Feasibility and application of Doppler imaging and image feature quantification in the abdomen, with emphasis on the uro-genital tract.
The objective of this project is to:
1) Detect for early and specific ultrasonographic signs of inflammation in tissue.
2) Apply data analysis techniques to detect and quantify physiological changes in tissue.
We have access to animals with well documented spontaneous abdominal disease. Inflammation is a common response to disease and we have good acute quantitative and qualitative biochemical markers of this process in dogs. Early signs of inflammation include altered blood flow to the affected region. Organ imaging by ultrasound can be used to detect changes in blood flow (spectral Doppler) and echo-texture (grey scale) in affected tissues, and thus help localise sites of inflammation that trigger global changes in inflammatory markers. Analysis of Doppler spectral data is often limited to simple ratios of velocities at particular time points in the cardiac cycle. The project proposes that more sophisticated statistical examination of Doppler spectra might yield patterns that can be used as early markers of inflammation. In a similar way Grey scale image evaluation is often limited to visual inspection in a clinical setting and to the measurement of linear dimensions. A more rigorous, statistical examination of these images again might reveal hidden patterns in the data.
Fintan McEvoy, Professor, Veterinary Imaging
Department of Small Animal Clinical Sciences (IMHS), KU, LIFE.
PhD student is employed on the project.