Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter October 7, 2015

Entorhinal cortex: a good biomarker of mild cognitive impairment and mild Alzheimer’s disease

Mengxi Zhou, Feng Zhang, Li Zhao, Jin Qian and Chunbo Dong

Abstract

Entorhinal cortex (EC), thought to be the location of the earliest lesions in Alzheimer’s disease (AD), has been widely studied in recent years. With the irreversible pathological changes of AD, there is an urgent need to find biomarkers that can be used to predict the presence of the disease before it is clinically expressed. The aim of this review is to summarize and analyze recent findings that are relevant to the important role of EC in the diagnosis of mild cognitive impairment (MCI) and mild AD and to describe a range of neuroimaging techniques used to define the EC boundary. A comprehensive literature search for articles published up to May 2015 was performed. Our research highlights the finding that atrophy in EC reflects the early pathological changes of AD and can be a strong predictor of prodromal AD. The early changes in EC are a good imaging biomarker that can be used to discriminate individuals with MCI from normal control subjects. A larger degree of atrophy in EC predicts increased disease severity, and the right EC in patients with mild AD exhibited greater changes than the left side. In addition, the EC seems to have an obvious advantage over the hippocampus as a biomarker when predicting future conversion to AD in individuals with MCI, and it may be of help in following the course of disease progression. In this review, we also summarize the main differences observed between the hippocampus and the EC when differentiating diseases. These findings will hopefully provide an opportunity for the effective prevention and early treatment of AD.


Corresponding author: Chunbo Dong, Department of Neurology, The First Affiliated Hospital of Dalian Medical University, 116011 Dalian, China, e-mail:

References

Anan, F., Masaki, T., Shimomura, T., Fujiki, M., Umeno, Y., Eshima, N., Saikawa, T., and Yoshimatsu, H. (2010). Abdominal visceral fat accumulation is associated with hippocampus volume in non-dementia patients with type 2 diabetes mellitus. Neuroimage 49, 57–62.10.1016/j.neuroimage.2009.08.021Search in Google Scholar

Anan, F., Masaki, T., Shimomura, T., Fujiki, M., Umeno, Y., Eshima, N., Saikawa, T., and Yoshimatsu, H. (2011). High-sensitivity C-reactive protein is associated with hippocampus volume in nondementia patients with type 2 diabetes mellitus. Metabolism. 60, 460–466.10.1016/j.metabol.2010.04.002Search in Google Scholar

Ashburner, J. and Friston, K.J. (2000). Voxel-based morphometry – the methods. Neuroimage 11, 805–821.10.1006/nimg.2000.0582Search in Google Scholar

Blennow, K., Hampel, H., Weiner, M., and Zetterberg, H. (2010). Cerebrospinal fluid and plasma biomarkers in Alzheimer disease. Nat. Rev. Neurol. 6, 131–144.10.1038/nrneurol.2010.4Search in Google Scholar

Bobinski, M., De Leon, M.J., Convit, A., De Santi, S., Wegiel, J., Tarshish, C.Y., Saint Louis, L.A., and Wisniewski, H.M. (1999). MRI of entorhinal cortex in mild Alzheimer’s disease. Lancet 353, 38–40.10.1016/S0140-6736(05)74869-8Search in Google Scholar

Braak, H. and Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 82, 239–259.10.1007/BF00308809Search in Google Scholar

Braak, H. and Braak, E. (1995). Staging of Alzheimer’s disease-related neurofibrillary changes. Neurobiol Aging 16, 271–278; discussion 278–284.10.1016/0197-4580(95)00021-6Search in Google Scholar

Braak, H., Braak, E., Bohl, J., and Bratzke, H. (1998). Evolution of Alzheimer’s disease related cortical lesions. J. Neural Transm. 54 (Suppl.), 97–106.10.1007/978-3-7091-7508-8_9Search in Google Scholar

Braak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H., and Del Tredici, K. (2006). Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 112, 389–404.10.1007/s00401-006-0127-zSearch in Google Scholar

Braskie, M.N., Small, G.W., and Bookheimer, S.Y. (2009). Entorhinal cortex structure and functional MRI response during an associative verbal memory task. Hum. Brain Mapp. 30, 3981–3992.10.1002/hbm.20823Search in Google Scholar

