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Research ArticleImaging

Improved Accuracy of Amyloid PET Quantification with Adaptive Template–Based Anatomic Standardization

Yuma Tsubaki, Takayoshi Kitamura, Natsumi Shimokawa, Go Akamatsu, Masayuki Sasaki and for the Japanese Alzheimer’s Disease Neuroimaging Initiative
Journal of Nuclear Medicine Technology September 2021, 49 (3) 256-261; DOI: https://doi.org/10.2967/jnmt.120.261701
Yuma Tsubaki
1Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan;
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Takayoshi Kitamura
2Department of Health Sciences, School of Medicine, Kyushu University, Fukuoka, Japan; and
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Natsumi Shimokawa
1Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan;
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Go Akamatsu
3National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
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Masayuki Sasaki
1Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan;
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  • FIGURE 1.
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    FIGURE 1.

    Workflow of PET-only quantitative evaluation method. First, PET images are anatomically standardized to either template using positive-template method, negative-template method, or adaptive-template method. Second, transformation vector used for standardization is calculated. Third, empirical PiB-prone region of interest (EPP-ROI) is inverse-transformed to individual PET image using transformation vector.

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    FIGURE 2.

    NCC results. *P < 0.05.

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    FIGURE 3.

    mcSUVR results. *P < 0.05.

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    FIGURE 4.

    mcSUVR receiver-operating-characteristic curves for each template. Areas under curve for positive template–based method, negative template–based method, and adaptive template–based method were 0.806, 0.801, and 0.815, respectively.

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    TABLE 1

    Participant Characteristics

    CharacteristicHCMCIAD
    Sex (n)
     Male303021
     Female283225
    Age (y)
     Mean ± SD66.4 ± 4.571.4 ± 5.574.4 ± 6.3
     Range60–8060–8262–84
    NINCDS-ADRDA——Probable AD
    MMSE-J
     Mean ± SD29.3 ± 1.126.7 ± 1.822.2 ± 1.8
     Range24–3024–3020–26
    CDR-J00.50.5 or 1.0
    WMS-RAbove cutoffBelow cutoffBelow cutoff
    Visually positive (n)144143
    Visually negative (n)44213
    • NINCDS-ADRDA = National Institute of Neurologic and Communicative Disorders and Alzheimer’s Disease and Related Disorders Association.

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    TABLE 2

    PET Scanners and Reconstruction Parameters for 11C-PiB PET in J-ADNI Study

    Scanner vendorScanner modelAlgorithmIterationsSubsets
    GE HealthcareAdvanceIterative (FORE + OSEM)616
    Discovery ST EliteIterative (VUE Point plus)240
    ShimadzuEminence Sophia G/XFORE + DRAMA4NA
    Eminence Sophia B/LFORE + DRAMA4NA
    Eminence G/XFORE + DRAMA4NA
    Headtome VIterative (FORE + OSEM)416
    SiemensECAT AccelIterative (FORE + OSEM)616
    ECAT Exact HR+Iterative (FORE + OSEM)416
    Biograph 6Iterative (FORE + OSEM)416
    Biograph 16Iterative (FORE + OSEM)414
    • FORE = Fourier rebinning; OSEM = ordered-subsets expectation maximization; NA = not available; DRAMA = dynamic row-action maximum-likelihood algorithm.

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    TABLE 3

    Visual Evaluation of Participants

    Visual evaluationClinical diagnosisNo. of participantsNo. of images
    Positive templateNegative templateAdaptive template
    PositiveHC145807
    MCI4162035
    AD4346038
    Total98166080
    NegativeHC4405851
    MCI2106227
    AD30468
    Total68016686
    Concordance rate59.0%41.0%89.2%
    Coefficient of associationnotnot0.80
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    TABLE 4

    Diagnostic Ability

    TemplateAUCCutoffSensitivitySpecificityAccuracy
    Positive0.8061.800.6570.8620.729
    Negative0.8011.400.750*0.7930.765
    Adaptive0.8151.400.759*0.7930.771
    • *P < 0.05 (difference from positive template).

    • AUC = area under curve.

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Journal of Nuclear Medicine Technology: 49 (3)
Journal of Nuclear Medicine Technology
Vol. 49, Issue 3
September 1, 2021
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Improved Accuracy of Amyloid PET Quantification with Adaptive Template–Based Anatomic Standardization
Yuma Tsubaki, Takayoshi Kitamura, Natsumi Shimokawa, Go Akamatsu, Masayuki Sasaki, for the Japanese Alzheimer’s Disease Neuroimaging Initiative
Journal of Nuclear Medicine Technology Sep 2021, 49 (3) 256-261; DOI: 10.2967/jnmt.120.261701

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Improved Accuracy of Amyloid PET Quantification with Adaptive Template–Based Anatomic Standardization
Yuma Tsubaki, Takayoshi Kitamura, Natsumi Shimokawa, Go Akamatsu, Masayuki Sasaki, for the Japanese Alzheimer’s Disease Neuroimaging Initiative
Journal of Nuclear Medicine Technology Sep 2021, 49 (3) 256-261; DOI: 10.2967/jnmt.120.261701
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Keywords

  • Alzheimer’s disease
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