DTI parameters of axonal integrity and demyelination of the optic radiation correlate with glaucoma indices

  • Georg Michelson
  • Tobias Engelhorn
  • Simone Wärntges
  • Ahmed El Rafei
  • Joachim Hornegger
  • Arnd Doerfler
Neurophthalmology

Abstract

Background

In glaucoma, damage of retinal ganglion cells may continue to the linked optic radiations. This study investigates the correlation of glaucoma severity indicators with parameters of axonal and myelin integrity of the optic radiations.

Methods

In this observational case–control study, 13 patients with normal-tension glaucoma, 13 patients with primary open-angle glaucoma, and seven control subjects (mean age, 57.6 ± 12.5 years) were randomly selected for diffusion tensor imaging (DTI) of the optic radiations. The results of the frequency doubling test (FDT) and the HRT-based linear discriminant functions of Burk (BLDF) and Mikelberg (MLDF) were correlated with the mean of the fractional anisotropy (FA), apparent diffusion coefficient (ADC), and radial diffusivity (RD) of the optic radiations. Multiple correlation analysis, corrected for age, stage of cerebral microangiopathy, diagnosis group, and gender was conducted at increasing thresholds of linear anisotropy (CL) to reduce mismeasurements because of complex fiber situations.

Results

The best correlations were found for BLDF with FA at CL threshold 0.3 (0.594, p = 0.001), with ADC at CL 0.4 (−0.511, p = 0.005), and with RD at CL 0.4 (−0.585, p = 0.001). MLDF correlated with FA at CL 0.4 (0.393, p = 0.035). The FDT score correlated with FA at CL 0 (−0.491, p = 0.007) and with RD at CL 0 (−0.375, p = 0.045).

Conclusions

In glaucoma, DTI-derived parameters of the axonal integrity (FA, ADC) and demyelination (RD) of the optic radiation are linked to HRT-based indices of glaucoma severity and to impairment of the spatial-temporal contrast sensitivity.

Keywords

Diffusion tensor imaging Glaucoma Optic nerve head Optic radiation 

Notes

Acknowledgements

This study was supported by the Federal Ministry of Education and Research (BMBF), Bonn, Germany (excellence cluster Medical Valley EMN, Grant MVEMN-A-02), and the Johannes und Frieda Marohn-Stiftung at the University of Erlangen, Germany.

The funding organizations had no role in the design or conduct of this research, in the collection, management, analysis, and interpretation of the data, or in preparation, review, or approval of the manuscript. .

None of the authors has any financial/ conflicting interests to disclose. The authors had full control of all primary data and agree to allow Graefe’s Archive for Clinical and Experimental Ophthalmology to review their data if requested.

Supplementary material

417_2011_1887_MOESM1_ESM.pdf (55 kb)
ESM 1 (PDF 54 kb)