Brickman, A.M., Honig, L.S., Scarmeas, N., Tatarina, O., Sanders, L., Albert, M.S., Brandt, J., Blacker, D., and Stern, Y. (2008). Measuring cerebral atrophy and white matter hyperintensity burden to predict the rate of cognitive decline in Alzheimer disease. Arch Neurol. 65, 1202–1208.10.1001/archneur.65.9.1202Search in Google Scholar

Brickman, A.M., Provenzano, F.A., Muraskin, J., Manly, J.J., Blum, S., Apa, Z., Stern, Y., Brown, T.R., Luchsinger, J.A., and Mayeux, R. (2012). Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community. Arch Neurol. 69, 1621–1627.10.1001/archneurol.2012.1527Search in Google Scholar

Burggren, A.C., Zeineh, M.M., Ekstrom, A.D., Braskie, M.N., Thompson, P.M., Small, G.W., and Bookheimer, S.Y. (2008). Reduced cortical thickness in hippocampal subregions among cognitively normal apolipoprotein E e4 carriers. Neuroimage 41, 1177–1183.10.1016/j.neuroimage.2008.03.039Search in Google Scholar

Burggren, A.C., Renner, B., Jones, M., Donix, M., Suthana, N.A., Martin-Harris, L., Ercoli, L.M., Miller, K.J., Siddarth, P., Small, G.W., et al. (2011). Thickness in entorhinal and subicular cortex predicts episodic memory decline in mild cognitive impairment. Int. J. Alzheimers Dis. 2011, 956053.10.4061/2011/956053Search in Google Scholar

Convit, A., De Leon, M.J., Tarshish, C., De Santi, S., Tsui, W., Rusinek, H., and George, A. (1997). Specific hippocampal volume reductions in individuals at risk for Alzheimer’s disease. Neurobiol. Aging 18, 131–138.10.1016/S0197-4580(97)00001-8Search in Google Scholar

de Toledo-Morrell, L., Goncharova, I., Dickerson, B., Wilson, R.S., and Bennett, D.A. (2000). From healthy aging to early Alzheimer’s disease: in vivo detection of entorhinal cortex atrophy. Ann NY Acad Sci. 911, 240–253.10.1111/j.1749-6632.2000.tb06730.xSearch in Google Scholar

de Toledo-Morrell, L., Stoub, T.R., Bulgakova, M., Wilson, R.S., Bennett, D.A., Leurgans, S., Wuu, J., and Turner, D.A. (2004). MRI-derived entorhinal volume is a good predictor of conversion from MCI to AD. Neurobiol. Aging 25, 1197–1203.10.1016/j.neurobiolaging.2003.12.007Search in Google Scholar

Devanand, D.P., Pradhaban, G., Liu, X., Khandji, A., De Santi, S., Segal, S., Rusinek, H., Pelton, G.H., Honig, L.S., Mayeux, R., et al. (2007). Hippocampal and entorhinal atrophy in mild cognitive impairment: prediction of Alzheimer disease. Neurology 68, 828–836.10.1212/01.wnl.0000256697.20968.d7Search in Google Scholar

Dickerson, B.C., Goncharova, I., Sullivan, M.P., Forchetti, C., Wilson, R.S., Bennett, D.A., Beckett, L.A., and de Toledo-Morrell, L. (2001). MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer’s disease. Neurobiol. Aging 22, 747–754.10.1016/S0197-4580(01)00271-8Search in Google Scholar

Du, A.T., Schuff, N., Amend, D., Laakso, M.P., Hsu, Y.Y., Jagust, W.J., Yaffe, K., Kramer, J.H., Reed, B., Norman, D., et al. (2001). Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 71, 441–447.10.1136/jnnp.71.4.441Search in Google Scholar

Du, A.T., Schuff, N., Zhu, X.P., Jagust, W.J., Miller, B.L., Reed, B.R., Kramer, J.H., Mungas, D., Yaffe, K., Chui, H.C., et al. (2003). Atrophy rates of entorhinal cortex in AD and normal aging. Neurology 60, 481–486.10.1212/01.WNL.0000044400.11317.ECSearch in Google Scholar

