MedicalResearch.com Interview with: Daniel L. Rubin, MD, MS  Assistant Professor of Radiology and Medicine (Biomedical Informatics) Department of Radiology | Stanford University Stanford, CA 94305-5488 Medical Research: What is the background for this study? What are the main findings? Dr. Rubin: Age-Related Macular Degeneration is the leading cause of blindness and central vision loss among adults older than 65. An estimated 10-15 million people in the United States suffer from the disease, in which the macula — the area of the retina responsible for vision — shows signs of degeneration. While about one of every five people with AMD develop the so-called “wet” form of the disease that can cause devastating blindness. In wet AMD, abnormal blood vessels accumulate underneath the macula and leak blood and fluid. When that happens, irreversible damage to the macula can quickly ensue if not treated quickly. Until now, there has been no effective way to tell which individuals with AMD are likely to convert to the wet stage. Current treatments are costly and invasive — they typically involve injections of medicines directly into the eyeball — making the notion of treating people with early or intermediate stages of Age-Related Macular Degeneration a non-starter. In our study, we report on a computerized method that analyzes images of the retina obtained with a test called spectral domain optical coherence tomography (SD-OCT), and our method can predict, with high accuracy, whether a patient with mild or intermediate Age-Related Macular Degeneration will progress to the wet stage. Our method generates a risk score, a value that predicts a patient’s likelihood of progressing to the wet stage within one year, three years or five years. The likelihood of progression within one year is most relevant, because it can be used to guide a recommendation as to how soon to schedule the patient’s next office visit. In our study, we analyzed data from 2,146 scans of 330 eyes in 244 patients seen at Stanford Health Care over a five-year period. Patients were followed for as long as four years, and predictions of the model were compared with actual instances of conversion to wet AMD. The model accurately predicted every occurrence of conversion to the wet stage of AMD within a year. In approximately 40% of the cases when the model predicted conversion to wet AMD within a year, the prediction was not borne out, however. We are currently refining the model to reduce the frequency of these false positives.