References

  1. 1.
    Yücel YH, Zhang Q, Weinreb RN, Kaufman PL, Gupta N (2003) Effects of retinal ganglion cell loss on mango-, parvo-, koniocellular pathways in the lateral geniculate nucleus and visual cortex in glaucoma. Prog Retin Eye Res 22:465–481PubMedCrossRefGoogle Scholar
  2. 2.
    Weber AJ, Chen H, Hubbard WC, Kaufman PL (2000) Experimental glaucoma and cell size, density, and number in the primate lateral geniculate nucleus. Invest Ophthalmol Vis Sci 41:1370–1379PubMedGoogle Scholar
  3. 3.
    Gupta N, Ang LC, Noël de Tilly L, Bidaisee L, Yücel YH (2006) Human glaucoma and neural degeneration in intracranial optic nerve, lateral geniculate nucleus, and visual cortex. Br J Ophthalmol 90:674–678PubMedCrossRefGoogle Scholar
  4. 4.
    van Swieten JC, van den Hout JH, van Ketel BA, Hijdra A, Wokke JH, van Gijn J (1991) Periventricular lesions in the white matter on magnetic resonance imaging in the elderly: a morphometric correlation with arteriolosclerosis and dilated perivascular spaces. Brain 114:761–774PubMedCrossRefGoogle Scholar
  5. 5.
    Fazekas F, Kleinert R, Offenbacher H, Schmidt R, Kleinert G, Payer F, Radner H, Lechner H (1993) Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology 43:1683–1689PubMedCrossRefGoogle Scholar
  6. 6.
    Wong TY, Klein R, Sharrett AR, Couper DJ, Klein BE, Liao DP, Hubbard LD, Mosley TH, Investigators ARIC (2002) Atheroslerosis Risk in Communities Study. Cerebral white matter lesions, retinopathy, and incident clinical stroke. JAMA 288:67–74PubMedCrossRefGoogle Scholar
  7. 7.
    Harris A, Sergott RC, Spaeth GL, Katz JL, Shoemaker JA, Martin BJ (1994) Color Doppler analysis of ocular vessel blood velocity in normal-tension glaucoma. Am J Ophthalmol 118:642–649PubMedGoogle Scholar
  8. 8.
    Schmidt R, Scheltens P, Erkinjuntti T, Pantoni L, Markus HS, Wallin A, Barkhof F, Fazekas F (2004) White matter lesion progression: a surrogate endpoint for trials in cerebral small-vessel disease. Neurology 63:139–144PubMedCrossRefGoogle Scholar
  9. 9.
    van Swieten JC, Geyskes GG, Derix MM, Peeck BM, Ramos LM, van Latum JC, van Gijn J (1991) Hypertension in the elderly is associated with white matter lesions and cognitive decline. Ann Neurol 30:825–830PubMedCrossRefGoogle Scholar
  10. 10.
    Liao D, Cooper L, Cai J, Toole J, Bryan N, Burke G, Shahar E, Nieto J, Mosley T, Heiss G (1997) The prevalence and severity of white matter lesions, their relationship with age, ethnicity, gender, and cardiovascular disease risk factors: the ARIC Study. Neuroepidemiology 16:149–162PubMedGoogle Scholar
  11. 11.
    Breteler MM, van Swieten JC, Bots ML, Grobbee DE, Claus JJ, van den Hout JH, van Harskamp F, Tanghe HL, de Jong PT, van Gijn J, Hofman A (1994) Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: The Rotterdam Study. Neurology 44:1246–1252PubMedCrossRefGoogle Scholar
  12. 12.
    Wen W, Sachdev PS (2004) Extent and distribution of white matter hyperintensities in stroke patients: the Sydney Stroke Study. Stroke 35:2813–2819PubMedCrossRefGoogle Scholar
  13. 13.
    Wong TY, Klein R, Klein BEK, Tielsch JM, Hubbard LD, Nieto FJ (2001) Retinal microvascular abnormalities and their relations with hypertension, cardiovascular diseases and mortality. Surv Ophthalmol 46:59–80PubMedCrossRefGoogle Scholar
  14. 14.
    Pierpaoli C, Jezzard P, Basser PJ, Barnett A, DiChiro G (1996) Diffusion tensor MR imaging of the human brain. Radiology 201:637–648PubMedGoogle Scholar
