Universal pulses for homogeneous excitation using single channel coils

Universal modes: Calibration-free time-interleaved acquisition of modes

PURPOSE

To introduce universal modes by applying the universal pulse concept to time-interleaved acquisition of modes (TIAMO), thereby achieving calibration-freeB 1 + $$ {B}_1^{+} $$ inhomogeneity mitigation for body imaging at ultra-high fields.

METHODS

Two databases of different RF arrays were used to demonstrate the feasibility of universal modes. The first comprised 31 cardiac in vivo data sets acquired at 7T while the second consisted of 6 simulated 10.5T pelvic data sets. Subject-specific solutions and universal modes were computed and subsequently evaluated alongside predefined default modes. For the cardiac database, subdivision into subpopulations was investigated. The optimization was performed using least-squares (LS) TIAMO and acquisition modes optimized for refocused echoes (AMORE). Finally, universal modes based on simulated pelvis data were applied in vivo at 10.5T.

RESULTS

In all studied cases, the universal modes yield improvements over the predefined default modes of up to 51% (cardiac) and 30% (pelvic) in terms of median excitation error when using two modes. The subpopulation-specific cardiac solutions revealed a further improvement of universal modes at the expense of increased errors when applied outside the appropriate subpopulation. Direct application of simulation-based universal modes in vivo resulted in up to a 14% reduction in excitation error compared to default modes and up to a 34% reduction in peak 10 g local specific absorption rate (SAR) compared to subject-specific solutions.

CONCLUSIONS

Universal modes are feasible for calibration-freeB 1 + $$ {B}_1^{+} $$ inhomogeneity mitigation at ultra-high fields. In addition, simulation-based solutions can be applied directly in vivo, eliminating the need for large in vivo databases.

Release of cognitive and multimodal MRI data including real-world tasks and hippocampal subfield segmentations

We share data from N = 217 healthy adults (mean age 29 years, range 20-41; 109 females, 108 males) who underwent extensive cognitive assessment and neuroimaging to examine the neural basis of individual differences, with a particular focus on a brain structure called the hippocampus. Cognitive data were collected using a wide array of questionnaires, naturalistic tests that examined imagination, autobiographical memory recall and spatial navigation, traditional laboratory-based tests such as recalling word pairs, and comprehensive characterisation of the strategies used to perform the cognitive tests. 3 Tesla MRI data were also acquired and include multi-parameter mapping to examine tissue microstructure, diffusion-weighted MRI, T2-weighted high-resolution partial volume structural MRI scans (with the masks of hippocampal subfields manually segmented from these scans), whole brain resting state functional MRI scans and partial volume high resolution resting state functional MRI scans. This rich dataset will be of value to cognitive and clinical neuroscientists researching individual differences, real-world cognition, brain-behaviour associations, hippocampal subfields and more. All data are freely available on Dryad.