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Current Alzheimer Research

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ISSN (Print): 1567-2050
ISSN (Online): 1875-5828

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Research Article

Comparing Medial Temporal Atrophy Between Early-Onset Semantic Dementia and Early-Onset Alzheimer's Disease Using Voxel-Based Morphometry: A Multicenter MRI Study

Author(s): Ryota Kobayashi*, Hiroshi Hayashi, Shinobu Kawakatsu, Yuzuru Shibuya, Daichi Morioka, Makoto Ohba, Masanori Yoshioka, Kazutaka Sakamoto, Masafumi Kanoto and Koichi Otani

Volume 19, Issue 7, 2022

Published on: 07 September, 2022

Page: [503 - 510] Pages: 8

DOI: 10.2174/1567205019666220820145429

Price: $65

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Abstract

Background: Early-onset Semantic dementia (EOSD) and early-onset Alzheimer's disease (EOAD) are often difficult to clinically differentiate in the early stages of the diseases because of the overlaps of clinical symptoms such as language symptoms. We compared the degree of atrophy in medial temporal structures between the two types of dementia using the voxel-based specific regional analysis system for Alzheimer’s disease (VSRAD).

Methods: The participants included 29 (age: 61.7±4.5 years) and 39 (age: 60.2±4.9 years) patients with EOSD and EOAD, respectively. The degree of atrophy in medial temporal structures was quantified using the VSRAD for magnetic resonance imaging data. Receiver operating characteristic (ROC) analysis was performed to distinguish patients with EOSD and EOAD using the mean Z score (Z-score) in bilateral medial temporal structures and the absolute value (laterality score) of the laterality of Z-score (| right–left |) for indicating the degree of asymmetrical atrophy in medial temporal structures.

Results: The EOSD group had significantly higher Z and laterality scores than the EOAD group (Zscores: mean ± standard deviation: 3.74±1.05 vs. 1.56±0.81, respectively; P<0.001; laterality score: mean ± standard deviation: 2.35±1.23 vs. 0.68±0.51, respectively; P<0.001). In ROC analysis, the sensitivity and specificity to differentiate EOSD from EOAD by a Z-score of 2.29 were 97% and 85%, respectively and by the laterality score of 1.05 were 93% and 85%, respectively.

Conclusion: EOSD leads to more severe and asymmetrical atrophy in medial temporal structures than EOAD. The VSRAD may be useful to distinguish between these dementias that have several clinically similar symptoms.

Keywords: Alzheimer’s disease, early-onset dementia, magnetic resonance, imaging semantic dementia, semantic variant, primary progressive aphasia, voxel-based morphometry

