Dynamic ICG and FA Software
Small Business Information
LICKENBROCK TECHNOLOGIES, LLC
LICKENBROCK TECHNOLOGIES, LLC, 4041 Forest Park Avenue, St. Louis, MO, 63108
AbstractDESCRIPTION (provided by applicant): Indocyanine Green (ICG) and Sodium Fluorescein (SF) are fluorescent dyes used clinically in eye fundus imaging, primarily for detecting vascular abnormalities in the retina and choroid, which is the layer behind the ret ina. It is used with the Heidelberg Retinal Tomograph (HRT) by visualizing movies that show the dynamics of the dye filling and draining through the vessels, modalities called dynamic ICG (d-ICG) or dynamic Fluorescein Angiography (d-FA). It is proposed to develop a new software technology, leading to a software product, that will facilitate straightforward interpretation of d-ICG and d-FA movies. This Phase I proposal focuses, first, on an important clinical application - that of measuring the response of neovascular lesions to drug treatment, such as Avastin. An algorithm that provides a basic measurement of the filling time of blood vessels, maps that filling time over the area of the fundus, and highlights changes in the filling time following treatment, will be developed and tested for its ability to show changes after treatment. A second application is that of identifying feeder vessels, for the laser treatment of neovascular diseases. Several additional applications and algorithms are proposed and are identified as the subject of focus for later research, including the Phase II research. PUBLIC HEALTH SIGNIFICANCE: The end objective of this project is to produce technology that results in a software product for automatically analyzing dynamic Indocyanin e Green (d-ICG) and Fluorescein (d-FA) angiographs. The Phase I project is aimed at showing feasibility of doing so, while the later Phase II project will be focused on building and testing the software to make it ready for integration into a product. Ther e are many clinical and medical research applications for the software, including the measurement of response to drug treatments for neovascular conditions, the detection of feeder vessels for laser treatment of neovascular conditions, and the early detect ion of vascular changes that occur in diabetic retinopathy. Because of these many applications, there is a good potential market to make the end-product profitable. However, the Phase I and Phase II projects will be focused upon the application that is bot h (a), needed in the clinic and (b), possible to produce as a sellable product in a relatively short amount of time. The second requirement, (b), is critical because the time it takes to develop and sell a product must be short in order to produce cash flo w necessary to deliver the product. To meet these 2 requirements, the first application of focus, and the most straightforward one to develop into a sellable product in a short time, will be in measuring the response to drug therapies. This product meets t hese two requirements partly because there is an immediate worldwide clinical and medical-research need for an objective measure of response to neovascular-disease drug therapies, data sets are readily available for testing the prototype software and our e xpertise equips us to assess, right away, the images output by the prototype product. The Phase I objective is to show that it is feasible to detect a response to drug therapy. If time permits, other applications will be shown to be feasible during Phase I as well. The specific aims are: (1) Design and implement algorithms for compensating the image sequences for motion and for measuring fill time. Fill time is the time that occurs between a reference instant (theoretically the instant of tracer injection, but this is difficult to determine so other reference points will be used) and the point where the pixel reaches 90% of its peak value. (2) Prototype a software algorithm that measures and displays changes in the fill time of blood vessels. (3) Prototype a graphical user interface (GUI) for executing the algorithm and interpreting the resulting measurements. (4) Test the algorithm for detecting response to tr
* information listed above is at the time of submission.