Du, A.T., Schuff, N., Kramer, J.H., Ganzer, S., Zhu, X.P., Jagust, W.J., Miller, B.L., Reed, B.R., Mungas, D., Yaffe, K., et al. (2004). Higher atrophy rate of entorhinal cortex than hippocampus in AD. Neurology 62, 422–427.10.1212/01.WNL.0000106462.72282.90Search in Google Scholar

Dubois, B., Feldman, H.H., Jacova, C., Dekosky, S.T., Barberger-Gateau, P., Cummings, J., Delacourte, A., Galasko, D., Gauthier, S., Jicha, G., et al. (2007). Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS-ADRDA criteria. Lancet Neurol. 6, 734–746.10.1016/S1474-4422(07)70178-3Search in Google Scholar

Ferri, C.P., Prince, M., Brayne, C., Brodaty, H., Fratiglioni, L., Ganguli, M., Hall, K., Hasegawa, K., Hendrie, H., Huang, Y., et al. (2005). Global prevalence of dementia: a Delphi consensus study. Lancet 366, 2112–2117.10.1016/S0140-6736(05)67889-0Search in Google Scholar

Firbank, M.J., Blamire, A.M., Teodorczuk, A., Teper, E., Burton, E.J., Mitra, D., and O’brien, J.T. (2010). High resolution imaging of the medial temporal lobe in Alzheimer’s disease and dementia with Lewy bodies. J. Alzheimers Dis. 21, 1129–1140.10.3233/JAD-2010-100138Search in Google Scholar

Fischl, B., Stevens, A.A., Rajendran, N., Yeo, B.T., Greve, D.N., Van Leemput, K., Polimeni, J.R., Kakunoori, S., Buckner, R.L., Pacheco, J., et al. (2009). Predicting the location of entorhinal cortex from MRI. Neuroimage 47, 8–17.10.1016/j.neuroimage.2009.04.033Search in Google Scholar

Frisoni, G.B., Fox, N.C., Jack, C.R., Jr., Scheltens, P., and Thompson, P.M. (2010). The clinical use of structural MRI in Alzheimer disease. Nat. Rev. Neurol. 6, 67–77.10.1038/nrneurol.2009.215Search in Google Scholar

Gomez-Isla, T., Price, J.L., Mckeel, D.W., Jr., Morris, J.C., Growdon, J.H., and Hyman, B.T. (1996). Profound loss of layer II entorhinal cortex neurons occurs in very mild Alzheimer’s disease. J. Neurosci. 16, 4491–4500.10.1523/JNEUROSCI.16-14-04491.1996Search in Google Scholar

Guzman, V.A., Carmichael, O.T., Schwarz, C., Tosto, G., Zimmerman, M.E., and Brickman, A.M. (2013). White matter hyperintensities and amyloid are independently associated with entorhinal cortex volume among individuals with mild cognitive impairment. Alzheimers Dement. 9, S124–S131.10.1016/j.jalz.2012.11.009Search in Google Scholar

Hayashi, H., Kawakatsu, S., Suzuki, A., Shibuya, Y., Kobayashi, R., Sato, C., and Otani, K. (2012). 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. 34, 328–331.10.1159/000345792Search in Google Scholar

Hirata, Y., Matsuda, H., Nemoto, K., Ohnishi, T., Hirao, K., Yamashita, F., Asada, T., Iwabuchi, S., and Samejima, H. (2005). Voxel-based morphometry to discriminate early Alzheimer’s disease from controls. Neurosci. Lett. 382, 269–274.10.1016/j.neulet.2005.03.038Search in Google Scholar

Hock, C., Golombowski, S., Muller-Spahn, F., Naser, W., Beyreuther, K., Monning, U., Schenk, D., Vigo-Pelfrey, C., Bush, A.M., Moir, R., et al. (1998). Cerebrospinal fluid levels of amyloid precursor protein and amyloid β-peptide in Alzheimer’s disease and major depression—inverse correlation with dementia severity. Eur. Neurol. 39, 111–118.10.1159/000007917Search in Google Scholar

