The Principles of Magnetic Resonance Imaging
Yi-Hsuan Kao, Department of Medical Radiation Technology, National Yang-Ming University
The clinical use of Magnetic Resonance Imaging (MRI) is based on the observation of water molecules (protons to be exact) in the human body. Its principles may be described as follows. Upon the application of an external static magnetic field, the protons of water molecules will be aligned with the magnetic field as magnetic dipoles. When they are disturbed by a second alternating magnetic field, at certain radio frequency, they begin to resonate. According to Faraday’s law, the processing of magnetic dipoles induce electric currents, giving rise to signals, in a copper coil (called a probe) surrounding them. The magnetic field strength used in most clinical MRI units is 1.5 Tesla. The corresponding precession frequency of the protons is 64 MHz. The signals are detected in high radio frequency (RF), but transformed into lower audio frequency ranged for sampling, recording, and analyses.
The spatial distribution of protons can be encoded into the signals by the application of linear magnetic field gradients (Gx = dBz/dx, Gy = dBz/dy, Gz = dBz/dz). The gradients correlate the precessing frequencies with spatial coordinates; whereas the signal intensity is proportional to the amount of materials (protons, or water) and their relaxation times (T1, T2, and T2*). In the case of pulsed RF excitation, Fourier Transform is needed for extracting the frequency and intensity information, resulting in the so-called MR images. Nowadays, MRI can produce excellent anatomic images with resolution down to mm region. MRI is an important tool for studying the brain, including (1) soft tissues (such as white and gray matters), (2) pathology (such as tumor, edema, and ischemia), and (3) angioma. In addition, functional MRI, developed more recently, provides better understanding of the brain undertaking stimuli; whereas perfusion and diffusion MRI are valuable for studying the micro-circulation of the blood capillary network of the brain.