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Improving Glaucoma Treatment Based on Wavelet-Fourier Analysis of Retinal Nerve Fiber Layer Thickness
| CO-PI(s): | Joern Soltau |
| Philip Chen |
University of Louisville
The goal of the present research is to provide a non-invasive method of assessing glaucoma in humans. The new method analyzes the map of the patient's retinal nerve fiber layer (RNFL) thicknesses by an innovative method ("Wavelet-Fourier Analysis" -- WFA) that we developed over the past several years. RNFL thickness measurements are obtained by non-invasive measurement with a scanning laser polarimeter or ocular tomograph, both of which have rapidly become commonplace in standard ophthalmology clinics. The WFA data analysis method dramatically improves their clinical utility. In this research we will shift our emphasis from using WFA to identify glaucoma cases (screening) to the more important issue of prediction of vision loss before it occurs. Specifically this work is directed towards the detection of: (1) which patients at risk for developing glaucoma (glaucoma "suspects") will develop glaucomatous loss of vision if not treated, and (2) which patients who already have glaucoma are at risk for suffering further additional loss of vision. We will address these issues by applying our current WFA technique to a large sample of hundreds of polarimetry scans of glaucoma patients and suspects acquired over a 4-7 year follow-up period. In addition we have also begin a prospective tomography study for the same purpose. First WFA will be applied directly to classify those suspects at risk of converting to glaucoma and those glaucomatous eyes at risk of progression. Secondly, WFA will be used to track changes in the RNFL structure that we expect to occur over time in those eyes that are heading for worsening disease and further blindness. By both approaches we will develop quantitative methods to non-invasively assess risk of permanent vision loss due to glaucoma allowing for improved patient care and for the preservation of more vision than is now presently possible.
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