« Previous Next »
[1]
Ramos EM, Dokuru DR, Van Berlo V, et al. Genetic screening of a large series of North American sporadic and familial frontotemporal dementia cases. Alzheimers Dement 2020; 16(1): 118-30.
[http://dx.doi.org/10.1002/alz.12011] [PMID: 31914217]
[2]
Awata S, Edahiro A, Arai T, et al. Prevalence and subtype distribution of early onset dementia in Japan. Psychogeriatrics 2020; 20(6): 817-23.
[http://dx.doi.org/10.1111/psyg.12596] [PMID: 32815229]
[3]
Neary D, Snowden JS, Gustafson L, et al. Frontotemporal lobar degeneration: A consensus on clinical diagnostic criteria. Neurology 1998; 51(6): 1546-54.
[http://dx.doi.org/10.1212/WNL.51.6.1546] [PMID: 9855500]
[4]
Mackenzie IR, Neumann M, Bigio EH, et al. Nomenclature and nosology for neuropathologic subtypes of frontotemporal lobar degeneration: An update. Acta Neuropathol 2010; 119(1): 1-4.
[http://dx.doi.org/10.1007/s00401-009-0612-2] [PMID: 19924424]
[5]
Bergeron D, Gorno ML, Rabinovici GD, et al. Prevalence of amyloid-β pathology in distinct variants of primary progressive aphasia. Ann Neurol 2018; 84(5): 729-40.
[http://dx.doi.org/10.1002/ana.25333] [PMID: 30255971]
[6]
Spinelli EG, Mandelli ML, Miller ZA, et al. Typical and atypical pathology in primary progressive aphasia variants. Ann Neurol 2017; 81(3): 430-43.
[http://dx.doi.org/10.1002/ana.24885] [PMID: 28133816]
[7]
Dubois B, Feldman HH, Jacova C, et al. Research criteria for the diagnosis of Alzheimer’s disease: Revising the NINCDS-ADRDA criteria. Lancet Neurol 2007; 6(8): 734-46.
[http://dx.doi.org/10.1016/S1474-4422(07)70178-3] [PMID: 17616482]
[8]
Cummings JL. Alzheimer’s disease. N Engl J Med 2004; 351(1): 56-67.
[http://dx.doi.org/10.1056/NEJMra040223] [PMID: 15229308]
[9]
Török N, Tanaka M, Vécsei L. Searching for peripheral biomarkers in neurodegenerative diseases: The tryptophan kynurenine metabolic pathway. Int J Mol Sci 2020; 21(24): 9338.
[http://dx.doi.org/10.3390/ijms21249338] [PMID: 33302404]
[10]
Hyman BT, Trojanowski JQ. Consensus recommendations for the postmortem diagnosis of Alzheimer disease from the national institute on aging and the reagan institute working group on diagnostic criteria for the neuropathological assessment of Alzheimer disease. J Neuropathol Exp Neurol 1997; 56(10): 1095-7.
[http://dx.doi.org/10.1097/00005072-199710000-00002] [PMID: 9329452]
[11]
Jack CR, Bernstein MA, Borowski BJ, et al. Update on the magnetic resonance imaging core of the Alzheimer’s disease neuroimaging initiative. Alzheimers Dement 2010; 6(3): 212-20.
[http://dx.doi.org/10.1016/j.jalz.2010.03.004] [PMID: 20451869]
[12]
Planche V, Manjon JV, Mansencal B, et al. Structural progression of Alzheimer’s disease over decades: The MRI staging scheme. Brain Commun 2022; 4(3): 109.
[http://dx.doi.org/10.1093/braincomms/fcac109]
[13]
Kawakatsu S, Kobayashi R, Hayashi H. Typical and atypical appearance of early onset Alzheimer’s disease: A clinical, neuroimaging and neuropathological study. Neuropathology 2017; 37(2): 150-73.
[http://dx.doi.org/10.1111/neup.12364] [PMID: 28093855]
[14]
Battaglia S, Garofalo S, Pellegrino G. Context dependent extinction of threat memories: Influences of healthy aging. Sci Rep 2018; 8: 12592.
[http://dx.doi.org/10.1038/s41598-018-31000-9]
[15]
Battaglia S, Fabius JH, Moravkova K, Fracasso A, Borgomaneri S. The neurobiological correlates of gaze perception in healthy individuals and neurologic patients. Biomedicines 2022; 10(3): 627.
[http://dx.doi.org/10.3390/biomedicines10030627] [PMID: 35327431]
[16]
Koedam EL, Lauffer V, van der Vlies AE, van der Flier WM, Scheltens P, Pijnenburg YA. Early versus late onset Alzheimer’s disease: More than age alone. J Alzheimers Dis 2010; 19(4): 1401-8.
[http://dx.doi.org/10.3233/JAD-2010-1337] [PMID: 20061618]
[17]
Montembeault M, Brambati SM, Joubert S, et al. Naming unique entities in the semantic variant of primary progressive aphasia and Alzheimer’s disease: Towards a better understanding of the semantic impairment. Neuropsychologia 2017; 95: 11-20.
