Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-24T01:22:17.211Z Has data issue: false hasContentIssue false
  • English
  • Français

Entorhinal cortex volume in older adults: Reliability and validity considerations for three published measurement protocols

Published online by Cambridge University Press:  09 August 2010

C.C. PRICE ,
M.F. WOOD ,
C.M. LEONARD ,
S. TOWLER ,
J. WARD ,
H. MONTIJO ,
I. KELLISON ,
D. BOWERS ,
T. MONK  and
J.C. NEWCOMER
...Show all authors
C.C. PRICE*
Affiliation:
Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, Florida McKnight Brain Institute, University of Florida, Gainesville, Florida Department of Anesthesiology, College of Medicine, University of Florida, Gainesville, Florida
M.F. WOOD
Affiliation:
College of Medicine, University of Florida, Gainesville, Florida
C.M. LEONARD
Affiliation:
McKnight Brain Institute, University of Florida, Gainesville, Florida Department of Neuroscience, College of Medicine, University of Florida, Gainesville, Florida
S. TOWLER
Affiliation:
Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, Florida
J. WARD
Affiliation:
Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, Florida
H. MONTIJO
Affiliation:
Duke University School of Medicine, Durham, North Carolina
I. KELLISON
Affiliation:
Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, Florida
D. BOWERS
Affiliation:
Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, Florida McKnight Brain Institute, University of Florida, Gainesville, Florida
T. MONK
Affiliation:
Department of Anesthesiology, Duke University, Durham, North Carolina
J.C. NEWCOMER
Affiliation:
Department of Psychiatry, Washington University, St. Louis, Missouri
I. SCHMALFUSS
Affiliation:
Department of Radiology, College of Medicine, University of Florida, Gainesville, Florida Department of Radiology, North Florida South Georgia Veteran Administration, Gainesville, Florida
*
*Correspondence and reprint requests to: Catherine C. Price, Ph.D., Clinical and Health Psychology, 101 S. Newell Drive, PO Box 100165, University of Florida, Gainesville, FL 32610. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Measuring the entorhinal cortex (ERC) is challenging due to lateral border discrimination from the perirhinal cortex. From a sample of 39 nondemented older adults who completed volumetric image scans and verbal memory indices, we examined reliability and validity concerns for three ERC protocols with different lateral boundary guidelines (i.e., Goncharova, Dickerson, Stoub, & deToledo-Morrell, 2001; Honeycutt et al., 1998; Insausti et al., 1998). We used three novice raters to assess inter-rater reliability on a subset of scans (216 total ERCs), with the entire dataset measured by one rater with strong intra-rater reliability on each technique (234 total ERCs). We found moderate to strong inter-rater reliability for two techniques with consistent ERC lateral boundary endpoints (Goncharova, Honeycutt), with negligible to moderate reliability for the technique requiring consideration of collateral sulcal depth (Insausti). Left ERC and story memory associations were moderate and positive for two techniques designed to exclude the perirhinal cortex (Insausti, Goncharova), with the Insausti technique continuing to explain 10% of memory score variance after additionally controlling for depression symptom severity. Right ERC-story memory associations were nonexistent after excluding an outlier. Researchers are encouraged to consider challenges of rater training for ERC techniques and how lateral boundary endpoints may impact structure-function associations. (JINS, 2010, 16, 846–855.)

