Abstract #0815

Efficient mesoscale multiparametric quantitative MRI using 3D-QALAS at 7T with self-supervised learning

Yohan Jun^1,2, Shohei Fujita^1,2, Yuting Chen^1,2,3, Azma Mareyam¹, Camilo Jaimes^2,4,5, Michael S Gee^2,4,5, Borjan Gagoski^2,6, and Berkin Bilgic^1,2,7

¹Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States, ²Department of Radiology, Harvard Medical School, Boston, MA, United States, ³State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China, ⁴Pediatric Imaging Research Center, Massachusetts General Hospital, Boston, MA, United States, ⁵Department of Radiology, Massachusetts General Hospital, Boston, MA, United States, ⁶Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States, ⁷Harvard/MIT Health Sciences and Technology, Cambridge, MA, United States

Synopsis

Keywords: Quantitative Imaging, Quantitative Imaging

Motivation: Mesoscale quantitative MRI (qMRI) has the potential to provide unique insights into tissue composition, but technical challenges have so far precluded this application.

Goal(s): To develop high-resolution multiparametric quantitative MRI using 3D-QALAS at 7T.

Approach: We propose to: 1) modify the adiabatic T₂-preparation module to account for shorter T₂ values and increased B₁⁺ inhomogeneity at 7T; 2) use multi-contrast/-slice zero-shot self-supervised-learning (ZS-SSL) for joint QALAS image reconstruction and 3) employ SSL parameter estimation algorithm that incorporates inversion efficiency estimation.

Results: In vivo results demonstrate that high-fidelity whole-brain T₁ and T₂ maps at 500µm isotropic resolution can be achieved within 16min at 7T.

Impact: We demonstrate high-fidelity mesoscale (500µm isotropic resolution) multiparametric qMRI with 3D-QALAS at 7T using self-supervised image reconstruction and parameter estimation.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.