Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-05T01:03:35.321Z Has data issue: false hasContentIssue false

Memory Performance and Quantitative Neuroimaging Software in Mild Cognitive Impairment: A Concurrent Validity Study

Published online by Cambridge University Press:  28 April 2020

Laura Glass Umfleet*
Affiliation:
Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA
Alissa M. Butts
Affiliation:
Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA
Julie K. Janecek
Affiliation:
Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA
Katherine Reiter
Affiliation:
Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA
Mohit Agarwal
Affiliation:
Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA
Benjamin L. Brett
Affiliation:
Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA
Joseph J. Ryan
Affiliation:
School of Nutrition, Kinesiology, and Psychological Science, University of Central Missouri, Warrensburg, MO64093, USA
James Reuss
Affiliation:
Prism Clinical Imaging, Inc., 890 Elm Grove Rd #209, Elm Grove, WI53122, USA
Andrew Klein
Affiliation:
Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA
Anthony N. Correro II
Affiliation:
Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA
Malgorzata Franczak
Affiliation:
Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA
*
*Correspondence and reprint requests to: Laura Glass Umfleet, Department of Neurology, Division of Neuropsychology, Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI53226, USA. Phone: +1 414 955 0664, Fax: +1 414 955 0076. E-mail: [email protected]

Abstract

Objective:

This study examined the relationship between patient performance on multiple memory measures and regional brain volumes using an FDA-cleared quantitative volumetric analysis program – Neuroreader™.

Method:

Ninety-two patients diagnosed with mild cognitive impairment (MCI) by a clinical neuropsychologist completed cognitive evaluations and underwent MR Neuroreader™ within 1 year of testing. Select brain regions were correlated with three widely used memory tests. Regression analyses were conducted to determine if using more than one memory measures would better predict hippocampal z-scores and to explore the added value of recognition memory to prediction models.

Results:

Memory performances were most strongly correlated with hippocampal volumes than other brain regions. After controlling for encoding/Immediate Recall standard scores, statistically significant correlations emerged between Delayed Recall and hippocampal volumes (rs ranging from .348 to .490). Regression analysis revealed that evaluating memory performance across multiple memory measures is a better predictor of hippocampal volume than individual memory performances. Recognition memory did not add further predictive utility to regression analyses.

Conclusions:

This study provides support for use of MR Neuroreader™ hippocampal volumes as a clinically informative biomarker associated with memory performance, which is a critical diagnostic feature of MCI phenotype.

Type
Regular Research
Copyright
Copyright © INS. Published by Cambridge University Press, 2020

