Imagine you’re at the hospital, in pain and anxious about what diagnosis might be coming. Your doctor orders an MRI scan, which means waiting for an available time slot so you can lie perfectly still inside the scanner’s narrow tube for up to an hour. As the MRI machine gradually collects data, you have only the intermittent crackling and banging of the electric current in the scanner’s magnetic coils for company. If you move during the scan, the image might not be clear enough to be useful, which would mean booking another appointment to come back and do the whole thing over again.
MRIs are often the best tool for diagnosing problems with organs, muscle, and other soft tissue. But even with recent advances, it takes a significant amount of time for the scanner to gather the necessary data. That is difficult for anyone, and it can be impossible for the very young or the seriously ill.
The time it takes to complete an MRI scan doesn’t just make the patient experience more grueling. It also limits how many people can be scanned in a given day. And some types of tissue are in constant motion as the scan takes place, so an image that takes a long time to generate can sometimes be too blurry to be useful. What’s more, when doctors need information quickly, they often must use other technology instead of waiting for the MRI scanner to do its work. X-rays and CT scans are much faster, but unlike MRIs, they expose the body to ionizing radiation. And with some types of tissue, MRIs can reveal more detail than alternatives.
Facebook AI researchers have partnered with doctors and medical imaging experts at NYU Langone Health to solve this problem and advance artificial intelligence research. We are using AI to create complete images from far less raw data. Since collecting that data is what makes MRIs so slow, this has the potential to speed up the scanning process significantly. So one day in the hopefully not-too-distant future, you might spend just a few minutes in the scanner’s tube to generate a crystal clear image.
After two years of work on this fastMRI initiative, Facebook AI and NYU Langone have reached an important milestone. A new clinical study to be published in the American Journal of Roentgenology shows for the first time that fastMRI images are interchangeable with those of regular MRIs. The study focused specifically on knee scans, and we are now working to extend the results to other parts of the body.
“This is an important step toward the clinical acceptance, and utilization of AI-accelerated MRI scans,” said Dr. Michael P. Recht, Louis Marx Professor and Chair of Radiology at NYU Langone Health.