Deep learning-based image reconstruction for higher resolution cardiac T1 mapping

Motivation: The MOLLI acquisition scheme is frequently used for T1 mapping of the heart. MOLLI restricts the spatial resolution of the resulting T1 maps due to acquiring the inversion recovery images in single-shot fashion. Goal(s): To allow the acquisition of higher spatial resolution T1 maps. Approach: Single-shot acquisitions are accelerated and image sets are reconstructed using a neural network. The deep learning-based reconstruction is integrated into an existing T1 mapping sequence. Results: The proposed method produces higher spatial resolution T1 maps. The corresponding T1 values do not differ significantly from T1 values computed by the vendor sequence. Impact: The acquisition of higher spatial resolution T1 maps is achieved. The proposed method may improve the detection of small focal lesions without increasing the required scan time or breath hold duration.