Dr. Jocelyn Wittstein

So we took all the work we did on the machine learning to build the models of the knees where we have all the cartilage traced all over the different parts of the knee.

And we use a very similar model that we use to study post-traumatic arthritis in ACL-torn knees, which is where we bring people in and we have them rest for 30 minutes so their cartilage is fully rested.

We do a resting MRI of their knee, and then that shows us the thickness of their cartilage all over it.

Then we have them walk for 30 minutes on a treadmill, which compresses your cartilage, and the cartilage is the smooth gliding surface of the knee.

compresses it, and then we put them back in the MRI scanner and we kind of re-scan them with this one sequence every six minutes for like 30 minutes.

And over the course of those 30 minutes, we see how much the cartilage rebounds to its normal thickness.

And then we generate a curve and it tells us how many minutes it would take for the cartilage to

go back to normal.

So like in a normal person, it'd be like 25 minutes.

And people who've had ACL tears, even just like one or two years after their injury, because they're so prone to developing arthritis over time from the trauma, it takes like, you know, more than an hour.

It takes a long time.

So we're applying this same tool that we developed for post-traumatic arthritis after ACL injury, except for the injury is not the ACL tear and PTOA or post-traumatic arthritis.

It's aging, sex hormones.

Plus or minus hormone therapy.

And so then we'll have their testosterone, their estrogen, their progesterone levels, and we will see how the early signs of arthritis are appearing in men versus women with and without hormone therapy with tests, you know, knowing their levels.

Basically, you know, my hypothesis is that I do think that...

you know, maintaining or supplementing, you know, the estrogen levels will preserve that resiliency of the cartilage.

That's my hypothesis.

I could be wrong.

So that it could be preventative, potentially.