  15. 15.
    Sotak CH (2002) The role of diffusion tensor imaging in the evaluation of ischemic brain injury – a review. NMR Biomed 15(7–8):561–569PubMedCrossRefGoogle Scholar
  16. 16.
    Xu J, Sun SW, Naismith RT, Snyder AZ, Cross AH, Song SK (2008) Assessing optic nerve pathology with diffusion MRI: from mouse to human. NMR Biomed 21(9):928–940PubMedCrossRefGoogle Scholar
  17. 17.
    Dong Q, Welsh RC, Chenevert TL, Carlos RC, Maly-Sundgren P, Gomez-Hassan DM, Mukherji SK (2004) Clinical applications of diffusion tensor imaging. J Magn Reson Imaging 19(1):6–18PubMedCrossRefGoogle Scholar
  18. 18.
    Song SK, Sun SW, Ju WK, Lin SJ, Cross AH, Neufeld AH (2003) Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. NeuroImage 20:1714–1722PubMedCrossRefGoogle Scholar
  19. 19.
    Song SK, Sun SW, Ramsbottom MJ, Chang C, Russell J, Cross AH (2002) Dysmyelination revealed through MRI as increased radial but unchanged axial diffusion of water. NeuroImage 17:1429–1436PubMedCrossRefGoogle Scholar
  20. 20.
    Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M (1986) MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 161(2):401–407PubMedGoogle Scholar
  21. 21.
    Burk RO, Noack H, Rohrschneider K, Volcker HE (1999) Prediction of glaucomatous visual field defects by reference plane independent three-dimensional optic nerve head parameters. In: Wall M, Wild JM (eds) Perimetry Update 1998/1999: Proceedings of the XIIIth International Perimetric Society Meeting, Gardone Riviera (BS), Italy, September 6–9, 1998, Kugler, The Hague, pp 463–474Google Scholar
  22. 22.
    Mikelberg FS, Parfitt CM, Swindale NV, Graham SL, Drance SM, Gosine R (1995) Ability of the Heidelberg Retina Tomograph to detect early glaucomatous visual field loss. J Glaucoma 4(4):242–247PubMedCrossRefGoogle Scholar
  23. 23.
    Patel SC, Friedman DS, Varadkar P, Robin AL (2000) Algorithm for interpreting the results of frequency doubling perimetry. Am J Ophthalmol 129(3):323–327PubMedCrossRefGoogle Scholar
  24. 24.
    El-Rafei A, Engelhorn T, Wärntges S, Dörfler A, Hornegger J, Michelson G (2011) A framework for voxel-based morphometric analysis of the optic radiation using diffusion tensor imaging in glaucoma. Magn Reson Imaging 29(8):1076–1087Google Scholar
  25. 25.
    Wakana S, Jiang H, Nagae-Poetscher LM, van Zijl PC, Mori S (2004) Fiber tract-based atlas of human white matter anatomy. Radiology 230(1):77–87PubMedCrossRefGoogle Scholar
  26. 26.
    Castedo J, Duque A, Roa E, Rodrigo P (2006) Atlas of white matter anatomy with fiber tractography by diffusion tensor MRI. 18th Annual Meeting of the Swiss Society of Neuroradiology SGNR/SSNR, Geneva Switzerland. http://www.neurorgs.com/inv/Publi/Pdf/Poster%20Castedo.pdf. Accessed 27 August 2009
  27. 27.
    UAMS (1997) The Anatomy Project. Nashville, TN: Parthenon Publishing Group, 1997. http://anatomy.uams.edu/AnatomyHTML/atlas_html/eye_38.html. Accessed 10 September 2009
  28. 28.
    Peled S, Gudbjartsson H, Westin CF, Kikinis R, Jolesz FA (1998) Magnetic resonance imaging shows orientation and asymmetry of white matter fiber tracts. Brain Res 780(1):27–33PubMedCrossRefGoogle Scholar
  29. 29.
    Kertesz A, Black SE, Tokar G, Benke T, Carr T, Nicholson L (1988) Periventricular and subcortical hyperintensities on magnetic resonance imaging. ‘Rims, caps, and unidentified bright objects’. Arch Neurol 45(4):404–408PubMedCrossRefGoogle Scholar
  30. 30.
