P. James Ross

Rapid field‐cycling MRI using fast spin‐echo

Fast field‐cycling MRI (FFC‐MRI) is a technique that promises to expand upon the diagnostic capabilities of conventional MRI by allowing the main field, B0, to be varied during a pulse sequence, thus allowing access to new types of endogenous contrast. However, this necessitates longer scan times, which can limit the techniques application to clinical research. In this paper, an adaptation of the fast spin‐echo (FSE) pulse sequence for use with FFC‐MRI is presented, known as field‐cycling fast spin‐echo (FC‐FSE). This technique allows much faster image acquisition, thus shortening scan times significantly.

Rapid Field-Cycling MRI using Fast Spin-Echo

Fast field‐cycling MRI (FFC‐MRI) is a technique that promises to expand upon the diagnostic capabilities of conventional MRI by allowing the main field, B0, to be varied during a pulse sequence, thus allowing access to new types of endogenous contrast. However, this necessitates longer scan times, which can limit the techniques application to clinical research. In this paper, an adaptation of the fast spin‐echo (FSE) pulse sequence for use with FFC‐MRI is presented, known as field‐cycling fast spin‐echo (FC‐FSE). This technique allows much faster image acquisition, thus shortening scan times significantly.

Rapid multi-field T(1) estimation algorithm for Fast Field-Cycling MRI.

Fast Field-Cycling MRI (FFC-MRI) is an emerging MRI technique that allows the main magnetic field to vary, allowing probing T1 at various magnetic field strengths. This technique offers promising possibilities but requires long scan times to improve the signal-to-noise ratio. This paper presents an algorithm derived from the two-point method proposed by Edelstein that can estimate T1 using only one image per field, thereby shortening the scan time by a factor of nearly two, taking advantage of the fact that the equilibrium magnetisation is proportional to the magnetic field strength. Therefore the equilibrium magnetisation only needs measuring once, then T1 can be found from inversion recovery experiments using the Bloch equations. The precision and accuracy of the algorithm are estimated using both simulated and experimental data, by Monte-Carlo simulations and by comparison with standard techniques on a phantom. The results are acceptable but usage is limited to the case where variations of the main magnetic field are fast compared with T1 and where the dispersion curve is relatively linear. The speed-up of T1-dispersion measurements resulting from the new method is likely to make FFC-MRI more acceptable when it is applied in the clinic.

Simple algorithm for the correction of MRI image artefacts due to random phase fluctuations

PURPOSE Fast Field-Cycling (FFC) MRI is a novel technology that allows varying the main magnetic field B0 during the pulse sequence, from the nominal field (usually hundreds of millitesla) down to Earths field or below. This technique uses resistive magnets powered by fast amplifiers. One of the challenges with this method is to stabilise the magnetic field during the acquisition of the NMR signal. Indeed, a typical consequence of field instability is small, random phase variations between each line of k-space resulting in artefacts, similar to those which occur due to homogeneous motion but harder to correct as no assumption can be made about the phase error, which appears completely random. Here we propose an algorithm that can correct for the random phase variations induced by field instabilities without prior knowledge about the phase error. METHODS The algorithm exploits the fact that ghosts caused by field instability manifest in image regions which should be signal free. The algorithm minimises the signal in the background by finding an optimum phase correction for each line of k-space and repeats the operation until the result converges, leaving the background free of signal. CONCLUSION We showed the conditions for which the algorithm is robust and successfully applied it on images acquired on FFC-MRI scanners. The same algorithm can be used for various applications other than Fast Field-Cycling MRI.