Abstract
Background Despite the technological advances made in the field of MRI, further improvements in both data acquisition and processing are required to expand the reliability and diagnostic accuracy of challenging CMR applications such as real-time stress imaging. Due to exaggerated breathing motion and high heart rates, real-time stress images are limited in terms of resolution and often exhibit significant artifacts. In this work, we combine a recently proposed method for variable density incoherent spatiotemporal sampling, called VISTA [1], and SPIRiT-based reconstruction [2] with 3D spatiotemporal regularization to reconstruct real-time stress cine images.
Highlights
Despite the technological advances made in the field of MRI, further improvements in both data acquisition and processing are required to expand the reliability and diagnostic accuracy of challenging CMR applications such as real-time stress imaging
Rest and stress (Bruce protocol) cine images were acquired from three healthy volunteers using a 1.5 T (Avanto, Siemens) scanner with 32-channel body coil array
For VISTA+SPIRiT, the reconstruction time for one dataset was under 30 minutes
Summary
Despite the technological advances made in the field of MRI, further improvements in both data acquisition and processing are required to expand the reliability and diagnostic accuracy of challenging CMR applications such as real-time stress imaging. Methods Rest and stress (Bruce protocol) cine images were acquired from three healthy volunteers using a 1.5 T (Avanto, Siemens) scanner with 32-channel body coil array. The acquisition was carried out under free-breathing conditions in both short and long axis orientations.
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