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A previously proposed nonlinear inverse reconstruction for autocalibrated parallel imaging simultaneously estimates coil sensitivities and image content. This work exploits this property for real-time MRI, where coil sensitivities need to be dynamically adapted to the conditions generated by moving objects. The development comprises (i) an extension of the nonlinear inverse algorithm to non-Cartesian k-space encodings, (ii) its implementation on a graphical processing unit to reduce reconstruction times, and (iii) the use of a convolution-based iteration, which considerably simplifies the graphical processing unit implementation compared to a gridding technique. The method is validated for real-time MRI of the human heart at 3 T using radio frequency-spoiled radial FLASH (pulse repetition time/echo time = 2.0/1.3 ms, flip angle 8 degrees). The results demonstrate artifact-free reconstructions from only 65-85 spokes, with 256 oversampled data points. Acquisition times of 130-170 ms resulted in 29-38 frames per second for sliding window reconstructions (factor 5). While offline reconstructions required 1-2 sec, real-time applications with modified parameters and slightly lower image quality were achieved within 90 ms per graphical processing unit.
Uecker et al. (Fri,) studied this question.