## MiVIP meets AI…

Well, I think it was inevitable. My data science lab has slowly crossed over to the dark side into the world of  Machine Learning and Artificial Intelligence.

Let me apologize for being MIA for so long. Life has been pretty hectic these past months as I have been building the MiDATA program here in the Department of Medical Imaging at the University of Toronto. The good news is that the MiVIP program will now be inviting students to participate in machine learning and artificial intelligence in medical image research.

This summer will include the launch our our MiStats+ML program where we will have students from the department of statistical sciences, computer sciences, and life sciences all work together on ML/AI projects in the MiDATA lab.

Stay tuned as we ramp up and get back to some our previous threads like MiWORD of the day…

See you in the blogosphere,

Pascal

## The Ram-ifications of Risk

In the final installment of this series, I want to discuss how we can use the Ratios of Risk in a clinical context. To recap, we previously discussed an absolute measure of risk difference (appropriately called the risk difference or RD), as well as a relative measure of risk difference (relative risk or RR).

To see how we can apply these risks, let’s tweak our original example. Let’s assume that smartphone thumb could potentially lead to loss of thumb function (not really, don’t worry!). Let’s also suppose that surgery is a possible treatment for smartphone thumb, and the following results were obtained after a trial.

 Surgery No Surgery (control) Totals Retained  thumb function 7 6 13 Lost thumb function 3 4 7 Totals 10 10 20

The big question is: how good an option is surgery?
Let’s calculate the RD (note that the “risk” here is of losing thumb function): 4/10 – 3/10= 0.1

In other words, there is a 10% greater risk of loosing thumb function if you did not have the surgery. Based on this information alone (or by calculating the RR and OR), we might be quick to conclude that surgery is a great intervention.

But before we do that, let’s calculate another statistic, which will prove to be very useful: it’s called the number needed to treat (or NNT), and is given by 1/RD. The NNT is the number of patients that must be treated for 1 additional patient to derive some benefit (retain an intact and functioning thumb). In our case, NNT = 1/0.1 = 10. So, in order save 1 patient from loosing his thumb, another 9 will have had to undergo surgery with no apparent benefit. As you can see, the NNT sheds a very humbling light on our intervention. The ideal NNT is equal to 1. Beyond that, we must keep in mind that the additional patients undergoing the treatment have been exposed to all the negative side effects, without the intended benefit.

Throughout this series we discussed the meaning of risk, how it can be used for comparison (the various ratios of risk), and finally its application in a clinical setting (the ramifications of risk). After all these posts, smartphone thumb may have started to seem like a very real threat. But I think you should be fine…. as long as you know the risks!

So what’s up with the Dodge Ram ad (I am actually a F150 guy myself)? Well I just thought it went well with ramifications of risk. Cheesy I know. But who knows maybe it will help you to remember…

See you in the blogosphere,

Indranil Balki and Pascal Tyrrell

## The Ratios of Risk With a Zip!

With summer here, I think it’s time that we continued our discussion on risk. No, I’m not talking about the dangers of your favourite adventure sport… but then I just got back from a trip to Costa Rica as part of the Canadian delegation for the Gateway to Trade  project and I, of course, went ziplining! Awesome.

It’s been a few months so I recommend catching up on Risky Business – Is it all Relative? and Happy New Year and Enjoy some AR&R

Before we get started I want to introduce a student of mine, Indranil Balki, who has agreed to come aboard and help me write this blog. Life is busy for me and I feel bad that I can’t post as much as I would like. So look to find Indranil signing off with me at the bottom of these posts.

When we last left off, we were interested in the idea of comparing risks – how many times more likely is it for a smartphone user to develop smartphone thumb than for a non-smartphone user?

We touched on one way to compare the two groups in the last post, by finding the risk difference A/(A+B) – C/(C+D). But to answer our question, we need a ratio. It turns out that this is called (helpfully) a risk ratio, or relative risk (RR). The RR is given by A/(A+B) divided by C/(C+D). A RR basically compares the risk in the exposed (smartphone owners) and unexposed conditions.

