Skip to main content

Advertisement

Log in

Prevalences of segmentation errors and motion artifacts in OCT-angiography differ among retinal diseases

  • Retinal Disorders
  • Published:
Graefe's Archive for Clinical and Experimental Ophthalmology Aims and scope Submit manuscript

Abstract

Purpose

To assess the prevalences of segmentation errors and motion artifacts in optical coherence tomography angiography (OCT-A) in different retinal diseases

Methods

In a retrospective analysis, multimodal retinal imaging including OCT-A was performed in one eye of 57 healthy controls (50.96 ± 22.4 years) and 149 patients (66.42 ± 14.1 years) affected by different chorioretinal diseases: early/intermediate age-related macular degeneration (AMD; n = 26), neovascular AMD (nAMD; n = 22), geographic atrophy due to AMD (GA; n = 6), glaucoma (n = 28), central serous chorioretinopathy (CSC; n = 14), epiretinal membrane (EM; n = 26), retinal vein occlusion (RVO; n = 11), and retinitis pigmentosa (RP; n = 16). Central 3 × 3 mm2 OCT-A imaging was performed with active eye-tracking (AngioVue, Optovue). Best-corrected visual acuity (BCVA) and signal strength index (SSI) were recorded. Images were independently evaluated by two graders using the OCT-A motion artifact score (MAS; scores I–IV) as well as a newly introduced segmentation accuracy score (SAS; score I–IIB).

Results

Mean SSI was 63.67 ± 9.2 showing a negative correlation with increasing age (rSp = − 0.42, p < 0.001, n = 206). In the healthy cohort, mean MAS was 1.45 ± 0.8 and segmentation was accurate (SAS I) in all eyes. In eyes with retinal pathologies, mean MAS was 2.1 ± 0.9 (p < 0.001). Lowest MAS was observed in GA (2.67 ± 0.5) and RVO (2.45 ± 1.1). Compared to an accurate segmentation in 100% in healthy subjects, 34.2% (n = 51) of all patients showed highest segmentation quality (p < 0.001). 63.8% showed segmentation errors in more than 5% of all single b-scans in one (SAS IIA, n = 58) or at least two (SAS IIB, n = 40) segmentation boundaries. Highest percentages of inaccurate segmentation (SAS IIA or IIB) were observed in the nAMD group (90.1%). The inner plexiform layer was the segmentation boundary most prone to inaccurate segmentation in all pathologies compared to the inner limiting membrane (ILM) and retinal pigment epithelium (RPE) segmentation layer. Incorrect ILM segmentation was only seen in patients with EM.

Conclusions

Prior to both qualitative and quantitative analysis, OCT-A images must be carefully reviewed as motion artifacts and segmentation errors in current OCT-A technology are frequent particularly in pathologically altered maculae.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Jia Y, Bailey ST, Hwang TS et al (2015) Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye. Proc Natl Acad Sci U S A 112:E2395–E2402

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Cole ED, Ferrara D, Novais EA, Louzada RN, Waheed NK (2016) Clinical trial endpoints for optical coherence tomography angiography in neovascular age-related macular degeneration. Retina 36(Suppl 1):S83–S92

    Article  PubMed  Google Scholar 

  3. Say EA, Ferenczy S, Magrath GN, Samara WA, Khoo CT, Shields CL (2017) Image quality and artifacts on optical coherence tomography angiography: comparison of pathologic and paired fellow eyes in 65 patients with unilateral choroidal melanoma treated with plaque radiotherapy. Retina 37(9):1660–1673

    Article  PubMed  Google Scholar 

  4. Sadda SR, Wu Z, Walsh AC et al (2006) Errors in retinal thickness measurements obtained by optical coherence tomography. Ophthalmology 113:285–293

    Article  PubMed  Google Scholar 

  5. Al-Sheikh M, Ghasemi Falavarjani K, Akil H, Sadda SR (2017) Impact of image quality on OCT angiography based quantitative measurements. Int J Retina Vitreous 3:13

    Article  PubMed  PubMed Central  Google Scholar 

  6. Lauermann JL, Treder M, Heiduschka P, Clemens CR, Eter N, Alten F (2017) Impact of eye-tracking technology on OCT-angiography imaging quality in age-related macular degeneration. Graefes Arch Clin Exp Ophthalmol 255:1535–1542

