Skip to main content

Recent Developments of Retinal Image Analysis in Alzheimer’s Disease and Potential AI Applications

  • Conference paper
  • First Online:
Computer Vision – ACCV 2018 Workshops (ACCV 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11367))

Included in the following conference series:

  • 1876 Accesses

Abstract

Alzheimers disease (AD) is the most common progressive neurodegenerative illness and cause of dementia in the elderly. The critical barriers for primary prevention in AD are the lack of rapid, non-invasive, sensitive and low-cost biomarkers. As the eye and brain share essential structural and pathogenic pathways, non-invasive eye biomarkers could be identified to obtain new insights into the onset and progression of AD and its complications in the eye. In this short review, recent developments of retinal image analysis in AD and potential artificial intelligence (AI) applications are presented. Some approaches are still very much novel research techniques, others are more established and transitioning into the clinical diagnostic arena. Together they provide us with the capability to move AD detection research forwards by using novel peripheral biomarkers.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Goedert, M., Spillantini, M.G.: A century of Alzheimer’s disease. Science 314, 777–781 (2006)

    Article  Google Scholar 

  2. Kawas, C.H., Corrada, M.M., Brookmeyer, R., et al.: Visual memory predicts Alzheimer’s disease more than a decade before diagnosis. Neurology 60, 1089–1093 (2003)

    Article  Google Scholar 

  3. Katz, B., Rimmer, S.: Ophthalmologic manifestations of Alzheimer’s disease. Surv. Ophthalmol. 34, 31–43 (1989)

    Article  Google Scholar 

  4. Cabrera DeBuc, D., Somfai, G.M., Koller, A.: Retinal microvascular network alterations: potential biomarkers of cerebrovascular and neural diseases. Am. J. Physiol. Heart Circ. Physiol. 312, H201–H212 (2017)

    Article  Google Scholar 

  5. Cogan, D.G., Kuwabara, T.: Comparison of retinal and cerebral vasculature in trypsin digest preparations. Br. J. Ophthalmol. 68, 10–12 (1984)

    Article  Google Scholar 

  6. Drexler, W., Liu, M., Kumar, A., Kamali, T., Unterhuber, A., Leitgeb, R.A.: Optical coherence tomography today: speed, contrast, and multimodality. J. Biomed. Opt. 19, 071412 (2014)

    Article  Google Scholar 

  7. London, A., Benhar, I., Schwartz, M.: The retina as a window to the brainfrom eye research to CNS disorders. Nat. Revi. Neurol. 9, 44 (2013)

    Article  Google Scholar 

  8. Cheung, A.T., Chen, P.C., Larkin, E.C., et al.: Microvascular abnormalities in sickle cell disease: a computer-assisted intravital microscopy study. Blood 99, 3999–4005 (2002)

    Article  Google Scholar 

  9. Optos Web site. www.optos.com. Accessed 27 Sept 2018

  10. Makita, S., Hong, Y., Yamanari, M., Yatagai, T., Yasuno, Y.: Optical coherence angiography. Opt. Express 14, 7821–7840 (2006)

    Article  Google Scholar 

  11. Wang, R.K., Jacques, S.L., Ma, Z., Hurst, S., Hanson, S.R., Gruber, A.: Three dimensional optical angiography. Opt. Express 15, 4083–4097 (2007)

    Article  Google Scholar 

  12. Wang, Y., Fawzi, A., Tan, O., Gil-Flamer, J., Huang, D.: Retinal blood flow detection in diabetic patients by Doppler Fourier domain optical coherence tomography. Opt. Express 17, 4061–4073 (2009)

    Article  Google Scholar 

  13. Yasuno, Y., Hong, Y., Makita, S., et al.: In vivo high-contrast imaging of deep posterior eye by 1-mm swept source optical coherence tomography and scattering optical coherence angiography. Opt. Express 15, 6121–6139 (2007)

