Administrative Post: 19 April, 2011 (2/2)

Siemens users may be interested in a user training guide & FAQ that we use at Berkeley to initiate newbies into the ways of the dark side. (Using the Force is often the only way to get an fMRI experiment to work. What, you thought the f stood for functional? Ha!)

The guide is a bit rough - sorry for English-isms and typos - is updated fairly regularly based on popular misconceptions and the like, and is worth exactly what you pay for it. It's free. Use and abuse it however you like. It's a Word document so that you can reorder things, add your own notes, etc. I would appreciate constructive feedback, especially if you find mistakes or have suggestions to improve it, but there's no need to ask permission to use it, change it, replicate it, sell it...

The most recent version of the training guide/FAQ is available from this web page:

http://bic.berkeley.edu/scanning

Locate the file attachment towards the bottom of the page, it's called 3T_user_training_FAQ_19April2011.doc. The most recent contents appears below.

Caveat emptor.

The document is only a component of user training, don't expect to learn how to scan by reading it! Rather, use the tips to extend your understanding, refine your experimental technique and so on. Note also that this document is for a Siemens TIM/Trio (with 32 receive channels) and running software VB15. There may be subtle or not-so-subtle differences for the Verio and Skyra platforms, for software VB17, VD11, etc. so keep your wits about you if you're not on a Trio with VB15!

You may have local differences, e.g. custom pulse sequences, that allow you to do things that contradict what you find in this user guide. Talk to your physicist and your local user group before taking anything you find in this guide/FAQ too literally.

Finally, you wont find many (any?) references in this guide/FAQ. It's for the training of newbies, not a comprehensive literature review! If you are seeking further information on something I mention in the guide and you can't find a suitable reference yourself, shoot me an email and I'll do my best to point you in a useful direction.

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User guide/FAQ contents (as of 19 April, 2011):

Administrative Post: 19 April, 2011 (1/2)

I have renamed the three posts entitled "Diagnosing artifacts in fMRI data: Part x" to be "Physics for understanding fMRI artifacts: Part x." I am developing new posts in the series and through post seven at least the content is all quite theoretical; I'm not actually discussing artifacts or showing data! (But don't worry, I'm limiting the content to the essential concepts required to understand and differentiate fMRI artifacts. It's not going to be an entire MRI physics course!)

Once I've concluded this background series of physics posts (there are another eight or nine posts to come) I'll start a new series that will be entitled something suitable for actual artifact recognition (with data!), along the lines of the original title of the series. Hopefully this re-categorization will allow future readers to establish suitable paths through the posts, when a strictly chronological path probably won't be the best one.

Shim and gradient heating effects in fMRI experiments

Another week, another tangent. At least this one is directly related to the artifacts that I promise to get back to soon!

In this post I will review the nature and typical magnitudes of heating effects in a scanner being used for fMRI. Ever wondered why you sometimes observe discontinuities, or 'steps,' in a time series comprising the concatenation of multiple blocks of EPI data? What causes these discontinuities? Are they a problem for fMRI? And are there ways to reduce or eliminate these discontinuities at the acquisition stage? To begin with, some background.

Electrical energy in, thermal and vibrational energy out

When you run the gradients to generate images, a lot of heat is produced through vibrations (friction) of the gradient coils - the Lorentz forces that result from putting electrical current through copper wires immersed in a magnetic field - as well as through direct (resistive) electrical mechanisms. Much of that heat is removed via water cooling inside the gradient set. Water typically enters at about 20 C and may exit the scanner as high as 30 C. Modern gradient designs are pretty efficient at removing heat from the gradient coil. (I've done throwaway tests on my Siemens Trio that suggest the steady state temperature of the return cooling water is achieved after about 15 minutes of continuous scanner operation.) But - and this is the crux of this post - the heat imparted to the scanner isn't removed at precisely the same rate that it is being produced. In other words, the scanner is unlikely to be in a truly steady thermal state while you're using it.

Go faster MRI at Berkeley!

With apologies for the continued delay to the artifact recognition series of posts - I've been distracted with some scanner problems - I thought I'd do a quick post on a recent methodological development that's generated some buzz in the field as well as in the media. The media buzz:

ABC 7 News video

UC Berkeley news center story

And in case you want to read the actual publication, it was published at PLoS ONE in early January. The work is part of the Human Connectome Project, an NIH-funded consortium involving Washington University (St Louis), Oxford, Minnesota and Berkeley. David Feinberg is the Berkeley representative.

The implications of these methodological developments could be quite substantial, possibly allowing better interpretation of brain dynamics than is currently permitted with the typical fMRI temporal resolution of two seconds or so. Of course, there are caveats. One is that the BOLD response is still low-pass filtered. And another is that the new "go faster" method involves several separate steps, each of which tends to exacerbate head motion sensitivity. Still, it looks good on highly motivated volunteers!

Physics for understanding fMRI artifacts: Part Three

Coffee break! Time for a few tangents

In this post we're going to do a whistle-stop tour of some background concepts that you should have seen before. None of the information in today's series of videos is essential to understanding what's coming up later, when we get to k-space, the EPI pulse sequence and artifacts, but it's interesting and useful to review. Besides, these videos are well made, entertaining and are available free so we might as well use them! So, if you have the time, go grab a coffee and spend the next hour being reminded of things you probably knew at some point in a dim and distant past. You might even learn something about scanner hardware you didn't know before.


The anatomy of a miniature scanner

Don't worry too much about following every detail in today's first video, which dissects a miniature MRI scanner. It contains the same basic components as your fMRI scanner. Below, I've given a few explanatory notes on the coils and components that are most relevant to us.

Physics for understanding fMRI artifacts: Part Two

We continue our review of the key principles of NMR with another video courtesy of Paul Callaghan. In it, Prof Callaghan introduces the idea of bulk magnetization; the thing that you induce in your subject's brain (which is ~80% water) when you slide the subject into the magnet, and which you then manipulate to produce images.

In the video shown previously (see Part One), Prof Callaghan introduced the phenomenon of resonance and demonstrated it with a spinning wheel. In MRI the resonance frequency is governed by a simple proportionality, as given in the Larmor equation. We will use this equation later on to establish different frequencies across an object, thereby encoding spatial information and yielding, ultimately, an image of that object. We will also see how the Larmor equation is used in the k-space formalism, so make sure you have a good understanding of this deceptively simple yet intuitively valuable equation.

Physics for understanding fMRI artifacts: Part One

This is the first in a series of posts in which I will attempt to provide you with the means to diagnose the manifold artifacts that plague fMRI. These artifacts can be inherent, e.g. distortion and dropout, or the consequences of a hardware issue, e.g. RF interference or gradient spiking, or may arise from your subject, e.g. cardiac pulsatility and head movement. However the artifacts arise, the aim is simple: by providing you the means to recognize what is going wrong in your experiment you may be able to discern the root cause, then remedy the problem and salvage your data.

It's a lot like plane spotting, only less fun.

The psychologists amongst you would be able to lecture me for days on category learning. Well, that's what this is. Except that before we can differentiate between one artifact and another we must first understand how EPI is designed to work in an ideal situation. (You don't need to know how planes fly to categorize them, apparently.) And to comprehend artifacts it's important for you to have a reasonable appreciation of the underlying physics, especially the concept of k-space. Here's the loose plan: