|Timeline of my ROP experience|
|Timeline of my ROP experience|
|Helena Lan Summer 2014 ROP|
What is research like? If you had asked me this
question several months ago, I would have answered, “You wear a lab coat and
goggles while mixing chemicals or observing organisms. Hopefully something
interesting will happen, so that you get to publish your findings!” Well, after
participating in the Research Opportunity Program (ROP) at the University of
Toronto, I discovered that medical imaging research is more than just
pipetting, and is all the more exciting!
So, what does medical imaging have to do with a Supernova? Well in the B-movie – Supernova a deep space medical ship responds to a distress signal from a nearby mining planet and gets too close to a Red Supergiant ready to go Supernova. Is your geek alert tingling?
Well, believe it or not Supernovas are explosions of giant stars. Nuclear fusion produces iron in the cores of these stars. Such dense matter at the core creates a tendency for the star to collapse on itself due to gravitational pull. This is kept in check by the massive amounts of energy the star is constantly releasing. But what happens when the star starts to run out of fuel? Yup, you guessed it. It collapses on itself and implodes. As the star rushes inwards, protons and electrons combine to produce neutrons that in turn collide with the core and produce a crazy big explosion. This sudden release of energy is accompanied by the production of x-rays. Yes, I am serious. What is left behind of the exploded star is either a neutron star or a black hole depending on the mass of the remains.
So, a supernova is essentially a giant x-ray machine? Maybe not. However, by studying these cosmic x-rays astronomers are able to help describe the structure of the universe (not Castle Greyskull). Cool.
Question for you: should we be concerned with being exposed to cosmic x-rays? No. Cosmic x-rays are pretty much completely filtered out by our atmosphere by the time they get to the surface. So, how do astronomers get readings? Good question. By placing their recording instruments on satellites and spacecraft, of course!
Now on to using supernova in a sentence today:
Serious example – So did you catch the last supernova in our galaxy? Happened about 400 years ago. No? The next one should be soon as it is overdue by about 300 years.
Less serious – Growing up I always loved the Chevy Nova SS. Especially when it was customized. It surely was a super Nova…
Enjoy Ray LaMontagne – Supernova to recover from today’s post and I’ll see you in the blogosphere.
|Angela Lo, MED YSP 2014 Student|
What!!? Do you find it on pizza or in the middle of green olives? Well actually, it is a word of Italian origin and describes minor changes in a painting during its composition. So, similar to erasing some of your hand writing and then writing over it again with the corrected text. I guess for you younger folk it would be like pressing back-space and then re-typing! The difference of course is that there would NOT be any pentimenti as there would no trace of your previous attempt…
So what does this have to do with medical imaging? In our last Mi word of the day we talked about x-rays. Now, today we take x-rays and our ability to peer inside the human body for granted. So what else can we see with x-rays? Believe it or not x-rays can also help to reveal how a painting evolved from first brush strokes to finished product. X-ray analysis can help to describe the paint composition to the different layers that may exist in the painting.
Consider, for example, “Patch of Grass” by Van Gogh seen above. It was discovered by x-ray analysis that this 1887 painting completely concealed a portrait of a woman that Van Gogh had painted over. He often did this to save money on canvases (maybe to buy Absinthe – how naughty!). In this case, in addition to Van Gogh’s pentimenti is his habit of painting over previous works. All of this adds to a type of “fingerprint” that art appraisers use to identify works of art from forgeries… Cool.
Today, we have to use “pentimenti” in a sentence (see rules here). Here are two examples to help you along:
Serious: I wonder how Van Gogh’s pentimenti differs from that of Rembrandt. Maybe I should ask the Musee du Louvre’s curator for some insight.
Last week I met with Helen, a clinical investigator program radiology resident from our department, about her research (shout out to Dr Laurent Milot’s research group). When discussing predictors and outcomes for her retrospective study it was suggested that some continuous variables be broken up into levels or categories based on given cut-points. This practice is often encountered in the world of medical research. The main reason? People in the medical community find it easier to understand results that are expressed as proportions, odds ratio, or relative risk. When working with continuous variables we end up talking about parameter estimates / beta weights and such – not as “reader friendly”.
