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Abstract #3449

Subpopulation universal pulses: practical online implementation

Igor Tyshchenko1,2, Joseph J. Bartlett1,2,3, Yasmin Blunck1,2, Bahman Tahayori4, Kelvin Chow5, Patrick Liebig6, Leigh A. Johnston1,2, and Simon Lévy7
1Department of Biomedical Engineering & Graeme Clark Institute, The University of Melbourne, Melbourne, Australia, 2Melbourne Brain Centre Imaging Unit, The University of Melbourne, Melbourne, Australia, 3School of Computer Science, University of Birmingham, Birmingham, United Kingdom, 4The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia, 5Cardiovascular MR R&D, Siemens Healthcare Ltd, Calgary, AB, Canada, 6Siemens Healthcare GmbH, Erlangen, Germany, 7MR Research Collaborations, Siemens Healthcare Pty Ltd, Melbourne, Australia

Synopsis

Keywords: Parallel Transmit & Multiband, High-Field MRI, UHF MRI, pTx, universal pulse, RF pulse design

Motivation: Subpopulation universal pulses (UPs) have shown promise as a compromise between one-size-fits-all UPs and tailored solutions. However, their practical application was not straightforward.

Goal(s): Design an automated online image-processing pipeline for head shape clustering and pulse selection, providing subpopulation 5kT-inversion UPs.

Approach: Implementation of a Python pipeline integrated into the image reconstruction routine, using localizer scans to classify head shapes and positions. The pipeline selects one of five precomputed subpopulation UPs or defaults to the generic UP without extending scan time.

Results: The pipeline successfully classified head shapes and selected appropriate pulses, resulting in improved contrast of MP2RAGE images.

Impact: The novel head clustering and pulse selection pipeline enables subpopulation universal pulses in clinical practice. It enables pulse selection for each head shape and position without extending scan time, facilitating personalized and efficient ultra-high field MRI.

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Keywords