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Abstract #3869

Improving SNR in deuterium metabolic imaging of cancer: spatial denoising, joint spectral/metabolic-kinetics processing, and beyond

Elton Montrazi1, Qingjia Bao2, Ricardo Martinho3, Dana Peters4, Talia Harris1, Keren Sasson1, Lilach Agemy1, Avigdor Scherz1, and Lucio Frydman1
1Weizmann, Rehovot, Israel, 2Chinese Academy of Sciences, Wuhan, China, 3University of Twente, Enschede, Netherlands, 4Yale School of Medicine, New Haven, CT, United States

Synopsis

Keywords: Deuterium, Cancer, MRSIAs DMI is a promising cancer screening approach but is challenged by low sensitivity, this study assesses multiple approaches to increase its SNR. Some of these –apodization, Compressed Sensing Multiplicative (CoSeM), Block-matching/3D filtering (BM3D)– involve image denoising. Others take into account the metabolic kinetics, and include it as dimension to be denoised. This can be achieved by smoothing the kinetic data axis via regularization, or by using subspace-constrained representations to concurrently solve for the 4D spatial/spectral/kinetics set. These methods can be further denoised –e.g., by CoSeM– leading to much clearer observations of lactate generated by in vivo tumor models.

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Keywords