Physics for understanding fMRI artifacts: CONTENTS

Figured it might be useful to have some summary/contents pages. I'll do similar admin posts as the other series mature, too. And I will label these pages with "Contents" to make them easier to find via the sidebar.


Part One

An introduction to the series, followed by an introductory video courtesy of Sir Paul Callaghan: What is NMR and how does it work?


Part Two

Further videos explaining the principles of nuclear magnetic resonance - how the intrinsic spin of certain atomic nuclei interacts with applied magnetic fields to yield useful information.


Part Three

Videos showing the anatomy of a miniature scanner, a basic NMR experiment, why shimming is important for NMR (and MRI), how and why a spin echo works, and the relaxation of spins back towards their ground state.


Part Four

Mathematics of oscillations: an introduction to imaginary and complex numbers, and frequency and phase.

Common persistent EPI artifacts: Abnormally high N/2 ghosts (2/2)

In the previous post I covered sources of persistent ghosts that arise as a result of some property of the subject, such as the orientation of the subject's head in the magnet. These are what I'm categorizing as subject-dependent effects. In this post I will review the most common sources of persistent ghosts attributable to the scanner, either from an intrinsic property that you might encounter inadvertently, or from mis-setting a parameter in your protocol. As I mentioned last time, I am restricting the discussion to factors that you have some control over as the scanner operator. Ghosts that arise because of a scanner installation error, such as poor gradient eddy current compensation or inaccurate gradient calibration, are issues for your facility physicist and/or your service engineer.

Scanner-dependent conditions:

Rotated read/phase encode axes 

GLOBAL - affects all slices to some extent.

This is an insidious problem that we could categorize as pilot error, except that it's very easily encountered without realizing it. When you set up your slice prescription you are primarily concerned with capturing all those brain regions you need for your experiment. Or you might be concerned with setting a particular slice angle relative to the brain anatomy, e.g. parallel to AC-PC. Now, if the subject's head is precisely aligned such that the read and phase encode axes of your imaging plane are matched perfectly with the gradient set axes (i.e. with the magnet's frame of reference), then for axial slices the readout dimension will be attained using pure X gradient (subject's left-right) while the phase encode dimension uses pure Y gradient (subject's anterior-posterior). (See Note 4 in the post on "Good" coronal and sagittal data for an explanation of why the gradients are established this way, for subject safety/comfort reasons.) But, if the head is twisted slightly, or you're a little sloppy with your slice positioning, then it is quite easy to have a readout gradient that is mostly X with a little bit of Y, and a phase encoding gradient that is mostly Y with a little bit of X. This in-plane rotation ought not be a problem if the X and Y gradients performed equivalently, but they're only similar and not identical. There tend to be small differences in the response time of the gradients, which means that when the scanner tries to drive the read gradient to its desired k-space trajectory, one component (say the X component) can respond faster than the other. This produces a slight mismatch between the target (ideal) k-space trajectory and the trajectory that's actually achieved by the gradients, thereby leading to a source of zigzags that will produce N/2 ghosting.

Now the good news. You've got to rotate the image plane by quite a lot before the ghosting starts to become apparent. It's common to have rotations of 1-2 degrees and these will generate almost no additional ghosting. Once the rotation gets much larger than 5 degrees (depending on the specifics of your scanner) then you might start to see additional ghosting. Below on the left is an ideal prescription, while on the right I've intentionally rotated the image plane by 8 degrees, leading to a small but noticeable increase in ghost level:

(Click to enlarge.)

Common persistent EPI artifacts: Abnormally high N/2 ghosts (1/2)

 
In this and a subsequent post I am going to cover some common situations when the N/2 ghosts can become abnormally high, i.e. higher than it is possible to achieve with comparatively small tweaks to the setup. For now I am going to restrict the discussion to temporally static, or persistent, ghosts. Furthermore, I will restrict the discussion to situations over which you can exert some control, usually through the subject setup and via EPI parameter selection. I'll cover the origins of dynamic ghosts later on in this series, once you've got a better grasp of the common persistent ghosting sources and are in a position to differentiate between a source that is intermittent and a (persistent) ghost that is being modulated by subject motion.

