Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70–78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a cerebrospinal fluid (CSF) expansion rate of 2.97 ± 0.07 ml/year (0.22 ± 0.04%/year). Hippocampal volume loss rate was higher than the GM and CSF global rates, 0.0114 ± 0.0004 ml/year (0.49 ± 0.04%/year). Regions of greatest GM loss were posterior inferior frontal lobe, medial parietal lobe and dorsal cerebellum. Rates of GM loss and CSF expansion were on the low end of the range of other published values, perhaps due to the relatively good health of the elder volunteers in this study. An additional smaller group of 6 subjects diagnosed with MCI at baseline were followed as well, and comparisons were made with the normal group in terms of both global and regional GM loss and CSF expansion rates. An increased rate of GM loss was found in the hippocampus bilaterally for the MCI group.
Citation: Charles D Smith, Linda J Van Eldik, Gregory A Jicha, Frederick A Schmitt, Peter T Nelson, Erin L Abner, Richard J Kryscio, Ronan R Murphy, Anders H Andersen. Brain structure changes over time in normal and mildly impaired aged persons[J]. AIMS Neuroscience, 2020, 7(2): 120-135. doi: 10.3934/Neuroscience.2020009
Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70–78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a cerebrospinal fluid (CSF) expansion rate of 2.97 ± 0.07 ml/year (0.22 ± 0.04%/year). Hippocampal volume loss rate was higher than the GM and CSF global rates, 0.0114 ± 0.0004 ml/year (0.49 ± 0.04%/year). Regions of greatest GM loss were posterior inferior frontal lobe, medial parietal lobe and dorsal cerebellum. Rates of GM loss and CSF expansion were on the low end of the range of other published values, perhaps due to the relatively good health of the elder volunteers in this study. An additional smaller group of 6 subjects diagnosed with MCI at baseline were followed as well, and comparisons were made with the normal group in terms of both global and regional GM loss and CSF expansion rates. An increased rate of GM loss was found in the hippocampus bilaterally for the MCI group.
[1] | Lockhart SN, DeCarli C (2014) Structural imaging measures of brain aging. Neuropsychol Rev 24: 271-289. doi: 10.1007/s11065-014-9268-3 |
[2] | Giorgio A, Santelli L, Tomassini V, et al. (2010) Age-related changes in grey and white matter structure throughout adulthood. Neuroimage 51: 943-951. doi: 10.1016/j.neuroimage.2010.03.004 |
[3] | Taki Y, Thyreau B, Kinomura S, et al. (2013) A longitudinal study of age- and gender-related annual rate of volume changes in regional gray matter in healthy adults. Hum Brain Mapp 34: 2292-2301. doi: 10.1002/hbm.22067 |
[4] | Madsen SK, Gutman BA, Joshi SH, et al. (2013) Mapping dynamic changes in ventricular volume onto baseline cortical surfaces in normal aging, MCI, and Alzheimer's disease. Multimodal Brain Image Anal (2013) 8159: 84-94. doi: 10.1007/978-3-319-02126-3_9 |
[5] | Fjell AM, Walhovd KB (2010) Structural brain changes in aging: courses, causes and cognitive consequences. Rev Neurosci 21: 187-221. doi: 10.1515/REVNEURO.2010.21.3.187 |
[6] | Maillet D, Rajah MN (2013) Association between prefrontal activity and volume change in prefrontal and medial temporal lobes in aging and dementia: A review. Ageing Res Rev 12: 479-489. doi: 10.1016/j.arr.2012.11.001 |
[7] | Gorbach T, Pudas S, Lundquist A, et al. (2017) Longitudinal association between hippocampus atrophy and episodic-memory decline. Neurobiol Aging 51: 167-176. doi: 10.1016/j.neurobiolaging.2016.12.002 |
