Genetic algorithm-based optimization of pulse sequences

Purpose: The performance of pulse sequences in vivo can be limited by fast relaxation rates, magnetic field inhomogeneity, and nonuniform spin excitation. We describe here a method for pulse sequence optimization that uses a stochastic numerical solver that in principle is capable of finding a global optimum. The method provides a simple framework for incorporating any constraint and implementing arbitrarily complex cost functions. Efficient methods for simulating spin dynamics and incorporating frequency selectivity are also described. Methods: Optimized pulse sequences for polarization transfer between protons and X-nuclei and excitation pulses that eliminate J-coupling modulation were evaluated experimentally using a surface coil on phantoms, and also the detection of hyperpolarized [2-C-13]lactate in vivo in the case of J-coupling modulation-free excitation. Results: The optimized polarization transfer pulses improved the SNR by similar to 50% with a more than twofold reduction in the B-1 field, and J-coupling modulation-free excitation was achieved with a more than threefold reduction in pulse length. Conclusion: This process could be used to optimize any pulse when there is a need to improve the uniformity and frequency selectivity of excitation as well as to design new pulses to steer the spin system to any desired achievable state.

Automated summary

The method described in the study utilizes a stochastic numerical solver for optimizing pulse sequences, providing a simple framework for incorporating constraints and complex cost functions. Experimental results show improved signal-to-noise ratio with optimized polarization transfer pulses and achieve J-coupling modulation-free excitation.