Before we get into the different experimental conditions that can lead to abnormally high ghosting, it is important that you are familiar with the reason why N/2 ghosts arise in EPI in the first place. So, if the following section sounds like Swahili (and you don't ordinarily speak Swahili) then I would encourage you to spend twenty minutes reviewing the section on N/2 ghosts in PFUFA Part Twelve before continuing here.

New blog! MathematiCal Neuroimaging

 
My colleague, DS has begun a new blog, mathematiCal Neuroimaging, dedicated to exploration of the mathematical principles underlying neuroimaging methods. Here are some excerpts from the section labeled About:

As the name of the blog partially implies, the topic here will be the mathematics and physics of neuroimaging. In particular the focus will be upon functional imaging of the brain.

 The style of this blog will range from tutorial-like expositions of present functional neuroimaging technology to whimsical explorations of how we might create better functional neuroimaging technology.

An entry on parallel imaging has just been posted. See you over there!

New stats/analysis blog, with MATLAB examples

New blog from Kendrick Kay on stats and analysis together with some supporting MATLAB
scripts. Looks VERY useful!

http://randomanalyses.blogspot.com

Common persistent EPI artifacts: Gibbs artifact, or ringing

 
Don't ask me why there's no apostrophe, it looks possessive to me. Perhaps it's (the) Gibbs artifact rather than Gibbs (his) artifact. Most people simply refer to the effect as ringing anyway, so let's move on. This post concerns a phenomenon that, like aliasing last time, isn't unique to EPI but is a feature of all MRIs that are obtained via Fourier transformation.

In short, ringing is a consequence of using a period of analog-to-digital conversion in order to apply a (discrete) FT to the signals and produce a digital image. Or, to put it another way, we are using a digital approximation to an analog process and thus we can never properly attain the infinite resolution that's required to fully represent every single feature of a real (analog) object. Ringing is an artifact that results from this imperfect approximation.

We had already encountered one consequence of digitization in the Nyquist criterion in PFUFA Part Six. However, for our practical purposes, ringing isn't a direct consequence of digitization like the Nyquist criterion, but instead results from the duration of the digitization (or ADC) period relative to the persistence of the signals being measured. In principle, a signal decaying exponentially decays forever, which is rather a long time to wait for the next acquisition in a time series, so we instead enable the ADC for a window of time that coincides with the bulk - say 99% - of the signal, then we turn it off. This square window imposed over the exponentially decaying signal causes some degree of truncation, and it's this truncation that leads to ringing. (See Note 1.)


An example of ringing in EPI of a phantom

Let's start with an unambiguous example of ringing by looking at the artifact in a homogeneous, regular phantom. Below is a 64x64 matrix EPI acquired from a spherical gel-filled phantom. You're looking for the wave-like patterns set up inside and outside the edges of the main signal region:

In the left image, which is contrasted to highlight ringing artifacts within the signal region itself, the primary ringing artifact appears as a series of concentric circles, each with progressively smaller diameter and lower intensity as you move in from the edge of the phantom. One section of the bright bands is indicated with a red arrow, but you should be able to trace these circles all the way around the image. Also visible is a strong interference pattern (blue arrows) that arises between the aforementioned ringing artifact and the overlapping N/2 ghosts. This is because the ghosts maintain the contrast properties of the main image; they are, after all, simply weak (misplaced) clones of the main image.

Another brief explanation of decoding

Here's another short video produced by UC's media people in which Jack Gallant explains in broad terms how his group's recent decoding experiment was conducted:

A good place to go next for more details is the Gallant Lab website. Read the FAQ on that page to gain a basic understanding of what the experiment was, and what it wasn't. Then go read the paper, it's written very accessibly!