    Article  Google Scholar 

  14. Zhang, Q., Lee, C.S., Chao, J., et al.: Wide-field optical coherence tomography based microangiography for retinal imaging. Sci. Rep. 6, 22017 (2016)

    Article  Google Scholar 

  15. Rha, J., Jonnal, R.S., Thorn, K.E., Qu, J., Zhang, Y., Miller, D.T.: Adaptive optics flood-illumination camera for high speed retinal imaging. Opt. Express. 14, 4552–4569 (2006)

    Article  Google Scholar 

  16. Roorda, A., Romero-Borja, F., Donnelly III, W., Queener, H., Hebert, T., Campbell, M.: Adaptive optics scanning laser ophthalmoscopy. Opt. Express 10, 405–412 (2002)

    Article  Google Scholar 

  17. Kim, J.E., Chung, M.: Adaptive optics for retinal imaging. Retina 33, 1483–1486 (2013)

    Article  Google Scholar 

  18. Park, B.H., de Boer, J.F.: Polarization sensitive optical coherence tomography. In: Drexler, W., Fujimoto, J.G. (eds.) Optical Coherence Tomography - Technology and Applications, pp. 1055–1101. Springer, Cham (2015)

    Chapter  Google Scholar 

  19. Ding, J., Strachan, M.W., Fowkes, F.G., et al.: Association of retinal arteriolar dilatation with lower verbal memory: the Edinburgh type 2 diabetes study. Diabetologia 54, 1653–1662 (2011)

    Article  Google Scholar 

  20. La Morgia, C., Ross-Cisneros, F.N., Koronyo, Y., et al.: Melanopsin retinal ganglion cell loss in Alzheimer disease. Ann. Neurol. 79, 90–109 (2016)

    Article  Google Scholar 

  21. Hart, N.J., Koronyo, Y., Black, K.L., Koronyo-Hamaoui, M.: Ocular indicators of Alzheimers: exploring disease in the retina. Acta Neuropathol. 132, 767–787 (2016)

    Article  Google Scholar 

  22. Blanks, J.C., Schmidt, S.Y., Torigoe, Y., Porrello, K.V., Hinton, D.R., Blanks, R.H.: Retinal pathology in Alzheimer’s disease. II. Regional neuron loss and glial changes in GCL. Neurobiol. Aging. 17, 385–395 (1996)

    Article  Google Scholar 

  23. Feke, G.T., Hyman, B.T., Stern, R.A., Pasquale, L.R.: Retinal blood flow in mild cognitive impairment and Alzheimers disease. Alzheimers Dement. (Amst.) 1, 144–151 (2015)

    Google Scholar 

  24. Frost, S., Kanagasingam, Y., Sohrabi, H., et al.: Retinal vascular biomarkers for early detection and monitoring of Alzheimers disease. Transl. Psychiatry 3, e233 (2013)

    Article  Google Scholar 

  25. Hinton, D.R., Sadun, A.A., Blanks, J.C., Miller, C.A.: Optic-nerve degeneration in Alzheimers disease. N. Engl. J. Med. 315, 485–487 (1986)

    Article  Google Scholar 

  26. Paquet, C., Boissonnot, M., Roger, F., Dighiero, P., Gil, R., Hugon, J.: Abnormal retinal thickness in patients with mild cognitive impairment and Alzheimers disease. Neurosci. Lett. 420, 97–99 (2007)

    Article  Google Scholar 

  27. Koronyo-Hamaoui, M., Koronyo, Y., Ljubimov, A.V., et al.: Identification of amyloid plaques in retinas from Alzheimers patients and noninvasive in vivo optical imaging of retinal plaques in a mouse model. Neuroimage 54, S204–S217 (2011)

    Article  Google Scholar 

  28. Berisha, F., Feke, G.T., Trempe, C.L., McMeel, J.W., Schepens, C.L.: Retinal abnormalities in early Alzheimers disease. Invest. Ophthalmol. Vis. Sci. 48, 2285–2289 (2007)