    Article  PubMed  CAS  Google Scholar 

  7. Spaide RF, Fujimoto JG, Waheed NK (2015) Image artifacts in optical coherence tomography angiography. Retina 35:2163–2180

    Article  PubMed  PubMed Central  Google Scholar 

  8. Lumbroso B, Huang D, Jia Y, Rispoli M, Romano A, Waheed NK (2015) Clinical OCT angiography atlas. Jaypee Brothers Medical Publishers, New Delhi

    Book  Google Scholar 

  9. Alten F, Lauermann JL, Clemens CR, Heiduschka P, Eter N (2017) Signal reduction in choriocapillaris and segmentation errors in spectral domain OCT angiography caused by soft drusen. Graefes Arch Clin Exp Ophthalmol 255(12):2347–2355

    Article  PubMed  CAS  Google Scholar 

  10. Ghasemi Falavarjani K, Al-Sheikh M, Akil H, Sadda SR (2017) Image artefacts in swept-source optical coherence tomography angiography. Br J Ophthalmol 101(5):564–568

    Article  PubMed  Google Scholar 

  11. Han IC, Jaffe GJ (2010) Evaluation of artifacts associated with macular spectral-domain optical coherence tomography. Ophthalmology 117:1177–89.e4

    Article  PubMed  Google Scholar 

  12. Kraus MF, Potsaid B, Mayer MA et al (2012) Motion correction in optical coherence tomography volumes on a per A-scan basis using orthogonal scan patterns. Biomed Opt Express 3(6):1182–1199

    Article  PubMed  PubMed Central  Google Scholar 

  13. 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 135:1197–1204

    Article  PubMed  Google Scholar 

  14. Decroos FC, Stinnett SS, Heydary CS, Burns RE, Jaffe GJ (2013) Reading center characterization of central retinal vein occlusion using optical coherence tomography during the COPERNICUS trial. Transl Vis Sci Technol 2(7):7

    Article  PubMed  PubMed Central  Google Scholar 

  15. Spaide RF, Curcio CA (2017) Evaluation of segmentation of the superficial and deep vascular layers of the retina by optical coherence tomography angiography instruments in normal eyes. JAMA Ophthalmol 135:259–262

    Article  PubMed  Google Scholar 

  16. Linderman R, Salmon AE, Strampe M, Russillo M, Khan J, Carroll J (2017) Assessing the accuracy of foveal avascular zone measurements using optical coherence tomography angiography: segmentation and scaling. Transl Vis Sci Technol 6(3):16

    Article  PubMed  PubMed Central  Google Scholar 

  17. Zhang M, Hwang TS, Campbell JP, Bailey ST, Wilson DJ, Huang D, Jia Y (2016) Projection-resolved optical coherence tomographic angiography. Biomed Opt Express 7(3):816–828

    Article  PubMed  PubMed Central  Google Scholar 

  18. Wang J, Zhang M, Hwang TS, Bailey ST, Huang D, Wilson DJ, Jia Y (2017) Reflectance-based projection-resolved optical coherence tomography angiography [invited]. Biomed Opt Express 8(3):1536–1548

    Article  PubMed  PubMed Central  Google Scholar 

  19. Onishi AC, Ashraf M, Soetikno BT, Fawzi AA (2018) Multilevel ischemia in disorganization of the retinal inner layers on projection-resolved optical coherence tomography angiography. Retina. https://doi.org/10.1097/IAE.0000000000002179

  20. Fenner BJ, Tan GS, Tan AC, Yeo IY, Wong TY, Cheung GC (2017) Identification of imaging features that determine quality and repeatability of retinal capillary plexus density measurements in OCT angiography. Br J Ophthalmol 102(4):509–514

    PubMed  Google Scholar 

  21. Shields CL, Say EA, Samara WA, Khoo CT, Mashayekhi A, Shields JA (2016) Optical coherence tomography angiography of the macula after plaque radiotherapy of choroidal melanoma: comparison of irradiated versus nonirradiated eyes in 65 patients. Retina 36(8):1493e1505

    Article  Google Scholar 

  22. Jeoung JW, Choi YJ, Park KH, Kim DM (2013) Macular ganglion cell imaging study: glaucoma diagnostic accuracy of spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci 54:4422–4429

