Detection and characterization of retinal disruption in mice using high angular resolution diffusion microscopy (HARDM)

Diabetic retinopathy is the leading cause of blindness among diabetics. One of the primary concerns with this pathology is that it cannot be diagnosed in its early stages. This project aims to use magnetic resonance imaging to investigate techniques for early detection of the disease. Primary protocols were developed on healthy control animals to establish the feasibility of the proposed methods, followed by experiments on diabetic mice. For these studies, we used high angular resolution diffusion microscopy (HARDM) as a non-invasive tool to detect this disease at an early stage. A spatial resolution up to 19 µm was achieved to visualize the organized structure within the retinal layers in healthy mice. In contrast to this, in diabetic animals, the integrity of the retina was found to be compromised. These findings were arrived at using image analysis, calculation of fractional anisotropy (FA), which is a unit describing organized structure within a region of interest, and statistical analysis. FA in the retina was observed to be markedly higher in healthy controls as compared to diabetic mice. A novel technique was developed, which uses the direction of eigenvectors in a region of interest to perform a quantitative analysis, thereby characterizing the extent of retinal disruption due to diabetic retinopathy or other pathologies. These techniques have successfully been applied to track the repair of the retina in mice models of retinal disruption before and after stem cell treatment. Similar procedures along with novel cell tracking methods were applied to track the migration of endothelial progenitor cells (EPCs), which are essentially stem cells whose primary function is to repair damaged tissue. The tracking was accomplished by labeling the EPCs using magnetic iron oxide nanoparticles (MION) which is detectable in MRI. These studies aim to contribute towards early detection of retinal diseases using non-invasive diffusion MRI.