Insausti, R., Juottonen, K., Soininen, H., Insausti, A.M., Partanen, K., Vainio, P., Laakso, M.P., and Pitkanen, A. (1998). MR volumetric analysis of the human entorhinal, perirhinal, and temporopolar cortices. Am. J. Neuroradiol. 19, 659–671.Search in Google Scholar

Ishii, K., Kawachi, T., Sasaki, H., Kono, A.K., Fukuda, T., Kojima, Y., and Mori, E. (2005). Voxel-based morphometric comparison between early- and late-onset mild Alzheimer’s disease and assessment of diagnostic performance of z score images. Am. J. Neuroradiol. 26, 333–340.Search in Google Scholar

Jack, C.R., Jr., Dickson, D.W., Parisi, J.E., Xu, Y.C., Cha, R.H., O’brien, P.C., Edland, S.D., Smith, G.E., Boeve, B.F., Tangalos, E.G., et al. (2002). Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia. Neurology 58, 750–757.10.1212/WNL.58.5.750Search in Google Scholar

Juottonen, K., Laakso, M.P., Insausti, R., Lehtovirta, M., Pitkanen, A., Partanen, K., and Soininen, H. (1998). Volumes of the entorhinal and perirhinal cortices in Alzheimer’s disease. Neurobiol. Aging 19, 15–22.10.1016/S0197-4580(98)00007-4Search in Google Scholar

Kamiyama, K., Wada, A., Sugihara, M., Kurioka, S., Hayashi, K., Hayashi, T., Yoshisako, T., Yamamoto, N., Tsuchie, Y., Yamaguchi, S., et al. (2010). Potential hippocampal region atrophy in diabetes mellitus type 2: a voxel-based morphometry VSRAD study. Jpn. J. Radiol. 28, 266–272.10.1007/s11604-009-0416-2Search in Google Scholar

Kerchner, G.A. (2011). Ultra-high field 7T MRI: a new tool for studying Alzheimer’s disease. J. Alzheimers Dis. 26 (Suppl. 3), 91–95.10.3233/JAD-2011-0023Search in Google Scholar

Kerchner, G.A., Hess, C.P., Hammond-Rosenbluth, K.E., Xu, D., Rabinovici, G.D., Kelley, D.A., Vigneron, D.B., Nelson, S.J., and Miller, B.L. (2010). Hippocampal CA1 apical neuropil atrophy in mild Alzheimer disease visualized with 7-T MRI. Neurology 75, 1381–1387.10.1212/WNL.0b013e3181f736a1Search in Google Scholar

Kerchner, G.A., Deutsch, G.K., Zeineh, M., Dougherty, R.F., Saranathan, M., and Rutt, B.K. (2012). Hippocampal CA1 apical neuropil atrophy and memory performance in Alzheimer’s disease. Neuroimage 63, 194–202.10.1016/j.neuroimage.2012.06.048Search in Google Scholar

Khan, W., Westman, E., Jones, N., Wahlund, L.O., Mecocci, P., Vellas, B., Tsolaki, M., Kloszewska, I., Soininen, H., Spenger, C., et al. (2015). Automated hippocampal subfield measures as predictors of conversion from mild cognitive impairment to Alzheimer’s disease in two independent cohorts. Brain Topogr 28, 746–759.10.1007/s10548-014-0415-1Search in Google Scholar

Killiany, R.J., Gomez-Isla, T., Moss, M., Kikinis, R., Sandor, T., Jolesz, F., Tanzi, R., Jones, K., Hyman, B.T., and Albert, M.S. (2000). Use of structural magnetic resonance imaging to predict who will get Alzheimer’s disease. Ann. Neurol. 47, 430–439.10.1002/1531-8249(200004)47:4<430::AID-ANA5>3.0.CO;2-ISearch in Google Scholar

Killiany, R.J., Hyman, B.T., Gomez-Isla, T., Moss, M.B., Kikinis, R., Jolesz, F., Tanzi, R., Jones, K., and Albert, M.S. (2002). MRI measures of entorhinal cortex vs hippocampus in preclinical AD. Neurology 58, 1188–1196.10.1212/WNL.58.8.1188Search in Google Scholar

