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Research ArticleHead and Neck
Open Access

Treatment Response Assessment of Head and Neck Cancers on CT Using Computerized Volume Analysis

L. Hadjiiski, S.K. Mukherji, S.K. Gujar, B. Sahiner, M. Ibrahim, E. Street, J. Moyer, F.P. Worden and H.-P. Chan
American Journal of Neuroradiology October 2010, 31 (9) 1744-1751; DOI: https://doi.org/10.3174/ajnr.A2177
L. Hadjiiski
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S.K. Mukherji
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S.K. Gujar
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B. Sahiner
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M. Ibrahim
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E. Street
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J. Moyer
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F.P. Worden
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H.-P. Chan
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  • Fig 1.
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    Fig 1.

    CT sections of a tonsil carcinoma on pre- and posttreatment CT scans. The carcinoma is necrotic on the pretreatment scan. This is also a subtle lesion (difficulty rating = 4 for the posttreatment scan) in the dataset. A and B, An axial section on the pretreatment scan (A), the automatic segmentation (white contour, B), and the reference-standard (hand-drawn) segmentation (black contour, B) superimposed on the pretreatment scan. C and D, An axial section on the posttreatment scan (C), the automatic segmentation (white contour, D), and the reference-standard segmentation (black contour, D) superimposed on the posttreatment scan. The radiologist's hand-drawn bounding box (white rectangle) used for the automatic segmentation is also shown in B and D. The lesion is shown on the best section marked by the radiologist for each scan.

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    Fig 2.

    CT sections of a heterogeneous tongue carcinoma on pre- and posttreatment CT scans. This lesion has a difficulty rating of 2. A and B, An axial section on the pretreatment scan (A), the automatic segmentation (white contour, B), and the reference-standard (hand-drawn) segmentation (black contour, B) superimposed on the pretreatment scan. C and D, An axial section on the posttreatment scan (C), the automatic segmentation (white contour, D), and the reference standard segmentation (black contour, D) superimposed on the posttreatment scan. The radiologist's hand-drawn bounding box (white rectangle) used for the automatic segmentation is also shown in B and D. The lesion is shown on the best section marked by the radiologist for each scan.

  • Fig 3.
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    Fig 3.

    Automatic-versus-manual estimates of the pretreatment volumes for the 34 primary-site tumors (correlation ICC = 0.98). A, Scatterplot. B, Bland-Altman plot. The solid line is the mean; the dashed line is ±2 SDs.

  • Fig 4.
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    Fig 4.

    Automatic-versus-manual estimates of the posttreatment volumes for the 34 primary-site tumors (correlation ICC = 0.98). A, Scatterplot. B, Bland-Altman plot. The solid line is the mean; the dashed line is ±2 SDs.

  • Fig 5.
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    Fig 5.

    Automatic-versus-manual estimates of the pre- to posttreatment volume change for the 34 primary-site tumors (correlation ICC = 0.95). A, Scatterplot. B, Bland-Altman plot. The solid line is the mean; the dashed line is ±2 SDs.

  • Fig 6.
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    Fig 6.

    Automatic-versus-manual estimates of the percentage pre- to posttreatment volume change for the 34 primary-site tumors (correlation ICC = 0.95). A, Scatterplot. B, Bland-Altman plot. The solid line is the mean; the dashed line is ±2 SDs.

Tables

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    Table 1:

    The average signed errors and average absolute errors of the automatic estimate of the percentage pre- to posttreatment volume change for the 34 primary tumors based on reading 1 and reading 2 bounding boxes

    Tumor TypeNumber of TumorsAverage Difficulty (mean, range)Reading 1Reading 2
    Signed Error (%)aAbsolute Error (%)aSigned Error (%)aAbsolute Error (%)a
    Tongue103.4, 2–5−2.5 ± 6.95.6 ± 4.41.8 ± 10.07.9 ± 6.0
    Tonsil24, 3–5−0.2 ± 5.53.9 ± 0.3−0.4 ± 14.110.0 ± 0.6
    Vallecular23.5, 2–5−5.1 ± 0.25.1 ± 0.2−8.3 ± 0.48.3 ± 0.4
    Supraglottic142, 1–3−0.9 ± 8.05.7 ± 5.5−5.4 ± 13.110.8 ± 8.8
    Epiglottic52.2, 1–3−2.8 ± 13.69.2 ± 9.4−3.6 ± 8.07.5 ± 3.1
    Hard palate13 −20.0 ± 020.0 ± 0−18.9 ± 018.9 ± 0
    Total34−2.4 ± 8.56.4 ± 5.9−3.3 ± 11.39.5 ± 6.8
    • a Mean.

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    Table 2:

    Pre- and posttreatment volumes for the 34 primary-site tumorsa

    RadiologistAutomatic
    PretreatmentPosttreatmentPretreatmentPosttreatment
    Average14.56.715.97.7
    Range2.1–55.40.4–42.02.2–61.30.6–45.1
    • a The estimated volumes (cubic centimeters) are based on the radiologists' outlined contours.

    • View popup
    Table 3:

    The average difference of box size between reading 1 and reading 2 in x-, y-, and z-dimensions

    Difference of the Box Size in DimensionSigned Difference (%)Absolute Difference (%)
    X0.0 ± 21.216.0 ± 13.7
    Y−2.1 ± 27.617.5 ± 21.3
    Z−14.1 ± 26.620.0 ± 22.4
    • View popup
    Table 4:

    Correlation between the automatic estimates obtained from the reading 1 and reading 2 bounding boxes for the 34 primary site tumors

    ICCP Valuea
    Pretreatment volume0.92.58
    Posttreatment volume0.88.86
    Pre- to posttreatment change0.89.29
    % Pre- to posttreatment change0.90.67
    • a Paired Student t test estimation.

    • View popup
    Table 5:

    The average signed errors and average absolute errors of the automatic estimate of the percentage pre- to posttreatment volume change of the necrotic and non-necrotic primary tumors based on reading 1 and reading 2 bounding boxes

    Tumor TypeNo. TumorsReading 1Reading 2
    Signed Error (%)aAbsolute Error (%)aSigned Error (%)aAbsolute Error (%)a
    Necrotic tumors10−2.5 ± 10.67.3 ± 9.6−0.8 ± 10.18.3 ± 4.8
    Non-necrotic tumors24−2.4 ± 7.76.1 ± 5.1−4.4 ± 11.110.0 ± 7.4
    P valueb0.970.610.410.52
    • a Mean.

    • b Student t test estimation.

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American Journal of Neuroradiology: 31 (9)
American Journal of Neuroradiology
Vol. 31, Issue 9
1 Oct 2010
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Treatment Response Assessment of Head and Neck Cancers on CT Using Computerized Volume Analysis
L. Hadjiiski, S.K. Mukherji, S.K. Gujar, B. Sahiner, M. Ibrahim, E. Street, J. Moyer, F.P. Worden, H.-P. Chan
American Journal of Neuroradiology Oct 2010, 31 (9) 1744-1751; DOI: 10.3174/ajnr.A2177

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Treatment Response Assessment of Head and Neck Cancers on CT Using Computerized Volume Analysis
L. Hadjiiski, S.K. Mukherji, S.K. Gujar, B. Sahiner, M. Ibrahim, E. Street, J. Moyer, F.P. Worden, H.-P. Chan
American Journal of Neuroradiology Oct 2010, 31 (9) 1744-1751; DOI: 10.3174/ajnr.A2177
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