Quantification of local circulation with oct angiography

Abstract

Impaired intraocular blood flow within vascular beds in the human eye is associated with certain ocular diseases including, for example, glaucoma, diabetic retinopathy and age-related macular degeneration. A reliable method to quantify blood flow in the various intraocular vascular beds could provide insight into the vascular component of ocular disease pathophysiology. Using ultrahigh-speed optical coherence tomography (OCT), a new 3D angiography algorithm called split-spectrum amplitude-decorrelation angiography (SSADA) was developed for imaging microcirculation within different intraocular regions. A method to quantify SSADA results was developed and used to detect perfusion changes in early stage ocular disease. Associated embodiments relating to methods for quantitatively measuring blood flow at various intraocular vasculature sites, systems for practicing such methods, and use of such methods and systems for diagnosing certain ocular diseases are herein described.

What is claimed is: 
     
         1 . A method for quantitatively measuring blood flow in an ocular vascular bed, said method comprising:
 selecting an ocular vascular bed from which to quantitatively measure blood flow;   scanning said ocular vascular bed to obtain M-B scans of OCT spectrum therefrom;   splitting the M-B scans of OCT spectrum into M spectral bands; and   determining a quantitative measurement of blood flow from the M spectral bands.   
     
     
         2 . The method of  claim 1 , wherein splitting the M-B scans of the OCT spectrum into M spectral bands comprises:
 creating overlapping filters covering the OCT spectrum; and   filtering the OCT spectrum with the overlapping filters.   
     
     
         3 . The method of  claim 1 , wherein determining a quantitative measurement of blood flow from the M spectral bands comprises:
 creating decorrelation images for the M spectral bands; and   combining the decorrelation images for the M spectral bands to create a flow image.   
     
     
         4 . The method of  claim 3 , wherein creating decorrelation images for the M spectral bands comprises:
 determining amplitude information for each spectral band; and   calculating decorrelation between adjacent amplitude frames for each spectral band.   
     
     
         5 . The method of  claim 4  further comprising removing background noise. 
     
     
         6 . The method of  claim 3 , wherein combining the decorrelation images for the M spectral bands to create a flow image comprises:
 averaging the decorrelation images for each spectral band to create an average decorrelation image for each spectral band; and   averaging the averaged decorrelation images from the M spectral bands.   
     
     
         7 . The method of  claim 6 , further comprising eliminating decorrelation images for each spectral band having excessive motion noise. 
     
     
         8 . The method of  claim 1 , wherein the ocular vascular bed is the ocular nerve head or the macula. 
     
     
         9 . The method of  claim 1 , wherein the ocular vascular bed is selected from the group consisting of the ocular disc, the temporal ellipse, the peripapillary retina, the peripapillary choroid, the macular retina, the macular choroid, the fovea avascular zone, and the area of non-perfusion. 
     
     
         10 . The method of  claim 1  further comprising:
 comparing said quantitative measurement of blood flow to a reference measurement of blood flow from a normal subject, wherein a decrease in said quantitative measurement of blood flow compared to the reference measurement of blood flow indicative of the presence of an ocular disease. 
 
     
     
         11 . The method of  claim 10 , wherein said ocular disease is glaucoma and wherein the ocular vascular bed is the optic nerve head. 
     
     
         12 . The method of  claim 10 , wherein said ocular disease is diabetic retinopathy and wherein the ocular vascular bed is the perifoveal avascular zone. 
     
     
         13 . The method of  claim 10 , wherein said ocular disease is age-related macular degeneration and wherein the ocular vascular bed is the choroidal neovascular membrane or the macular choroid. 
     
     
         14 . The method of  claim 10 , wherein the ocular vascular bed is the ocular nerve head or the macula. 
     
     
         15 . The method of  claim 10 , wherein the ocular vascular bed is selected from the group consisting of the ocular disc, the temporal ellipse, the peripapillary retina, the peripapillary choroid, the macular retina, the macular choroid, the fovea avascular zone, and the area of non-perfusion. 
     
     
         16 . A system for quantitatively measuring blood flow in an ocular vascular bed, said system comprising:
 an optical coherence tomography apparatus; and   one or more processors coupled to said apparatus and adapted to cause said apparatus to obtain M-B scans of OCT spectrum from said ocular vascular bed, split the M-B scans of OCT spectrum into M spectral bands, and determine a quantitative measurement of blood flow from the M spectral bands.   
     
     
         17 . The system of  claim 16 , wherein the one or more processors adapted to cause the apparatus to split the M-B scans of OCT spectrum into M spectral bands further comprises being adapted to cause the apparatus to create overlapping filters covering the OCT spectrum and filter said OCT spectrum with the overlapping filters. 
     
     
         18 . The system of  claim 16 , wherein the one or more processors adapted to cause the apparatus to determine a quantitative measurement of blood flow from the M spectral bands further comprises being adapted to cause the apparatus to create decorrelation images for the M spectral bands and combine the decorrelation images for the M spectral bands to determine a quantitative measurement of blood flow. 
     
     
         19 . The system of  claim 18 , wherein the one or more processors adapted to cause the apparatus to create decorrelation images for M spectral bands further comprises being adapted to cause the apparatus to determine amplitude information for each spectral band and calculate decorrelation between adjacent amplitude frames for each spectral band. 
     
     
         20 . The system of  claim 18 , wherein the one or more processors adapted to cause the apparatus to combine the decorrelation images for the M spectral bands to determine a quantitative measurement of blood flow further comprises being adapted to cause the apparatus to average the decorrelation images for each spectral band to create and average decorrelation image for each spectral band and average the averaged decorrelation images from the M spectral bands.