Kirov, Ii, Hardy, C.J., Matsuda, K., Messinger, J., Cankurtaran, C.Z., Warren, M., Wiggins, G.C., Perry, N.N., Babb, J.S., Goetz, R.R., et al. (2013). In vivo 7 Tesla imaging of the dentate granule cell layer in schizophrenia. Schizophr Res. 147, 362–367.10.1016/j.schres.2013.04.020Search in Google Scholar

Kordower, J.H., Chu, Y., Stebbins, G.T., Dekosky, S.T., Cochran, E.J., Bennett, D., and Mufson, E.J. (2001). Loss and atrophy of layer II entorhinal cortex neurons in elderly people with mild cognitive impairment. Ann Neurol. 49, 202–213.10.1002/1531-8249(20010201)49:2<202::AID-ANA40>3.0.CO;2-3Search in Google Scholar

Landau, S.M., Harvey, D., Madison, C.M., Reiman, E.M., Foster, N.L., Aisen, P.S., Petersen, R.C., Shaw, L.M., Trojanowski, J.Q., Jack, C.R., Jr., et al. (2010). Comparing predictors of conversion and decline in mild cognitive impairment. Neurology 75, 230–238.10.1212/WNL.0b013e3181e8e8b8Search in Google Scholar

Lee, S.H., Coutu, J.P., Wilkens, P., Yendiki, A., Rosas, H.D., and Salat, D.H. (2015). Tract-based analysis of white matter degeneration in Alzheimer’s disease. Neuroscience 301, 79–89.10.1016/j.neuroscience.2015.05.049Search in Google Scholar

Li, X., Jiao, J., Shimizu, S., Jibiki, I., Watanabe, K., and Kubota, T. (2012). Correlations between atrophy of the entorhinal cortex and cognitive function in patients with Alzheimer’s disease and mild cognitive impairment. Psychiatry Clin. Neurosci. 66, 587–593.10.1111/pcn.12002Search in Google Scholar

Mak, E., Su, L., Williams, G.B., Watson, R., Firbank, M.J., Blamire, A.M., and O’brien, J.T. (2015). Progressive cortical thinning and subcortical atrophy in dementia with Lewy bodies and Alzheimer’s disease. Neurobiol. Aging 36, 1743–1750.10.1016/j.neurobiolaging.2014.12.038Search in Google Scholar

Manning, E.N., Barnes, J., Cash, D.M., Bartlett, J.W., Leung, K.K., Ourselin, S., and Fox, N.C. (2014). APOE epsilon4 is associated with disproportionate progressive hippocampal atrophy in AD. PLoS One 9, e97608.10.1371/journal.pone.0097608Search in Google Scholar

Marui, W., Iseki, E., Kato, M., Akatsu, H., and Kosaka, K. (2004). Pathological entity of dementia with Lewy bodies and its differentiation from Alzheimer’s disease. Acta Neuropathol. 108, 121–128.10.1007/s00401-004-0869-4Search in Google Scholar

Matsuda, H. (2007). The role of neuroimaging in mild cognitive impairment. Neuropathology 27, 570–577.10.1111/j.1440-1789.2007.00794.xSearch in Google Scholar

Mendez, M.F. (2006). The accurate diagnosis of early-onset dementia. Int. J. Psychiatry Med. 36, 401–412.10.2190/Q6J4-R143-P630-KW41Search in Google Scholar

Nakashima, Y., Morita, K., Ishii, Y., Shouji, Y., and Uchimura, N. (2010). Characteristics of exploratory eye movements in elderly people: possibility of early diagnosis of dementia. Psychogeriatrics 10, 124–130.10.1111/j.1479-8301.2010.00327.xSearch in Google Scholar

Nakata, Y., Aoki, S., Sato, N., Yasmin, H., Masutani, Y., and Ohtomo,K. (2010). Tract-specific analysis for investigation of Alzheimer disease: a brief review. Jpn. J. Radiol. 28, 494–501.10.1007/s11604-010-0460-ySearch in Google Scholar

