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AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Research ArticleHead and Neck Imaging
Open Access

MRI Texture Analysis Predicts p53 Status in Head and Neck Squamous Cell Carcinoma

M. Dang, J.T. Lysack, T. Wu, T.W. Matthews, S.P. Chandarana, N.T. Brockton, P. Bose, G. Bansal, H. Cheng, J.R. Mitchell and J.C. Dort
American Journal of Neuroradiology January 2015, 36 (1) 166-170; DOI: https://doi.org/10.3174/ajnr.A4110
M. Dang
bDepartment of Radiology (M.D., J.T.L.), University of Calgary, Calgary, Alberta, Canada
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J.T. Lysack
bDepartment of Radiology (M.D., J.T.L.), University of Calgary, Calgary, Alberta, Canada
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T. Wu
eSchool of Computing, Informatics, Decision Systems Engineering (G.B., T.W.), Arizona State University, Tempe, Arizona.
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T.W. Matthews
aFrom the Section of Otolaryngology–Head and Neck Surgery (T.W.M., S.P.C., P.B., J.C.D.)
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S.P. Chandarana
aFrom the Section of Otolaryngology–Head and Neck Surgery (T.W.M., S.P.C., P.B., J.C.D.)
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N.T. Brockton
dDepartment of Population Health Research (N.T.B.), Alberta Health Services, Calgary, Alberta, Canada
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P. Bose
aFrom the Section of Otolaryngology–Head and Neck Surgery (T.W.M., S.P.C., P.B., J.C.D.)
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G. Bansal
eSchool of Computing, Informatics, Decision Systems Engineering (G.B., T.W.), Arizona State University, Tempe, Arizona.
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H. Cheng
cDepartment of Radiology (H.C., J.R.M.), Mayo Clinic College of Medicine, Scottsdale, Arizona
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J.R. Mitchell
cDepartment of Radiology (H.C., J.R.M.), Mayo Clinic College of Medicine, Scottsdale, Arizona
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J.C. Dort
aFrom the Section of Otolaryngology–Head and Neck Surgery (T.W.M., S.P.C., P.B., J.C.D.)
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  • Fig 1.
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    Fig 1.

    Sample of the FTFT-2D input data for texture analysis. A, Original DICOM MR image (T2WI). B, Region-of-interest mask of the tumor.

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    Fig 2.

    Tumors outlined on source MR images (Post-Gad T1WI) of 256 × 256 image size. The tumor in the left image is p53-negative. The tumor in the right image is p53-positive.

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    Fig 3.

    Graphic display of the average local spectrum for a p53-negative tumor (left image, black shades) and for a p53-positive tumor (right image, blue shades). The average amplitudes of ST at individual pixels were obtained by using FTFT-2D by using the same intensity range and scale for the 2 plots. Darker shades indicate higher ST amplitudes.

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    Fig 4.

    Radial ST amplitude plots for a p53-negative (black line) tumor and a p53-positive (blue line) tumor (the same tumor as in Fig 3).

Tables

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    Table 1:

    Clinical characteristicsa

    Characteristicp53-Positivep53-Negative
    Female11
    Male77
    Age (yr) (mean)56 ± 1356 ± 11
    T213
    T321
    T454
    N111
    N277
    • ↵a All P values are not significant.

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    Table 2:

    Discriminatory texture features

    Texture AttributeMRI SequenceRadial Frequency Band (cycles/mm)
    Average value of the local spectrumADC map0.189–0.231
    0.269–0.307
    0.307–0.344
    0.344–0.382
    Post-Gad T1WI0.382–0.420
    SD of the local spectrumADC map0.307–0.344
    0.496–0.533
    Post-Gad T1WI0.420–0.458
    0.458–0.496
    0.496–0.533
    Maximum value of the local spectrumADC map0.231–0.269
    0.269–0.307
    Post-Gad T1WI0.382–0.420
    0.496–0.533
    T2WI0.496–0.533
    • Note:—SD indicates standard deviation.

    • View popup
    Table 3:

    BN classification of p53 status

    TP RateFP RatePrecisionRecallF-MeasureROC Area
    p53-Positive0.6250.3750.6250.6250.6250.680
    p53-Negative0.6250.3750.6250.6250.6250.680
    Weighted average0.6250.3750.6250.6250.6250.680
    • Note:—BN indicates Bayesian network; FP, false-positive; TP, true-positive; ROC, receiver operating characteristic.

    • View popup
    Table 4:

    Discriminatory texture features

    Texture AttributeMRI SequenceRadial Frequency Band (cycles/mm)
    Average value of the local spectrumADC map0.269–0.307
    SD of the local spectrumPost-Gad T1WI0.458–0.496
    0.496–0.533
    Maximum value of the local spectrumADC map0.269–0.307
    Post-Gad T1WI0.382–0.420
    0.496–0.533
    T2WI0.496–0.533
    • View popup
    Table 5:

    BN classification results

    TP RateFP RatePrecisionRecallF-MeasureROC Areap53 Status
    p53-Positive0.8750.2500.7780.8750.8240.742Positive
    p53-Negative0.7500.1250.8570.7500.8000.742Negative
    Weighted average0.8130.1880.8170.8130.8120.742
    • Note:—BN indicates Bayesian network; FP, false-positive; ROC, receiver operating characteristic; TP, true-positive.

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M. Dang, J.T. Lysack, T. Wu, T.W. Matthews, S.P. Chandarana, N.T. Brockton, P. Bose, G. Bansal, H. Cheng, J.R. Mitchell, J.C. Dort
MRI Texture Analysis Predicts p53 Status in Head and Neck Squamous Cell Carcinoma
American Journal of Neuroradiology Jan 2015, 36 (1) 166-170; DOI: 10.3174/ajnr.A4110

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MRI Texture Analysis Predicts p53 Status in Head and Neck Squamous Cell Carcinoma
M. Dang, J.T. Lysack, T. Wu, T.W. Matthews, S.P. Chandarana, N.T. Brockton, P. Bose, G. Bansal, H. Cheng, J.R. Mitchell, J.C. Dort
American Journal of Neuroradiology Jan 2015, 36 (1) 166-170; DOI: 10.3174/ajnr.A4110
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