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Research ArticleADULT BRAIN
Open Access

Predictive Utility of Marketed Volumetric Software Tools in Subjects at Risk for Alzheimer Disease: Do Regions Outside the Hippocampus Matter?

T.P. Tanpitukpongse, M.A. Mazurowski, J. Ikhena and J.R. Petrella for the Alzheimer's Disease Neuroimaging Initiative
American Journal of Neuroradiology March 2017, 38 (3) 546-552; DOI: https://doi.org/10.3174/ajnr.A5061
T.P. Tanpitukpongse
aFrom the Department of Radiology (T.P.T., M.A.M., J.R.P.), Duke University Medical Center, Durham, North Carolina
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M.A. Mazurowski
aFrom the Department of Radiology (T.P.T., M.A.M., J.R.P.), Duke University Medical Center, Durham, North Carolina
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J. Ikhena
bDuke University School of Medicine (J.I.), Durham, North Carolina.
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J.R. Petrella
aFrom the Department of Radiology (T.P.T., M.A.M., J.R.P.), Duke University Medical Center, Durham, North Carolina
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References

  1. 1.↵
    1. deToledo-Morrell L,
    2. Stoub TR,
    3. Bulgakova M, et al
    . MRI-derived entorhinal volume is a good predictor of conversion from MCI to AD. Neurobiol Aging 2004;25:1197–203 doi:10.1016/j.neurobiolaging.2003.12.007 pmid:15312965
    CrossRefPubMedWeb of Science
  2. 2.↵
    1. Fritzsche KH,
    2. Stieltjes B,
    3. Schlindwein S, et al
    . Automated MR morphometry to predict Alzheimer's disease in mild cognitive impairment. Int J Comput Assist Radiol Surg 2010;5:623–32 doi:10.1007/s11548-010-0412-0 pmid:20440655
    CrossRefPubMed
  3. 3.↵
    1. Douaud G,
    2. Menke RA,
    3. Gass A, et al
    . Brain microstructure reveals early abnormalities more than two years prior to clinical progression from mild cognitive impairment to Alzheimer's disease. J Neurosci 2013;33:2147–55 doi:10.1523/JNEUROSCI.4437-12.2013 pmid:23365250
    Abstract/FREE Full Text
  4. 4.↵
    1. Wang PN,
    2. Lirng JF,
    3. Lin KN, et al
    . Prediction of Alzheimer's disease in mild cognitive impairment: a prospective study in Taiwan. Neurobiol Aging 2006;27:1797–806 doi:10.1016/j.neurobiolaging.2005.10.002 pmid:16321457
    CrossRefPubMedWeb of Science
  5. 5.↵
    1. Eckerström C,
    2. Olsson E,
    3. Borga M, et al
    . Small baseline volume of left hippocampus is associated with subsequent conversion of MCI into dementia: the Göteborg MCI study. J Neurol Sci 2008;272:48–59 doi:10.1016/j.jns.2008.04.024 pmid:18571674
    CrossRefPubMed
  6. 6.↵
    1. Varon D,
    2. Barker W,
    3. Loewenstein D, et al
    ; Alzheimer's Disease Neuroimaging Initiative. Visual rating and volumetric measurement of medial temporal atrophy in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort: baseline diagnosis and the prediction of MCI outcome. Int J Geriatr Psychiatry 2015;30:192–200 doi:10.1002/gps.4126 pmid:24816477
    CrossRefPubMed
  7. 7.↵
    1. Jack CR Jr.,
    2. Shiung MM,
    3. Weigand SD, et al
    . Brain atrophy rates predict subsequent clinical conversion in normal elderly and amnestic MCI. Neurology 2005;65:1227–31 doi:10.1212/01.wnl.0000180958.22678.91 pmid:16247049
    Abstract/FREE Full Text
  8. 8.↵
    1. Desikan RS,
    2. Fischl B,
    3. Cabral HJ, et al
    . MRI measures of temporoparietal regions show differential rates of atrophy during prodromal AD. Neurology 2008;71:819–25 doi:10.1212/01.wnl.0000320055.57329.34 pmid:18672473
    Abstract/FREE Full Text
  9. 9.↵
    1. Devanand DP,
    2. Pradhaban G,
    3. Liu X, et al
    . Hippocampal and entorhinal atrophy in mild cognitive impairment: prediction of Alzheimer disease. Neurology 2007;68:828–36 doi:10.1212/01.wnl.0000256697.20968.d7 pmid:17353470
    Abstract/FREE Full Text
  10. 10.↵
    1. Petrella JR,
    2. Coleman RE,
    3. Doraiswamy PM
    . Neuroimaging and early diagnosis of Alzheimer disease: a look to the future. Radiology 2003;226:315–36 doi:10.1148/radiol.2262011600 pmid:12563122
    CrossRefPubMedWeb of Science