Nho, K., Risacher, S.L., Crane, P.K., Decarli, C., Glymour, M.M., Habeck, C., Kim, S., Lee, G.J., Mormino, E., Mukherjee, S., et al. (2012). Voxel and surface-based topography of memory and executive deficits in mild cognitive impairment and Alzheimer’s disease. Brain Imaging Behav. 6, 551–567.10.1007/s11682-012-9203-2Search in Google Scholar

Pennanen, C., Kivipelto, M., Tuomainen, S., Hartikainen, P., Hanninen, T., Laakso, M.P., Hallikainen, M., Vanhanen, M., Nissinen, A., Helkala, E.L., et al. (2004). Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol. Aging 25, 303–310.10.1016/S0197-4580(03)00084-8Search in Google Scholar

Petersen, R.C. (2004). Mild cognitive impairment as a diagnostic entity. J. Intern. Med. 256, 183–194.10.1111/j.1365-2796.2004.01388.xSearch in Google Scholar

Petersen, R.C., Doody, R., Kurz, A., Mohs, R.C., Morris, J.C., Rabins,P.V., Ritchie, K., Rossor, M., Thal, L., and Winblad, B. (2001). Current concepts in mild cognitive impairment. Arch. Neurol. 58, 1985–1992.10.1001/archneur.58.12.1985Search in Google Scholar

Poldrack, R.A. (2007). Region of interest analysis for fMRI. Soc. Cogn. Affect. Neurosci. 2, 67–70.10.1093/scan/nsm006Search in Google Scholar

Price, C.C., Wood, M.F., Leonard, C.M., Towler, S., Ward, J., Montijo, H., Kellison, I., Bowers, D., Monk, T., Newcomer, J.C., et al. (2010). Entorhinal cortex volume in older adults: reliability and validity considerations for three published measurement protocols. J. Int. Neuropsychol. Soc. 16, 846–855.10.1017/S135561771000072XSearch in Google Scholar

Rogaeva, E. (2002). The solved and unsolved mysteries of the genetics of early-onset Alzheimer’s disease. Neuromolecular Med. 2, 1–10.10.1385/NMM:2:1:01Search in Google Scholar

Rosen, C., Hansson, O., Blennow, K., and Zetterberg, H. (2013). Fluid biomarkers in Alzheimer’s disease – current concepts. Mol. Neurodegener. 8, 20.10.1186/1750-1326-8-20Search in Google Scholar

Shibuya, Y., Kawakatsu, S., Hayashi, H., Kobayashi, R., Suzuki, A., Sato, C., and Otani, K. (2013). Comparison of entorhinal cortex atrophy between early-onset and late-onset Alzheimer’s disease using the VSRAD, a specific and sensitive voxel-based morphometry. Int. J. Geriatr. Psychiatry 28, 372–376.10.1002/gps.3834Search in Google Scholar

Shiino, A., Watanabe, T., Kitagawa, T., Kotani, E., Takahashi, J., Morikawa, S., and Akiguchi, I. (2008). Different atrophic patterns in early- and late-onset Alzheimer’s disease and evaluation of clinical utility of a method of regional z-score analysis using voxel-based morphometry. Dement. Geriatr. Cogn. Disord. 26, 175–186.10.1159/000151241Search in Google Scholar

Soldan, A., Pettigrew, C., Lu, Y., Wang, M.C., Selnes, O., Albert, M., Brown, T., Ratnanather, J.T., Younes, L., and Miller, M.I. (2015). Relationship of medial temporal lobe atrophy, APOE genotype, and cognitive reserve in preclinical Alzheimer’s disease. Hum. Brain Mapp. 36, 2826–2841.10.1002/hbm.22810Search in Google Scholar

Squire, L.R. and Zola, S.M. (1996). Memory, memory impairment, and the medial temporal lobe. Cold Spring Harb. Symp. Quant. Biol. 61, 185–195.10.1101/SQB.1996.061.01.021Search in Google Scholar

Stoub, T.R., Rogalski, E.J., Leurgans, S., Bennett, D.A., and de Toledo-Morrell, L. (2010). Rate of entorhinal and hippocampal atrophy in incipient and mild AD: relation to memory function. Neurobiol. Aging 31, 1089–1098.10.1016/j.neurobiolaging.2008.08.003Search in Google Scholar

