EUROTIMES Glaucoma ARTICLES

OCT-A in glaucoma


Howard Larkin

Posted: Monday, July 22, 2019

Advances in optical coherence tomography (OCT) enabling detection of blood flow and blood vessel density across larger areas of the retina may make OCT angiography (OCT-A) a more powerful tool for assessing glaucoma than relying on structural measures such as retinal nerve fibre layer (RNFL) thickness generated by conventional OCT, David Huang MD, PhD, told the Glaucoma Subspecialty Day at the 2018 American Academy of Ophthalmology Annual Meeting in Chicago, USA.

OCT-A algorithms in development may even help simulate the location and severity of visual field defects, making it easier to identify and track patients at the highest risk of progression, said Dr Huang, of the Casey Eye Institute, Oregon Health and Science University, Portland, Oregon, USA.

Where to look
In 2014, OCT-A studies by Dr Huang and colleagues established that glaucoma reduces perfusion at multiple levels of the optic nerve head and that capillaries of the superficial disc and lamina cribrosa are greatly attenuated (Jia Y et al. Ophthalmol 2014; 121:1322). More recently, OCT-A has revealed that glaucoma capillary loss is most pronounced in the nerve fibre layer plexus and the ganglion cell layer plexus, together known as the superficial vascular complex (SVC), than in the intermediate and deep capillary plexuses, together known as the deep vascular complex (Campbell P et al. Sci Rep 2017;7:42201).

Studies with projection-resolved OCT-A also have found greater mean reduction in vessel density in the macular SVC than in the intermediate or deep plexuses of glaucoma patients, and the 22% in the SVC is statistically significant (p<0.001), while lesser losses in the deeper layers are not (Takusagawa HL et al. Ophthalmal 2017;124:1589). Macular SVC low perfusion areas also correlate with ganglion cell complex thinning and visual field defects.

As a result, focusing on capillary loss in the SVC can generate good diagnostic accuracy, as high as 0.98 in his study, Dr Huang said. Nonetheless, some published studies have found poor diagnostic accuracy with OCT-A imaging of the macula, Dr Huang noted. However, these were done using scans of 3mm-to-4mm square in the central macula, which is not greatly affected. A larger 6mm square scan area is needed for effective OCT-A, he said.

Some studies using a larger OCT-A scanning field have demonstrated higher accuracy diagnosing early glaucoma vs normal based on disc and peri-papillary vessel density than peripapillary nerve fibre layer thickness. This ranges from 0.84 for fellow eyes of unilateral glaucoma to 0.96 for pre-perimetric glaucoma patients for OCT-A vs about 0.77 for RNFL in both studies (Yarmohammadi A et al. Ophthalmol 2018;125:578. Akil H et al. PLOS ONE 2017;12:e0170476).“I pos

tulate this is possible because OCT-A can detect reduced perfusion related to lower metabolism in sick ganglion cells prior to apoptosis and structural thinning,” Dr Huang said.

Overall, OCT-A has been shown to correlate with visual field loss more closely than nerve fibre layer thickness, correlating at R2=0.697 vs R2=0.035 (Liu L et al. JAMA Ophthalmol 2015;133:1045), Dr. Huang said. OCT-A has also been shown to be more sensitive for advanced glaucoma cases, correlating with SAP mean deviation down to about -15dB compared with about -10dB for nerve fibre layer thickness (Yarmohammadi A et al. Ophthalmol 2016;123:2498). This may be because perfusion continues to drop off after the structural thickness floor has been reached, Dr Huang said.

Based on this correspondence, Dr Huang has recently begun an attempt to simulate visual field performance based on perfusion measured by OCT-A in eight segments that follow nerve fibre trajectory based on extended Garway-Heath sectors (Tan O et al. Transl Vis Sci Technol 2018;7:16).

“This project is still early and so far, we are finding fairly good correspondence with early and moderate glaucoma but not so good in advanced cases.”

He plans to report progress as the 
project continues.

David Huang: huangd@ohsu.edu