Keywords

InsaustiGoncharovaMemoryParagraph memoryStory memoryAlzheimer
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 16 , Issue 5 , September 2010 , pp. 846 - 855
Copyright
Copyright © The International Neuropsychological Society 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders DSM-IV TR fourth edition (text revision). Washington, DC: American Psychiatric Association Press.Google Scholar
Barta, P.E., Dhingra, L., Royall, R., & Schwartz, E. (1997). Improving stereological estimates for the volume of structures identified in three-dimensional arrays of spatial data. Journal of Neuroscience Methods, 75, 111–118.CrossRefGoogle ScholarPubMed
Bellgowan, P.S., Buffalo, E.A., Bodurka, J., & Martin, A. (2009). Lateralized spatial and object memory encoding in entorhinal and perirhinal cortices. Learning & Memory, 16, 433–438.CrossRefGoogle ScholarPubMed
Braak, H., & Braak, E. (1994). Morphological criteria for the recognition of Alzheimer’s disease and the distribution pattern of cortical changes related to this disorder. Neurobiology of Aging, 15, 355–360.CrossRefGoogle ScholarPubMed
Braak, H., & Braak, E. (1997). Frequency of stages of Alzheimer-related lesions in different age categories. Neurobiology of Aging, 18, 351–357.CrossRefGoogle ScholarPubMed
Bigler, E.D., Neeley, E.S., Miller, M.J., Tate, D.F., Rice, S.A., Cleavinger, H., et al. . (2004). Cerebral volume loss, cognitive deficit and neuropsychological performance: Comparative measures of brain atrophy: I. Dementia. Journal of the International Neuropsychological Society, 10, 442–452.CrossRefGoogle ScholarPubMed
Bigler, E.D., & Tate, D.F. (2001). Brain Volume, intracranial volume, and dementia. Investigative Radiology, 36, 539–546.CrossRefGoogle ScholarPubMed
Buckley, M.J. (2005). The role of the perirhinal cortex and hippocampus in learning, memory, and perception. The Quarterly Journal of Experimental Psychology, 58B, 246–268.CrossRefGoogle Scholar
Buckner, R.L., Head, D., Parker, J., Fotenos, A.F., Marcus, D., Morris, J.C., et al. . (2004). A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: Reliability and validation against manual measurement of total intracranial volume. Neuroimage, 33, 724–738.CrossRefGoogle Scholar
Charlson, M.E., Pompei, P., Ales, K.L., & MacKenzie, C.R. (1987). A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Disorders, 40, 373–383.CrossRefGoogle ScholarPubMed
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.Google Scholar
deToledo-Morrell, L., Stoub, T.R., Bulgakova, M., Wilson, R.S., Bennett, D.A., Leurgans, S., et al. . (2004). MRI derived entorhinal volume is a good predictor of conversion from MCI to AD. Neurobiology of Aging, 25, 1197–1203.CrossRefGoogle ScholarPubMed
Dickerson, B.C., Fezcko, E., Augustinack, J.C., Pacheco, J., Morris, J.C., Fischl, B., et al. . (2009). Differential effects of aging and Alzheimer’s disease on medial temporal lobe cortical thickness and surface area. Neurobiology of Aging, 30, 432–440.CrossRefGoogle ScholarPubMed
Feczko, E., Augustinack, J.C., Fischl, B., & Dickerson, B.C. (2009). An MRI-based method for measuring volume, thickness and surface area of entorhinal, perirhinal, and posterior parahippocampal cortex. Neurobiology of Aging, 30, 420–431.CrossRefGoogle ScholarPubMed
Fischl, B., Stevens, A.A., Rajendran, N., Yeo, T., Greve, D.N., Leemput, K., et al. . (2009). Predicting the location of entorhinal cortex from MRI. Neuroimage, 47, 8–17.CrossRefGoogle ScholarPubMed
Folstein, M., Folstein, S., & McHugh, P. (1975). Mini-mental state: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatry Research, 12, 189–198.CrossRefGoogle Scholar
Goncharova, I.I., Dickerson, B.C., Stoub, T.R., & deToledo-Morrell, L. (2001). MRI of human entorhinal cortex: A reliable protocol for volumetric measurement. Neurobiology of Aging, 22, 737–745.CrossRefGoogle ScholarPubMed
Honeycutt, N.A., Smith, P.D., Ayward, E., Li, Q., Chan, M., Barta, P.E., et al. . (1998). Mesial temporal lobe measurements on magnetic resonance imaging scans. Psychiatry Research, 26, 85–94.CrossRefGoogle Scholar
Insausti, R., Juottonen, K., Soininen, H., Insausti, A.M., Partanen, K., Vainio, P., et al. . (1998). MR volumetric analysis of the human entorhinal, perirhinal, and temporopolar cortices. AJNR American Journal of Neuroradiology, 19, 659–671.Google ScholarPubMed