For example, let’s say that 20% of smartphone users developed smartphone thumb and 10% of non-smartphone users developed smartphone thump. Then the RR is 2, meaning that you are twice as likely to get the disease if you own a smartphone than if you don’t.

Well wasn’t that an elegant way to compare the risks between two groups? As you might have guessed, a RR of 1 shows no difference in risk between the groups, and an RR > 2 or <0.5 is usually considered statistically significant.

So let’s say you meet a friend at school and he finally reveals that he has smartphone thumb (don’t worry, it’s not contagious – I think!). Since you’ve been following this blog, you immediately wonder, what’s the probability that he has a smartphone? To answer this reverse question, it turns out that you technically need what is called an odds ratio (OR). The OR is comparable to the RR if the prevalence of the disease is low. But it is a slightly different way to compare risks.

Given that you have smartphone thumb, the odds that you had the exposure are given by the probability that you had a smartphone (A/A+C), divided by the probably that you didn’t have it (C/A+C). This simplifies to A/C. Similarly, the odds of exposure in those without smartphone thumb is B/D. The odds ratio then, is calculated by dividing these 2 odds. OR = A/C ÷ B/D. An OR of, say 3, tells us that there’s a 3 times higher chance your friend has a smartphone than he doesn’t.

Well, that might have been a tough post! Take some time to think about it, have a gander at some ziplining in Costa Rica here and don’t spend too much time on your smartphone…

See you in the blogosphere,

Indranil Balki and Pascal Tyrrell

## A Medical Ethics ROP Journey with Jayun Bae

 Jayun Bae – ROP299Y 2016-17
My name is Jayun Bae and I am completing my second year in the Neuroscience and Bioethics majors at the University of Toronto, St. George. I was a 2016-2017 Research Opportunity Program (ROP) student in Dr. Pascal Tyrrell’s lab, working on a study that investigated the ethics of sharing patient data with private organizations (see my timeline above). I am a member of the Hart House Debating Club and an events associate for the Life Science Student Network.

My ROP project was necessitated by the partnership proposed by the Medical image Networking Enterprise (MiNE) that would establish a data-sharing relationship between public and private sector organizations. The ethical concerns with the partnership involved patient consent, privacy, and financial gain – but there were also issues that I
uncovered throughout the project. It quickly became clear that the answers could not be found through an examination of precedence or legal documents, because many of the research actions that would take place (specifically involving private organizations) fell in the grey area between what was legal and what was ethical. For example, the Personal Information Protection and Electronic Documents Act (PIPEDA) and Personal Health Information Protection Act (PHIPA) are two guidelines for organizations to follow when handling patient data – but neither are able to clearly and positively dictate how this partnership should operate.
Therefore, I developed a study that would seek expert opinions through the administration of a survey. I conducted interviews at Sunnybrook Health Sciences Centre and the University of Toronto and performed qualitative data analysis. My ROP project was presented at the ROP Poster Fair and the Victoria College Research Day events. The ROP was an extremely valuable experience in gaining research skills, and I’m grateful to
Dr. Tyrrell for the guidance and mentorship. The project is not yet completed, so I am looking forward to continuing the study beyond the scope of the ROP.
Please have a look at my poster from the 2017 ROP Research Day below:

## MRI, Statistics, Carotid Arteries, and 1000 Cups of Coffee with George Wang

 GeorgeWang – ROP299Y 2016-17
I’m George. I have recently completed my 2nd year undergrad at the University of Toronto studying physiology and physics. In the fall-winter term of 2016-17 I had the privilege to work in Pascal’s group, looking into carotid artery MRI and using the volume of the carotid artery vessel wall as a marker for atherosclerosis. Having an acquired interest in medical imaging and a previous summer position working with PET, I saw this as an excellent opportunity to expand my knowledge of the field while having the chance to be exposed to clinical research methods. Above is my account of how the year went in a nutshell.

Have a look at my poster from the ROP Research Day below…

## Happy New Year and Enjoy Some AR&R…

 Or Attributable Risk Reduction…

First let me wish you all a fantastic New Year! Last year was crazy and I think this year is looking like it will be more of the same…

So in a previous post called Risky Business: Is It All Relative? we started talking about risk. We agreed that in lay terms a risk is generally associated with a bad event. However, a risk in statistical terms refers simply to the probability (usually statistical probability value between 0 and 1) that an event will occur, whether it be a good or a bad event.

