AI for automatic vertebral motion tracking of fluoroscopic images

几个世纪以来，医生们一直被认为是由于受伤或过度使用而导致的脊柱疾病，因此被认为是由于脊柱稳定性的丧失。在过去，这无法得到证实，但使用一种称为定量荧光透视（QF）的技术，该技术依赖于在运动过程中捕获的低剂量运动X射线图像，现在可以。QF被认为是脊柱运动测量的黄金标准，但由于缺乏常规使用的准备，它很少被科学家，研究人员和临床医生（主要是脊柱外科医生和物理治疗师）使用。在这个项目中，我们的目标是将人工智能（AI）应用于QF，以便它可以更广泛地用于研究和患者护理。QF没有被广泛使用的原因是它涉及通过计算机定位和跟踪椎骨运动图像，允许自动测量椎骨的运动。如果没有自动化，这个过程对于日常使用来说太耗时了。与此同时，如果图像不是非常清晰和对齐良好，自动测量会带来多重挑战。失真（例如，由于脊柱侧凸），退化（例如，通过肥胖者的脂肪）或衰退（例如，患有骨质疏松症的人）的图像目前导致测量过程几乎不可避免的失败-否认了广泛使用QF来研究脊柱疾病的能力。我们将应用人工智能方法，以便计算机可以被训练以令人难以置信的速度进行椎骨图像的配准和跟踪，即使使用质量差的图像。这将允许非常快速地执行大量检查，从而进行更详细的审查和验证，并且速度比人类操作员快得多。这将开启脊柱护理研究的新纪元。该项目将利用参与者同意将其数据用于未来研究的多年研究中收集的QF数据。不会招募额外的参与者，因此本项目不需要额外的X射线辐射风险。

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.