhomogeneity is assessed and a quantitative approach to selecting appropriate voxel geometry is developed in this report. Application of the developed technique to BOLD sensitivity improvement of the human amygdala is presented. Field inhomogeneity was measured experimentally at 1.5 T and 3 T and the dominant susceptibility field gradient in the human amygdala was observed approximately along the superior-inferior direction. Based on the field mapping studies, an optimal selection for the slice orientation would be an oblique pseudo-coronal plane with its frequency-encoding direction parallel to the field gradient measured from each subject. Experimentally this was confirmed by comparing the normalized standard deviation of time-series echo-planar imaging signals acquired with different slice orientations, in the absence of a functional stimulus. A further confirmation with a carefully designed functional magnetic resonance imaging study is needed. Although the BOLD sensitivity may generally be improved by a voxel size commensurable with the activation volume, our quantitative analysis shows that the optimal voxel size also depends on the susceptibility field gradient and is usually smaller than the activation volume. The predicted phenomenon is confirmed with a hybrid simulation, in which the functional activation was mathematically added to the experimentally acquired rest-period echo-planar imaging data.

Adult↗