Insausti, R., Tunon, T., Sobreviela, T., Insausti, A.M., & Gonzalo, L.M. (1995). The human entorhinal cortex: A cytoarchitectonic analysis. The Journal of Comparative Neurology, 355, 171–198.CrossRefGoogle ScholarPubMed
Jeukens, C.R., Vlooswijk, M.C., Majoie, H.J., de Krom, M.C., Aldenkamp, A.P., Hofman, P.A., et al. . (2009). Hippocampal MRI volumetry at 3 Tesla: Reliability and practical guidance. Investigative Radiology, 44, 509–517.CrossRefGoogle ScholarPubMed
Juottonen, K., Laakso, M.P., Partanen, K., & Soininen, H. (1999). Comparative MR analysis of the entorhinal cortex and hippocampus in diagnosing Alzheimer disease. AJNR American Journal of Neuroradiology, 20, 139–144.Google ScholarPubMed
Landis, J.R., & Koch, G.G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174.CrossRefGoogle ScholarPubMed
Lawton, M.P., & Brody, E.M. (1969). Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist, 9, 179–186.CrossRefGoogle ScholarPubMed
Leonard, B.W., Amaral, D.G., Squire, L.R., & Zola-Morgan, S. (1995). Transient memory impairment in monkeys with bilateral lesions of the entorhinal cortex. Journal of Neuroscience, 15, 5637–5659.CrossRefGoogle ScholarPubMed
Newcomer, J.W., Selke, G., Melson, A., Hershey, T., Craft, S., Richards, K., et al. . (1999). Decreased memory performance in healthy humans induced by stress-level cortisol treatment. Archives of General Psychiatry, 56, 527–533.CrossRefGoogle ScholarPubMed
Reitz, C., Brickman, A., Brown, T.R., Manly, J., DeCarli, C., Small, S.A., et al. . (2009). Linking hippocampal structure and function to memory performance in an aging population. Archives of Neurology, 66, 1385–1392.CrossRefGoogle Scholar
Rosen, A.C., Prull, M.W., Gabrieli, J.D., Stoub, T., O’Hara, R., Friedman, L., et al. . (2003). Differential associations between entorhinal and hippocampal volumes and memory performance in older adults. Behavioral Neuroscience, 117, 1150–1160.CrossRefGoogle ScholarPubMed
Shattuck, D.W., & Leahy, R.M. (2002). BrainSuite: An automated cortical surface identification tool. Medical Image Analysis, 6, 129–142.CrossRefGoogle ScholarPubMed
Sheikh, J.I., & Yesavage, J.A. (1986). Geriatric depression scale (GDS): Recent evidence and development of a shorter version. In Brink, T.L. (Ed.), Clinical gerontology: A guide to assessment and intervention (pp. 165–173). Binghamton, NY: Haworth Press.Google Scholar
Smith, S.M., Jenkinson, M., Woolrich, M.W., Beckmann, C.F., Behrens, T.E., Johansen-Berg, H., et al. . (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage, 23(Suppl. 1), S208–S219.CrossRefGoogle ScholarPubMed
von Gunten, A., Bouras, C., Kovari, E., Giannakopoulos, P., & Hof, P.R. (2006). Neural substrates of cognitive and behavioral deficits in atypical Alzheimer’s disease. Brain Research Reviews, 51, 176–211.CrossRefGoogle ScholarPubMed
Warner, R.M. (2008). Applied statistics: From bivariate through multivariate techniques (pp. 276–277). Los Angeles: SAGE Publications.Google Scholar
Wechsler, D. (1999). Wechsler abbreviated scale of intelligence. San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (1987). Wechsler memory scale–revised. New York, NY: Harcourt Brace Jovanovich.Google Scholar
Xu, Y., Jack, C.R. Jr., O’Brien, P.C., Kokmen, E., Smith, G.E., Ivnik, R.J., et al. . (2000). Usefulness of MRI measures of entorhinal cortex versus hippocampus in AD. Neurology, 54, 1760–1767.CrossRefGoogle ScholarPubMed
Yushkevich, P.A., Piven, J., Hazlett, H.C., Smith, R.G., Ho, S., Gee, J.C., et al. . (2006). User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. Neuroimage, 31, 1116–1128.CrossRefGoogle ScholarPubMed
Zhan, J., Brys, M., Glodzik, L., Tsui, W., Javier, E., Wegiel, J., et al. . (2009). An entorhinal cortex sulcal pattern is associated with Alzheimer’s disease. Human Brain Mapping, 30, 874–882.CrossRefGoogle ScholarPubMed
Zikjenbos, A.P., Dawant, B.M., Margolin, R.A., & Palmer, A.C. (1994). Morphometric analysis of white matter lesions in MR images: Method and validation. IEEE Transactions on Medical Imaging, 13, 716–724.Google Scholar
Zola-Morgan, S., Squire, L.R., & Amaral, D.G. (1986). Human amnesia and the medial temporal region: Enduring memory impairment following a bilateral lesion limited to field CA1 of the hippocampus. Journal of Neuroscience, 6, 2950–2967.CrossRefGoogle ScholarPubMed