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A diffusion tensor imaging study to compare normative fractional anisotropy values with patients suffering from Parkinson’s disease in the brain grey and white matter

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Abstract

Diffusion tensor imaging (DTI) appears as a sensitive method to study Parkinson’s disease (PD) pathophysiology and severity. Fractional anisotropy (FA) value is one of the scalar derivatives of DTI used to find out anisotropy within a voxel in a tissue and used for determining white matter integrity in aging and neurodegenerative diseases. We studied DTI derived FA in early PD subjects as their routine MRI scans were normal. 40 patients with early PD and 40 healthy controls were employed to evaluate changes in microstructural white and grey matter in the brain’s using DTI derived FA values. Comparison of FA values in the brain’s white and grey matter of patients with PD and age matched controls at the corpus callosum, centrum semiovale, pons, putamen, caudate nucleus, substantia nigra, cerebral peduncles and cerebellar peduncles, was done using a region of interest (ROI) technique, with b-value 1000s/mm2 and TE = 100 milliseconds using 1.5 T MRI system. PD patients showed differences in FA values in both the grey and white matter areas of the brain’s compared to healthy controls. Our study revealed the presence of damage in the substantia nigra, corpus callosum, putamen and cerebral peduncles mainly in the PD group. Our findings indicate that DTI and region of interest (ROI) methods can be used in patients with early PD to study microstructural alterations mainly in the substantia nigra, putamen and corpus callosum.

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Data availability

The data collected in the current study comprises of screenshot images taken after obtaining FA values of PD patients and healthy controls using diffusion tensor imaging fibre track software. The data will be shared on request as per the Kasturba Medical hospital ethical committee patient privacy guidelines. The datasets used and/or analysed during the current study is available from the corresponding author on reasonable request.

References

  1. Daniel SE, Lees AJ. Parkinson's disease society brain Bank, London: overview and research. Journal of neural transmission Supplementum. 1993;39:165.

    Google Scholar 

  2. Gattellaro G, Minati L, Grisoli M, Mariani C, Carella F, Osio M, et al. White matter involvement in idiopathic Parkinson disease: a diffusion tensor imaging study. Am J Neuroradiol. 2009 Jun 1;30(6):1222–6.

    Article  Google Scholar 

  3. Skidmore FM, Yang M, Baxter L, Von Deneen KM, Collingwood J, He G, et al. Reliability analysis of the resting state can sensitively and specifically identify the presence of Parkinson disease. Neuroimage. 2013 Jul 15;75:249–61.

    Article  Google Scholar 

  4. Mori S, Zhang J. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron. 2006 Sep 7;51(5):527–39.

    Article  Google Scholar 

  5. Alexander AL, Lee JE, Lazar M, Field AS. Diffusion tensor imaging of the brain. Neurotherapeutics. 2007 Jul 1;4(3):316–29.

    Article  Google Scholar 

  6. Zhang K, Yu C, Zhang Y, Wu X, Zhu C. Voxel-based analysis of diffusion tensor indices in the brain in patients with Parkinson ’ s disease. Eur J Radiol [Internet]. 2017;77(2):269–73.

    Article  Google Scholar 

  7. Saeed U, Compagnone J, Aviv RI, Strafella AP, Black SE, Lang AE, et al. Imaging biomarkers in Parkinson’s disease and Parkinsonian syndromes: current and emerging concepts. Translational neurodegeneration. 2017 Dec;6(1):8.

    Article  Google Scholar 

  8. Cochrane CJ, Ebmeier KP. Diffusion tensor imaging in parkinsonian syndromes: a systematic review and meta-analysis. Neurology. 2013 Feb 26;80(9):857–64.

    Article  Google Scholar 

  9. Schwarz ST, Abaei M, Gontu V, Morgan PS, Bajaj N, Auer DP. Diffusion tensor imaging of nigral degeneration in Parkinson's disease: a region-of-interest and voxel-based study at 3 T and systematic review with meta-analysis. NeuroImage: Clinical. 2013 Jan 1;3:481–8.