    Article  Google Scholar 

  29. Cheung, C.Y., Ong, Y.T., Ikram, M.K., et al.: Microvascular network alterations in the retina of patients with Alzheimers disease. Alzheimers Dement. 10, 135–142 (2014)

    Article  Google Scholar 

  30. Curcio, C.A., Drucker, D.N.: Retinal ganglion cells in Alzheimers disease and aging. Ann. Neurol. 33, 248–257 (2004)

    Article  Google Scholar 

  31. Frost, S., Martins, R.N., Kanagasingam, Y.: Ocular biomarkers for early detection of Alzheimers disease. J. Alzheimers Dis. 22, 1–16 (2010)

    Article  Google Scholar 

  32. Guo, L., Duggan, J., Cordeiro, M.: Alzheimers disease and retinal neurodegeneration. Curr. Alzheimer Res. 7, 3–14 (2010)

    Article  Google Scholar 

  33. Parisi, V., Restuccia, R., Fattapposta, F., Mina, C., Bucci, M.G., Pierelli, F.: Morphological and functional retinal impairment in Alzheimers disease patients. Clin. Neurophysiol. 112, 1860–1867 (2001)

    Article  Google Scholar 

  34. Hampel, H., Toschi, N., Babiloni, C., et al.: Revolution of Alzheimer precision neurology: passageway of systems biology and neurophysiology. J. Alzheimers Dis. 64, S47–S105 (2018)

    Article  Google Scholar 

  35. http://www.neurovisionimaging.com

  36. Aizenstein, H.J., Nebes, R.D., Saxton, J.A., et al.: Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch. Neurol. 65, 1509–1517 (2008)

    Article  Google Scholar 

  37. Koronyo, Y., Biggs, D., Barron, E., et al.: Retinal amyloid pathology and proof-of-concept imaging trial in Alzheimers disease. JCI Insight 2017(2), 93621 (2017)

    Article  Google Scholar 

  38. www.optinadx.com

  39. https://www.newswire.ca/news-releases/optina-diagnostics-looks-to-advance-biomarker-discovery-through-collaboration-with-imagia-689742211.html

  40. Snyder, P.J.: Alzheimer’s & dementia: diagnosis. Assess. Dis. Monit. 4, 169178 (2016)

    Google Scholar 

  41. Santos, C.Y., Johnson, L.N., Sinoff, S.E., Festa, E.K., Heindel, W.C., Snyder, P.J.: Change in retinal structural anatomy during the preclinical stage of Alzheimer’s disease. Alzheimers Dement. (Amst.) 10, 196–209 (2018)

    Google Scholar 

  42. Csincsik, L., MacGillivray, T.J., Flynn, E., et al.: Peripheral retinal imaging biomarkers for Alzheimers disease: a pilot study. Ophthalmic Res. 59, 182192 (2018)

    Article  Google Scholar 

  43. Campbell, M.C., Corapi, F., Emptage, L., et al.: The relationship between amyloid in the retina and a brain-based post-mortem diagnosis of alzheimers disease. Alzheimer’s Dement.: J. Alzheimer’s Assoc. 13, P284–P285 (2017)

    Article  Google Scholar 

  44. Baumann, B., Woehrer, A., Ricken, G., et al.: Visualization of neuritic plaques in Alzheimers disease by polarization-sensitive optical coherence microscopy. Sci. Rep. 7, 43477 (2017)

    Article  Google Scholar 

  45. Danesh-Meyer, H.V., Birch, H., Ku, J.F., Carroll, S., Gamble, G.: Reduction of optic nerve fibers in patients with Alzheimer disease identified by laser imaging. Neurology 67, 1852–1854 (2006)

    Article  Google Scholar 

  46. Kurna, S.A., Akar, G., Altun, A., Agirman, Y., Gozke, E., Sengor, T.: Confocal scanning laser tomography of the optic nerve head on the patients with Alzheimers disease compared to glaucoma and control. Int. Ophthalmol. 34, 1203–1211 (2014)