    Article  PubMed  Google Scholar 

  23. Mwanza JC, Durbin MK, Budenz DL et al (2012) Glaucoma diagnostic accuracy of ganglion cell-inner plexiform layer thickness: comparison with nerve fiber layer and optic nerve head. Ophthalmology 119:1151–1158

    Article  PubMed  Google Scholar 

  24. Kim HJ, Lee SY, Park KH, Kim DM, Jeoung JW (2016) Glaucoma diagnostic ability of layer-by-layer segmented ganglion cell complex by spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci 57:4799–4805

    Article  PubMed  CAS  Google Scholar 

  25. Nelis P, Alten F, Clemens CR, Heiduschka P, Eter N (2017) Quantification of changes in foveal capillary architecture caused by idiopathic epiretinal membrane using OCT angiography. Graefes Arch Clin Exp Ophthalmol 255:1319–1324

    Article  PubMed  CAS  Google Scholar 

  26. Rogala J, Zangerl B, Assaad N, Fletcher EL, Kalloniatis M, Nivison-Smith L (2015) In vivo quantification of retinal changes associated with drusen in age-related macular degeneration. Invest Ophthalmol Vis Sci 56:1689–1700

    Article  PubMed  CAS  Google Scholar 

  27. Muftuoglu IK, Ramkumar HL, Bartsch DU, Meshi A, Gaber R, Freeman WR (2017) Quantitative analysis of the inner retinal layer thickness in age-related macular degeneration using corrected optical coherence tomography segmentation. Retina. https://doi.org/10.1097/IAE.0000000000001759

  28. Louzada RN, de Carlo TE, Adhi M et al (2017) Optical coherence tomography angiography artifacts in retinal pigment epithelial detachment. Can J Ophthalmol 52(4):419–424

    Article  PubMed  Google Scholar 

  29. Lang A, Carass A, Bittner AK, Ying HS, Prince JL (2017) Improving graph-based OCT segmentation for severe pathology in retinitis pigmentosa patients. Proc SPIE Int Soc Opt Eng 10137

  30. Spaide RF (2016) Volume-rendered optical coherence tomography of retinal vein occlusion pilot study. Am J Ophthalmol 165:133–144

    Article  PubMed  Google Scholar 

  31. Iida Y, Muraoka Y, Ooto S, Suzuma K, Murakami T, Iida-Miwa Y, Ghashut R, Tsujikawa A (2017) Morphologic and functional retinal vessel changes in branch retinal vein occlusion: an optical coherence tomography angiography study. Am J Ophthalmol 182:168–179

    Article  PubMed  Google Scholar 

  32. Niu S, Chen Q, de Sisternes L, Rubin DL, Zhang W, Liu Q (2014) Automated retinal layers segmentation in SD-OCT images using dual gradient and spatial correlation smoothness constraint. Comput Biol Med 54:116–128

    Article  PubMed  Google Scholar 

  33. Treder M, Lauermann JL, Eter N (2018) Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning. Graefes Arch Clin Exp Ophthalmol 256(2):259–265

    Article  PubMed  CAS  Google Scholar 

  34. Bogunovic H, Waldstein S, Schlegl T, Langs G, Sadeghipour A, Liu X, Gerendas B, Osborne A, Schmidt-Erfurth U (2017) Prediction of anti-VEGF treatment requirements in neovascular AMD using a machine learning approach. Invest Ophthalmol Vis Sci 58:3240–4248

    Article  PubMed  CAS  Google Scholar 

  35. de Sisternes L, Jonna G, Moss J, Marmor MF, Leng T, Rubin DL (2017) Automated intraretinal segmentation of SD-OCT images in normal and age-related macular degeneration eyes. Biomed Opt Express 8(3):1926–1949

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Florian Alten.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

For this type of study, formal consent is not required.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lauermann, J.L., Woetzel, A.K., Treder, M. et al. Prevalences of segmentation errors and motion artifacts in OCT-angiography differ among retinal diseases. Graefes Arch Clin Exp Ophthalmol 256, 1807–1816 (2018). https://doi.org/10.1007/s00417-018-4053-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00417-018-4053-2

Keywords

Navigation