Measurement of Foveal Avascular Zone Dimensions and its Reliability in Healthy Eyes Using Optical Coherence Tomography Angiography

2016 ◽  
Vol 165 ◽  
pp. 201-202 ◽  
Author(s):  
Colin S. Tan ◽  
Louis W. Lim ◽  
Kai Xiong Cheong ◽  
Vernon S. Chow ◽  
Isaac W. Chay ◽  
...  
2020 ◽  
Author(s):  
Laura Gutierrez-Benitez ◽  
Yolanda Palomino ◽  
Noe Casas

PURPOSE: To develop and evaluate an automated method to measure the foveal avascular zone (FAZ) area in healthy eyes on Heidelberg Spectralis Optical Coherence Tomography Angiography (HS-OCTA). This method is referred to as the modified Kanno-Saitama macro (mKSM). METHODS: This cross-sectional study included 29 eyes of 25 healthy volunteers who underwent HS-OCTA at the macular area twice at the same time. Regardless of the quality of the images, all of them were included. Macular data on the superficial vascular plexus, intermediate capillary plexus and deep capillary plexus were processed by mKSM. The FAZ area was measured twice automatically using the mKSM and twice manually by two independent examiners. RESULTS: Intrascan intraclass coefficient ranged from 0,948 to 0,993 for manual measurements and was 1 for mKSM method. Interscan intraclass coefficients ranged from 0,925 to 0,973 for manual measurements and from 0,770 to 0,902 for mKSM method. Despite that the difference between human examiners is smaller than between human examiners and mKSM according to Bland-Altman plots, the scatterplots show a strong correlation between human and automatic measurements. The best results are obtained in intermediate capillary plexus. CONCLUSIONS: Automated determination of the FAZ area in HS-OCTA is feasible and less human-dependent by mKSM even if the image is not perfectly centred or has artefacts. The mKSM processing could contribute to our understanding of the three vascular plexuses.


Retina ◽  
2017 ◽  
Vol 37 (11) ◽  
pp. 2102-2111 ◽  
Author(s):  
George N. Magrath ◽  
Emil Anthony T. Say ◽  
Kareem Sioufi ◽  
Sandor Ferenczy ◽  
Wasim A. Samara ◽  
...  

2021 ◽  
Vol 14 (5) ◽  
pp. e240208
Author(s):  
Hana A Mansour ◽  
Sami Uwaydat ◽  
Muhamad H Yunis ◽  
Ahmad M Mansour

Optical coherence tomography angiography imaging in two patients with oculocutaneous albinism, one with severe nystagmus, showed persistence of both the superficial and the deep retinal capillary plexus adding another vascular feature to the foveal hypoplasia.


Author(s):  
Jian Liu ◽  
Shixin Yan ◽  
Nan Lu ◽  
Dongni Yang ◽  
Chunhui Fan ◽  
...  

The size and shape of the foveal avascular zone (FAZ) have a strong positive correlation with several vision-threatening retinovascular diseases. The identification, segmentation and analysis of FAZ are of great significance to clinical diagnosis and treatment. We presented an adaptive watershed algorithm to automatically extract FAZ from retinal optical coherence tomography angiography (OCTA) images. For the traditional watershed algorithm, “over-segmentation” is the most common problem. FAZ is often incorrectly divided into multiple regions by redundant “dams”. This paper analyzed the relationship between the “dams” length and the maximum inscribed circle radius of FAZ, and proposed an adaptive watershed algorithm to solve the problem of “over-segmentation”. Here, 132 healthy retinal images and 50 diabetic retinopathy (DR) images were used to verify the accuracy and stability of the algorithm. Three ophthalmologists were invited to make quantitative and qualitative evaluations on the segmentation results of this algorithm. The quantitative evaluation results show that the correlation coefficients between the automatic and manual segmentation results are 0.945 (in healthy subjects) and 0.927 (in DR patients), respectively. For qualitative evaluation, the percentages of “perfect segmentation” (score of 3) and “good segmentation” (score of 2) are 99.4% (in healthy subjects) and 98.7% (in DR patients), respectively. This work promotes the application of watershed algorithm in FAZ segmentation, making it a useful tool for analyzing and diagnosing eye diseases.


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