Joint image and field map estimation for multi-echo hyperpolarized ¹³ C metabolic imaging of the heart

Image reconstruction of metabolic images from hyperpolarized ¹³ C multi-echo data acquisition is sensitive to susceptibility-induced phase offsets, which are particularly challenging in the heart. A model-based framework for joint estimation of metabolite images and field map from echo shift-encoded data is proposed. Using simulations, it is demonstrated that correction of signal spilling due to incorrect decomposition of metabolites and geometrical distortions over a wide range of off-resonance gradients is possible. In vivo feasibility is illustrated using hyperpolarized [1-¹³ C]pyruvate in the pig heart.

The model-based reconstruction for multi-echo, multicoil data was implemented as a nonconvex minimization problem jointly optimizing for metabolic images and B₀ . A comprehensive simulation framework for echo shift-encoded hyperpolarized [1-¹³ C]pyruvate imaging was developed and applied to assess reconstruction performance and distortion correction of the proposed method. In vivo data were obtained in four pigs using hyperpolarized [1-¹³ C]pyruvate on a clinical 3T MR system with a six-channel receiver coil. Dynamic images were acquired during suspended ventilation using cardiac-triggered multi-echo single-shot echo-planar imaging in short-axis orientation.

Simulations revealed that off-resonance gradients up to ±0.26 ppm/pixel can be corrected for with reduced signal spilling and geometrical distortions yielding an accuracy of ≥90% in terms of Dice similarity index. In vivo, improved geometrical consistency (10% Dice improvement) compared to image reconstruction without field map correction and with reference to anatomical data was achieved.

Joint image and field map estimation allows addressing off-resonance-induced geometrical distortions and metabolite spilling in hyperpolarized ¹³ C metabolic imaging of the heart.