AI for automatic vertebral motion tracking of fluoroscopic images

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For centuries, doctors have been presented with spinal disorders that followed injury or overuse and were therefore thought to be due to loss of spinal stability. In the past, this could not be confirmed, but using a technology called Quantitative Fluoroscopy (QF), which relies on low-dose motion X-ray images captured during motion, it now can. QF is regarded as the gold standard for spinal motion measurement, but due to lack of readiness for routine use, it is rarely available to scientists, researchers and clinicians (mainly spinal surgeons and physical therapists). In this project we aim to bring Artificial Intelligence (AI) to bear on QF so it can be used more widely in research and patient care. The reason QF is not in wide use is that it involves the locating and tracking of vertebral motion images by a computer, allowing movement of vertebrae to be measured automatically. Without automation, the process is too time consuming for routine use. At the same time, automatic measurement poses multiple challenges if the images are not very clear and well aligned. Distorted (e.g., due to scoliosis), degraded (e.g., by fat in obese people) or fading (e.g., people with osteoporosis) images currently lead to almost inevitable failure of measurement process - denying the ability to use QF widely for investigating spinal disorders. We will apply AI methods so that computers can be trained to do both the registration and the tracking of vertebral images at incredible speed, even using images of poor quality. This will allow a huge number of inspections to be performed very quickly, resulting in much more detailed scrutiny and verification and at a much higher speed than a human operator. This will initiate a new era in spine care research.This project will leverage the QF data which has already been collected over multiple years of prior research, where the participants consented for their data to be used for future research. No additional participants will be recruited, hence no additional X-ray radiation risk will be required for this project.