An Optimized Encoding Scheme for Planning Vessel-Encoded Pseudocontinuous Arterial Spin Labeling.

Abstract

Vessel-encoded pseudocontinuous arterial spin labeling allows the acquisition of vessel-selective angiograms and vascular territory perfusion maps. The technique generates a periodic variation in inversion efficiency across space that can be manipulated to encode specific combinations of vessels. Currently, the choice of these encodings is limited to scenarios with few vessels and may not optimize the signal-to-noise ratio (SNR). Here we present an automated, rapid method for calculating a minimal number of SNR optimal encodings for any number and arrangement of vessels. The proposed optimized encoding scheme (OES) is a Fourier-based method that finds SNR optimized encodings to best match the ideal encodings for a set of vessels. For nine or fewer vessels, the calculation takes less than 3 s. In simulations, the OES method produces encodings for a range of vessel geometries that, on average, have an SNR efficiency 37% greater than that for random encoding. When labeling vessels in the neck in healthy subjects, the OES encodings result in images with higher SNR than other encoding methods. The OES results in a minimal number of encodings with a higher SNR efficiency than other encoding methods, regardless of the number or geometry of the vessels.