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

Ahdidan, J., Raji, C.A., DeYoe, E.A., Mathis, J., Noe, K., Rimestad, J.,…Lopez, O. (2016). Quantitative neuroimaging software for clinical assessment of hippocampal volumes on MR Imaging. Journal of Alzheimer’s Disease, 49, 723732.CrossRefGoogle ScholarPubMed
Barbeau, E.J., Ranjeva, J.P., Didic, M., Confort-Gouny, S., Felician, O., Soulier, E.,…Poncet, M. (2008). Profile of memory impairment and gray matter loss in amnestic mild cognitive impairment. Neuropsychologia, 46, 10091019.CrossRefGoogle ScholarPubMed
Baron, J., Chetelat, G., Desgranges, B., Perchey, G., Landeau, B., de la Sayette, V., & Eustache, F. (2001). In vivo mapping of gray matter loss with voxel-based morphometry in mild Alzheimer’s disease. Neuroimage, 14, 298309.CrossRefGoogle ScholarPubMed
Brandt, J. & Benedict, R.H.B. (2001). Hopkins Verbal Learning Test-Revised. Lutz, FL: Psychological Assessment Resources.Google Scholar
Bondi, M.W. & Smith, G.E. (2014). Mild cognitive impairment: A concept and diagnostic entity in need of input from neuropsychology. Journal of the International Neuropsychological Society, 20, 129134.CrossRefGoogle ScholarPubMed
Bottino, C.M, Castro, C.C., Gomes, R.L., Buchpiguel, C.A., Marchetti, R.L., & Neto, M.R. (2002). Volumetric MRI measurements can differentiate Alzheimer’s disease, mild cognitive impairment, and normal aging. International Psychogeriatrics, 14, 5972.CrossRefGoogle ScholarPubMed
Brooks, B.L., Iverson, G.L., Holdnack, J.A., & Feldman, H.H. (2008). Potential for misclassification of mild cognitive impairment: A study of memory scores on the Wechsler Memory Scale-III in healthy older adults. Journal of the International Neuropsychological Society, 14, 463478.CrossRefGoogle ScholarPubMed
Busatto, G., Garrido, G., Almeida, O., Castro, C., Camargo, C., Cid, C.,…Bottino, C.M. (2003). A voxel-based morphometry study of temporal lobe gray matter reductions in Alzheimer’s disease. Neurobiology of Aging, 24, 221231.CrossRefGoogle ScholarPubMed
Busse, A., Hensel, A., Guhne, U, Angermeyer, M.C., & Riedel-Heller, S.G. (2006). Mild cognitive impairment: Long-term course of four clinical subtypes. Neurology, 67, 21762785.CrossRefGoogle ScholarPubMed
Chetelat, G., Desgranges, B., De La Sayette, V., Viader, F., Eustache, F., & Baron, J-C. (2002). Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment. Neuroreport, 13, 19391943.CrossRefGoogle ScholarPubMed
Chetelat, G., Landeau, B., Eustache, F., Mezenge, F., Viader, F., de la Sayette, V.,…Baron, J. C. (2005). Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: A longitudinal MRI study. Neuroimage, 27, 934946.CrossRefGoogle ScholarPubMed
Clark, L.R., Delano-Wood, L., Libon, D.J., McDonald, C.R., Nation, D.A., Bangen, K.J., … Bondi, M.W. (2013). Are empirically-derived subtypes of mild cognitive impairment consistent with conventional subtypes? Journal of the International Neuropsychological Society, 19, 635645.CrossRefGoogle ScholarPubMed
deToledo-Morrell, L., Stoub, T., Bulgakova, M., Wilson, R., Bennett, D., Leurgans, S.,…Turner, D.A. (2004). MRI-derived entorhinal volume is a good predictor of conversion from MCI to AD. Neurobiology of Aging, 25, 11971203.CrossRefGoogle ScholarPubMed
DeVivo, R., Zajac, L., Mian, A., Cervantes-Arslanian, A., Steinberg, E., Alosco, M.,…Killany, R. (2019). Differentiating between healthy control participants and those with mild cognitive impairment using volumetric MRI data. JINS, 25, 800810.Google ScholarPubMed
Du, A.T., Schuff, N., Amend, D., Lasskso, M.P., Hsu, Y.Y., Jagust, W.J.,…Weiner, M.W. (2001). Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 71, 441447.CrossRefGoogle ScholarPubMed
