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Research ArticleAdult Brain
Open Access

Computational Identification of Tumor Anatomic Location Associated with Survival in 2 Large Cohorts of Human Primary Glioblastomas

T.T. Liu, A.S. Achrol, L.A. Mitchell, W.A. Du, J.J. Loya, S.A. Rodriguez, A. Feroze, E.M. Westbroek, K.W. Yeom, J.M. Stuart, S.D. Chang, G.R. Harsh and D.L. Rubin
American Journal of Neuroradiology April 2016, 37 (4) 621-628; DOI: https://doi.org/10.3174/ajnr.A4631
T.T. Liu
aFrom the Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program (T.T.L., D.L.R.)
bDepartment of Radiology (T.T.L., L.A.M., W.A.D., K.W.Y., D.L.R.)
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A.S. Achrol
cStanford Institute for Neuro-Innovation and Translational Neurosciences (A.S.A.)
dInstitute for Stem Cell Biology and Regenerative Medicine (A.S.A.)
eDepartment of Neurosurgery (A.S.A., J.J.L., S.A.R., E.M.W., S.D.C., G.R.H.), Stanford University School of Medicine, Stanford, California
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L.A. Mitchell
bDepartment of Radiology (T.T.L., L.A.M., W.A.D., K.W.Y., D.L.R.)
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W.A. Du
bDepartment of Radiology (T.T.L., L.A.M., W.A.D., K.W.Y., D.L.R.)
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J.J. Loya
eDepartment of Neurosurgery (A.S.A., J.J.L., S.A.R., E.M.W., S.D.C., G.R.H.), Stanford University School of Medicine, Stanford, California
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S.A. Rodriguez
eDepartment of Neurosurgery (A.S.A., J.J.L., S.A.R., E.M.W., S.D.C., G.R.H.), Stanford University School of Medicine, Stanford, California
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A. Feroze
fDepartment of Neurological Surgery (A.F.), University of Washington School of Medicine, Seattle, Washington
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E.M. Westbroek
eDepartment of Neurosurgery (A.S.A., J.J.L., S.A.R., E.M.W., S.D.C., G.R.H.), Stanford University School of Medicine, Stanford, California
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K.W. Yeom
bDepartment of Radiology (T.T.L., L.A.M., W.A.D., K.W.Y., D.L.R.)
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J.M. Stuart
gBiomolecular Engineering (J.M.S.), University of California Santa Cruz, Santa Cruz, California.
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S.D. Chang
eDepartment of Neurosurgery (A.S.A., J.J.L., S.A.R., E.M.W., S.D.C., G.R.H.), Stanford University School of Medicine, Stanford, California
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G.R. Harsh IV
eDepartment of Neurosurgery (A.S.A., J.J.L., S.A.R., E.M.W., S.D.C., G.R.H.), Stanford University School of Medicine, Stanford, California
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D.L. Rubin
aFrom the Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program (T.T.L., D.L.R.)
bDepartment of Radiology (T.T.L., L.A.M., W.A.D., K.W.Y., D.L.R.)
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    Fig 1.

    An overview of the image-processing pipeline and model training and validation procedure to identify locations associated with survival. A, The image-processing pipeline is applied to both training (Stanford University Medical Center) and validation (TCGA) cohorts. B, Algorithm training identifies anatomic regions associated with survival, which is validated in the TCGA cohort. The training algorithm using the threshold-free cluster enhancement method takes as the input group labels dichotomized by survival outcome and the superimposed tumor heat map of the Stanford University Medical Center patient cohort analyzed in the image-processing pipeline; the pipeline outputs anatomic regions significantly associated with the 2 survival groups, which are used to classify the TCGA validation set into a poor survival group and a good survival group on the basis of tumor regions present or absent in the prognostic region.

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    Fig 2.

    Axial, sagittal, and coronal section views of the region associated with poor survival in the training cohort (false discovery rate, P < .05). The cluster of voxels associated with poor survival was localized in the occipitotemporal periventricular white matter in the right hemisphere (right periatrial).

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    Fig 3.

