Introduction

This presentation aims to introduce the scientific/technical basics of multicontrast/multiparametric imaging. The motivations will be introduced, followed by acquisition schemes and reconstruction approaches. Specific examples in cardiovascular applications will also be discussed, including IR TrueFISP (CABIRIA) approach, cardiac MRF, and multicontrast imaging using multitasking.

Methods

In single-parametric imaging or mapping, the sequence is sensitive to one parameter at a time. However, for multi-parametric mapping, the ideal sequence should be sensitive to all parameters we want to measure, such as T1, T2, T2*, etc. Therefore, the goal of the pulse sequence design is to maximize the sensitivity of the sequence to the desired parameters and minimize its sensitivity to the unwanted parameters. The first approach is to employ the sequence types that generate multiple contrasts, such as SSFP type sequences, which are sensitive to both T1 and T2. Either based on those sequences or other sequence types, we can add magnetization preparation modules to further sensitize the sequence to specific parameters. At last, we can also explore the readout dimension. For example, multi-echo acquisition enables T2* and chemical shift encoding. Two reconstruction methods will be introduced for multiparametric mapping: model-based reconstruction and machine learning. MRI reconstruction is an ill-posed problem and the solution can be found by solving the regularized inverse problem by taking advantage of some prior knowledge of the images. The prior knowledge includes sparsity in temporal or spatial domain, or low-rank nature of the data. Machine learning is an emerging technique to solve reconstruction problems. It requires a lot of training data, but once the training process is completed, the reconstruction becomes a lot faster than model-based reconstruction.

Conclusion

Simultaneous multicontrast/multiparametric imaging achieves comprehensive tissue characterization efficiently. Its application in CMR is challenging but promising and appealing.

Acknowledgements

No acknowledgement found.

References

No reference found.