Stranahan, A.M. and Mattson, M.P. (2010). Selective vulnerability of neurons in layer II of the entorhinal cortex during aging and Alzheimer’s disease. Neural Plast. 2010, 108190.10.1155/2010/108190Search in Google Scholar

Teipel, S.J., Grothe, M., Lista, S., Toschi, N., Garaci, F.G., and Hampel, H. (2013). Relevance of magnetic resonance imaging for early detection and diagnosis of Alzheimer disease. Med. Clin. North Am. 97, 399–424.10.1016/j.mcna.2012.12.013Search in Google Scholar

Testa, C., Laakso, M.P., Sabattoli, F., Rossi, R., Beltramello, A., Soininen, H., and Frisoni, G.B. (2004). A comparison between the accuracy of voxel-based morphometry and hippocampal volumetry in Alzheimer’s disease. J. Magn. Reson. Imaging 19, 274–282.10.1002/jmri.20001Search in Google Scholar

Teunissen, C.E., De Vente, J., Steinbusch, H.W., and De Bruijn, C. (2002). Biochemical markers related to Alzheimer’s dementia in serum and cerebrospinal fluid. Neurobiol. Aging 23, 485–508.10.1016/S0197-4580(01)00328-1Search in Google Scholar

Van Hoesen, G.W. and Solodkin, A. (1993). Some modular features of temporal cortex in humans as revealed by pathological changes in Alzheimer’s disease. Cereb. Cortex 3, 465–475.10.1093/cercor/3.5.465Search in Google Scholar

Varon, D., Loewenstein, D.A., Potter, E., Greig, M.T., Agron, J., Shen, Q., Zhao, W., Celeste Ramirez, M., Santos, I., Barker, W., et al. (2011). Minimal atrophy of the entorhinal cortex and hippocampus: progression of cognitive impairment. Dement. Geriatr. Cogn. Disord. 31, 276–283.10.1159/000324711Search in Google Scholar

Velayudhan, L., Proitsi, P., Westman, E., Muehlboeck, J.S., Mecocci, P., Vellas, B., Tsolaki, M., Kloszewska, I., Soininen, H., Spenger, C., et al. (2013). Entorhinal cortex thickness predicts cognitive decline in Alzheimer’s disease. J. Alzheimers Dis. 33, 755–766.10.3233/JAD-2012-121408Search in Google Scholar

Witter, M.P., Wouterlood, F.G., Naber, P.A., and Van Haeften, T. (2000). Anatomical organization of the parahippocampal-hippocampal network. Ann. N. Y. Acad. Sci. 911, 1–24.10.1111/j.1749-6632.2000.tb06716.xSearch in Google Scholar

Xu, Y., Jack, C.R., Jr., O’brien, P.C., Kokmen, E., Smith, G.E., Ivnik, R.J., Boeve, B.F., Tangalos, R.G., and Petersen, R.C. (2000). Usefulness of MRI measures of entorhinal cortex versus hippocampus in AD. Neurology 54, 1760–1767.10.1212/WNL.54.9.1760Search in Google Scholar

Yu, L., Boyle, P., Schneider, J.A., Segawa, E., Wilson, R.S., Leurgans, S., and Bennett, D.A. (2013). APOE epsilon4, Alzheimer’s disease pathology, cerebrovascular disease, and cognitive change over the years prior to death. Psychol. Aging 28, 1015–1023.10.1037/a0031642Search in Google Scholar

Zhan, J., Brys, M., Glodzik, L., Tsui, W., Javier, E., Wegiel, J., Kuchna, I., Pirraglia, E., Li, Y., Mosconi, L., et al. (2009). An entorhinal cortex sulcal pattern is associated with Alzheimer’s disease. Hum. Brain Mapp. 30, 874–882.10.1002/hbm.20549Search in Google Scholar

Received: 2015-5-12
Accepted: 2015-8-1
Published Online: 2015-10-7
Published in Print: 2016-2-1

©2016 by De Gruyter