Genetic algorithm-based optimization of pulse sequences

Abstract

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 [2-13C]lactate in vivo in the case of J-coupling modulation-free excitation. Results: The optimized polarization transfer pulses improved the SNR by ~50% with a more than twofold reduction in the B1 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.