Unfortunately, as Neil Sedaka sang about in his famous song Breaking Up Is Hard to Do, by breaking up continuous variables you pay a stiff penalty when it comes to your ability to describe the relationship that you are interested in and the sample size requirements (see loss of power) of your study.
You are now a newly minted research scientist (need a refresher? See Pocket Protector) and are interested in discovering relationships among variables or between predictors and outcomes. The more accurate your findings the better the description of the relationships and the better the interpretation/ conclusions you can make.The bottom line is that dichotomizing/ categorizing a continuous measure will result in loss of information. Essentially, the “signal” which is the information captured by your measure will be reduced by categorization and, therefore, when you perform a statistical test that compares this signal to the “noise” or error of the model (observed differences between your patients for example) you will find yourself at a disadvantage (loss of power). David Streiner (great author and great guy!) gives a more complete explanation in one of his papers.
Now, as we see in the funny movie with Vince Vaugh and Jennifer Aniston, The Break Up, there are times when categorization may make sense. For example when the variable you are considering is not normally distributed (see Are You My Type?) or when the relationship that you are studying is not linear. We will talk about these situations in a later post.
Don’t forget: you will get further ahead if you keep your variables as continuous data whenever possible.
See you in the blogosphere,
Yup! Want some of that. Not only is Superman cool but he has x-ray vision. Unbelievable. Or is it? Radiologists have the same x-ray vision but without the Spandex suit – or at least they don’t wear it to work that I am aware of.
The word of the day is x-ray. You have already successfully used “Roentgen” in casual conversation last week (don’t know what I am talking about? See Mi Word of the Day Is… Roentgen!) and today I will talk a little about what Roentgen was first in measuring and describing – x-rays.
Let’s say you are in your lab and you are working with passing electrical discharges through vacuum tubes – a typical Saturday afternoon activity with friends. As chance would have it your little sister’s barium salts paintings happen to be drying near-by and you notice a faint glow emanating from them every time you run your experiments. No matter how much you try to block any light coming from your vacuum tubes the glow persists. What? That’s odd. How’s that happening? Well my friend, you have just crossed over into the Twilight Zone (awesome old tv series) and discovered a form of electromagnetic radiation.
Visible light is but a very small part of the electromagnetic spectrum. Moving from visible light to longer wavelengths and lower frequencies we find infrared (keeps food warm at restaurants), microwaves (to warm your pizza pop) and radio (not the one streamed through the internet!).
Now if you move in the opposite direction from visible light you find shorter wavelengths with higher frequencies starting with ultraviolet (what helps you get that summer tan), x-rays (word of the day), and finally gamma rays (topic for another day!). So x-rays are about the size of atoms and radio waves the size of buildings. Crazy. I think what is surprising is that with the naked eye we “see” so little and yet so much (philosophy anyone?).
So, x-rays are short wavelength, high frequency, high energy electromagnetic radiation that is able to penetrate some substances more easily than others. For example, they penetrate flesh more easily than bone, and bone more easily than lead. Thus they make it possible to see bones within flesh and a bullet embedded in bone. The ability of X rays to penetrate depends on their wavelength and on the density and thickness of the substance being scanned.
See you in the blogosphere,
Welcome to the first Medical imaging Word of the Day! Here is how it works:
1- I introduce and discuss a word.
2- You have to use the word in a sentence by the end of the day. No need to use it in the correct context – actually out of context is more fun and elicits a more entertaining response!
OK, here we go. The word of the day is Roentgen – typically pronounced “Rent-gun”.
Wilhelm Roentgen was a physicist from northern Germany who in 1895 was the first to detect the now famous x-ray. Interestingly, he was not the first to produce them. The x-ray is part of the electromagnetic spectrum that contains shorter wavelengths (0.01 to 10 nm) than visible light (390-700 nm). We will talk about this in another post as today it is about Roentgen.