The clinical evaluation of blinding retinal diseases such as Inherited Retinal Degenerations, Diabetes, Age Related Macular Degeneration (AMD) and Glaucoma necessitates integration of clinical data obtained from various modalities. Macular degeneration is the leading cause of vision loss in Americans 60 years of age and older. As many as 11 million people in the United States have some form of age-related macular degeneration and this number is expected to double to 22 million by 2050. Estimates of the global cost of visual impairment due to age-related macular degeneration is US $343 billion, including US $255 billion in direct health care costs. Early detection of age-related macular degeneration is very important because there are treatments that can delay or reduce the severity of the disease.
For diagnosis, prognosis and progression of retinal diseases the physician relies on identification of retinal pathological features from retinal images (clinically named as fundus images) and on numerical data obtained from psychophysical and electrophysiological retinal functional tests. Structural and functional changes may occur concomitantly or one may precede the other, often depending upon the stage of the disease. However, correlating or associating the individual changes in the various diagnostic tests can be challenging. The location of diseased areas in the fundus may not coincide with corresponding numerical changes on the same location on the functional tests. A major technical hurdle is that the physical size of the images varies among the diagnostic tests, and the physician has to physically lay the images side by side to view and draw qualitative conclusions about the nature and extent of the disease. Automatic analysis and correspondence of quantitative local fundus variations as well as individual test points among the diagnostic tests will provide a more accurate description of the disease, thus facilitating the physician with diagnosis and management.
Multimodal imaging in retinal diseases
The proposed technology is a software tool that facilitates fast and accurate quantification of retinal changes by presenting several complex diagnostic test results in an intuitive and easy to use mobile device interface. The software integrates functional and structural data from many different modalities, scales and normalizes the data, and then produces an intuitive visualization with the results from all input tests overlaid. This functionality allows physicians to quantify retinal function and morphology to measure disease severity by comparing and correlating results about the same area of the retina provided by different tests. The tool’s effectiveness has been demonstrated in retinitis pigmentosa, hydroxychloroquine induced retinopathy, and diabetes patients. It was used to identify and monitor disease severity and progression across two subsequent patient visits.
- Tool for pharmaceutical companies to validate drug safety and efficacy in clinical trials and drug marketing
- Help physician to identify disease markers to detect early signs of disease
- A clinical study tool for evaluation of clinical trial data in Reading Centers
- Allow a physician to visualize disease progression over time
- Increased sensitivity and specificity to localized abnormalities vs. global abnormalities will improve diagnostic process and permit early treatment intervention and patient costs