Refinement and reduction through application of a quantitative score system for estimation of TB-induced disease burden using computed tomography

By Sally A Sharpe - Donna Smyth - Anthony McIntyre - Fergus Gleeson - Mike J Dennis

Until validated correlates of protection are identified, animal models remain the only way to test the efficacy of the new vaccines and drugs urgently needed to fight the global epidemic caused by infection with Mycobacterium tuberculosis. Non-human primates (NHP) offer the most relevant models of human tuberculosis (TB) and are central to the development process for new interventions. Efficacy evaluations are dependent on the capability of the test model to discriminate improved outcomes between treated groups after experimental exposure to M. tuberculosis and therefore the ability to measure TB-induced disease burden is central to the process. We have developed a score system that allows us to quantify the disease burden induced in macaques by infection with M. tuberculosis, based on the extent and features of disease visible on computed tomography (CT) images. The CT determined disease burden was then verified against that obtained using an established pathology-based approach. Trials of the system as a tool to measure disease burden have shown the approach capable of revealing differences between treatment groups in order to: (a) characterise outcome of infection and enable model refinement; (b) demonstrate the efficacy of drug treatment regimens by showing differences in outcome between test groups. Initial trials suggest that the imaging-based score system provides a valuable additional tool for the measurement of TB-induced disease burden that offers the opportunity to apply both refinement and reduction within studies.