Chalmers Conferences, 9th European Conference on Mathematical and Theoretical Biology

Quantification of Arthritis Progression Using Micro-CT Data
Carl-Magnus Svensson, Ingo Irmler, Bianca Hofmann, Hans Peter Saluz, Marc Thilo Figge

Last modified: 2014-03-27


Rheumatoid arthritis (RA) is an autoimmune disease that affects approximately 1% of the adult population leading to pain, disability and, if not treated, significantly decreased life span. Although the exact aetiology of RA is not known, evidence suggests that autoreactive T cells together with other immune cells are creating an inflammatory cytokine milieu around the joints of the patient. The chronic inflammation causes destruction of tissue, especially cartilage and bone, which at early stages are painful and at later stages severely debilitating. Although RA is an exclusively human disease, animal models of arthritis are an invaluable tool to hypothesise about the aetiology and to test therapeutic strategies. The degree of arthritis, RA or animal models, in a limb is today scored semi-quantitatively by the physician or experimentalist, based on bone degradation from X-ray images. Sometimes metabolic data recorded by PET or fluorescence imaging is available for the scoring and in the case of RA the patient answers questions about pain levels. Although the scoring methods are clinically well motivated and tested, the score will still be dependent on the individual’s judgement and any evaluation of the disease progress will be subjective. We will present a quantitative measure based on the cortical bone thickness in a longitudinal study of arthritis in a murine model. The mice are immunised with a glucose-6-phosphate isomerase peptide (GIP) inducing arthritis and their paws are imaged using a micro-CT scanner throughout the experiment. This gives us three dimensional image data of the arthritic paw during the different stages of the disease which is the basis of our analysis. The raw data are segmented using texture based segmentation to separate individual bones from each other. After segmentation we extract the metatarsals from the three dimensional datasets and determine the central axis of each bone. As the positioning of the paw is potentially different for each animal and for each occasion, it is of outmost importance to identify slices orthogonal to the central axis of each metatarsal. Thereafter, we measure the average thickness of the cortical bone. By fitting a linear function to the thickness profile we describe the morphology of individual metatarsals by the two parameters of a linear function. In this compact way we can compare the cortical bone morphology between individuals, between different immunisation protocols and even determine arthritis effects in a single animal over time. We demonstrate how the arthritis significantly affects the cortical bone thickness and quantify this effect. We also discuss how the quantification of arthritic bone degradation can help with the evaluation of therapy strategies in animal models and RA diagnostics. We will outline how detailed quantification of bone degradation, which our analysis is an important step in, will become an important tool for both experimentalists and clinicians.


Arthritis; Image analysis; Micro-CT data