[8] | Schmitt FA, Nelson PT, Abner E, et al. (2012) University of Kentucky Sanders-Brown healthy brain aging volunteers: donor characteristics, procedures and neuropathology. Curr Alzheimer Res 9: 724-733. doi: 10.2174/156720512801322591 |
[9] | McKhann G, Drachman D, Folstein M, et al. (1984) Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology 34: 939-944. doi: 10.1212/WNL.34.7.939 |
[10] | Albert MS, DeKosky ST, Dickson D, et al. (2011) The diagnosis of mild cognitive impairment 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 7: 270-279. doi: 10.1016/j.jalz.2011.03.008 |
[11] | Jicha GA, Abner EL, Schmitt FA, et al. (2012) Preclinical AD Workgroup staging: pathological correlates and potential challenges. Neurobiol Aging 33: 622 e1-622 e16. doi: 10.1016/j.neurobiolaging.2011.02.018 |
[12] | Tustison NJ, Avants BB, Cook PA, et al. (2010) N4ITK: improved N3 bias correction. IEEE Trans Med Imaging 29: 1310-1320. doi: 10.1109/TMI.2010.2046908 |
[13] | Smith CD, Johnson ES, Van Eldik LJ, et al. (2016) Peripheral (deep) but not periventricular MRI white matter hyperintensities are increased in clinical vascular dementia compared to Alzheimer's disease. Brain Behav 6: e00438. doi: 10.1002/brb3.438 |
[14] | Gudbjartsson H, Patz S (1995) The Rician distribution of noisy MRI data. Magn Reson Med 34: 910-914. doi: 10.1002/mrm.1910340618 |
[15] | Andersen AH (1996) On the Rician distribution of noisy MRI data. Magn Reson Med 36: 331-333. doi: 10.1002/mrm.1910360222 |
[16] | Ashburner J, Ridgway GR (2012) Symmetric diffeomorphic modeling of longitudinal structural MRI. Front Neurosci 6: 197. |
[17] | Tabatabaei-Jafari H, Shaw ME, Cherbuin N (2015) Cerebral atrophy in mild cognitive impairment: A systematic review with meta-analysis. Alzheimers Dement (Amst) 1: 487-504. doi: 10.1016/j.dadm.2015.11.002 |
[18] | Smith CD, Chebrolu H, Wekstein DR, et al. (2007) Age and gender effects on human brain anatomy: a voxel-based morphometric study in healthy elderly. Neurobiol Aging 28: 1075-1087. doi: 10.1016/j.neurobiolaging.2006.05.018 |
[19] | Allen JS, Bruss J, Brown CK, et al. (2005) Normal neuroanatomical variation due to age: the major lobes and a parcellation of the temporal region. Neurobiol Aging 26: 1245-1260. doi: 10.1016/j.neurobiolaging.2005.05.023 |
[20] | Bagarinao E, Watanabe H, Maesawa S, et al. (2017) An unbiased data-driven age-related structural brain parcellation for the identification of intrinsic brain volume changes over the adult lifespan. Neuroimage 169: 134-144. doi: 10.1016/j.neuroimage.2017.12.014 |
[21] | Cardenas VA, Du AT, Hardin D, et al. (2003) Comparison of methods for measuring longitudinal brain change in cognitive impairment and dementia. Neurobiol Aging 24: 537-544. doi: 10.1016/S0197-4580(02)00130-6 |
[22] | Good CD, Johnsrude IS, Ashburner J, et al. (2001) A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 14: 21-36. doi: 10.1006/nimg.2001.0786 |
[23] | Resnick SM, Pham DL, Kraut MA, et al. (2003) Longitudinal magnetic resonance imaging studies of older adults: a shrinking brain. J Neurosci 23: 3295-3301. doi: 10.1523/JNEUROSCI.23-08-03295.2003 |
[24] | Hedman AM, van Haren NE, Schnack HG, et al. (2012) Human brain changes across the life span: a review of 56 longitudinal magnetic resonance imaging studies. Hum Brain Mapp 33: 1987-2002. doi: 10.1002/hbm.21334 |
[25] | Jack CR, Weigand SD, Shiung MM, et al. (2008) Atrophy rates accelerate in amnestic mild cognitive impairment. Neurology 70: 1740-1752. doi: 10.1212/01.wnl.0000281688.77598.35 |
[26] | Resnick SM, Goldszal AF, Davatzikos C, et al. (2000) One–year age changes in MRI brain volumes in older adults. Cereb Cortex 10: 464-472. doi: 10.1093/cercor/10.5.464 |
