The aim of this study is to evaluate a real-time magnetic resonance imaging (MRI) method that not only promises high spatiotemporal resolution but also practical robustness in a wide range of scientific and clinical applications.
The proposed method relies on highly undersampled gradient-echo sequences with radial encoding schemes. The serial image reconstruction process solves the true mathematical task that emerges as a nonlinear inverse problem with the complex image and all coil sensitivity maps as unknowns. Extensions to model-based reconstructions for quantitative parametric mapping further increase the number of unknowns, for example, by adding parameters for phase-contrast flow or T1 relaxation. In all cases, an iterative numerical solution that minimizes a respective cost function is achieved with use of the iteratively regularized Gauss-Newton method. Convergence is supported by regularization, for example, to the preceding frame, whereas temporal fidelity is ensured by downsizing the regularization strength in comparison to the data consistency term in each iterative step. Practical implementations of highly parallelized algorithms are realized on a computer with multiple graphical processing units. It is “invisibly” integrated into a commercial 3-T MRI system to allow for conventional usage and to provide online reconstruction, display, and storage of regular DICOM image series.
Depending on the application, the proposed method offers serial imaging, that is, the recording of MRI movies, with variable spatial resolution and up to 100 frames per second (fps)—corresponding to 10 milliseconds image acquisition times. For example, movements of the temporomandibular joint during opening and closing of the mouth are visualized with use of simultaneous dual-slice movies of both joints at 2 × 10 fps (50 milliseconds per frame). Cardiac function may be studied at 30 to 50 fps (33.3 to 20 milliseconds), whereas articulation processes typically require 50 fps (20 milliseconds) or orthogonal dual-slice acquisitions at 2 × 25 fps (20 milliseconds). Methodological extensions to model-based reconstructions achieve improved quantitative mapping of flow velocities and T1 relaxation times in a variety of clinical scenarios.
Real-time gradient-echo MRI with extreme radial undersampling and nonlinear inverse reconstruction allows for direct monitoring of arbitrary physiological processes and body functions. In many cases, pertinent applications offer hitherto impossible clinical studies (eg, of high-resolution swallowing dynamics) or bear the potential to replace existing MRI procedures (eg, electrocardiogram-gated cardiac examinations). As a consequence, many novel opportunities will require a change of paradigm in MRI-based radiology. At this stage, extended clinical trials are needed.
From the *Biomedizinische NMR, Max-Planck-Institut für Biophysikalische Chemie;
†DZHK (German Centre for Cardiovascular Research); and
‡Institute for Diagnostic and Interventional Radiology, University Medical Center, Göttingen, Germany.
Received for publication March 25, 2019; and accepted for publication, after revision, April 25, 2019.
Conflicts of interest and sources of funding: The authors hold a patent and software knowhow about the real-time magnetic resonance imaging technique used here. M.U. gratefully acknowledges financial support by the German Centre for Cardiovascular Research.
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Correspondence to: Jens Frahm, PhD, Biomedizinische NMR, Max-Planck-Institut für Biophysikalische Chemie, Am Fassberg 11, 37070 Göttingen, Germany. E-mail: email@example.com.
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