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Introducing MRI Parallel Imaging

23 June, 2011 | MRI

MRI Parallel ImagingHow is MRI Parallel Imaging Used?

MRI parallel imaging utilizes the multiple elements of phased array coil system. Each element of the coil system is associated with a dedicated radio frequency channel (a special single-channel radio receiver) whose output is processed and combined with the outputs of the other channels (signals acquired by the other coil elements). This technology improves the signal–to-noise ratio (the signal quality) as compared to a standard MRI scanner coil system; while covering the same explored body volume.

The spatial data acquired by the array of coil elements is used for partial phase encoding, only to speed up the acquisition process.
The acceleration factors routinely employed at a magnetic field strength of 1.5 T can range from 2 to 3. At field 3T, this factor can be even higher.

How Parallel Imaging Improves MRI Scanning

Multi-channel radio frequency and parallel imaging technologies are hardware and software implementations, respectively aimed at improving the coverage signal resolution and speed of MRI scanner examinations. With multi-channel technology, the MRI scanner signal used to form an image is collected by an array of separate coil elements. Each element relays signal information along a separate channel to an image reconstruction computer. Such arrays of coil elements can improve imaging coverage and the ratio of signal-to-noise in the image. The number of elements in the array of detectors is an important factor in characterizing a parallel imaging system. Parallel imaging technology uses complex software algorithms to reconstruct the signals from multiple channels in an way that can reduce imaging times or increase  image resolution, in image resolution (without the corresponding increase in imaging times associated with standard MRI scanner imaging).

MRI Parallel Imaging Applications

Multi-channel coil and receiving systems and parallel imaging technologies were first implemented in brain examinations. Recent developments in both hardware and software have allowed for broader clinical applications of these technologies, such as in cardiac, lung, abdomen, and limb studies. For example, parallel imaging, in partnership with multi-channel radiofrequency systems allows for better visualization of small lesions and blood vessels that may allow for an earlier diagnosis of cancer and cardiovascular disease. Greater imaging coverage is possible with multi-channel radiofrequency system technology facilitating oncology screening and peripheral angiography. Finally, scan times are considerably reduced using parallel imaging, allowing for tolerable breath holds when scanning patients. The latest MRI scanner at 1.5T and 3T all feature multi-channel radiofrequency system technology and parallel imaging.

Multi-channel technology and parallel imaging allows for significant improvements in most clinical MRI scanner examinations. There is no significant degradation in performance, compared to non-parallel imaging. Faster scanning could increase the patient throughout, as well as dramatically improve patient comfort during scans.

This technology could potentially contribute to the use of MRI scanning as an alternative to CT scanning and play a significant role in radiation protection strategies, particularly in young patients.
MRI scanning offers superb soft tissue contrast, however high- resolution scans are often excluded, due to long scan times. Parallel imaging offers much shorter acquisition times, while retaining the high resolution necessary for early lesion and/or tumor detection.

Parallel Imaging in MRI Scanning Outline

For better understanding of parallel imaging in MRI scanners, the following is a step-by-step outline:

  • The MRI is non-invasive imaging method used in medicine.
  • The imaged patient in MRI scanning is placed in a strong magnetic field.
  • All protons in the tissue align parallel to the direction of the magnetic field.
  • The protons are excited to a higher energy state, using a radio frequency electromagnetic pulse.
  • The excited protons return back to the energy equilibrium.
  • The accepted energy is retransmitted back and picked up by the coil system.
  • This energy is passed to the channel receiver and can be measured.
  • The retransmitted electromagnetic energy has to have an exact frequency that depends on the chemical properties of the tissue, strength of the magnetic field and temperature.
  • The special position of the signal origin cannot be resolved unless it is spatially encoded to facilitate the retrieval of images.
  • Magnetic gradient fields are used to locally change the resonance frequency, so the frequency of the MRI signal becomes dependent on the spatial position of the signal source.
  • A K-space image is formed, measuring the retransmitted signal (the K- space image corresponds to the image in the Fourier space).
  • The real image of the patient is obtained by Fourier transform of the K-space image (it resolves the correspondence of the frequency and spatial position of the signal).
  • In the standard MRI scanner, the signal is received by a simple coil with quite homogeneous sensitivity over the whole imaged volume.
  • In the parallel imaging MRI scanner, the signals are received simultaneously by several receiver coils with varying spatial sensitivity. This brings more information about the spatial position of the MRI signal.
  • So, it becomes clear that parallel imaging in MRI scanning speeds up the acquisition of the data. This advantage is useful for:
  1. The ability to image dynamic process without major movement artifacts.
  2. Shortening the acquisition time of the MRI scanner, which improves the throughput rate of the MRI scanner.

The Three Ways to Reconstruct the Scan Information

There are two major types of reconstruction methods to recover the information of the scan: SENSE or SENSE – based, which occurs in image domain, and GRAPPA or SMASH-based which occurs in K-space.
A third type of regenerative method, the so-called hybrid technique, has recently been developed. These are complex algorithms developed to restore the data omitted during the reduced acquisition.

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