Top

Graefe's Archive for Clinical and Experimental Ophthalmology

Published in:

01-09-2019 | Retinal Disorders

Running pattern of choroidal vessel in en face OCT images determined by machine learning–based quantitative method

Authors: Hideki Shiihara, Taiji Sakamoto, Hiroto Terasaki, Naoko Kakiuchi, Yuki Shinohara, Masatoshi Tomita, Shozo Sonoda

Published in: Graefe's Archive for Clinical and Experimental Ophthalmology | Issue 9/2019

Abstract

Purpose

To evaluate the new method to quantitate the running pattern of the vessels in Haller’s layer in en face optical coherence tomographic (OCT) images using the new algorithm.

Methods

A retrospective and cross-sectional study. The en face image of top 25% slab of Haller’s layer was analyzed. The vascular area in these images was calculated after binarization. Then, the vessels were thinned, and the total length of the vessels and the mean vessel diameter were calculated. Based on the angle of vessel running, “natural oblique vessel” was defined. The ratio of the natural oblique vessel to the whole vessels was defined as the “symmetry index”. To examine the reproducibility of the software, the images obtained on two different examination dates of the same subject (25 eyes of 25 healthy subjects) were analyzed. Also, to compare the symmetry index and subjective evaluations, 180 eyes and 180 healthy subjects were analyzed. The subjective evaluations classified the images into 3 groups, the Symmetrical, Semi-symmetrical, and Asymmetrical types. Symmetry index was compared in each group.

Results

The inter-measurement correlation coefficient (ICC) of the vessel area, vessel length, and vessel diameter were 0.955, 0.934, and 0.954, respectively. The ICC of the symmetry index was 0.926. The symmetry index of the Symmetrical type was 60.4 ± 7.2%, that of the Semi-symmetry type was 56.2 ± 4.6%, and that of the Asymmetry type was 52.6 ± 5.2%.

Conclusions

The present algorithm can analyze vessels in Haller’s layer of the en face images of choroid in an objective manner with good repeatability.

Lutty GA, Cao J, McLeod DS (1997) Relationship of polymorphonuclear leukocytes to capillary dropout in the human diabetic choroid. Am J Pathol 151:707PubMedPubMedCentral

Imamura Y, Fujiwara T, Margolis R, Spaide RF (2009) Enhanced depth imaging optical coherence tomography of the choroid in central serous chorioretinopathy. Retina 29:1469–1473CrossRef

Laude A, Cackett PD, Vithana EN, Yeo IY, Wong D, Koh AH, Wong TY, Aung T (2010) Polypoidal choroidal vasculopathy and neovascular age-related macular degeneration: same or different disease? Prog Retin Eye Res 29:19–29CrossRef

Saito M, Kano M, Itagaki K, Ise S, Imaizumi K, Sekiryu T (2016) Subfoveal choroidal thickness in polypoidal choroidal vasculopathy after switching to intravitreal aflibercept injection. Jpn J Ophthalmol 60:35–41CrossRefPubMed

Yoshikawa M, Akagi T, Nakanishi H, Ikeda HO, Morooka S, Yamada H, Hasegawa T, Iida Y, Yoshimura N (2017) Longitudinal change in choroidal thickness after trabeculectomy in primary open-angle glaucoma patients. Jpn J Ophthalmol 61:105–112CrossRefPubMed

Dansingani KK, Balaratnasingam C, Klufas MA, Sarraf D, Freund KB (2015) Optical coherence tomography angiography of shallow irregular pigment epithelial detachments in pachychoroid spectrum disease. Am J Ophthalmol 160:1243–1254. e1242CrossRef

Dansingani KK, Balaratnasingam C, Naysan J, Freund KB (2016) En face imaging of pachychoroid spectrum disorders with swept-source optical coherence tomography. Retina 36:499–516CrossRef

Savastano MC, Dansingani KK, Rispoli M, Virgili G, Savastano A, Freund KB, Lumbroso B (2017) Classification of haller vessel arrangements in acute and chronic central serous chorioretinopathy imaged with en face optical coherence tomography. Retina 38:1211–1215CrossRef

Savastano MC, Rispoli M, Savastano A, Lumbroso B (2015) En face optical coherence tomography for visualization of the choroid. Ophthalmic Surg Lasers Imaging Retina 46:561–565CrossRefPubMed

10.

Hiroe T, Kishi S (2018) Dilatation of asymmetric vortex vein in central serous chorioretinopathy. Ophthalmol Retin 2:152–161CrossRef

11.

Spaide RF, Koizumi H, Pozonni MC (2008) Enhanced depth imaging spectral-domain optical coherence tomography. Am J Ophthalmol 146:496–500CrossRef

12.

Esmaeelpour M, Považay B, Hermann B, Hofer B, Kajic V, Kapoor K, Sheen NJ, North RV, Drexler W (2010) Three-dimensional 1060-nm OCT: choroidal thickness maps in normal subjects and improved posterior segment visualization in cataract patients. Invest Ophthalmol Vis Sci 51:5260–5266CrossRefPubMed

13.

Copete S, Flores-Moreno I, Montero JA, Duker JS, Ruiz-Moreno JM (2014) Direct comparison of spectral-domain and swept-source OCT in the measurement of choroidal thickness in normal eyes. Br J Ophthalmol 98:334–338CrossRef

14.