  11. 11.↵
    1. Petrella JR
    . Neuroimaging and the search for a cure for Alzheimer disease. Radiology 2013;269:671–91 doi:10.1148/radiol.13122503 pmid:24261497
    CrossRefPubMed
  12. 12.↵
    1. Liu Y,
    2. Paajanen T,
    3. Zhang Y, et al
    ; Addneuromed Consortium. Analysis of regional MRI volumes and thicknesses as predictors of conversion from mild cognitive impairment to Alzheimer's disease. Neurobiol Aging 2010;31:1375–85 doi:10.1016/j.neurobiolaging.2010.01.022 pmid:20447732
    CrossRefPubMed
  13. 13.↵
    1. Ross DE,
    2. Ochs AL,
    3. Seabaugh JM, et al
    ; Alzheimer's Disease Neuroimaging Initiative. Man versus machine: comparison of radiologists' interpretations and NeuroQuant® volumetric analyses of brain MRIs in patients with traumatic brain injury. J Neuropsychiatry Clin Neurosci 2013;25:32–39 doi:10.1176/appi.neuropsych.11120377 pmid:23487191
    CrossRefPubMed
  14. 14.↵
    1. Davatzikos C,
    2. Fan Y,
    3. Wu X, et al
    . Detection of prodromal Alzheimer's disease via pattern classification of magnetic resonance imaging. Neurobiol Aging 2008;29:514–23 doi:10.1016/j.neurobiolaging.2006.11.010 pmid:17174012
    CrossRefPubMedWeb of Science
  15. 15.↵
    1. Misra C,
    2. Fan Y,
    3. Davatzikos C
    . Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI. Neuroimage 2009;44:1415–22 doi:10.1016/j.neuroimage.2008.10.031 pmid:20594615
    CrossRefPubMedWeb of Science
  16. 16.↵
    1. Davatzikos C,
    2. Bhatt P,
    3. Shaw LM, et al
    . Prediction of MCI to AD conversion, via MRI, CSF biomarkers, and pattern classification. Neurobiol Aging 2011;32::2322.e19–27 doi:10.1016/j.neurobiolaging.2010.05.02327 pmid:20594615
    CrossRefPubMed
  17. 17.↵
    1. Vemuri P,
    2. Wiste HJ,
    3. Weigand SD, et al
    ; Alzheimer's Disease Neuroimaging Initiative. MRI and CSF biomarkers in normal, MCI, and AD subjects: predicting future clinical change. Neurology 2009;73:294–301 doi:10.1212/WNL.0b013e3181af79fb pmid:19636049
    Abstract/FREE Full Text
  18. 18.↵
    1. Plant C,
    2. Teipel SJ,
    3. Oswald A, et al
    . Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's disease. Neuroimage 2010;50:162–74 doi:10.1016/j.neuroimage.2009.11.046 pmid:19961938
    CrossRefPubMed
  19. 19.↵
    1. Fennema-Notestine C,
    2. McEvoy LK,
    3. Hagler DJ Jr.
    ; The Alzheimer's Disease Neuroimaging Initiative. Structural neuroimaging in the detection and prognosis of pre-clinical and early AD. Behav Neurol 2009;21:3–12 doi:10.1155/2009/698156 pmid:19847040
    CrossRefPubMedWeb of Science
  20. 20.↵
    1. Moradi E,
    2. Pepe A,
    3. Gaser C, et al
    ; Alzheimer's Disease Neuroimaging Initiative. Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects. Neuroimage 2015;104:398–412 doi:10.1016/j.neuroimage.2014.10.002 pmid:25312773
    CrossRefPubMed
  21. 21.↵
    1. Zhan Y,
    2. Chen K,
    3. Wu X, et al
    ; Alzheimer's Disease Neuroimaging Initiative. Identification of conversion from normal elderly cognition to Alzheimer's disease using multimodal support vector machine. J Alzheimers Dis 2015;47:1057–67 doi:10.3233/JAD-142820 pmid:26401783
    CrossRefPubMed
  22. 22.↵
    1. Adaszewski S,
    2. Dukart J,
    3. Kherif F, et al
    ; Alzheimer's Disease Neuroimaging Initiative. How early can we predict Alzheimer's disease using computational anatomy? Neurobiol Aging 2013;34:2815–26 doi:10.1016/j.neurobiolaging.2013.06.015 pmid:23890839
    CrossRefPubMed
  23. 23.↵
    1. Ahdidan J,
    2. Raji CA,
    3. DeYoe EA, et al
    . Quantitative neuroimaging software for clinical assessment of hippocampal volumes on MRI. J Alzheimers Dis 2015;49:723–32 doi:10.3233/JAD-150559 pmid:26484924
    CrossRefPubMed
  24. 24.↵
    1. Brewer JB,
    2. Magda S,
    3. Airriess C, et al
    . Fully-automated quantification of regional brain volumes for improved detection of focal atrophy in Alzheimer disease. AJNR Am J Neuroradiol 2009;30:578–80 doi:10.3174/ajnr.A1402 pmid:19112065
    Abstract/FREE Full Text
  25. 25.↵
    1. Ahdidan J,
    2. Hviid LB,
    3. Chakravarty MM, et al
