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Research ArticleAdult Brain

Performance and Predictive Value of a User-Independent Platform for CT Perfusion Analysis: Threshold-Derived Automated Systems Outperform Examiner-Driven Approaches in Outcome Prediction of Acute Ischemic Stroke

S. Dehkharghani, R. Bammer, M. Straka, L.S. Albin, O. Kass-Hout, J.W. Allen, S. Rangaraju, D. Qiu, M.J. Winningham and F. Nahab
American Journal of Neuroradiology August 2015, 36 (8) 1419-1425; DOI: https://doi.org/10.3174/ajnr.A4363
S. Dehkharghani
aFrom the Departments of Radiology and Imaging Sciences (S.D., L.S.A., J.W.A., D.Q.)
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R. Bammer
cDepartment of Radiology (R.B.), Stanford University Hospital, Stanford, California
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M. Straka
dInstitut für Radiologie und Nuklearmedizin (M.S.), Kantonsspital Winterthur, Winterthur, Switzerland
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L.S. Albin
aFrom the Departments of Radiology and Imaging Sciences (S.D., L.S.A., J.W.A., D.Q.)
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O. Kass-Hout
eDepartment of Neurology (O.K.-H.), Catholic Health System, Buffalo, New York.
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J.W. Allen
aFrom the Departments of Radiology and Imaging Sciences (S.D., L.S.A., J.W.A., D.Q.)
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S. Rangaraju
bNeurology (S.R., M.J.W., F.N.), Emory University Hospital, Atlanta, Georgia
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D. Qiu
aFrom the Departments of Radiology and Imaging Sciences (S.D., L.S.A., J.W.A., D.Q.)
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M.J. Winningham
bNeurology (S.R., M.J.W., F.N.), Emory University Hospital, Atlanta, Georgia
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F. Nahab
bNeurology (S.R., M.J.W., F.N.), Emory University Hospital, Atlanta, Georgia
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    Fig 1.

    CTA CS. CTA CS methodology as proposed by Tan et al.9 Axial 20-mm maximum-intensity-projection images demonstrate the extent and asymmetry in the peripheral leptomeningeal collateral supply graded as relative to the contralateral normal hemisphere (pathologic MCA territory indicated by a red ROI). A, A score of zero suggests near-complete absence of surface collateralization. B, A score of 1 indicates greater than zero but <50% collateral flow. C, A score of 2 suggests >50% but <100% of normal leptomeningeal collaterals. D, A score of 3 suggests normal or, when present, greater than normal surface collaterals.

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    Fig 2.

    RAPID CTP core-penumbra mismatch. Sample output from RAPID perfusion module. The upper of 2 perfusion slabs (4-cm supratentorial coverage across 8 contiguous 5-mm sections) underwent delay-insensitive deconvolution, normalization and lesion segmentation, and thresholding for the production of infarct core and hypoperfused tissue estimates. Similar analysis was undertaken for the inferior perfusion slab (not shown) and cumulative predicted core and penumbral volumes established for each patient. Default output parameters for infarct core (rCBV <30%, A), infarct core (rCBF <30%, B), and hypoperfused tissues (Tmax >6 seconds, C) are shown. The final infarct volume (not shown) measured 97 mL.

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    Fig 3.

    Analysis pipeline, final infarct volume. Postprocessing steps for determination of final infarction volume on follow-up. Optimization of image contrast for intensity-wise lesion segmentation was performed with manual thresholding toward production of a binary image, with cross-reference to the original DWI data to exclude spurious areas related to susceptibility or EPI distortions.

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    Table 1:

    Ninety-day adjusted odds ratios: favorable clinical outcome (mRS ≤2)a

    VariableOdds Ratio95% CIP Value
    Final infarct volume0.840.72–0.98.03
    NCCT-ASPECTS3.231.09–9.54003
    CBV-ASPECTS1.781.13–2.80.01
    CBF-ASPECTS1.461.01–2.11.05
    Collateral score2.270.88–5.83.09b
    Clot burden score1.661.07–2.59.02
    RAPID rCBV core0.920.86–0.98.01
    RAPID rCBF core0.920.85–0.99.02
    RAPID Tmax >4 sec0.980.96–0.99.03
    RAPID Tmax >6 sec0.980.97–0.99.01
    RAPID Tmax >8 sec0.980.96–1.00.06b
    RAPID Tmax >10 sec0.980.96–1.00.06b
    • ↵a NCCT-ASPECTS, CBV-ASPECTS, and CBF-ASPECTS represent ASPECTS applied respectively to noncontrast CT, cerebral blood volume maps, or cerebral blood flow maps.

