Boer V.O.,Radiotherapy and Nuclear Medicine |
Siero J.C.,Radiotherapy and Nuclear Medicine |
Hoogduin H.,Radiotherapy and Nuclear Medicine |
van Gorp J.S.,Radiotherapy and Nuclear Medicine |
And 3 more authors.
NMR in Biomedicine | Year: 2011
In vivo MRS of the human brain at 7 tesla allows identification of a large number of metabolites at higher spatial resolutions than currently possible at lower field strengths. However, several challenges complicate in vivo localization and artifact suppression in MRS at high spatial resolution within a clinically feasible scan time at 7 tesla. Published MRS sequences at 7 tesla suffer from long echo times, inherent signal-to-noise ratio (SNR) loss, large chemical shift displacement artifacts or long repetition times because of excessive radiofrequency (RF) power deposition. In the present study a pulse-acquire sequence was used that does not suffer from these high field drawbacks. A slice selective excitation combined with high resolution chemical shift imaging for in-plane localization was used to limit chemical shift displacement artifacts. The pulse-acquire approach resulted in a very short echo time of 1.4ms. A cost function guided shimming algorithm was developed to constrain frequency offsets in the excited slice, therefore adiabatic frequency selective suppression could be employed to minimize artifacts from high intensity lipids and water signals in the excited slice. The high sensitivity at a TR of 1s was demonstrated both on a supraventricular slice as well as in an area very close to the skull in the frontal cortex at a nominal spatial resolution of 0.25 cc within a feasible scan time. Copyright © 2011 John Wiley & Sons, Ltd. MRS at 7 tesla is shown with limited chemical shift dispersion artifacts, short echo time and full signal acquisition using a pulse-acquire CSI approach. Sensitivity was maximized using a very short echo time and a short repetition time which was realized using low power lipid and water suppression in combination with a cost function guided shimming algorithm, leading to a highly time-efficient sequence allowing high-resolution MRS of the human brain. © 2011 John Wiley & Sons, Ltd.