    Article  Google Scholar 

  47. Cordeiro, M.F., Guo, L., Coxon, K.M., et al.: Imaging multiple phases of neurodegeneration: a novel approach to assessing cell death in vivo. Cell Death Dis. 1, e3 (2010)

    Article  Google Scholar 

  48. DeBuc, D.C., Kostic, M., Oropesa, S., Somfai, G.M., Mendoza-Santiesteban, C.: Investigating multimodal diagnostic eye biomarkers of cognitive impairment by measuring vascular and neurogenic changes in the retina. Alzheimer’s Dement.: J. Alzheimer’s Assoc. 14, P1095 (2018)

    Article  Google Scholar 

  49. Bulut, M., Kurtulus, F., Gozkaya, O., et al.: Evaluation of optical coherence tomography angiographic findings in Alzheimers type dementia. Br. J. Ophthalmol. 102, 233–237 (2018)

    Article  Google Scholar 

  50. Jiang, H., Wei, Y., Shi, Y., et al.: Altered macular microvasculature in mild cognitive impairment and Alzheimer disease. J. Neuroophthalmol. 38, 292–298 (2018)

    Article  Google Scholar 

  51. Olafsdottir, O.B., Saevarsdottir, H.S., Hardarson, S.H., et al.: Retinal oxygen metabolism in patients with mild cognitive impairment. Alzheimers Dement. (Amst.) 10, 340–345 (2018)

    Google Scholar 

  52. Stefnsson, E., Olafsdottir, O.B., Einarsdottir, A.B., et al.: Retinal oximetry discovers novel biomarkers in retinal and brain diseases. Invest. Ophthalmol. Vis. Sci. 58, BIO227–BIO233 (2017)

    Article  Google Scholar 

  53. Munk, M.R., Giannakaki-Zimmermann, H., Berger, L., et al.: OCT-angiography: a qualitative and quantitative comparison of 4 OCT-A devices. PLoS One 12, e0177059 (2017)

    Article  Google Scholar 

  54. Cosatto, V.F., Liew, G., Rochtchina, E., et al.: Retinal vascular fractal dimension measurement and its influence from imaging variation: results of two segmentation methods. Curr. Eye Res. 35, 850–856 (2010)

    Article  Google Scholar 

  55. Cheung, C.Y., Tay, W.T., Mitchell, P., et al.: Quantitative and qualitative retinal microvascular characteristics and blood pressure. J. Hypertens. 29, 1380–1391 (2011)

    Article  Google Scholar 

  56. Soucy, J.P., Chevrefils, C., Sylvestre, J.P., et al.: An amyloid ligand-free optical retinal imaging method to predict cerebral amyloid PET status. Alzheimer’s Dement.: J. Alzheimer’s Assoc. 14, P771 (2018)

    Article  Google Scholar 

  57. Sandeep, C.S., Kumar, A.S., Mahadevan, K., Manoj, P.: Classification of OCT images for the early diagnosis of Alzheimer’s disease. In: 2017 International Conference on Intelligent Computing and Control (I2C2), Coimbatore, pp. 1–5 (2017)

    Google Scholar 

  58. Sandeep, C.S., Kumar, S.A., Mahadevan, K., Manoj, P.: Analysis of MRI and OCT images for early diagnosis of Alzheimers disease using wavelet networks. AMSE J. Lect. Model. Simul. 31–40 (2017). http://amsemodelling.com/publications/lectures_on_modelling_and_simulation.html

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Delia Cabrera DeBuc .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Cabrera DeBuc, D., Arthur, E. (2019). Recent Developments of Retinal Image Analysis in Alzheimer’s Disease and Potential AI Applications. In: Carneiro, G., You, S. (eds) Computer Vision – ACCV 2018 Workshops. ACCV 2018. Lecture Notes in Computer Science(), vol 11367. Springer, Cham. https://doi.org/10.1007/978-3-030-21074-8_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-21074-8_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-21073-1

  • Online ISBN: 978-3-030-21074-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics