MR Sequence Design in the Low Stochastic Regime - Development of a Low-SAR “T2-Weighted” Scan

Motivation: The introduction of Machine Learning-based Image Reconstruction ("Deep Learning") offers a fresh opportunity to explore MR parameter space without the restrictive requirement to maximise MR signal. Goal(s): Demonstrate an application of the Low Stochastic Regime approach using low flip angle refocusing with good SNR and strong tissue contrast. Approach: Fast Spin Echo (FSE) images were acquired using reduced flip angle refocusing and extended echo train lengths, in combination with Deep Learning-Reconstruction (“DL-Recon”). Results: Using DL-Recon to effectively weaken the conventional constraint of maximising MR signal, the redesigned sequence produced images with lower RF power deposition but similar contrast to the product CPMG sequence. Impact: Clinical applications where T2-weighted imaging is SAR-limited.