We also defined the risk of “smartphone thumb” as the number of new cases of smartphone thumb (the outcome) in a given period of time divided by the total number of people who own a smartphone (the exposure) and are at risk. This was called the cumulative incidence or absolute risk. Now what if we wanted to compare this risk to people who did not receive a smartphone for their birthday or Christmas for that matter? Let’s look at the results in a contingency table:

So, the absolute risk of smartphone thumb is A/(A+B) and similarly for those sad people without a smartphone their risk is C/(C+D). Now your chances of developing smartphone thumb are not necessarily 0 as maybe you are an avid gamer and play a little too much Xbox on the weekends. The reduction in risk can be expressed as the risk difference (also called the attributable risk reduction – ARR) and can be calculated as RD = A/(A+B) – C/(C+D). We can also estimate the proportion of cases of smartphone thumb among smartphone users that can be attributed to smartphone use by calculating the attributable risk percent: [RD/ A/(A+B)] x 100.

Let’s say 20% of smartphone users develop smartphone thumb whereas only 10% or non-smartphone users do. The RD is then equal to 10% (0.2 – 0.1 *100). The reduction in the chances of experiencing smartphone thumb who own a smartphone is the AR% which in this case is 50% (0.1/0.2*100).

That was easy. What’s next? Well, what if we want to know how many times more likely is it for a smartphone user to develop smartphone thumb than for a non-smartphone user? Let’s talk about that next post.

For now, decompress listening to “Under my Thumb” by the Rolling Stones. Classic…

See you in the blogosphere,

Pascal Tyrrell

## Engaging Primary Care in Research: Not Always an Easy Task

 Stella Song ROP Summer 2016

I am Stella Bing Xin Song, currently a second year student studying pharmacology and psychology at University of Toronto. I was fortunate to be a part of the 2016 Research Opportunity Program (ROP) supervised by Dr. Pascal Tyrrell in the Department of Medical Imaging at University of Toronto.

My ROP project focused on evaluating the feasibility of using MRI as the primary imaging modality for carotid artery stenosis diagnosis and assessment (not sure what we are talking about? See previous posts here and here). Along with Ginni Ting, a student volunteer in Dr. Tyrrell’s lab, we surveyed physicians in the Niagara region of Ontario to learn about their perspectives on this proposal. Our community partner in this research was Heart Niagara – a fantastic local organization that has been guiding advances in cardiac health education and services since 1977.

Most of the responding physicians saw approximately 2000 or more patients per year. Physicians expressed a variety of care-related decisions for carotid artery stenosis patients, especially for those where diagnosis was less obvious with less than 70% stenosis. Most responding physicians would consider MRI over Ultrasound as the first-line diagnostic imaging modality, because of its ability to detect IPH yielding more pertinent information. IPH is bleeding within the plaques, which causes them to become more vulnerable (see vulnerable plaque). There is a 6 times greater risk of stroke in people with IPH! For those who were reluctant to consider it, they expressed that it was mostly due to their concerns for the relative cost and current wait time for MRI.

Unfortunately, the response rate for this online survey was very low. Reasons given for the reluctance to participate were that physicians were on a tight schedule and were busy with their patients. Feedback from participants was that the online survey seemed long. Nevertheless, from the responses received, we were able to learn more about physicians’ perspectives of using MRI for carotid artery stenosis diagnosis and assessment.

In the end, it was an exciting and valuable experience to plan out and execute this research project. Most importantly, I had the pleasure to join Dr. Tyrrell’s lab and meet his team. I am grateful for all the help and support which I have received throughout my time at the lab. I look forward to continuing to work as a member of Dr. Tyrrell’s lab.

Stella Bing

## Risky Business: Is It All Relative?

Now this movie takes me back a few years. Tom Cruise’s first big movie Risky Business. His underwear dance scene is pretty famous (haven’t scene it yet? Have a gander here).

