Recent progress in ASL

Highlights

• This article will briefly review the fundamentals of ASL, and then review new trends and variants of ASL including different labeling schemes, vascular territory mapping and velocity selective ASL, as well as arterial blood volume imaging techniques.

• This article will also review recent processing techniques to reduce partial volume effects and physiological noise.

• The article will examine how ASL techniques can be leveraged to calculate additional physiological parameters beyond perfusion and finally, it will review a few recent applications of ASL in the literature.

Abstract

This article aims to provide the reader with an overview of recent developments in Arterial Spin Labeling (ASL) MRI techniques. A great deal of progress has been made in recent years in terms of the SNR and acquisition speed. New strategies have been introduced to improve labeling efficiency, reduce artefacts, and estimate other relevant physiological parameters besides perfusion. As a result, ASL techniques has become a reliable workhorse for researchers as well as clinicians. After a brief overview of the technique's fundamentals, this article will review new trends and variants in ASL including vascular territory mapping and velocity selective ASL, as well as arterial blood volume imaging techniques. This article will also review recent processing techniques to reduce partial volume effects and physiological noise. Next the article will examine how ASL techniques can be leveraged to calculate additional physiological parameters beyond perfusion and finally, it will review a few recent applications of ASL in the literature.

Introduction

A major goal of modern medical imaging is to move beyond qualitative images that may be informative about the shape, size and texture of tissue, and into a world where medical images are also quantitative. One of the more popular and prominent techniques is arterial spin labeling (ASL), which can produce quantitative images of perfusion. Brain perfusion (defined as the amount of blood delivered to a unit of tissue per unit of time) is a well known indicator of tissue metabolism and function. As such, it is proving to be a powerful workhorse to study brain function and gaining prominence as a clinical tool, but it is still an evolving technique.

The concept behind ASL is relatively simple: conceptually, it is very similar to tracer injection perfusion measurements (e.g., bolus tracking MRI, autoradiography, PET … etc.) except that, instead of injecting a tracer into the blood stream and tracking its accumulation into the tissue, the tracer consists of the blood water in the arteries itself. The tracer is created by inverting the magnetization of the blood in the arteries that feed the organ of interest with a train of RF pulses. As this “labeled” blood flows into the tissue, it reduces the available magnetization in the tissue. As a result, images collected downstream of the labeling location appear slightly darker. By subtracting the labeled images from a set of control images, we can calculate the amount of blood that entered the organ since the beginning of the labeling period. For example, the most common use of ASL is for brain perfusion imaging, is done by labeling blood just before it enters the brain through the carotid and vertebral arteries. After a brief delay, a set of “labeled” brain images is acquired. Next, a second set of “control” images is acquired identical to the first, except that this time, the labeling pulses do not invert the blood magnetization at all, but simply serve as a control for any side effects of the labeling pulses (namely magnetization transfer (Williams et al., 1992, Wolff and Balaban, 1989, Zhang et al., 1995)). The subtraction of these two images is roughly proportional to the perfusion rate (see Fig. 1, depicting the ASL technique). If desired, one can acquire a time series of such image pairs in order to examine the brain's activity during a stimulation paradigm.

The main variations of the technique have to do with the labeling scheme. One could label a large segment of the neck region with a single pulse, as in the case of Pulsed ASL techniques, or one could apply a long pulse (or a train of pulses) at a thin slice through the neck that labels the blood as it flows through it, as in the case of continuous and pseudo-continuous ASL. More recently, “velocity selective” techniques have been developed such that only moving spins are labeled, regardless of their spatial position.

In general, ASL subtraction images have been shown to be roughly proportional to the perfusion rate with the appropriate scaling factors for the specific technique. Since the invention of ASL, there have been numerous validation studies of different ASL variants and their corresponding quantification models that compared them to other independent perfusion measurements (Chappell et al., 2013, Chen et al., 2008, Ewing et al., 2005, Gao et al., 2014, Hartkamp et al., 2014, Ye, 2000).

While ASL was invented around the same time as the BOLD effect was discovered (Detre et al., 1992, Williams et al., 1992), it has only been in the last five years that ASL has been widely adopted by the neuroimaging community. Largely, this recent resurgence of ASL has come about because of a combination of technical advances. The technique was previously challenged by its inherent low signal to noise ratio (SNR), and slow temporal resolution. With the advent of parallel imaging (Blaimer et al., 2004, Deshmane et al., 2012, Pruessmann et al., 1999), the development of pseudo-continuous labeling (Dai et al., 2008) and background suppression schemes (Ye et al., 2000b, St. Lawrence et al., 2005, Garcia et al., 2005), ASL images can now be acquired with sufficient speed and quality to be a robust, quantitative imaging tool. Another major hurdle to the adoption of ASL was the great diversity of schemes used by different investigators. It was not until 2014, that the community came together to make a set of recommendations for the implementation of a robust variant of ASL that could be used reliably as a “standard” implementation, even if not necessarily the best possible implementation for every application. However, this has created a de facto standard and helped the different vendors implement an ASL pulse sequence that can be distributed as a packaged product (Alsop et al., 2015). At the time of this writing, there are efforts under way to establish gold standards for calibration and validation of ASL images. Specifically, a profile for ASL is being created for the Quantitative Imaging Biomarkers Alliance (QIBA see http://www.rsna.org/qiba) that will describe a set of applications, capabilities and standards for ASL as a quantitative biomarker.

Having said that, this article will focus on recent progress in the development of ASL techniques at the time of writing. As mentioned earlier, a great deal of progress has been made in recent years on fast image acquisition techniques to boost the SNR and speed of the measurement. Additionally, new strategies have been introduced to improve labeling efficiency, reduce artefacts, and estimate other relevant physiological parameters using ASL techniques besides perfusion. As a result, a host of new applications for ASL techniques is becoming available to researchers, although we will only focus on neuroimaging applications.