The ability to identify and measure ocular inflammation is vital in the management of eye diseases. It is particularly important in the areas of uveitis (the fourth leading cause of blindness worldwide) and post cataract surgery (most common ophthalmic surgery). Currently, ocular inflammation is measured via clinical examination through a slit lamp microscope or indirect ophthalmoscope. These methods are subject to clinical interpretation and variability between observers.
The breakthrough – the ATAC automated algorithm, developed by Sunil K. Srivastava, MD, Sumit Sharma, MD, and Careen Y. Lowder, MD, PhD takes an objective, continuous measurement allowing clinicians to assess small changes in inflammation, instead of grading inflammation by a category scale score. Ultimately, the automated analysis evolution will lead to a new standard in clinical trials outcomes in the measurement of inflammation. The ophthalmic, pharmaceutical and device industry community has identified clinical trial end-points for Inflammatory Eye Diseases a significant area of interest with the goal of incorporating objective measures of inflammation into clinical trials, in lieu of the current subjective measures.
The ATAC software uses a readily available OCT device to image the anterior segment of the eye, inflammatory cells are identified by the software program, systematically counted, and shared with the clinician for final review. The output results include a continuous measure of the number of inflammatory cells identified per cubic millimeter. In a prospective study evaluating this technology, the software was found to be highly reliable and reproducible. Imaging and analysis could be performed within minutes. Additionally, a prospective study utilizing this software to measure inflammation in cataract surgery patients found the software was superior at detecting inflammation than clinicians and was successful in monitoring patients for improvement or worsening over time. The successful implementation of this software into clinicians hands will allow rapid identification and monitoring of inflammation in patients with a large variety of eye diseases. Additionally, the adaptation of this software method will develop new clinical trial standards for novel drug development.