Dear Editor
Iread the study conducted by Alizade et al. [1] which was interesting. I need to indicate some points about the use of Optical Coherence Tomography (OCT) in ophthalmology and optic nerve diseases. As Alizadeh et al. [1] stated, OCT has become popular for the diagnosis and follow-up of retinal and optic nerve diseases due to its high reproducibility. In this letter, I discuss the role of OCT in optic nerve ischemia and share my experiences in this field. Then, I review the role of OCT angiography (OCT-A) and recent developments in this field, as well as the role of artificial intelligence in ophthalmology. 
Optic nerve ischemia is one of the common causes of acute vision loss, but the pathophysiology and cause of this disease have not yet been fully determined. Previously, the thickness of retinal nerve fiber layer (RNFL) had been measured at the beginning of imaging with OCT in this disease. The thickness of this layer is about 100 microns in people with normal vision, but in people with optic nerve ischemia, it decreases after about 6-8 weeks. In the early stages of this disease, the measurement of RNFL thickness is not accurate enough due to swelling of the optic nerve [2]. With the progress of OCT, as mentioned in Alizadeh et al.’s article [1] , the measurement of macular ganglion cell layer (mGCL) thickness is done. We measured the thickness of the mGCL in patients with optic nerve ischemia at intervals of one month and three months after vision loss and found that the mGCL damage occurs faster than the RNFL damage. Therefore, this layer can be used to check the prognosis of the disease in the early stages [3]. With the further development of OCT, it became possible to take pictures of the deep optic nerve layers such that it is now possible to image the lamina cribrosa layer and measure the thickness of the prelaminar layer [4]. Interestingly, in patients with optic nerve ischemia, the prelaminar layer of the optic nerve is thicker than in people with normal vision. Our subsequent studies showed that this is due to the existence of thick peripapillary choroid. In other words, the main cause of optic nerve ischemia is the high choroidal thickness (pachychoroid), which causes the prelaminar layer to move forward and compress the ciliary arteries around the nerve. This is similar to compartment syndrome, causing decreased blood supply and nerve ischemia. We showed the high choroidal thickness in optic nerve ischemia for the first time in 2015, and numerous studies confirmed it [5, 6].
With the invention of OCT-A, it became possible to take images of the peripapillary vessels without injecting contrast material. At first, it seemed that OCT-A shows the vessels responsible for optic nerve ischemia, but it was found that it is not possible to image the deep peripapillary vessels that are responsible for optic nerve ischemia, and the OCT-A shows only superficial vessels that are in the RNFL [8]. In our studies, we showed that the dropout of peripapillary blood vessels may be secondary to RNFL damage, and this reduction cannot differentiate optic nerve ischemia and optic neuritis [9]. For example, the density of peripapillary blood vessels in glaucoma are reduced similar to optic nerve ischemia. Interestingly, damage to the nerve and vascular layer match the visual field defects [10]. The OCT-A also provides the possibility of imaging the small vessels of peripapillary choroid. In several studies, we compared the density of the small vessels of peripapillary choroid in patients with optic nerve ischemia and glaucoma. Although the attenuation of surface layer vessels was the same in both diseases due to damage to the nerve layer, attenuation in small vessels of choroid was observed only in patients with glaucoma, indicating the primary role of small choroidal vessel density attenuation in the pathophysiology of glaucoma. This attenuation was not observed in patients with optic nerve ischemia [11]. It should be noted that the attenuation of small choroidal vessels in glaucoma is specific to open-angle glaucoma; in closed-angle glaucoma, vessel density attenuation is not seen [12].
Finally, I mention some points about the use of artificial intelligence (AI) in ophthalmology and the segmentation of layers in OCT. The most common use of AI is to diagnose diseases from the fundus photos. In a study, we showed that AI can differentiate papilledema from optic nerve ischemia and optic nerve drusen [13]. If AI be used in emergency rooms, it can determine the cause of optic neuritis even without the presence of an ophthalmologist. So far, after performing OCT, the RNFLs are separated and their thicknesses are measured by the software of the OCT device, but due to decrease or increase in their thickness caused by the disease, this type of measurement may not be accurate. Therefore, AI was used to determine the thickness of these layers [14]. In this regard, in a study, we showed that the determination of RNFL thickness and layer segmentation by OCT machine in optic nerve ischemia may not be accurate and manual segmentation or AI should be used [15].
Overall, peripapillary and macular OCT and OCT-A allow better evaluating the optic neuropathies in ophthalmology and AI has potential to provide clear differentiation of diseases, allowing for better use of resources and time.

Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflicts of interest
The authors declared no conflict of interest.


References

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