K-Space Characteristics & MRI Image Production PDF
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University of Jeddah
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This document is about k-space characteristics, filling, and signal amplitude in magnetic resonance imaging (MRI). It elucidates how data acquisition in MRI is related to creating images, details the factors influencing signal-to-noise ratios, spatial resolution, and scan times.
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K space K space characteristics K space is an area where data collected from the signal are stored. The unit of K space is radiants per cm. K space is rectangular and has two axes; 1. Frequency axis (centered in the middle of K space and perpendicular to the phase axis). 2. Phase axis (center...
K space K space characteristics K space is an area where data collected from the signal are stored. The unit of K space is radiants per cm. K space is rectangular and has two axes; 1. Frequency axis (centered in the middle of K space and perpendicular to the phase axis). 2. Phase axis (centered in the middle of a series of horizontal lines) Every time a frequency or phase encoding is performed, data are collected and stored in a line of K space. This data is later processed to produce an image of the patient. 5 K space filling and signal amplitude Phase axis In order to fill out different lines of K space, the slope of the phase encoding gradient must be altered after each TR. The central lines of K space are filled with data produced after the application of shallow phase encoding gradient slopes. The outer lines are filled with data produced after the application of the steep phase encoding gradient slopes. The lines in-between the central and outer portions are filled with the intermediate phase encoding slopes. 8 Frequency axis: Frequencies sampled from the signal are mapped into K space relative to the frequency axis. The center of the echo represent the maximum signal amplitude (all magnetic moments are in phase at this point). The signal amplitude on either sides is less (magnetic moments are either rephasing or dephasing) 10 K space filling and spatial resolution The outer lines of K.s contain data produced after steep phase encoding gradient slopes. The number of phase encodings performed determines the number of pixels in the FOV along the phase encoding axis. Large number of phase encoding performed more pixels in the FOV along the phase axis. If the field FOV is fixed, pixels of smaller dimensions high spatial resolution image. Data collected after steep phase encoding gradient slopes have greater spatial resolution in the image. 11 Remember The outer lines of K space contain data with a high spatial resolution as they are filled by steep phase encoding gradient slopes. The central lines of K space contain data with a low spatial resolution as they are filled by shallow phase encoding gradient slopes. The outer portion of K space contains data that have low signal amplitude and high spatial resolution. The central portion of K space contains data that have high signal amplitude and low spatial resolution. 12 Image Production &Data acquisition The information obtained from the encoding process has to be translated onto the image. The image consists of a field of view (FOV) that relates to the amount of anatomy covered. The FOV is divided up into pixels or picture elements. The pixels exist within a two dimensional grid or matrix into which the system maps each individual signal. The number of pixels within the FOV depends on the number of frequency samples and phase encoding performed. 14 Each pixel is allocated a signal intensity, depending on the signal amplitude, with a distinct and phase shift value. This is performed by a mathematical process known as Fast Fourier Transform (FFT). During FFT the system converts this raw data so that the signal amplitude is measured relative to its frequency. This enables the creation of an image, where each pixel is allocated a signal intensity corresponding to the amplitude of signal originating from the anatomy at the position of each pixel in the matrix. For more information go to Reference (MRI at a Glance) - k space and data acquisition. 15 Signal to noise ratio (SNR) • The noise represents frequencies that exist randomly in space and time. • The noise is constant for every patient and depends on the build of the patient, the area under examination and the inherent noise of the system. • Signal to noise ratio (SNR) is the ratio of the amplitude of the signal received to the average amplitude of the noise. 19 The factors affect the SNR 1. Magnetic field strength of the system. 2.Proton density of the area under examination. 3.Voxel volume. 4.TR, TE and flip angel. 5.Number of signal averages (NEX). 6.Receiver bandwidth. 7.Coil type. 1- Magnetic field strength • As the field strength increase, so the energy gap between low and high energy nuclei increase. • Fewer nuclei have enough energy to align in opposite to B0. • Therefore, the number of spin-up nuclei increase relative to the number of spin down nuclei. • The NMV therefore increases in size at higher field strength and as a result there is more available magnetization to image the patient. • SNR is increase. 21 TR, TE and flip angel Number of excitation (NEX) • This is the number of times data are collected with the same amplitude of the phase encoding slope (the number of signal averages). • The NEX controls the amount of data that is sorted in each line of K-space. • Doubling the NEX therefore doubles the amount of data that is sorted in each line of Kspace. • The data contain both signal and noise. • To double the SNR we need to increase the NEX and the scan time by factor of four. 29 Receiver bandwidth • This is the range of frequencies that are sampled during the application of the readout gradient. • Reducing the receiver bandwidth results in less noise being sampled relative to signal because noise is occurs at all frequencies and randomly in all time. • The SNR increase as the receiver bandwidth is decreases. 31 To optimizing the image quality the SNR must be highest as possible. To achieve this: The voxel size is affected by these factors.