Publications by authors named "Minzhi Gui"

This study introduces a practical four-dimensional (4D) planning scheme of IMAT using 4D computed tomography (4D CT) for planning tumor tracking with dynamic multileaf beam collimation. We assume that patients can breathe regularly, i.e.

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Purpose: Dose-rate-regulated tracking (DRRT) is a tumor tracking strategy that programs the MLC to track the tumor under regular breathing and adapts to breathing irregularities during delivery using dose rate regulation. Constant-dose-rate tracking (CDRT) is a strategy that dynamically repositions the beam to account for intrafractional 3D target motion according to real-time information of target location obtained from an independent position monitoring system. The purpose of this study is to illustrate the differences in the effectiveness and delivery accuracy between these two tracking methods in the presence of breathing irregularities.

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Purpose: The authors have developed a novel technique using an electronic portal imaging device (EPID) to verify the geometrical accuracy of delivery of dose-rate-regulated tracking (DRRT). This technique, called verification of real-time tracking with EPID (VORTE), can potentially be used for both on-line and off-line quality assurance (QA) of MLC-based dynamic tumor tracking.

Methods: The shape and position of target as a function of time, which is assumed to be known, is projected onto the EPID plane.

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Purpose: To investigate an iterative image reconstruction algorithm using the nonuniform fast Fourier transform (NUFFT) for PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) MRI.

Materials And Methods: Numerical simulations, as well as experiments on a phantom and a healthy human subject were used to evaluate the performance of the iterative image reconstruction algorithm for PROPELLER, and compare it with that of conventional gridding. The trade-off between spatial resolution, signal to noise ratio, and image artifacts, was investigated for different values of the regularization parameter.

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Purpose: Planning for the delivery of intensity-modulated radiation therapy (IMRT) to a moving target, referred to as four-dimensional (4D) IMRT planning, is a crucial step for achieving the treatment objectives for sites that move during treatment delivery. The authors proposed a simplistic method that accounts for both rigid and nonrigid respiration-induced target motion based on 4D computed tomography (4DCT) data sets.

Methods: A set of MLC apertures and weights was first optimized on a reference phase of a 4DCT data set.

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The development of accurate, non-invasive methods for mapping white matter fiber-tracts is of critical importance. However, fiber-tracking is typically performed on diffusion tensor imaging (DTI) data obtained with echo-planar-based imaging techniques (EPI), which suffer from susceptibility-related image artifacts, and image warping due to eddy-currents. Thus, a number of white matter fiber-bundles mapped using EPI-based DTI data are distorted and/or terminated early.

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Purpose: To assess the effects of cardiac-induced brain pulsation on the noise of the diffusion tensor in Turboprop (a form of periodically rotated overlapping parallel lines with enhanced reconstruction [PROPELLER] imaging) diffusion tensor imaging (DTI).

Materials And Methods: A total of six healthy human subjects were imaged with cardiac-gated as well as nongated Turboprop DTI. Gated and nongated Turboprop DTI datasets were also simulated using actual data acquired exclusively during the diastolic or systolic period of the cardiac cycle.

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Accurate localization of white matter fiber tracts in relation to brain tumors is a goal of critical importance to the neurosurgical community. White matter fiber tractography by means of diffusion tensor magnetic resonance imaging (DTI) is the only non-invasive method that can provide estimates of brain connectivity. However, conventional tractography methods are based on data acquisition techniques that suffer from image distortions and artifacts.

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White matter fiber-tractography by means of diffusion tensor imaging (DTI) is a noninvasive technique that provides estimates of the structural connectivity of the brain. However, conventional fiber-tracking methods using DTI are based on echo-planar image acquisitions (EPI), which suffer from image distortions and artifacts due to magnetic susceptibility variations and eddy currents. Thus, a large percentage of white matter fiber bundles that are mapped using EPI-based DTI data are distorted, and/or terminated early, while others are completely undetected.

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