Fifty-sixth annual meeting of the American association of physicists in medicine
SU-E-J-131: Automatic Detection of Gold Fiducial Markers On MR Images Using the RASOR Technique
The detection of gold fiducial markers on MR images is important for CT-MR registration and will be key to upcoming MRI-only treatment planning. Visualization of gold fiducials with MRI is, however, challenging as seeds lead to small signal voids that are difficult to detect on regular MR scans. Here, we demonstrate that by using a balanced radial SSFP sequence in combination with an off-resonance reconstruction, gold fiducials can be given a positive contrast facilitating automatic detection.
Three gold fiducials (HA2 Medizintechnik, Germany, 1x 5 mm²) were placed in three orthogonal orientations in an agarose gel phantom. We used a 3D stack of stars transient balanced gradient echo (tbGE) sequence with SPAIR fat suppression (TR/TE = 3.3/1.63ms, 1×1×2 mm³ acquired voxels, BW=1085Hz/vox). To create positive contrast at the seed locations the RASOR technique employs an additional off-resonance reconstruction at 3000 Hz. Background-suppression was obtained by subtracting the on-resonance image twice from the off-resonance image.
The short echo time of the sequence combined with a “balanced” gradient scheme resulted in well localized and sharp signal voids at fiducial locations. By employing RASOR reconstruction the gold fiducials were depicted hyperintense and allowed determination of the locatation and orientation of the fiducials. The radial readout ensures accurate localization as any susceptibility induced geometrical shift for a radial readout line, is balanced by an opposite radial readout. Thus the centre-of-gravity of the hyperintensity reflects the true position of the fiducials.
A radial balanced sequence in combination with short TR and TR and high spatial resolution, results in accurate depiction of gold fiducials while being standardly available on MR systems. The RASOR reconstruction results in a positive contrast facilitating automatic detection. This enables automatic registration between CT and MRI based on fiducial markers, and in the may warrant an MRI-only planning approach.