Edmonds, E.C., Delano-Wood, L., Clark, L.R., Jak, A.J., Nation, D.A., McDonald, C.R.for the Alzheimer’s Disease Neuroimaging Initiative. (2015). Susceptibility of the conventional criteria for MCI to false positive diagnostic errors. Alzheimer’s & Dementia, 11, 415424.CrossRefGoogle ScholarPubMed
Fischer, P., Jungwirth, S., Zehetmayer, S., Weissgram, S., Hoeningschnabl, S., Gelpi, E., & Tragl, K. H. (2007). Conversion from subtypes of mild cognitive impairment to Alzheimer’s dementia. Neurology, 68, 288291.CrossRefGoogle Scholar
Gauthier, S., Reisberg, B., Zaudig, M., Petersen, R.C., Ritchie, K., Broich, K.,…Winblad, B. (2006). Mild cognitive impairment. The Lancet, 367, 12621270.CrossRefGoogle ScholarPubMed
Hirata, Y., Matsuda, H., Nemoto, K., Ohnishi, R., Hirao, K., Yamashita, F.,…Samejima, H. (2005). Voxel-based morphometry to discriminate early Alzheimer’s disease from controls. Neuroscience Letters, 382, 269274.CrossRefGoogle ScholarPubMed
Jack, C.R., Petersen, R.C., O’Brien, P.C., & Tangalos, E.G. (1992). MR-based hippocampal volumetry in the diagnosis of Alzheimer’s disease, Neurology, 42, 183188.CrossRefGoogle ScholarPubMed
Jack, C.R., Therneau, R.M., Wiste, H.J., Weigand, S.D., Knopman, D.S., Lowe, V.J….Petersen, R.C. (2016). Transition rates between amyloid and neurodegeneration biomarker states and to dementia: A population-based, longitudinal cohort study. Lancet Neurology, 15, 5664.CrossRefGoogle ScholarPubMed
Jak, A.J., Urban, S., McCauley, A., Bangen, K.J., Delano-Wood, L., Corey-Bloom, J., & Bondi, M.W. (2009). Profile of hippocampal volumes and stroke risk varies by neuropsychological definition of mild cognitive impairment. Journal of the International Neuropsychological Society, 2, 18.Google Scholar
Karas, G.B., Scheltens, P., Rombouts, S.A., Visser, P.J., van Schijndel, R.A., Fox, N.C., & Barkhof, N.C. (2004). Global and local gray matter loss in mild cognitive impairment and Alzheimer’s disease. Neuroimage, 23, 708716.CrossRefGoogle ScholarPubMed
Knopman, D.S., DeKosky, S.T., Cummings, J.L., Chui, H., Corey-Bloom, J., Relkin, N.,…Stevens, J.C. (2001). Practice parameter: Diagnosis of dementia (an evidence based review): Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology, 56, 11431153.CrossRefGoogle ScholarPubMed
Kovacevic, S., Rafii, M.S., Brewer, J.B., & the Alzheimer’s Disease Neuroimaging Initiative. (2009). High-throughput, fully-automated volumetry for prediction of MMSE and CDR decline in mild cognitive impairment. Alzheimer’s Disease & Associated Disorders, 23, 139145.CrossRefGoogle ScholarPubMed
Lange, K.L., Bondi, M.W., Salmon, D.P., Galasko, D., Delis, D.C., Thomas, R.G., & Thal, L. J. (2002). Decline in verbal memory during preclinical Alzheimer’s disease: Examination of the effect of APOE genotype. Journal of the International Neuropsychological Society, 8, 943955.CrossRefGoogle ScholarPubMed
Marra, C., Ferraccioli, M., Vita, M.G., Quaranta, D., & Gainotti, G. (2011). Patterns of cognitive decline and rates of conversion to dementia in patients with degenerative and vascular forms of MCI. Current Alzheimer Research, 8, 2431.CrossRefGoogle ScholarPubMed
Mitchell, A.J. & Shiri-Feshki, M. (2009). Rate of progression of mild cognitive impairment to dementiameta-analysis of 41 robust inception cohort studies. Acta Psychiatrica Scandinavica, 119, 252265.CrossRefGoogle Scholar
Momenan, R., Rawlings, R., Fong, G., Knutson, B., & Hommer, D. (2004). Voxel-based homogeneity probability maps of gray matter in groups: Assessing the reliability of functional effects. Neuroimage, 21, 965972.CrossRefGoogle ScholarPubMed
Nordlund, A., Rolstad, S., Hellstrom, P., Sjogren, M., Hansen, S., & Wallin, A. (2005). The Goteborg MCI study: Mild cognitive impairment is a heterogeneous condition. Journal of Neurology, Neurosurgery, and Psychiatry, 76, 14851490.CrossRefGoogle ScholarPubMed