Adhi M, Liu JJ, Qavi AH, Grulkowski I, Lu CD, Mohler KJ, Ferrara D, Kraus MF, Baumal CR, Witkin AJ (2014) Choroidal analysis in healthy eyes using swept-source optical coherence tomography compared to spectral domain optical coherence tomography. Am J Ophthalmol 157:1272–1281. e1271CrossRef

15.

Matsuo Y, Sakamoto T, Yamashita T, Tomita M, Shirasawa M, Terasaki H (2013) Comparisons of choroidal thickness of normal eyes obtained by two different spectral-domain OCT instruments and one swept-source OCT instrument. Invest Ophthalmol Vis Sci 54:7630–7636CrossRef

16.

Uji A, Balasubramanian S, Lei J, Baghdasaryan E, Al-Sheikh M, Sadda SR (2017) Choriocapillaris imaging using multiple en face optical coherence tomography angiography image averaging. JAMA Ophthalmol 135:1197–1204CrossRefPubMedPubMedCentral

17.

Spaide RF (2017) Choriocapillaris signal voids in maternally inherited diabetes and deafness and in pseudoxanthoma elasticum. Retina 37:2008–2014CrossRef

18.

Sohrab M, Wu K, Fawzi AA (2012) A pilot study of morphometric analysis of choroidal vasculature in vivo, using en face optical coherence tomography. PLoS One 7:e48631CrossRefPubMedPubMedCentral

19.

Shiihara H, Sonoda S, Terasaki H, Kakiuchi N, Shinohara Y, Tomita M, Sakamoto T (2018) Automated segmentation of en face choroidal images obtained by optical coherent tomography by machine learning. Jpn J Ophthalmol 62:643–651CrossRefPubMed

20.

Stroustrup B (2013) The C++ programming language, 4th edn. Pearson Education India, London

21.

Zuiderveld K (1994) Contrast limited adaptive histogram equalization. Graphics gems: 474–485

22.

Buades A, Coll B, Morel J-M (2005) A non-local algorithm for image denoising. In Proc IEEE CVPR 60–65

23.

Otsu N (1979) A threshold selection method from gray-level histograms. Man Cybern 9:62–66CrossRef

24.

Zhang T, Suen CY (1984) A fast parallel algorithm for thinning digital patterns. Commun ACM 27:236–239CrossRef

25.

Mori K, Gehlbach PL, Yoneya S, Shimizu K (2004) Asymmetry of choroidal venous vascular patterns in the human eye. Ophthalmology 111:507–512CrossRefPubMed

26.

Yoneya S, Tso MO (1987) Angioarchitecture of the human choroid. Arch Ophthalmol 105:681–687CrossRefPubMed

27.

Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174CrossRefPubMed

28.

Kuroda Y, Ooto S, Yamashiro K, Oishi A, Nakanishi H, Tamura H, Ueda-Arakawa N, Yoshimura N (2016) Increased choroidal vascularity in central serous chorioretinopathy quantified using swept-source optical coherence tomography. Am J Ophthalmol 169:199–207CrossRefPubMed

29.

Fujiwara A, Morizane Y, Hosokawa M, Kimura S, Kumase F, Shiode Y, Doi S, Hirano M, Toshima S, Hosogi M (2016) Factors affecting choroidal vascular density in normal eyes: quantification using en face swept-source optical coherence tomography. Am J Ophthalmol 170:1–9CrossRefPubMed

30.

Maruyama-Inoue M, Yamane S, Satoh H, Sato S, Kadonosono K (2017) Choroidal angioarchitecture according to ultra-widefield indocyanine green angiography in age-related macular degeneration. Journal of VitreoRetinal Diseases 1:365–371CrossRef

31.

Borrelli E, Sarraf D, Freund KB, Sadda SR (2018) OCT angiography and evaluation of the choroid and choroidal vascular disorders. Prog Retin Eye Res 67:30–55CrossRefPubMed

32.

Mennel S, Hausmann N, Meyer CH, Peter S (2005) Photodynamic therapy and indocyanine green guided feeder vessel photocoagulation of choroidal neovascularization secondary to choroid rupture after blunt trauma. Graefes Arch Clin Exp Ophthalmol 243:68–71CrossRefPubMed

Title: Running pattern of choroidal vessel in en face OCT images determined by machine learning–based quantitative method
Authors: Hideki Shiihara
Taiji Sakamoto
Hiroto Terasaki
Naoko Kakiuchi
Yuki Shinohara
Masatoshi Tomita
Shozo Sonoda
Publication date: 01-09-2019
Publisher: Springer Berlin Heidelberg
Published in: Graefe's Archive for Clinical and Experimental Ophthalmology / Issue 9/2019
Print ISSN: 0721-832X
Electronic ISSN: 1435-702X
DOI: https://doi.org/10.1007/s00417-019-04399-8

At a glance: The STEP trials

Springer Medicine

Running pattern of choroidal vessel in en face OCT images determined by machine learning–based quantitative method

Abstract

Purpose

Methods

Results

Conclusions

At a glance: The STEP trials

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 9/2019

The association between cone density and visual function in the macula of patients with retinitis pigmentosa

The influence of age, refractive error, visual demand and lighting conditions on accommodative ability in Malay children and adults

Treat and extend versus pro re nata regimens of ranibizumab and aflibercept in neovascular age-related macular degeneration: a comparative study

Ophthalmologic health status of an aging population—data from the Berlin Aging Study II (BASE-II)

Longitudinal vasculature changes in branch retinal vein occlusion with projection-resolved optical coherence tomography angiography

Imaging analysis with optical coherence tomography angiography after primary repair of macula-off rhegmatogenous retinal detachment