Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid-β-induced pathology

Springer Science and Business Media LLC - Tập 10 - Trang 1-16 - 2018
Jelle Praet1, Nikolay V. Manyakov2, Leacky Muchene3, Zhenhua Mai1,4, Vasilis Terzopoulos4,5, Steve de Backer6, An Torremans7, Pieter-Jan Guns1,8, Tom Van De Casteele2, Astrid Bottelbergs2, Bianca Van Broeck2, Jan Sijbers9, Dirk Smeets1,4, Ziv Shkedy3, Luc Bijnens2, Darrel J. Pemberton2, Mark E. Schmidt2, Annemie Van der Linden1, Marleen Verhoye1
1Bio-Imaging Lab, University of Antwerp, Antwerp (Wilrijk), Belgium
2Janssen Research and Development, Beerse, Belgium
3Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Hasselt, Belgium
4Icometrix R&D, Leuven, Belgium
5Institute for Biological and Medical Imaging, Technische Universität München, Munich, Germany
6DCILabs, Keerbergen, Belgium
7HistoGeneX, Antwerpen, Belgium
8Expert Group Antwerp Molecular Imaging (EGAMI), University of Antwerp, Antwerp, Belgium
9imec-Vision Lab, University of Antwerp, Antwerp, Belgium

Tóm tắt

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia in the elderly population. In this study, we used the APP/PS1 transgenic mouse model to explore the feasibility of using diffusion kurtosis imaging (DKI) as a tool for the early detection of microstructural changes in the brain due to amyloid-β (Aβ) plaque deposition. We longitudinally acquired DKI data of wild-type (WT) and APP/PS1 mice at 2, 4, 6 and 8 months of age, after which these mice were sacrificed for histological examination. Three additional cohorts of mice were also included at 2, 4 and 6 months of age to allow voxel-based co-registration between diffusion tensor and diffusion kurtosis  metrics and immunohistochemistry. Changes were observed in diffusion tensor (DT) and diffusion kurtosis (DK) metrics in many of the 23 regions of interest that were analysed. Mean and axial kurtosis were greatly increased owing to Aβ-induced pathological changes in the motor cortex of APP/PS1 mice at 4, 6 and 8 months of age. Additionally, fractional anisotropy (FA) was decreased in APP/PS1 mice at these respective ages. Linear discriminant analysis of the motor cortex data indicated that combining diffusion tensor and diffusion kurtosis metrics permits improved separation of WT from APP/PS1 mice compared with either diffusion tensor or diffusion kurtosis metrics alone. We observed that mean kurtosis and FA are the critical metrics for a correct genotype classification. Furthermore, using a newly developed platform to co-register the in vivo diffusion-weighted magnetic resonance imaging with multiple 3D histological stacks, we found high correlations between DK metrics and anti-Aβ (clone 4G8) antibody, glial fibrillary acidic protein, ionised calcium-binding adapter molecule 1 and myelin basic protein immunohistochemistry. Finally, we observed reduced FA in the septal nuclei of APP/PS1 mice at all ages investigated. The latter was at least partially also observed by voxel-based statistical parametric mapping, which showed significantly reduced FA in the septal nuclei, as well as in the corpus callosum, of 8-month-old APP/PS1 mice compared with WT mice. Our results indicate that DKI metrics hold tremendous potential for the early detection and longitudinal follow-up of Aβ-induced pathology.

