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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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    Fig 1.

    Example of NeuroQuant (A, left) and Neuroreader (A, right) color segmentations in the same subject and hippocampal scatter (B, left) and Bland-Altman plots (B, right). Note the high correlation (r = 0.79, P < .05) of hippocampal volumetrics between software packages across all subjects and the small underestimation bias (−0.12 mL, P < .05) of NR with respect to NQ.

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    Table 1:

    Characteristics of study populationsa

    CharacteristicAll PatientsMCI (Nonconverter)MCI to AD (Converter)P Value
    No.19210785
    Age (yr)74.8 ± 7.374.7 ± 7.675.0 ± 6.9.7604
    Sex.3262
        Female75 (39)38 (36)37 (44)
        Male117 (61)69 (64)48 (56)
    Education (yr)15.7 ± 2.915.7 ± 3.015.6 ± 2.8.7637
    ADAS-13 (baseline)17.7 ± 6.415.2 ± 6.120.9 ± 5.3<.0001
    MMSE (baseline)27.1 ± 1.727.6 ± 1.726.5 ± 1.6<.0001
    • Note:—MMSE indicates Mini-Mental State Examination.

    • ↵a MCI or AD status was determined at 3-year follow-up by the ADNI criteria. Data are means. Percentages listed in parentheses are rounded to the nearest percentage.

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    Table 2:

    AUC values for different brain regions separated by software package (NQ, NR) and method of analysis (univariable-multivariable)

    FeatureAUC NQ (95% CI)AUC NR (95% CI)
    Univariable analysis
        Hippocampus0.69 (0.61–0.76)0.68 (0.60–0.76)
        Amygdala0.67 (0.59–0.74)0.65 (0.57–0.73)
        Cerebellum0.58 (0.49–0.66)0.57 (0.49–0.66)
        Putamen0.58 (0.50–0.66)0.62 (0.54–0.70)
        Thalamus0.56 (0.47–0.64)0.56 (0.48–0.64)
        Lateral ventricle0.54 (0.46–0.62)0.54 (0.46–0.62)
        Pallidum0.52 (0.43–0.60)NA
        Caudate0.51 (0.42–0.59)NA
        Cortical gray matter0.64 (0.56–0.72)NA
        Forebrain parenchyma0.62 (0.54–0.70)NA
        Inferior lateral ventricle0.60 (0.52–0.68)NA
        Temporal lobeNA0.63 (0.55–0.71)
        Parietal lobeNA0.61 (0.53–0.69)
        Frontal lobeNA0.60 (0.52–0.68)
        Occipital lobeNA0.59 (0.51–0.68)
        Ventral diencephalonNA0.51 (0.43–0.60)
    Multivariable analysis
        Logistic regression0.63 (0.55–0.71)0.65 (0.58–0.73)
        Random forest0.60 (0.52–0.68)0.62 (0.54–0.71)
    • Note:—NA indicates not applicable.

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    Table 3:

    Pearson correlation coefficients for NQ and NR volumetrics in regions with the same name

    FeaturePearson Coefficient (r)95% CIP Value
    Thalamus0.600.51–0.69<.001
    Putamen0.610.51–0.69<.001
    Lateral ventricles0.990.99–0.99<.001
    Hippocampus0.790.72–0.83<.001
    Cerebellum0.870.83–0.90<.001
    Amygdala0.710.64–0.78<.001
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American Journal of Neuroradiology: 38 (3)
American Journal of Neuroradiology
Vol. 38, Issue 3
1 Mar 2017
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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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