[http://dx.doi.org/10.1016/j.neuropsychologia.2016.12.009] [PMID: 27939367]
[18]
Chan D, Fox NC, Scahill RI, et al. Patterns of temporal lobe atrophy in semantic dementia and Alzheimer’s disease. Ann Neurol 2001; 49(4): 433-42.
[http://dx.doi.org/10.1002/ana.92] [PMID: 11310620]
[19]
Eikelboom WS, Janssen N, Jiskoot LC, Berg E, Roelofs A, Kessels RPC. Episodic and working memory function in primary progressive Aphasia: A meta analysis. Neurosci Biobehav Rev 2018; 92: 243-54.
[http://dx.doi.org/10.1016/j.neubiorev.2018.06.015] [PMID: 29928907]
[20]
Gorno ML, Hillis AE, Weintraub S, et al. Classification of primary progressive aphasia and its variants. Neurology 2011; 76(11): 1006-14.
[http://dx.doi.org/10.1212/WNL.0b013e31821103e6] [PMID: 21325651]
[21]
Falgàs N, Balasa M, Bargalló N, et al. Diagnostic accuracy of MRI visual rating scales in the diagnosis of early onset cognitive impairment. J Alzheimers Dis 2020; 73(4): 1575-83.
[http://dx.doi.org/10.3233/JAD-191167] [PMID: 31958089]
[22]
Galton CJ, Patterson K, Graham K, et al. Differing patterns of temporal atrophy in Alzheimer’s disease and semantic dementia. Neurology 2001; 57(2): 216-25.
[http://dx.doi.org/10.1212/WNL.57.2.216] [PMID: 11468305]
[23]
Galton CJ, Gomez AB, Antoun N, et al. Temporal lobe rating scale: Application to Alzheimer’s disease and frontotemporal dementia. J Neurol Neurosurg Psychiatry 2001; 70(2): 165-73.
[http://dx.doi.org/10.1136/jnnp.70.2.165] [PMID: 11160463]
[24]
Whitwell JL, Sampson EL, Watt HC, Harvey RJ, Rossor MN, Fox NC. A volumetric magnetic resonance imaging study of the amygdala in frontotemporal lobar degeneration and Alzheimer’s disease. Dement Geriatr Cogn Disord 2005; 20(4): 238-44.
[http://dx.doi.org/10.1159/000087343] [PMID: 16088140]
[25]
Pol LA, Hensel A, Flier WM, et al. Hippocampal atrophy on MRI in frontotemporal lobar degeneration and Alzheimer’s disease. J Neurol Neurosurg Psychiatry 2006; 77(4): 439-42.
[http://dx.doi.org/10.1136/jnnp.2005.075341] [PMID: 16306153]
[26]
Barnes J, Whitwell JL, Frost C, Josephs KA, Rossor M, Fox NC. Measurements of the amygdala and hippocampus in pathologically confirmed Alzheimer’s disease and frontotemporal lobar degeneration. Arch Neurol 2006; 63(10): 1434-9.
[http://dx.doi.org/10.1001/archneur.63.10.1434] [PMID: 17030660]
[27]
Matsuda H, Mizumura S, Nemoto K, et al. Automatic voxel based morphometry of structural MRI by SPM8 plus diffeomorphic anatomic registration through exponentiated lie algebra improves the diagnosis of probable Alzheimer’s disease. AJNR Am J Neuroradiol 2012; 33(6): 1109-14.
[http://dx.doi.org/10.3174/ajnr.A2935] [PMID: 22300935]
[28]
Matsuda H. Voxel based morphometry of brain MRI in normal aging and Alzheimer’s disease. Aging Dis 2013; 4(1): 29-37.
[PMID: 23423504]
[29]
Hayashi H, Kawakatsu S, Suzuki A, et al. Application of the VSRAD, a specific and sensitive voxel-based morphometry, to comparison of entorhinal cortex atrophy between dementia with Lewy bodies and Alzheimer’s disease. Dement Geriatr Cogn Disord 2012; 34(5-6): 328-31.
[http://dx.doi.org/10.1159/000345792] [PMID: 23208522]
[30]
Patrizia CU. S Food and Drug Administration FDA’s decision to approve new treatment for Alzheimer’s Disease US Food and Drug 2021 Available from: https://www.fda.gov/drugs/news-events-human-drugs/fdas-decision-approve-new-treatment-alzheimers-disease
[31]
McKhann GM, Knopman DS, Chertkow H, 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(3): 263-9.
[http://dx.doi.org/10.1016/j.jalz.2011.03.005] [PMID: 21514250]
[32]
Hayashi H, Kobayashi R, Kawakatsu S, Morioka D, Otani K. Utility of easy Z score imaging system assisted SPECT in detecting onset age dependent decreases in cerebral blood flow in the posterior cingulate cortex, precuneus, and parietal lobe in Alzheimer’s disease with amyloid accumulation. Dement Geriatr Cogn Disord Extra 2020; 10(2): 63-8.
