Abstract #4475

RECOMPOSE – Reproducing DECOMPOSE Using Susceptibility Maps Acquired for Clinical Research

Patrick Fuchs¹, Jingjia Chen^2,3, Oliver C Kiersnowski¹, Russell Murdoch¹, Chunlei Liu^2,3, and Karin Shmueli¹

¹Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States, ³Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States

Synopsis

Keywords: Susceptibility, Quantitative Susceptibility mapping

Here, we reproduced the results of the DECOMPOSE susceptibility separation model using new $$$T_2^*$$$-weighted data independently acquired using three clinically applicable sequences and processed with different QSM pipelines. This allowed us to investigate the sensitivity of DECOMPOSE to various dipole inversion algorithms. Good susceptibility source separation results were achieved using a 5-echo GRE acquisition, but maps of diamagnetic and paramagnetic sources from a highly accelerated 5-echo EPI sequence were noisy. When the input susceptibility maps exhibited artefacts, these were exacerbated by DECOMPOSE. Care must be taken not to lose local structural information when using (highly) regularised input susceptibility maps.

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