    • ↵b Statistical significance in logistic regression observed with all tested variables with the exception of RAPID-derived Tmax of >8 seconds and >10 seconds and the CTA collateral score (P > .05).

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    Table 2:

    ROC analysis: dichotomized favorable outcome (mRS ≤2)a

    VariableAUCP Value95% CIOOPSensitivitySpecificity
    Final infarct (mL)0.96<.0010.91–1.0029.191%88%
    RAPID rCBV core0.86.0010.74–0.9610.485%78%
    RAPID rCBF core0.81<.0010.68–0.935.673%72%
    RAPID Tmax >4 sec0.80<.010.65–0.93146.673%67%
    RAPID Tmax >6 sec0.77<.010.63–0.9281.977%72%
    RAPID Tmax >8 sec0.76<.010.60–0.9153.177%72%
    RAPID Tmax >10 sec0.74<.010.58–0.8926.673%72%
    NCCT-ASPECTS0.72.010.57–0.879.568%68%
    CBV-ASPECTS0.75.010.61–0.895.076%62%
    CBF-ASPECTS0.72.020.57–0.875.058%66%
    Clot burden score0.74.010.59–0.896.558%77%
    Collateral scoreb.72.200.56–0.891.570%70%
    • Note:—OOP indicates optimal operating point, optimal cut-off from ROC analysis for the variable of interest.

    • ↵a Results of ROC analysis relative to dichotomized favorable clinical outcome (90-day mRS ≤2). Performance indicated by ROC AUC in descending-order performance.

    • ↵b Significant relationships were observed for all tested variables, with the exception of the CTA collateral score.

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    Table 3:

    Parameter correlation with final infarct volumea

    VariableCorrelationP Value
    RAPID rCBV core0.77<.001
    RAPID rCBF core0.75<.001
    RAPID Tmax >4 sec0.38<.01
    RAPID Tmax >6 sec0.44<.001
    RAPID Tmax >8 sec0.49<.001
    RAPID Tmax >10 sec0.54<.001
    NCCT-ASPECTS−0.40<.01
    CBV-ASPECTS−0.50<.001
    CBF-ASPECTS−0.48<.001
    Clot burden scoreb−0.23.11
    Collateral score−0.41<.01
    • ↵a Correlational analysis between tested variables and final infarct volume (MRI or CT, in milliliters). The strongest overall correlations were observed with RAPID-derived core estimates (rCBF core and rCBV core). Negative correlations were observed between all ASPECTS and CTA-derived measures relative to the final infarct volume.

    • ↵b Significant relationships were observed for all tested variables with the exception of the CTA clot burden score.

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American Journal of Neuroradiology: 36 (8)
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S. Dehkharghani, R. Bammer, M. Straka, L.S. Albin, O. Kass-Hout, J.W. Allen, S. Rangaraju, D. Qiu, M.J. Winningham, F. Nahab
Performance and Predictive Value of a User-Independent Platform for CT Perfusion Analysis: Threshold-Derived Automated Systems Outperform Examiner-Driven Approaches in Outcome Prediction of Acute Ischemic Stroke
American Journal of Neuroradiology Aug 2015, 36 (8) 1419-1425; DOI: 10.3174/ajnr.A4363

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Performance and Predictive Value of a User-Independent Platform for CT Perfusion Analysis: Threshold-Derived Automated Systems Outperform Examiner-Driven Approaches in Outcome Prediction of Acute Ischemic Stroke
S. Dehkharghani, R. Bammer, M. Straka, L.S. Albin, O. Kass-Hout, J.W. Allen, S. Rangaraju, D. Qiu, M.J. Winningham, F. Nahab
American Journal of Neuroradiology Aug 2015, 36 (8) 1419-1425; DOI: 10.3174/ajnr.A4363
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