Abstract #1554

Automated subject-specific pixels selection for improved image reconstruction in free-running coronary MRA using SIMBA

Ludovica Romanin^1,2, Christopher W. Roy², Milan Prsa³, Tobias Rutz⁴, Estelle Tenisch², Matthias Stuber^2,5, and Davide Piccini^1,2

¹Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, ²Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ³Division of Pediatric Cardiology, Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁴Service of Cardiology, Heart and Vessel Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁵Center for Biomedical Imaging (CIBM), Lausanne, Switzerland

Synopsis

This work proposes an automated subject-specific individual pixels selection as an alternative to a fixed coil selection for the initialization of the input data to a similarity-driven multi-dimensional binning algorithm (SIMBA) for free-running motion-suppressed whole-heart acquisitions. By selecting timeseries with a high low-frequency energy content, we include only pixels with respiratory and cardiac information. Compared to the original method, this leads to a more accurate choice of end-expiration and diastolic phases for the reconstruction of sharp whole-heart and coronary images. Moving forward, the method needs to be refined, optimized and tested to further improve the image quality.

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