Abstract #3086

FIRE and MATLAB for Free-Breathing Segmented LGE – A Novel Sequence and Reconstruction Approach for Selecting and Correcting Data by Respiration

Wolfgang G Rehwald^1,2, Kelvin Chow³, Rafael Rojas⁴, Nestor Mena⁴, Diana Alexandrov⁴, George Gamoneda⁴, David Wendell⁴, Ryan Seward⁴, Jeana Dement⁴, Vera Kimbrell⁴, Han Kim⁴, Indraneel Borgohain⁵, Igor Klem⁴, and Raymond Kim⁴

¹Siemens Healthineers, Durham, NC, United States, ²Duke Cardiovascular MR Center, Duke University, Durham, NC, United States, ³Siemens Healthineers, Chicago, IL, United States, ⁴Duke Cardiovascular MR Center, Duke University Hospital, Durham, NC, United States, ⁵Siemens Healthineers, Princeton, NJ, United States

Synopsis

Keywords: Image Reconstruction, Motion Correction, Reordering

We introduce a free breathing segmented LGE technique combining a new acquisition, reordering and reconstruction scheme. The on-scanner reconstruction uses MATLAB and FIRE. The method produces image quality (IQ) and SNR otherwise only obtainable with breath held segmented interleaved LGE. In 27 patients, we show that IQ is superior to free breathing segmented interleaved LGE with multiple averages. SNR is higher compared to averaged motion corrected single shots when matching spatial and temporal resolution, the number of used measurements per image, and the readout type. Being a segmented technique, temporal and spatial resolution limitations of single shots do not apply.

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