    . Longitudinal MR study of brain structure and hippocampus volume in major depressive disorder. Acta Psychiatr Scand 2011;123:211–19 doi:10.1111/j.1600-0447.2010.01644.x pmid:21219263
    CrossRefPubMed
  26. 26.↵
    1. DeLong ER,
    2. DeLong DM,
    3. Clarke-Pearson DL
    . Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44:837–45 doi:10.2307/2531595 pmid:3203132
    CrossRefPubMedWeb of Science
  27. 27.↵
    1. Breiman L
    . Random forests. Machine Learning 2001;45:5–32 doi:10.1023/A:1010933404324
    CrossRefWeb of Science
  28. 28.↵
    1. Heister D,
    2. Brewer JB,
    3. Magda S, et al
    ; Alzheimer's Disease Neuroimaging Initiative. Predicting MCI outcome with clinically available MRI and CSF biomarkers. Neurology 2011;77:1619–28 doi:10.1212/WNL.0b013e3182343314 pmid:21998317
    Abstract/FREE Full Text
  29. 29.↵
    1. Risacher SL,
    2. Saykin AJ,
    3. West JD, et al
    ; Alzheimer's Disease Neuroimaging Initiative (ADNI). Baseline MRI predictors of conversion from MCI to probable AD in the ADNI cohort. Curr Alzheimer Res 2009;6:347–61 doi:10.2174/156720509788929273 pmid:19689234
    CrossRefPubMedWeb of Science
  30. 30.↵
    1. Yi HA,
    2. Moller C,
    3. Dieleman N, et al
    . Relation between subcortical grey matter atrophy and conversion from mild cognitive impairment to Alzheimer's disease. J Neurol Neurosurg Psychiatry 2016;87:425–32 doi:10.1136/jnnp-2014-309105 pmid:25904810
    Abstract/FREE Full Text
  31. 31.↵
    1. Macdonald KE,
    2. Bartlett JW,
    3. Leung KK, et al
    ; ADNI investigators. The value of hippocampal and temporal horn volumes and rates of change in predicting future conversion to AD. Alzheimer Dis Assoc Disord 2013;27:168–73 doi:10.1097/WAD.0b013e318260a79a pmid:22760170
    CrossRefPubMed
  32. 32.↵
    1. Karas G,
    2. Sluimer J,
    3. Goekoop R, et al
    . Amnestic mild cognitive impairment: structural MR imaging findings predictive of conversion to Alzheimer disease. AJNR Am J Neuroradiol 2008;29:944–49 doi:10.3174/ajnr.A0949 pmid:18296551
    Abstract/FREE Full Text
  33. 33.↵
    1. Wyman BT,
    2. Harvey DJ,
    3. Crawford K, et al
    ; Alzheimer's Disease Neuroimaging Initiative. Standardization of analysis sets for reporting results from ADNI MRI data. Alzheimers Dement 2013;9:332–37 doi:10.1016/j.jalz.2012.06.004 pmid:23110865
    CrossRefPubMedWeb of Science
  34. 34.↵
    1. Hill DL,
    2. Schwarz AJ,
    3. Isaac M, et al
    . Coalition Against Major Diseases/European Medicines Agency biomarker qualification of hippocampal volume for enrichment of clinical trials in predementia stages of Alzheimer's disease. Alzheimers Dement 2014;10:21–9.e3 doi:10.1016/j.jalz.2013.07.003 pmid:24985687
    CrossRefPubMed
  35. 35.↵
    1. Hawkins DM
    . The problem of overfitting. J Chem Inf Comput Sci 2004;44:1–12 doi:10.1021/ci0342472 pmid:14741005
    CrossRefPubMedWeb of Science
  36. 36.↵
    1. Gomar JJ,
    2. Bobes-Bascaran MT,
    3. Conejero-Goldberg C, et al
    ; Alzheimer's Disease Neuroimaging Initiative. Utility of combinations of biomarkers, cognitive markers, and risk factors to predict conversion from mild cognitive impairment to Alzheimer disease in patients in the Alzheimer's Disease Neuroimaging Initiative. Arch Gen Psychiatry 2011;68:961–69 doi:10.1001/archgenpsychiatry.2011.96 pmid:21893661
    CrossRefPubMedWeb of Science
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Cite this article
T.P. Tanpitukpongse, M.A. Mazurowski, J. Ikhena, J.R. Petrella
Predictive Utility of Marketed Volumetric Software Tools in Subjects at Risk for Alzheimer Disease: Do Regions Outside the Hippocampus Matter?
American Journal of Neuroradiology Mar 2017, 38 (3) 546-552; DOI: 10.3174/ajnr.A5061

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Predictive Utility of Marketed Volumetric Software Tools in Subjects at Risk for Alzheimer Disease: Do Regions Outside the Hippocampus Matter?
T.P. Tanpitukpongse, M.A. Mazurowski, J. Ikhena, J.R. Petrella
American Journal of Neuroradiology Mar 2017, 38 (3) 546-552; DOI: 10.3174/ajnr.A5061
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