    Article  Google Scholar 

  10. Atkinson-Clement C, Pinto S, Eusebio A, Coulon O. Diffusion tensor imaging in Parkinson's disease: review and meta-analysis. NeuroImage: Clinical. 2017 Jan 1;16:98–110.

    Article  Google Scholar 

  11. Chan LL, Ng KM, Yeoh CS, Rumpel H, Li HH, Tan EK. Putaminal diffusivity correlates with disease progression in parkinson's disease: prospective 6-year study. Medicine. 2016 Feb;95(6).

  12. Zhan W, Kang GA, Glass GA, Zhang Y, Shirley C, Millin R, et al. Regional alterations of brain microstructure in Parkinson’s disease using diffusion tensor imaging. Mov Disord. 2012;27(1):90–7.

    Article  Google Scholar 

  13. Langley J, Huddleston DE, Merritt M, Chen X, McMurray R, Silver M, et al. Diffusion tensor imaging of the substantia nigra in Parkinson’s disease revisited. Hum Brain Mapp. 2016;37(7):2547–56.

    Article  Google Scholar 

  14. Duncan GW, Firbank MJ, Yarnall AJ, Khoo TK, Brooks DJ, Barker RA, et al. Gray and white matter imaging: a biomarker for cognitive impairment in early Parkinson’s disease? Mov Disord. 2016;31(1):103–10.

    Article  Google Scholar 

  15. Chen N-K, Chou Y, Sundman M, Hickey P, Kasoff WS, Bernstein A, et al. Alteration of diffusion-tensor MRI measures in brain regions involved in early stages of Parkinson’s disease. Brain Connect. 2018;brain.2017.0558.

  16. Rolheiser TM, Fulton HG, Good KP, Fisk JD, McKelvey JR, Scherfler C, et al. Diffusion tensor imaging and olfactory identification testing in early-stage Parkinson’s disease. J Neurol. 2011;258(7):1254–60.

    Article  Google Scholar 

  17. Joshi N, Rolheiser TM, Fisk JD, McKelvey JR, Schoffer K, Phillips G, et al. Lateralized microstructural changes in early-stage Parkinson’s disease in anterior olfactory structures, but not in substantia nigra. J Neurol. 2017;264(7):1497–505.

    Article  Google Scholar 

  18. Schwarz ST, Abaei M, Gontu V, Morgan PS, Bajaj N, Auer DP. Diffusion tensor imaging of nigral degeneration in Parkinson’s disease: a region-of-interest and voxel-based study at 3 T and systematic review with meta-analysis. NeuroImage Clin. 2013;3:481–8.

    Article  Google Scholar 

  19. Melzer TR, Watts R, Macaskill MR, Pitcher TL, Livingston L, Keenan RJ, et al. White matter microstructure deteriorates across cognitive stages in Parkinson disease. Neurology. 2013;80(20):1841–9.

    Article  Google Scholar 

  20. Pozorski V, Oh JM, Adluru N, Merluzzi AP, Theisen F. Okonkwo O, et al. Longitudinal white matter microstructural change in Parkinson’s disease. 2018:1–12.

  21. Prakash BD, Sitoh Y-Y, Tan LCS, Au WL. Asymmetrical diffusion tensor imaging indices of the rostral substantia nigra in Parkinson’s disease. Parkinsonism Relat Disord. 2012 Nov;18(9):1029–33.

    Article  Google Scholar 

  22. Zhang Y, Wu IW, Tosun D, Foster E, Schuff N. Progression of regional microstructural degeneration in Parkinson’s disease: a multicenter diffusion tensor imaging study. PLoS One. 2016;11(10):1–16.

    Google Scholar 

  23. Vaillancourt DE, Spraker MB, Prodoehl J, Abraham I, Corcos DM, Zhou XJ, et al. High-resolution diffusion tensor imaging in the substantia nigra of de novo Parkinson disease. Neurology. 2009 Apr 21;72(16):1378–84.

