UCLA researchers in the Department of Radiology have developed a novel method that addresses a common issue of MRI imaging misinterpretation due to the high field effects of B1+ inhomogeneity.
Magnetic Imaging Resonance (MRI) is a modern non-invasive anatomical imaging technique for the visualization of disease states. MRI, like many other forms of non-invasive imaging, relies on contrast for visualization. MR images collected with higher fields offer greater signal to noise ratio, producing a greater observed contrast. This greater proportion of contrast leads to greater target organ visualization as well as a better understanding of disease evolution with scans taken over the course of treatment. However, a major issue to the use of higher fields for imaging lies in the length of the wavelength emitted, which is commonly the same as the organ of interest, leading to constructive and destructive interferences masking the true contrast: a process known as B1+ inhomogeneity. While many attempts have been made to correct for this inhomogeneity, there is still considerable progress to be made to counteract its drawbacks. Therefore, the development of a correction technique could make the use of higher fields more reasonable for clinical applications of MRI, leading to greater potential patient care.
Dr. Sung at UCLA has developed a novel method to decrease the observed B1+ inhomogeneity in MRI. This method relies on the optimization of the reference region technique for a specified application (i.e. prostate cancer). Optimization of the reference region is achieved through the calibration of the reference region against a mapped sub region that has been weighted through another B1+ inhomogeneity mapping. This invention could lead to the more reasonable and routine use of higher fields in MRI, leading to the better assessment of disease progression.
The technique has been used and optimized in fat tissues, but further optimization is still underway.
MRI, B1+ field inhomogeneity, high field imaging, parametric mapping, reference region mapping, anatomical imaging, disease progression visualization, vital organ health