Abstract
MRI is a very well-established non-invasive imaging technique that provides the best contrast resolution among the existing diagnostic imaging modalities. MRI has been used as a gold standard for brain imaging involving all neurodegenerative diseases. However, specific neuro-related disorders are still not easily detectable using routine MR imaging. Hence, the use and need of specialized and hybrid imaging techniques must be realized for the early detection of neurodegenerative disorders which are not picked by routine MR imaging techniques. Diffusion-tensor imaging (DTI) is a sophisticated imaging technique that can help in detecting microstructural brain abnormalities. FA values derived from DTI as its scalar derivative can help in predicting early changes and findings over a wide range of neurodegenerative diseases.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cochrane CJ, Ebmeier KP. Diffusion tensor imaging in parkinsonian syndromes: a systematic review and meta-analysis. Neurology. 2013;80(9):857–64.
Atkinson-Clement C, Pinto S, Eusebio A, Coulon O. Diffusion tensor imaging in Parkinson’s disease: review and meta-analysis. NeuroImage Clin. 2017;16:98–110.
Giannelli M, Cosottini M, Michelassi MC, Lazzarotti G, Belmonte G, Bartolozzi C, et al. Dependence of brain DTI maps of fractional anisotropy and mean diffusivity on the number of diffusion weighting directions. J Appl Clin Med Phys. 2009;11(1):2927. http://www.jacmp.org/index.php/jacmp/article/view/2927/1797.
Bisdas S, Bohning DEE, Besenski N, Nicholas JSS, Rumboldt Z. Reproducibility, interrater agreement, and age-related changes of fractional anisotropy measures at 3T in healthy subjects: effect of the applied b-value. AJNR Am J Neuroradiol. 2008;29(6):1128–33. http://www.ajnr.org/cgi/doi/10.3174/ajnr.A1044.
Chou M, Mori S. Effects of b-value and echo time on magnetic resonance diffusion tensor imaging-derived parameters at 1.5 T: a voxel-wise study. J Med Biol Eng. 2012;33(1):45–50.
Zhang Y, Schuff N, Jahng G-H, Bayne W, Mori S, Schad L, et al. Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer disease. Neurology. 2007;68(1):13–9. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1941719&tool=pmcentrez&rendertype=abstract.
Zhang Y, Burock MA. Diffusion tensor imaging in Parkinson’s disease and parkinsonian syndrome: a systematic review. Front Neurol. 2020;11:1–25.
Heim B, Krismer F, De Marzi R, Seppi K. Magnetic resonance imaging for the diagnosis of Parkinson’s disease. J Neural Transm. 2017;124(8):915–64.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Kotian, R.P., Koteshwar, P. (2022). Diffusion-Tensor Imaging and Fractional Anisotropy Protocol at 1.5-T MRI for Early Parkinson’s Disease. In: Diffusion Tensor Imaging and Fractional Anisotropy. Springer, Singapore. https://doi.org/10.1007/978-981-19-5001-8_7
Download citation
DOI: https://doi.org/10.1007/978-981-19-5001-8_7
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-5000-1
Online ISBN: 978-981-19-5001-8
eBook Packages: MedicineMedicine (R0)