Abstract #3704

The effect of SNR optimization on cell quantification accuracy for fluorine-19 MRI sequences: bSSFP, FSE, and FLASH

Kai D. Ludwig¹, Erin B. Adamson¹, Christian M. Capitini^2,3, and Sean B. Fain^1,4,5

¹Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ²Pediatrics, University of Wisconsin-Madison, Madison, WI, United States, ³Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, United States, ⁴Radiology, University of Wisconsin-Madison, Madison, WI, United States, ⁵Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States

Several MRI data acquisition methods have been used for fluorine-19 (19F) MRI cell tracking and optimizing the image SNR helps mitigate low sensitivity. An optimization workflow is presented for three 19F pulse sequences based upon relaxation parameters measured in a 19F reference phantom. Bloch simulations reveal signal differences between the reference phantom and pure 19F cellular label for SNR-optimized bSSFP, FSE, and FLASH. The simulated relative errors in 19F signal suggest SNR optimization can compromise signal quantification and thus in vivo cell quantification but could provide insight for improved methods to balance the degree of spin-density weighting and SNR.

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