Tài liệu tham khảo

Alzheimer’s Association. 2015 Alzheimer’s disease facts and figures. Alzheimers Dement. 2015;11:332–84. Howard R, McShane R, Lindesay J, Ritchie C, Baldwin A, Barber R, et al. Donepezil and memantine for moderate-to-severe Alzheimer’s disease. N Engl J Med. 2012;366:893–903. Leifer BP. Early diagnosis of Alzheimer’s disease: clinical and economic benefits. J Am Geriatr Soc. 2003;51(5 Suppl Dementia):S281–8. Liu-Seifert H, Siemers E, Holdridge KC, Andersen SW, Lipkovich I, Carlson C, et al. Delayed-start analysis: mild Alzheimer’s disease patients in solanezumab trials, 3.5 years. Alzheimers Dement (N Y). 2015;1:111–21. McKhann G, Knopman DS, Chertkow H, Hymann B, Jack Jr CR, Kawas C, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:263–9. Vemuri P, Jack Jr CR. Role of structural MRI in Alzheimer’s disease. Alzheimers Res Ther. 2010;2:23. Jack Jr CR, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12:207–16. Haass C, Selkoe DJ. Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer’s amyloid β-peptide. Nat Rev Mol Cell Biol. 2007;8:101–12. Nir TM, Jahanshad N, Villalon-Reina JE, Toga AW, Jack CR, Weiner MW, et al. Effectiveness of regional DTI measures in distinguishing Alzheimer’s disease, MCI, and normal aging. Neuroimage Clin. 2013;3:180–95. Jensen JH, Helpern JA, Ramani A, Lu H, Kaczynski K. Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med. 2005;53:1432–40. Radde R, Bolmont T, Kaeser SA, Coomaraswamy J, Lindau D, Stoltze L, et al. Aβ42-driven cerebral amyloidosis in transgenic mice reveals early and robust pathology. EMBO Rep. 2006;7:940–6. Vanhoutte G, Pereson S, Delgado Y, Palacios R, Guns PJ, Asselbergh B, Veraart J, et al. Diffusion kurtosis imaging to detect amyloidosis in an APP/PS1 mouse model for Alzheimer’s disease. Magn Reson Med. 2013;69:1115–21. Jenkinson M, Beckmann C, Behrens TE, Woolrich MW, Smith SM. FSL. Neuroimage. 2012;62:782–90. Veraart J, Poot DHJ, Van Hecke W, Blockx I, Van der Linden A, Verhoye M, et al. More accurate estimation of diffusion tensor parameters using diffusion kurtosis imaging. Magn Reson Med. 2011;65:138–45. Veraart J, Rajan J, Peeters RR, Leemans A, Sunaert S, Sijbers J. Comprehensive framework for accurate diffusion MRI parameter estimation. Magn Reson Med. 2013;70:972–84. den Dekker AJ, Sijbers J. Data distributions in magnetic resonance images: a review. Phys Med. 2014;30:725–41. Poot DHJ, Den Dekker AJ, Achten E, Verhoye M, Sijbers J. Optimal experimental design for diffusion kurtosis imaging. IEEE Trans Med Imaging. 2010;29:819–29. Avants B, Tustison N, Song G. Advanced Normalization Tools: V1.0. Insight J. 2009;July–December:1–35. Ruifrok AC, Johnston DA. Quantification of histochemical staining by color deconvolution. Anal Quant Cytol Histol. 2001;23:291–9. Bigun J, Granlund GH. Optimal orientation detection of linear symmetry. Proc IEEE First Int Conf Comput Vis. 1987;54:433–8. Lowe DG. Object recognition from local scale-invariant features. In: Proceedings of the Seventh IEEE International Conference on Computer Vision. 1999. p. 1150–7. Ourselin S, Roche A, Subsol G, Pennec X, Ayache N. Reconstructing a 3D structure from serial histological sections. Image Vis Comput. 2001;19:25–31. Modat M, Ridgway GR, Taylor ZA, Lehmann M, Barnes J, Hawkes DJ, et al. Fast free-form deformation using graphics processing units. Comput Methods Programs Biomed. 2010;98:278–84. Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics. 1982;38:963–74. Hubbard AE, Ahern J, Fleischer NL, Van der Laan M, Lippman SA, Jewell N, et al. To GEE or not to GEE. Epidemiology. 2010;21:467–74. Verbeke G, Molenberghs G. Linear mixed models for longitudinal data. New York: Springer; 2000. Hastie T, Tibshirani R, Friedman J. The elements of statistical learning: data mining, inference and prediction. New York: Springer; 2003. Tibshirani R. Regression selection and shrinkage via the Lasso. J R Stat Soc B. 1996;58:267–88. Friston KJ, Ashburner JT, Kiebel SJ, Nichols TE, Penny WD. Statistical parametric mapping: the analysis of functional brain images. London: Academic Press; 2007. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc. 1995;57:289–300. Carlin BP, Louis TA. Bayesian methods for data analysis. 3rd ed. Boca Raton, FL: CRC Press; 2008. Silver NC, Dunlap WP. Averaging correlation coefficients: should Fisher’s z transformation be used? J Appl Psychol. 1987;72:146–8. Struyfs H, Van Hecke W, Veraart J, Sijbers J, Slaets S, De Belder M, et al. Diffusion kurtosis imaging: a possible MRI biomarker for AD diagnosis? J Alzheimers Dis. 2015;48:937–48. Fellgiebel A, Wille P, Müller MJ, Winterer G, Scheurich A, Vucurevic G, et al. Ultrastructural hippocampal and white matter alterations in mild cognitive impairment: a diffusion tensor imaging study. Dement Geriatr Cogn Disord. 