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.

Highlights

  • Vessel-selective angiograms and vascular territory maps allow collateral circulation in the brain to be visualized

  • We propose a rapid optimized encoding scheme (OES) that automates the choice of signal-to-noise ratio (SNR)-efficient encodings, regardless of the number or arrangement of vessels

  • The average SNR efficiency of the OES encodings remained close to the ideal value of one (Fig. 2a)

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Summary

INTRODUCTION

Vessel-selective angiograms and vascular territory maps allow collateral circulation in the brain to be visualized. With vessel-encoded pseudocontinuous arterial spin labeling (VEPCASL) the labeling efficiency varies periodically across the plane in which vessels are tagged. Planning-free VEPCASL is possible, where a few fixed encodings are applied and vascular territory information is achieved using a voxel clustering method [19]. We propose a rapid optimized encoding scheme (OES) that automates the choice of SNR-efficient encodings, regardless of the number or arrangement of vessels. This builds on work previously presented in abstract form [21]. Ideal encoding matrices are those whose SNR efficiency is equal to one for all vessels [14], which requires that the arteries are perfectly tagged (À1) and controlled (þ1) an equal number of times. The columns describe (from left to right) the label/control state of the right internal carotid artery, left internal carotid artery, right vertebral artery, left vertebral artery, and static tissue, respectively, for each encoding (or row)

À1 À1 1 1
METHODS
Random Method
OES Method
RESULTS
DISCUSSION
CONCLUSIONS
Full Text
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