Abstract #2622

ROVir Enables Substantially Easier Real-Time Imaging of Small Regions-of-Interest

Chin-Cheng Chan¹, Danielle Kara^2,3, Deborah Kwon⁴, Eric Roselli⁵, Christopher Nguyen^2,3,6, and Justin P. Haldar¹

¹Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, ²Cardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, OH, United States, ³Imaging Science Section, Diagnostics Institute, Cleveland Clinic, Cleveland, OH, United States, ⁴Cardiovascular Medicine, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, OH, United States, ⁵Cardiovascular Surgery, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, OH, United States, ⁶Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States

Synopsis

Keywords: Image Reconstruction, Image Reconstruction, Dynamic Imaging; Real-Time Imaging; Reduced Field-of-View; Virtual Coils; Cardiac Imaging

Motivation: Many real-time MRI experiments use large FOVs, even though most of the FOV is uninformative. Using a large FOV helps avoid aliasing but requires a higher level of undersampling and more complicated reconstruction. The ROVir (region-optimized virtual coils) technique can potentially alleviate these issues.

Goal(s): To develop a more efficient approach to real-time imaging of small regions-of-interest.

Approach: We use ROVir to suppress the signal from uninteresting spatial regions, enabling a smaller FOV (with closer-to-Nyquist k-space sampling). This allows substantially simpler reconstruction.

Results: ROVir with simple reconstruction achieves similar/potentially-better image quality than more sophisticated regularization-based reconstructions, with substantially less computation.

Impact: High-resolution real-time MRI over a large FOV is usually highly-undersampled and requires advanced/time-consuming reconstruction methods. We demonstrate that ROVir can be used to shrink the size of the FOV to enable a much simpler/easier reconstruction problem.

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