Image-driven subject-specific spine models

Many millions of people in the UK suffer problems with their spine or back. These problems incur a very high cost, both socially and economically, and we need to find ways of preventing or solving them. But to achieve this, we need high-quality tools that can help us understand how healthy spines function and what happens when they develop problems. Our project is concerned with developing and testing 'image-driven subject-specific spine models' which have the potential to provide a tool for determining forces in the spine.

Determining the force that an individual spine is experiencing is essential for understanding spine function. Abnormal forces are linked to many problems, including manual handling injury, disc degeneration, and back pain. Measuring force directly in the spine, however, is very invasive. Models provide a non-invasive method but, to provide accurate assessments, they need to include information about the individual (subject-specific). The subject-specificity is essential because everyone has unique anatomy and tissues, and uses their spines differently.

We have successfully piloted a modelling approach for measuring spinal force that includes subject-specific anatomy and spinal motion. The method involves using medical imaging not only to provide information on an individual's anatomy but also to observe the movement of their spine during activity. The observed motion is then applied to the model and force calculated. The use of spinal motion to drive models is a relatively recent innovation that we, and other groups, have shown to be feasible. It has several benefits, including the ability to identify localised forces within the spine and avoiding the need to model unknown muscle forces.

In the proposed project, our first goal is to extend our pilot work by including subject-specific tissue properties in our models. Very few models of the spine include subject-specific tissue properties. However, we know tissues vary a lot between individuals and having subject-specific properties will increase the accuracy of our models. We will, therefore, develop a method for estimating tissue properties from medical imaging data. Models will be created from specimens that have been tested to determine their mechanical response. We will then learn how we can use the image data to set tissue properties that allow our models to reproduce the measured mechanical response.

Our subsequent goals are to test our image-driven subject-specific modelling method rigorously and develop them for real application. Subject-specific models have many potential applications for determining forces, but these applications differ in their tolerance for error. We will, therefore, evaluate and characterise the magnitude and sources of error in our models. Initially, we will use specimens which can be mechanically tested so that we can compare model results to forces measured in the specimens. We will use this information to improve our methods for collecting data from people then we will perform more testing of our method using volunteers who we will ask to perform specified activities. Again we will compare our model results to the expected forces.

The development and testing of our image-driven subject-specific spine models will provide a new tool for determining forces in the spine. It will also provide new tools for measuring and modelling spine movement and quantifying the properties of the spinal tissues. But more than this, our project will pave the way to a real understanding of how the spine functions and how problems in the spine can be prevented or treated more effectively.