[http://dx.doi.org/10.1159/000507654] [PMID: 32774341]
[33]
Murray ME, Lowe VJ, Graff NR, et al. Clinicopathologic and 11C Pittsburgh compound B implications of thal amyloid phase across the Alzheimer’s disease spectrum. Brain 2015; 138(5): 1370-81.
[http://dx.doi.org/10.1093/brain/awv050] [PMID: 25805643]
[34]
Hayashi H, Kobayashi R, Kawakatsu S, Ohba M, Morioka D, Otani K. Comparison of the decreases in regional cerebral blood flow in the posterior cingulate cortex, precuneus, and parietal lobe between suspected non Alzheimer’s disease pathophysiology and Alzheimer’s disease. Psychogeriatrics 2021; 21(5): 716-21.
[http://dx.doi.org/10.1111/psyg.12729] [PMID: 34101304]
[35]
Ulugut EH, Groot C, Heilbron R, et al. A clinical radiological framework of the right temporal variant of frontotemporal dementia. Brain 2020; 143(9): 2831-43.
[http://dx.doi.org/10.1093/brain/awaa225] [PMID: 32830218]
[36]
Wachinger C, Salat DH, Weiner M, Reuter M. Whole brain analysis reveals increased neuroanatomical asymmetries in dementia for hippocampus and amygdala. Brain 2016; 139(12): 3253-66.
[http://dx.doi.org/10.1093/brain/aww243] [PMID: 27913407]
[37]
Jeremic D, Jiménez DL, Navarro LJD. Past, present and future of therapeutic strategies against amyloid-β peptides in Alzheimer’s disease: A systematic review. Ageing Res Rev 2021; 72: 101496.
[http://dx.doi.org/10.1016/j.arr.2021.101496] [PMID: 34687956]
[38]
Young JJ, Lavakumar M, Tampi D, Balachandran S, Tampi RR. Frontotemporal dementia: Latest evidence and clinical implications. Ther Adv Psychopharmacol 2018; 8(1): 33-48.
[http://dx.doi.org/10.1177/2045125317739818] [PMID: 29344342]
[39]
Ferreira D, Nordberg A, Westman E. Biological subtypes of Alzheimer disease: A systematic review and meta analysis. Neurology 2020; 94(10): 436-48.
[http://dx.doi.org/10.1212/WNL.0000000000009058] [PMID: 32047067]
[40]
Lesman SOH, La JR, Iaccarino L, et al. Diagnostic accuracy of amyloid versus 18f-fluorodeoxyglucose positron emission tomography in autopsy confirmed dementia. Ann Neurol 2021; 89(2): 389-401.
[http://dx.doi.org/10.1002/ana.25968] [PMID: 33219525]
[41]
La JR, Perrotin A, Sayette V, et al. Hippocampal subfield volumetry in mild cognitive impairment, Alzheimer’s disease and semantic dementia. Neuroimage Clin 2013; 3: 155-62.
[http://dx.doi.org/10.1016/j.nicl.2013.08.007] [PMID: 24179859]
[42]
Battaglia S, Harrison BJ, Fullana MA. Does the human ventromedial prefrontal cortex support fear learning, fear extinction or both? A commentary on subregional contributions. Mol Psychiatry 2022; 27(2): 784-6.
[http://dx.doi.org/10.1038/s41380-021-01326-4] [PMID: 34667263]
[43]
Battaglia S. Neurobiological advances of learned fear in humans. Adv Clin Exp Med 2022; 31(3): 217-21.
[http://dx.doi.org/10.17219/acem/146756] [PMID: 35195964]
[44]
Serra L, De Simone MS, Fadda L, et al. Memory for public events in amnestic mild cognitive impairment: The role of hippocampus and ventro medial prefrontal cortex. J Neuropsychol 2022; 16(1): 131-48.
[http://dx.doi.org/10.1111/jnp.12259] [PMID: 34170071]
[45]
Schlecht M, Jayachandran M, Rasch GE, Allen TA. Dual projecting cells linking thalamic and cortical communication routes between the medial prefrontal cortex and hippocampus. Neurobiol Learn Mem 2022; 188: 107586.
[http://dx.doi.org/10.1016/j.nlm.2022.107586] [PMID: 35045320]
[46]
Ossenkoppele R, Jansen WJ, Rabinovici GD, et al. Prevalence of amyloid PET positivity in dementia syndromes: A meta analysis. JAMA 2015; 313(19): 1939-49.
[http://dx.doi.org/10.1001/jama.2015.4669] [PMID: 25988463]
[47]
Goto M, Abe O, Aoki S, et al. Diffeomorphic anatomical registration through exponentiated lie algebra provides reduced effect of scanner for cortex volumetry with atlas based method in healthy subjects. Neuroradiology 2013; 55(7): 869-75.
[http://dx.doi.org/10.1007/s00234-013-1193-2] [PMID: 23619702]

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