2004;18:101–8. Müller MJ, Greverus D, Weibrich C, Dellani PR, Scheurich A, Stoeter P, et al. Diagnostic utility of hippocampal size and mean diffusivity in amnestic MCI. Neurobiol Aging. 2007;28:398–403. Cherubini A, Péran P, Spoletini I, Di Paola M, Di Iulio F, Hagberg GE, et al. Combined volumetry and DTI in subcortical structures of mild cognitive impairment and Alzheimer’s disease patients. J Alzheimers Dis. 2010;19:1273–82. Hong YJ, Yoon B, Lim SC, Shim YS, Kim JY, Ahn KJ, et al. Microstructural changes in the hippocampus and posterior cingulate in mild cognitive impairment and Alzheimer’s disease: a diffusion tensor imaging study. Neurol Sci. 2013;34:1215–21. Nowrangi MA, Lyketsos CG, Leoutsakos JS, Oishi K, Albert M, Mori S, et al. Longitudinal, region-specific course of diffusion tensor imaging measures in mild cognitive impairment and Alzheimer’s disease. Alzheimers Dement. 2013;9:519–28. Amlien IK, Fjell AM. Diffusion tensor imaging of white matter degeneration in Alzheimer’s disease and mild cognitive impairment. Neuroscience. 2014;276:206–15. Zerbi V, Kleinnijenhuis M, Fang X, Jansen D, Veltien A, Van Asten J, et al. Gray and white matter degeneration revealed by diffusion in an Alzheimer mouse model. Neurobiol Aging. 2013;34:1440–50. Garcia-Alloza M, Robbins EM, Zhang-Nunes SX, Purcell SM, Betensky RA, Raju S, et al. Characterization of amyloid deposition in the APPswe/PS1dE9 mouse model of Alzheimer disease. Neurobiol Dis. 2006;24:516–24. Di Paola M, Phillips O, Orfei MD, Piras F, Cacciari C, Caltagirone C, et al. Corpus callosum structure is topographically correlated with the early course of cognition and depression in Alzheimer’s disease. J Alzheimers Dis. 2015;45:1097–108. Duan JH, Wang HQ, Xu J, Lin X, Chen SQ, Kang Z, et al. White matter damage of patients with Alzheimer’s disease correlated with the decreased cognitive function. Surg Radiol Anat. 2006;28:150–6. Fu JLL, Liu Y, Li YMM, Chang C, Li WB. Use of diffusion tensor imaging for evaluating changes in the microstructural integrity of white matter over 3 years in patients with amnesic-type mild cognitive impairment converting to Alzheimer’s disease. J Neuroimaging. 2014;24:343–8. Mielke MM, Kozauer NA, Chan KCG, George M, Toroney J, Zerrate M, et al. Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer’s disease. Neuroimage. 2009;46:47–55. Rémy F, Vayssière N, Saint-Aubert L, Barbeau E, Pariente J. White matter disruption at the prodromal stage of Alzheimer’s disease: Relationships with hippocampal atrophy and episodic memory performance. Neuroimage Clin. 2015;7:482–92. Rowley J, Fonov V, Wu O, Eskildsen SF, Schoemaker D, Wu L, et al. White matter abnormalities and structural hippocampal disconnections in amnestic mild cognitive impairment and Alzheimer’s disease. PLoS One. 2013;8:e74776. Salat DH, Tuch DS, van der Kouwe AJW, Greve DN, Pappu V, Lee SY, et al. White matter pathology isolates the hippocampal formation in Alzheimer’s disease. Neurobiol Aging. 2010;31:244–56. Zhang Y, Schuff N, Du AT, Rosen HJ, Kramer JH, Gorno-Tempini ML, et al. White matter damage in frontotemporal dementia and Alzheimer’s disease measured by diffusion MRI. Brain. 2009;132:2579–92. Gold BT, Zhu Z, Brown CA, Andersen AH, LaDu MJ, Tai L, et al. White matter integrity is associated with cerebrospinal fluid markers of Alzheimer’s disease in normal adults. Neurobiol Aging. 2014;35:2263–71. Genc S, Steward CE, Malpas CB, Velakoulis D, O’Brien TJ, Desmond PM. Short-term white matter alterations in Alzheimer’s disease characterized by diffusion tensor imaging. J Magn Reson Imaging. 2016;43:627–34. Mahoney CJ, Simpson IJ, Nicholas JM, Fletcher PD, Downey LE, Golden HL, et al. Longitudinal diffusion tensor imaging in frontotemporal dementia. Ann Neurol. 2015;77:33–46. Kitamura S, Kiuchi K, Taoka T, Hashimoto K, Ueda S, Yasuno F, et al. Longitudinal white matter changes in Alzheimer’s disease: a tractography-based analysis study. Brain Res. 2013;1515:12–8. Wang D, Guo ZH, Liu XH, Li YH, Wang H. Examination of hippocampal differences between Alzheimer disease, amnestic mild cognitive impairment and normal aging: diffusion kurtosis. Curr Alzheimer Res. 2015;12:80–7. Woolf NJ. Global and serial neurons form a hierarchically arranged interface proposed to underlie memory and cognition. Neuroscience. 1996;74:625–51. Whitehouse PJ, Martino AM, Antuono PG, Lowenstein PR, Coyle JT, Price DL, et al. Nicotinic acetylcholine binding sites in Alzheimer’s disease. Brain Res. 1986;371:146–51. Shimohama S, Taniguchi T, Fujiwara M, Kameyama M. Changes in nicotinic and muscarinic cholinergic receptors in Alzheimer-type dementia. J Neurochem. 1986;46:288–93.