Radiofrequency Bias Correction of Magnetization Prepared Rapid Gradient Echo MRI at 7.0 Tesla Using an External Reference in a Sequential Protocol.
Hampus OlssonMikael NovénJimmy LättRonnie WirestamGunther HelmsPublished in: Tomography (Ann Arbor, Mich.) (2021)
At field strengths of 7 T and above, T1-weighted imaging of human brain suffers increasingly from radiofrequency (RF) B1 inhomogeneities. The well-known MP2RAGE (magnetization prepared two rapid acquisition gradient echoes) sequence provides a solution but may not be readily available for all MR systems. Here, we describe the implementation and evaluation of a sequential protocol to obtain normalized magnetization prepared rapid gradient echo (MPRAGE) images at 0.7, 0.8, or 0.9-mm isotropic spatial resolution. Optimization focused on the reference gradient-recalled echo (GRE) that was used for normalization of the MPRAGE. A good compromise between white-gray matter contrast and the signal-to-noise ratio (SNR) was reached at a flip angle of 3° and total scan time was reduced by increasing the reference voxel size by a factor of 8 relative to the MPRAGE resolution. The average intra-subject coefficient-of-variation (CV) in segmented white matter (WM) was 7.9 ± 3.3% after normalization, compared to 20 ± 8.4% before. The corresponding inter-subject average CV in WM was 7.6 ± 7.6% and 13 ± 7.8%. Maps of T1 derived from forward signal modelling showed no obvious bias after correction by a separately acquired flip angle map. To conclude, a non-interleaved acquisition for normalization of MPRAGE offers a simple alternative to MP2RAGE to obtain semi-quantitative purely T1-weighted images. These images can be converted to T1 maps, analogously to the established MP2RAGE approach. Scan time can be reduced by increasing the reference voxel size which has only a miniscule effect on image quality.
Keyphrases
- contrast enhanced
- magnetic resonance
- computed tomography
- diffusion weighted
- diffusion weighted imaging
- image quality
- high resolution
- magnetic resonance imaging
- dual energy
- deep learning
- convolutional neural network
- white matter
- optical coherence tomography
- loop mediated isothermal amplification
- randomized controlled trial
- single molecule
- primary care
- healthcare
- ultrasound guided
- network analysis
- machine learning
- solid state