Simultaneous multislice cardiac multimapping based on locally low-rank and sparsity constraints

Area of Science:

• Cardiovascular Magnetic Resonance Imaging
• Quantitative Myocardial Imaging
• Medical Physics

Background:

• Current quantitative myocardial T1 and T2 mapping requires multiple breath-holds, limiting clinical efficiency.
• Simultaneous acquisition of multislice myocardial T1 and T2 maps is needed for faster cardiovascular assessments.

Purpose of the Study:

• To develop and validate a simultaneous multislice (SMS) multimapping technique for quantifying T1 and T2 in three short-axis myocardial slices within a single breath-hold.
• To assess the accuracy, precision, and reproducibility of the proposed method.

Main Methods:

• Developed an SMS-Multimapping sequence with multiband radiofrequency excitations and Cartesian fast low-angle shot readouts.
• Implemented a reconstruction algorithm using locally low-rank and sparsity (LLRS) constraints to address artifacts from 12-fold acceleration.
• Validated the technique in phantoms and in vivo with 20 healthy subjects and 4 patients.

Main Results:

• SMS-Multimapping with LLRS accurately reconstructed T1 and T2 maps with a six-fold acceleration.
• The LLRS algorithm significantly improved image quality compared to existing parallel imaging methods.
• Quantitative results for T1 and T2 mapping showed comparable accuracy and acceptable reproducibility to established methods (MOLLI, bSSFP), with improved precision for T1.

Conclusions:

• SMS-Multimapping combined with LLRS reconstruction enables efficient, single-breath-hold multislice myocardial T1 and T2 mapping.
• The technique offers a six-fold reduction in scan time, enhancing patient comfort and diagnostic throughput.
• This method provides accurate, precise, and reproducible quantitative myocardial tissue characterization.