    Article  Google Scholar 

  24. Péran P, Cherubini A, Assogna F, Piras F, Quattrocchi C, Peppe A, et al. Magnetic resonance imaging markers of Parkinson’s disease nigrostriatal signature. Brain. 2010 Nov;133(11):3423–33.

    Article  Google Scholar 

  25. Chan L-L, Rumpel H, Yap K, Lee E, Loo H-V, Ho G-L, et al. Case control study of diffusion tensor imaging in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 2007 Dec 1;78(12):1383–6.

    Article  Google Scholar 

  26. Chan LL, Ng KM, Yeoh CS, Rumpel H, Li HH, Tan EK. Putaminal diffusivity correlates with disease progression in Parkinson’s disease. Med (United States). 2016;95(6):1–4.

    Google Scholar 

  27. Rulseh AM, Keller J, Tintěra J, Kožíšek M, Vymazal J. Chasing shadows: what determines DTI metrics in gray matter regions? An in vitro and in vivo study. J Magn Reson Imaging. 2013 Nov;38(5):1103–10.

    Article  Google Scholar 

  28. Pfefferbaum A, Adalsteinsson E, Rohlfing T, Sullivan EV. Diffusion tensor imaging of deep gray matter brain structures: effects of age and iron concentration. Neurobiol Aging. 2010 Mar;31(3):482–93.

    Article  Google Scholar 

  29. White ML, Zhang Y. Three-tesla diffusion tensor imaging of Meyer’s loop by tractography, color-coded fractional anisotropy maps, and eigenvectors. Clin Imaging. 2010 Jan;34(6):413–7.

    Article  Google Scholar 

  30. Goldman JG, Bledsoe IO, Merkitch D, Dinh V, Bernard B, Stebbins GT. Corpus callosal atrophy and associations with cognitive impairment in Parkinson disease. Neurology. 2017 Mar 28;88(13):1265–72.

    Article  Google Scholar 

  31. Wiltshire K, Foster S, Kaye JA, Small BJ, Camicioli R. Corpus callosum in neurodegenerative diseases: findings in Parkinson’s disease. Dement Geriatr Cogn Disord. 2005;20(6):345–51.

    Article  Google Scholar 

  32. Meijer FJA, Van Rumund A, Tuladhar AM. Conventional 3T brain MRI and diffusion tensor imaging in the diagnostic workup of early stage parkinsonism. Neuroradiology. 2015;57:655–69.

    Article  Google Scholar 

  33. Meijer FJA, Bloem BR, Mahlknecht P, Seppi K, Goraj B. Update on diffusion MRI in Parkinson’s disease and atypical parkinsonism. J Neurol Sci. 2013;332(1–2):21–9.

    Article  Google Scholar 

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Funding

Bombay Scientific, Mumbai, Maharashtra, India.

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Authors and Affiliations

Authors

Contributions

RK conceptualized the study. RK, PK and SN have given inputs in study design. RK collected the data. RK analysed the data and wrote the first draft of manuscript and all co- authors contributed in critical review of data analysis and manuscript writing. RK will act as guarantor for this paper. All authors have read and approved the manuscript.

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Correspondence to Rahul P Kotian.

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Conflict of interest

The authors declare that they have no competing interests in this study.

Ethical approval

The study protocol followed was reviewed and approved by the Research Committee of Manipal College of Health Profession and Manipal Academy of Higher Education, and ethical clearance was also obtained by Kasturba Medical College and Hospital, MAHE, Manipal.

Informed consent

A detailed explanation about the study was given by the principal investigator after which they provided consent for publication. All the patients included in this research gave written informed consent to publish the data contained within this study.

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Kotian, R.P., Prakashini, K. & Nair, N.S. A diffusion tensor imaging study to compare normative fractional anisotropy values with patients suffering from Parkinson’s disease in the brain grey and white matter. Health Technol. 10, 1283–1289 (2020). https://doi.org/10.1007/s12553-020-00454-1

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  • DOI: https://doi.org/10.1007/s12553-020-00454-1

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