Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Reviews in the Neurosciences

Editor-in-Chief: Huston, Joseph P.

Editorial Board: Topic, Bianca / Adeli, Hojjat / Buzsaki, Gyorgy / Crawley, Jacqueline / Crow, Tim / Gold, Paul / Holsboer, Florian / Korth, Carsten / Li, Jay-Shake / Lubec, Gert / McEwen, Bruce / Pan, Weihong / Pletnikov, Mikhail / Robbins, Trevor / Schnitzler, Alfons / Stevens, Charles / Steward, Oswald / Trojanowski, John

IMPACT FACTOR 2018: 2.157
5-year IMPACT FACTOR: 2.935

CiteScore 2017: 2.81

SCImago Journal Rank (SJR) 2017: 0.980
Source Normalized Impact per Paper (SNIP) 2017: 0.804

See all formats and pricing
More options …
Volume 27, Issue 2


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

Mengxi Zhou
  • Department of Neurology, The First Affiliated Hospital of Dalian Medical University, 116011 Dalian, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Feng Zhang
  • Department of Neurology, The First Affiliated Hospital of Dalian Medical University, 116011 Dalian, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Li Zhao
  • Department of Neurology, The First Affiliated Hospital of Dalian Medical University, 116011 Dalian, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jin Qian
  • Department of Neurology, The First Affiliated Hospital of Dalian Medical University, 116011 Dalian, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Chunbo Dong
  • Corresponding author
  • Department of Neurology, The First Affiliated Hospital of Dalian Medical University, 116011 Dalian, China
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-10-07 | DOI: https://doi.org/10.1515/revneuro-2015-0019


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.

Keywords: Alzheimer’s disease; early diagnosis; entorhinal cortex; neuroimaging; mild cognitive impairment


  • 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.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.CrossrefGoogle Scholar

  • Ashburner, J. and Friston, K.J. (2000). Voxel-based morphometry – the methods. Neuroimage 11, 805–821.CrossrefGoogle 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.CrossrefGoogle 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.Google Scholar

  • Braak, H. and Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 82, 239–259.CrossrefGoogle Scholar

  • Braak, H. and Braak, E. (1995). Staging of Alzheimer’s disease-related neurofibrillary changes. Neurobiol Aging 16, 271–278; discussion 278–284.CrossrefGoogle 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.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.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.CrossrefGoogle 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.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.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.CrossrefGoogle 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.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.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.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.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.CrossrefGoogle 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.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.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.CrossrefGoogle 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.CrossrefGoogle 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.CrossrefGoogle 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.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.CrossrefGoogle 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.CrossrefGoogle 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.CrossrefGoogle 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.CrossrefGoogle 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.CrossrefGoogle 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.CrossrefGoogle 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.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.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.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.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.CrossrefGoogle 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.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.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.CrossrefGoogle 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.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.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.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.CrossrefGoogle 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.CrossrefGoogle 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.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.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.CrossrefGoogle 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.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.CrossrefGoogle 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.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.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.Google Scholar

  • Matsuda, H. (2007). The role of neuroimaging in mild cognitive impairment. Neuropathology 27, 570–577.CrossrefGoogle Scholar

  • Mendez, M.F. (2006). The accurate diagnosis of early-onset dementia. Int. J. Psychiatry Med. 36, 401–412.CrossrefGoogle 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.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.CrossrefGoogle 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.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.Google Scholar

  • Petersen, R.C. (2004). Mild cognitive impairment as a diagnostic entity. J. Intern. Med. 256, 183–194.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.Google Scholar

  • Poldrack, R.A. (2007). Region of interest analysis for fMRI. Soc. Cogn. Affect. Neurosci. 2, 67–70.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.Google Scholar

  • Rogaeva, E. (2002). The solved and unsolved mysteries of the genetics of early-onset Alzheimer’s disease. Neuromolecular Med. 2, 1–10.Google Scholar

  • Rosen, C., Hansson, O., Blennow, K., and Zetterberg, H. (2013). Fluid biomarkers in Alzheimer’s disease – current concepts. Mol. Neurodegener. 8, 20.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.CrossrefGoogle 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.CrossrefGoogle 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.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.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.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.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.CrossrefGoogle 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.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.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.CrossrefGoogle 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.CrossrefGoogle 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.CrossrefGoogle 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.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.CrossrefGoogle 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.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.CrossrefGoogle Scholar

About the article

Corresponding author: Chunbo Dong, Department of Neurology, The First Affiliated Hospital of Dalian Medical University, 116011 Dalian, China, e-mail: dcb101@sina.com

Received: 2015-05-12

Accepted: 2015-08-01

Published Online: 2015-10-07

Published in Print: 2016-02-01

Citation Information: Reviews in the Neurosciences, Volume 27, Issue 2, Pages 185–195, ISSN (Online) 2191-0200, ISSN (Print) 0334-1763, DOI: https://doi.org/10.1515/revneuro-2015-0019.

Export Citation

©2016 by De Gruyter.Get Permission

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

Renée DeVivo, Lauren Zajac, Asim Mian, Anna Cervantes-Arslanian, Eric Steinberg, Michael L. Alosco, Jesse Mez, Robert Stern, and Ronald Killany
Journal of the International Neuropsychological Society, 2019, Volume 25, Number 08, Page 800
Ines Mahjoub, Mohamed Ali Mahjoub, and Islem Rekik
Scientific Reports, 2018, Volume 8, Number 1
Jessica Peter, Lena V. Schumacher, Verena Landerer, Ahmed Abdulkadir, Christoph P. Kaller, Jacob Lahr, and Stefan Klöppel
Journal of Alzheimer's Disease, 2017, Page 1

Comments (0)

Please log in or register to comment.
Log in