    Garaci FG, Bolacchi F, Cerulli A, Melis M, Spanò A, Cedrone C, Floris R, Simonetti G, Nucci C (2009) Optic nerve and optic radiation neurodegeneration in patients with glaucoma: in vivo analysis with 3-T diffusion-tensor MR imaging. Radiology 252(2):496–501PubMedCrossRefGoogle Scholar
  31. 31.
    Hodapp E, Parrish RK, Anderson DR (1993) Clinical decisions in glaucoma. Mosby, St. Louis, MOGoogle Scholar
  32. 32.
    Vickers JC, Schumer RA, Podos SM, Wang RF, Riederer BM, Morrison JH (1995) Differential vulnerability of neurochemically identified subpopulations of retinal neurons in a monkey model of glaucoma. Brain Res 680(1–2):23–35PubMedCrossRefGoogle Scholar
  33. 33.
    Maddess T, Henry GH (1992) Performance of nonlinear visual units in ocular hypertension and glaucoma. Clin Vision Sci 7(5):371–383Google Scholar
  34. 34.
    White AJ, Sun H, Swanson WH, Lee BB (2002) An examination of physiological mechanisms underlying the frequency-doubling illusion. Invest Ophthalmol Vis Sci 43(11):3590–3599PubMedGoogle Scholar
  35. 35.
    Yücel YH, Zhang Q, Gupta N, Kaufman PL, Weinreb RN (2000) Loss of neurons in magnocellular and parvocellular layers of the lateral geniculate nucleus in glaucoma. Arch Ophthalmol 118:378–384PubMedGoogle Scholar
  36. 36.
    Fechtner RD, Weinreb RN (1994) Mechanisms of optic nerve damage in primary open angle glaucoma. Surv Ophthalmol 39:23–42PubMedCrossRefGoogle Scholar
  37. 37.
    Burk RO, Vihanninjoki K, Bartke T, Tuulonen A, Airaksinen PJ, Völcker HE, König JM (2000) Development of the standard reference plane for the Heidelberg Retina Tomograph. Graefes Arch Clin Exp Ophthalmol 238(5):375–384PubMedCrossRefGoogle Scholar
  38. 38.
    Sun SW, Liang HF, Le TQ, Armstrong RC, Cross AH, Song SK (2006) Differential sensitivity of in vivo and ex vivo diffusion tensor imaging to evolving optic nerve injury in mice with retinal ischemia. NeuroImage 32(3):1195–1204PubMedCrossRefGoogle Scholar
  39. 39.
    Sun S-W, Liang H-F, Cross AH, Song S-K (2008) Evolving Wallerian degeneration after transient retinal ischemia in mice characterized by diffusion tensor imaging. NeuroImage 40(1):1–10PubMedCrossRefGoogle Scholar
  40. 40.
    Barrick TR, Charlton RA, Clark CA, Markus HS (2010) White matter structural decline in normal ageing; a prospective longitudinal study using tract based spatial statistics. Neuroimage 51(2):565–577Google Scholar
  41. 41.
    Hirsch JG, Bock M, Essig M, Schad LR (1999) Comparison of diffusion anisotropy measurements in combination with the FLAIR technique. Magn Reson Imaging 17:705–716PubMedCrossRefGoogle Scholar
  42. 42.
    Basser PJ, Pierpaoli C (1996) Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B 111(3):209–219PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Georg Michelson
    • 1
    • 4
    • 5
  • Tobias Engelhorn
    • 2
  • Simone Wärntges
    • 1
    • 4
  • Ahmed El Rafei
    • 3
    • 5
  • Joachim Hornegger
    • 3
    • 5
  • Arnd Doerfler
    • 2
  1. 1.Department of OphthalmologyUniversity Erlangen-NurembergErlangenGermany
  2. 2.Department of NeuroradiologyUniversity Erlangen-NurembergErlangenGermany
  3. 3.Department of Computer Science - Pattern Recognition LabUniversity Erlangen-NurembergErlangenGermany
  4. 4.Interdisciplinary Center of Ophthalmologic Preventive Medicine and Imaging (IZPI)University Erlangen-NurembergErlangenGermany
  5. 5.Graduate School in Advanced Optical Technologies (SAOT)ErlangenGermany

Personalised recommendations