Automated design of pulse sequences for magnetic resonance fingerprinting using physics-inspired optimization

Significance Magnetic resonance is a widely used noninvasive medical imaging technology. Most clinical MRI scans generate qualitative or “weighted” images. A recent new technology, magnetic resonance fingerprinting (MRF), simultaneously extracts quantitative voxel-by-voxel measurements of multiple intrinsic tissue properties such as T1 and T2 relaxation rates in a single scan, rapid enough for clinical use. These have been used for tumor characterization, epilepsy lesion detection, and for estimating variability of tissues in asymptomatic subjects. Here, we find that detailed computer models of random and systematic errors can be combined with physics-inspired optimization heuristics to discover MRF pulse sequences achieving substantially improved performance relative to MRF pulse sequences previously designed by human experts. Magnetic resonance fingerprinting (MRF) is a method to extract quantitative tissue properties such as T1 and T2 relaxation rates from arbitrary pulse sequences using conventional MRI hardware. MRF pulse sequences have thousands of tunable parameters, which can be chosen to maximize precision and minimize scan time. Here, we perform de novo automated design of MRF pulse sequences by applying physics-inspired optimization heuristics. Our experimental data suggest that systematic errors dominate over random errors in MRF scans under clinically relevant conditions of high undersampling. Thus, in contrast to prior optimization efforts, which focused on statistical error models, we use a cost function based on explicit first-principles simulation of systematic errors arising from Fourier undersampling and phase variation. The resulting pulse sequences display features qualitatively different from previously used MRF pulse sequences and achieve fourfold shorter scan time than prior human-designed sequences of equivalent precision in T1 and T2. Furthermore, the optimization algorithm has discovered the existence of MRF pulse sequences with intrinsic robustness against shading artifacts due to phase variation.