Browsing by Author "Alhamud, Alkathafi Ali"

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    Implementation of anatomical navigators for real time motion correction in diffusion tensor imaging
    (2012) Alhamud, Alkathafi Ali; Van der Kouwe, Andre; Meintjes, Ernesta
    Prospective motion correction methods using an optical system, diffusion-weighted prospective acquisition correction, or a free induction decay navigator have recently been applied to correct for motion in diffusion tensor imaging. These methods have some limitations and drawbacks. This article describes a novel technique using a three-dimensional-echo planar imaging navigator, of which the contrast is independent of the b-value, to perform prospective motion correction in diffusion weighted images, without having to reacquire volumes during which motion occurred, unless motion exceeded some preset thresholds. Water phantom and human brain data were acquired using the standard and navigated diffusion sequences, and the mean and whole brain histogram of the fractional anisotropy and mean diffusivity were analyzed.
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    Real-time motion and magnetic field correction for GABA editing using EPI volumetric navigated MEGA-SPECIAL sequence: Reproducibility and Gender effects
    (2016) Saleh, Muhammad G; Meintjies, Ernesta; Alhamud, Alkathafi Ali
    γ-aminobutyric acid (GABA) is the primary inhibitory neurotransmitter and is of great interest to the magnetic resonance spectroscopy (MRS) community due to its role in several neurological diseases and disorders. Since GABA acquisition without macromolecule contamination requires long scan times and strongly depends on magnetic field (B0) stability, it is highly susceptible to motion and B0 inhomogeneity. In this work, a pair of three-dimensional (3D) echo planar imaging (EPI) volumetric navigators (vNav) with different echo times, were inserted in MEGA-SPECIAL to perform prospective correction for changes in the subject's head position and orientation, as well as changes in B0. The navigators do not increase acquisition time and have negligible effect on the GABA signal. The motion estimates are obtained by registering the first of the pairs of successive vNav volume images to the first volume image. The 3D field maps are calculated through complex division of the pair of vNav contrasts and are used for estimating zero- and first-order shim changes in the volume of interest (VOI). The efficacy of the vNav MEGA-SPECIAL sequence was demonstrated in-vitro and in vivo. Without motion and shim correction, spectral distortions and increases in spectral fitting error, linewidth and GABA concentration relative to creatine were observed in the presence of motion. The navigated sequence yielded high spectral quality despite significant subject motion. Using the volumetric navigated MEGA-SPECIAL sequence, the reproducibility of GABA measurements over a 40 minute period was investigated in two regions, the anterior cingulate (ACC) and medial parietal (PAR) cortices, and compared for different analysis packages, namely LCModel, jMRUI and GANNET. LCModel analysis yielded the most reproducible results, followed by jMRUI and GANNET. GABA levels in ACC were unchanged over time, while GABA levels in PAR were significantly lower for the second measurement. In ACC, GABA levels did not differ between males and females. In contrast, males had higher GABA levels in PAR. This gender difference was, however, only present in the first acquisition. Only in males did GABA levels in PAR decrease over time. These results demonstrate that gender differences are regional, and that GABA levels may fluctuate differently in different regions and sexes.
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    Simultaneous DTI and rs-fMRI using the navigated diffusion sequence
    (2016) Mofya, Mwape; Meintjes, Ernesta M; Alhamud, Alkathafi Ali; Taylor, Paul A
    Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) experiments are normally performed separately. The idea of extracting inherently co-registered activation/connectivity maps and diffusion parameters has resulted in efforts to develop methods for simultaneous fMRI and DTI data acquisition. Recently, a 3D echo planar imaging (EPI) acquisition was successfully inserted after each DTI volume to perform real-time motion correction, with the two sequence protocols remaining separate. We examined using a single 3D EPI acquisition, inserted following each DTI volume acquisition (hereafter called the single nav sequence), modified to acquire BOLD resting state fMRI (rs-fMRI) data. We also investigated inserting a second 3D EPI acquisition in the middle of each DTI volume acquisition (hereafter called the double nav sequence) to increase fMRI temporal resolution. Two adult subjects were scanned with the navigated sequences and the standard separate 2D EPI BOLD and DTI acquisitions for comparison. Preprocessing and analysis of data was performed using FATCAT, AFNI , FSL and in-house Python scripts. Four standard resting state networks (RSNs) were visually identified using the navigated diffusion sequences. While RSNs were apparent in the single nav case, they were quite noisy and in some cases entire regions did not show connectivity. The double nav connectivity maps were more similar to the standard BOLD connectivity maps in terms of the spatial extent of the regions showing connectivity to the seed. The whole brain distributions of fractional anisotropy (FA) and mean diffusivity (MD) were similar among the different acquisition protocols. The jackknife standard error was comparable between the navigated and standard protocols. Further comparisons of diffusion data made using probabilistic tractography and connectivity matrices showed overall small differences indicating that connections derived from the standard DTI, single nav and double nav protocols were overall similar. We have therefore shown a significant "proof of concept" of successfully acquiring simultaneous DTI and rs-fMRI data, and therefore for investigating brain structural and functional connectivity simultaneously.
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    The use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord
    (2005) Alhamud, Alkathafi Ali; Capper, Wayne; Vaughan, Christopher Leonard (Kit)
    Present-day obstetric decision-making is based on measuring the umbilical arterial blood flow velocity waveforms from one site of the cord. There is an ongoing debate on the predictive value of Doppler measurements in the evaluation of the foetal condition. The aim of this thesis is to investigate the use ofa neural network to recognise blood flow waveform shape patterns associated with placental insufficiency. Eleven backpropagation neural networks have been developed and trained based on the waveforms that are generated from the foetal mathematical model (developed in previous research) at both ends of the cord. Only two networks trained successfully. These two networks are the Levenberg-Marquardt algorithm (Trainlm) and the resilient backpropagation algorithm (Trainrp).