Ochs, A.L., Ross, D.E., Zannoni, M.D., Abildskov, T.J., & Bigler, E.D. (2015). Comparison of automated brain volume measures obtained with NeuroQuant(R) and FreeSurfer. Journal of Neuroimaging, 25, 721727.CrossRefGoogle ScholarPubMed
Petersen, R.C., Smith, G.E., Waring, S.C., Ivnik, R.J., Tangalos, E.G., & Kokmen, E. (1999). Mild cognitive impairment: Clinical characterization and outcome. Archives of Neurology, 56, 303308.CrossRefGoogle ScholarPubMed
Rabin, L., Paré, N., Saykin, A., Brown, M.J., Wishart, H.A., Flashman, L.A., & Santulli, R. B. (2009). Differential memory test sensitivity for diagnosing amnestic mild cognitive impairment and predicting conversion to Alzheimer’s disease. Aging, Neuropsychology, and Cognition, 16, 357376.CrossRefGoogle ScholarPubMed
Ringman, J.M., Pope, W., & Salamon, N. (2010). Insensitivity of visual assessment of hippocampal atrophy in familial Alzheimer’s disease. Journal of Neurology, 257, 839842.CrossRefGoogle ScholarPubMed
Rombouts, S., Barkhof, F., Witter, M., & Scheltens, P. (2000). Unbiased whole-brain analysis of gray matter in Alzheimer’s disease. Neuroscience Letters, 285, 231233.CrossRefGoogle ScholarPubMed
Scahill, R.I., Schott, J.M., Stevens, J.M., Rossor, M.N., & Fox, N.C. (2002). Mapping the evolution of regional atrophy in Alzheimer’s disease: Unbiased analysis of fluidregistered serial MRI. Proceedings of the National Academy of Sciences of the United States of America, 99, 47034707.CrossRefGoogle Scholar
Schretlen, D.J., Testa, S.M., Winicki, J.M., Pearlson, G.D., & Gordon, B. (2008). Frequency and bases of abnormal performance by healthy adults on neuropsychological testing. Journal of the International Neuropsychological Society, 14, 436445.CrossRefGoogle ScholarPubMed
Sperling, R. & Johnson, K. (2013). Biomarkers of Alzheimer’s disease: Current and future applications to diagnostic criteria. Continuum, 19, 325338.Google Scholar
Squire, L.R., Stark, C.E.L., & Clark, R.E. (2004). The medial temporal lobe. Annual Review of Neuroscience, 27, 279306.CrossRefGoogle ScholarPubMed
Tabert, M.H., Manly, J.J., Liu, X., Pelton, G.H., Rosenblum, S., Jacobs, M.,…Devanand, D. P. (2006). Neuropsychological prediction of conversion to Alzheimer’s disease in patients with mild cognitive impairment. Archives of General Psychiatry , 63, 913924.CrossRefGoogle ScholarPubMed
Tanpitukpongse, T.P., Mazurowski, M.A., Ikhena, J., Petrella, J.R., & for the Alzheimer’s Disease Neuroimaging Initiative (2017). Predictive utility of marketed volumetric software tools in subjects at risk for Alzheimer’s disease: Do regions outside the hippocampus matter? AJNR, 38, 546552.CrossRefGoogle ScholarPubMed
Varon, D., Barker, W., Loewenstein, D., Greig, M., Bohorquez, A., Santos, I.,…Alzhiemer’s Disease Neuroimaging Initiative. (2015). Visual rating and volumetric measurement of medial temporal atrophy in the Alzhiemer’s Disease Neuroimaging Initiative (ADNI) cohort: Baseline diagnosis and the prediction of MCI outcome. International Journal of Geriatric Psychiatry, 30, 192200.CrossRefGoogle Scholar
Wechsler, D. (2009). Wechsler Memory Scale–Fourth Edition (4th ed.). San Antonio, TX: Pearson.Google Scholar
Whitwell, J.L., Shiung, M.M., Przybelski, S.A., Weigand, S.D., Knopman, D.S., Boeve, B.F.,…Jack, C.R. (2008). MRI patterns of atrophy associated with progression to AD in amnestic mild cognitive impairment. Neurology, 70, 512520.CrossRefGoogle ScholarPubMed
Wolf, H., Hensel, A., Kruggel, F., Riedel-Heller, S.G., Arendt, T., Wahlund, L.-O., & Gertz, H.-J. (2004). Structural correlates of mild cognitive impairment. Neurobiology of Aging, 25, 913924.CrossRefGoogle ScholarPubMed