[27] | Enzinger C, Fazekas F, Matthews PM, et al. (2005) Risk factors for progression of brain atrophy in aging: six-year follow-up of normal subjects. Neurology 64: 1704-1711. doi: 10.1212/01.WNL.0000161871.83614.BB |
[28] | Burgmans S, van Boxtel MP, Vuurman EF, et al. (2009) The prevalence of cortical gray matter atrophy may be overestimated in the healthy aging brain. Neuropsychology 23: 541-550. doi: 10.1037/a0016161 |
[29] | Sigurdsson S, Aspelund T, Forsberg L, et al. (2012) Brain tissue volumes in the general population of the elderly: the AGES-Reykjavik study. Neuroimage 59: 3862-3870. doi: 10.1016/j.neuroimage.2011.11.024 |
[30] | Pfefferbaum A, Sullivan EV (2015) Cross-sectional versus longitudinal estimates of age-related changes in the adult brain: overlaps and discrepancies. Neurobiol Aging 36: 2563-2567. doi: 10.1016/j.neurobiolaging.2015.05.005 |
[31] | Driscoll I, Davatzikos C, An Y, et al. (2009) Longitudinal pattern of regional brain volume change differentiates normal aging from MCI. Neurology 72: 1906-1913. doi: 10.1212/WNL.0b013e3181a82634 |
[32] | DeCarli C, Massaro J, Harvey D, et al. (2005) Measures of brain morphology and infarction in the framingham heart study: establishing what is normal. Neurobiol Aging 26: 491-510. doi: 10.1016/j.neurobiolaging.2004.05.004 |
[33] | Nelson PT, Head E, Schmitt FA, et al. (2011) Alzheimer's disease is not “brain aging”: neuropathological, genetic, and epidemiological human studies. Acta Neuropathol 121: 571-587. doi: 10.1007/s00401-011-0826-y |
[34] | Raz N, Lindenberger U, Rodrigue KM, et al. (2005) Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cereb Cortex 15: 1676-1689. doi: 10.1093/cercor/bhi044 |
[35] | Morra JH, Tu Z, Apostolova LG, et al. (2009) Automated mapping of hippocampal atrophy in 1-year repeat MRI data from 490 subjects with Alzheimer's disease, mild cognitive impairment, and elderly controls. Neuroimage 45: S3-15. doi: 10.1016/j.neuroimage.2008.10.043 |
[36] | Raz N, Rodrigue KM, Head D, et al. (2004) Differential aging of the medial temporal lobe: a study of a five-year change. Neurology 62: 433-438. doi: 10.1212/01.WNL.0000106466.09835.46 |
[37] | Grieve SM, Clark CR, Williams LM, et al. (2005) Preservation of limbic and paralimbic structures in aging. Hum Brain Mapp 25: 391-401. doi: 10.1002/hbm.20115 |
[38] | Fiford CM, Ridgway GR, Cash DM, et al. (2017) Patterns of progressive atrophy vary with age in Alzheimer's disease patients. Neurobiol Aging 63: 22-32. doi: 10.1016/j.neurobiolaging.2017.11.002 |
[39] | Jack CR, Petersen RC, Xu Y, et al. (1998) Rate of medial temporal lobe atrophy in typical aging and Alzheimer's disease. Neurology 51: 993-999. doi: 10.1212/WNL.51.4.993 |
[40] | Apostolova LG, Thompson PM (2008) Mapping progressive brain structural changes in early Alzheimer's disease and mild cognitive impairment. Neuropsychologia 46: 1597-1612. doi: 10.1016/j.neuropsychologia.2007.10.026 |
[41] | Guo X, Wang Z, Li K, et al. (2010) Voxel-based assessment of gray and white matter volumes in Alzheimer's disease. Neurosci Lett 468: 146-150. doi: 10.1016/j.neulet.2009.10.086 |
[42] | Byun MS, Kim SE, Park J, et al. (2015) Heterogeneity of regional brain atrophy patterns associated with distinct progression rates in Alzheimer's disease. PLoS One 10: e0142756. doi: 10.1371/journal.pone.0142756 |
[43] | Takao H, Hayashi N, Ohtomo K (2013) Effects of the use of multiple scanners and of scanner upgrade in longitudinal voxel-based morphometry studies. J Magn Reson Imaging 38: 1283-1291. doi: 10.1002/jmri.24038 |