So what does Tom Cruise in underwear have anything to do with our blog? Well it is the concept of risk that interests me today. David Streiner was a fantastic professor of mine and is the author of many great stats publications. He talks about risk here. I will endeavor to do the topic justice with his help over the next few posts.

What do we mean when we talk about risk? In lay terms a risk is generally associated with a bad event. However, a risk in statistical terms refers simply to the probability (usually statistical probability value between 0 and 1) that an event will occur, whether it be a good or a bad event.

Now that you are clear on that, you are probably wondering what are the best ways of describing risk or – better yet – comparing estimates or risk between groups (wondering what a statistical estimate is? See my earlier post here).

Let’s say that you have just received the latest and greatest smartphone for your birthday and you can’t wait to text everyone you know to tell them about it. This would be considered the exposure: your smartphone. The outcome would be “smartphone thumb”: a painful thumb resulting from smartphone overuse (don’t believe me? See here). We can define the risk of smartphone thumb as the number of new cases of smartphone thumb (the outcome) in a given period of time divided by the total number of people who own a smartphone (the exposure) and are at risk. This is also called the cumulative incidence or absolute risk

As you have an inquisitive mind, you are now wondering what would be the difference in levels between conditions: people with a smartphone compared to people without. Well this can be expressed as absolute differences in risk or relative changes in risk and I will have mercy and address this in more detail… next post!

For now, decompress by listening to the Barenaked Ladies singing Pinch me (believe it or not this song has something in common with Tom Cruise from Risky Business. Get it yet?).

See you in the blogosphere,

Pascal Tyrrell

## Sharing Medical Images for Research: Patients’ Perspectives

 Michelle Cheung – YSP 2nd Place Award

Michelle was our second YSP student this summer and did a great job at particpating in one of our studies in looking at patients’ willingness to share their medical images for research. This study is also part of the MiNE project.

Here is what Michelle had to say:

“My name is Michelle Cheung and I am a rising senior at Henry M. Gunn High School in Palo Alto, California. In my free time, I love to bake, read, travel with family, and take Barre classes. I also enjoy volunteering with friends at local charitable events and the Key Club at school. I am very interested in human biology and hope to study genetics and biotechnology next fall.

I really enjoyed the three weeks with the YSP Research Program. I learned so much about medical imaging modalities and had the amazing opportunity of helping research assistants survey patients at the Sunnybrook Hospital for the MiNE project. At first, it was a little daunting, but over time, I became more confident and comfortable interacting with patients, and grew to love surveying. The continuous surveying each day highlights the aspect and importance of repetition in conducting scientific research. Above all, it was an absolute pleasure getting to know the MiDATA and VBIRG lab. I’m grateful to my mentors and the lab members for exposing me to a whole new lab world I never thought existed beyond the traditional wet labs.”

Great job Michelle!

Have a peek at Michelle’s award winning poster and…

… I’ll see you in the blogosphere.

Pascal Tyrrell

## Wow! What a Busy Summer….

 Jenny Joo – YSP 2016

Over 20 students in the lab this summer beavering away at some great projects. Last week my two Youth Summer Program (University of Toronto) students finished their three week stay with us.

Jenny and Michelle both did fantastic work.

Today Jenny will show you her poster entitled:“Comparing Healthy and Unhealthy Carotid Arteries”

Jenny Joo is from Richmond Hill, Ontario, entering her senior year of high school. She plans on studying life science at the University
of Toronto in the future. She spent the last 3 weeks in U of T’s YSP Medical
Research program, where she was placed in two different medical imaging labs: The
MiDATA lab of U of T and the Vascular Biology Imaging Research lab at
Sunnybrook Hospital.

Jenny chose to do research on the
MRI scans of the carotid artery because it focused on both research and
clinical aspects and had this to say about her experience with us: “It has been an enriching 3 weeks working with my PI, Pascal
Tyrrell, my mentors, John Harvey and Moran Foster, and the rest of the research
group.”

Great work Jenny Joo!

Have a peek at her poster and…

… I’ll see you in the blogosphere.

Pascal Tyrrell