Quantitative T1 MRI of the brain provides valuable insight into the health status of brain tissue. To estimate T1, an image slice is acquired with multiple inversion time (TI) values, and then the variation in measured intensities versus TI values are t to a MR spin-relaxation model to extract the underlying quantitative T1 recovery value. The gold standard for T1 mapping is currently Inversion-Recovery Spin Echo (IR-SE). However, this MRI sequence requires a prohibitively long data acquisition time, which prevents clinical adoption. Inversion-recovery data acquisition time can be reduced by both adopting fast MR imaging methods such as echo planar imaging (EPI) and creative slice ordering in the acquisition of EPI data that form the full imaged volume. At ultrahigh MRI eld strength, 7 Tesla, T1-Mapping using EPI is limited by inherent imaging artifacts. One dominant artifact is EPI ghosting, which manifests as copies of the measured image displaced from the original source location. In certain cases, these displaced copies can create ripple artifacts that may change over the course of an imaging session, introducing temporal instability into the data. These artifacts appear more prominently at higher magnetic eld strength, particularly when imaging structures deep within the brain. This proposal seeks to improve and validate a new, novel method for rapid T1-Mapping at ultra-high eld, named Multiple-Inversion EPI (MI-EPI).
In Aim 1, we seek to integrate our recent high-performance EPI technology that we have shown reduce inherent EPI imaging artifacts, including Dual-Polarity GRAPPA, Dual-Polarity slice-GRAPPA, and FLEET, into a spin-echo (SE) readout variant of the Multi-Inversion Simultaneous Multi-Slice (SMS) EPI sequence. We seek to demonstrate that quantitative T1 maps can be consistently and robustly generated from multiple inversion-time data collected using SE MI-EPI. We then will further extend our high-performance EPI technology into an SMS-EPI diffusion weighted sequence, and develop an DICOM-compatible image reconstruction framework to generate FLAIR and MPRAGE images from the quantitative T1 maps. Finally, we seek to develop a segmented spin-echo MI-EPI sequence to reduce geometric distortion and improve spatial resolution.
In Aim 2, we seek to combine all of the above to implement a 10 minute, all EPI based, whole-brain neurological examination protocol. The success of our proposal will be identi ed by the ability to characterize an improvement in image quality and delity with the underlying anatomy in the T1-Mapping application. The successful completion of this project will directly improve neuroimaging studies, by enabling rapid, high quality T1-Mapping and a short, whole-brain neurological exam at 7T eld strength.
This proposal will extend and validate recent developments in MRI image formation at ultra-high field (7T), with the goal of improving image quality and reducing data acquisition time in clinical protocols. The ultimate outcome of this research will improve the applicability of these methods to the diagnosis and treatment of neuropsychiatric disorders.