    Kaplan-Meier survival curves of patients with GBMs depict decreased overall survival in TCGA patients with an overlap (group I) versus nonoverlap (group II) with the voxels significantly associated with survival identified from the training cohort in the test cohort (log-rank test, P = .034).

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    Fig 4.

    Axial postcontrast T1-weighted images of 4 patients from group II. A, A 69-year-old man with a right parietal GBM and an overall survival of 27 months. B, A 49-year-old man with a right temporal GBM and an overall survival of 25 months. C, A 63-year-old man with a left temporal GBM and an overall survival of 21 months. D, A 36-year-old woman with a left frontal GBM, an overall survival of 6 months, and the smallest tumor volume in the group of intermediate tumors.

Tables

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    Table 1:

    Summary of clinical variables in the training cohort

    Survival Groups
    Poor (OS ≤ 11 mo)Medium (11 < OS < 17 mo)Good (OS ≥ 17 mo)
    Total No.1523863
    Median age (yr)69.057.259.5
    % Male61.260.557.1
    Median survival (mo)4.114.121.2
    Mean survival (mo)4.814.026.3
    Mean CEL volume (cm3)34.134.028.9
    STR/GTR/biopsy only (No.)53/13/8617/8/1317/36/10
    • Note:—STR indicates subtotal resection; GTR, gross total resection.

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    Table 2:

    Univariate and multivariate Cox survival analysis of clinical variables

    Univariate CoxMultivariate Cox
    HR (95% CI)P ValueHR (95% CI)P Value
    TCGA test cohorta
        Age younger than 64 yr0.19 (0.26–0.55)4.1e–7b0.36 (0.24–0.53)3.7e–7b
        Male sex1.05 (0.73–1.50).79––
        CEL tumor volume (cm3)
            Large1.68 (1.10–2.54).015b1.80 (1.18–2.75).0064b
            Intermediate––––
            Small0.90 (0.58–1.37).621.11 (0.71–1.71).65
        Right laterality0.927 (0.65–1.32).67––
        STR2.52 (0.73–8.68).14––
        Tumor location = right periatrial location1.66 (1.03–2.67).036b2.0 (1.01–2.64).045b
    Restricted set of intermediate and large tumorsc
        Age younger than 64 yr0.19 (0.26–0.55)4.1e–70.46 (0.30–0.72).00062
        Tumor location = right periatrial location1.84 (1.10–3.08).0191.87 (1.11–3.15).018
    • Note:—HR indicates hazard ratio; STR, subtotal resection.

    • ↵a Age, CEL tumor volume, and tumor location were independently significant in multivariate analysis (overall P < 3.52e–8). Surgical resection is subtotal resection or gross total resection, available for 24 cases in the TCGA test cohort.

    • ↵b P value < .05, indicating the variable is significant.

    • ↵c Tumor location remained significant in Cox analysis performed on the restricted set of intermediate and large tumors.

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American Journal of Neuroradiology: 37 (4)
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T.T. Liu, A.S. Achrol, L.A. Mitchell, W.A. Du, J.J. Loya, S.A. Rodriguez, A. Feroze, E.M. Westbroek, K.W. Yeom, J.M. Stuart, S.D. Chang, G.R. Harsh, D.L. Rubin
Computational Identification of Tumor Anatomic Location Associated with Survival in 2 Large Cohorts of Human Primary Glioblastomas
American Journal of Neuroradiology Apr 2016, 37 (4) 621-628; DOI: 10.3174/ajnr.A4631

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Computational Identification of Tumor Anatomic Location Associated with Survival in 2 Large Cohorts of Human Primary Glioblastomas
T.T. Liu, A.S. Achrol, L.A. Mitchell, W.A. Du, J.J. Loya, S.A. Rodriguez, A. Feroze, E.M. Westbroek, K.W. Yeom, J.M. Stuart, S.D. Chang, G.R. Harsh, D.L. Rubin
American Journal of Neuroradiology Apr 2016, 37 (4) 621-628; DOI: 10.3174/ajnr.A4631
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