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Research ArticleAdult Brain

Evaluation of Thick-Slab Overlapping MIP Images of Contrast-Enhanced 3D T1-Weighted CUBE for Detection of Intracranial Metastases: A Pilot Study for Comparison of Lesion Detection, Interpretation Time, and Sensitivity with Nonoverlapping CUBE MIP, CUBE, and Inversion-Recovery-Prepared Fast-Spoiled Gradient Recalled Brain Volume

B.C. Yoon, A.F. Saad, P. Rezaii, M. Wintermark, G. Zaharchuk and M. Iv
American Journal of Neuroradiology September 2018, 39 (9) 1635-1642; DOI: https://doi.org/10.3174/ajnr.A5747
B.C. Yoon
aFrom the Department of Radiology, Division of Neuroimaging and Neurointervention, Stanford University, Stanford, California.
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A.F. Saad
aFrom the Department of Radiology, Division of Neuroimaging and Neurointervention, Stanford University, Stanford, California.
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P. Rezaii
aFrom the Department of Radiology, Division of Neuroimaging and Neurointervention, Stanford University, Stanford, California.
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M. Wintermark
aFrom the Department of Radiology, Division of Neuroimaging and Neurointervention, Stanford University, Stanford, California.
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G. Zaharchuk
aFrom the Department of Radiology, Division of Neuroimaging and Neurointervention, Stanford University, Stanford, California.
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M. Iv
aFrom the Department of Radiology, Division of Neuroimaging and Neurointervention, Stanford University, Stanford, California.
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    Fig 1.

    Total number of brain metastases detected. No significant difference was found among the total number of metastases detected using CUBE, nC-MIP, oC-MIP, and IR-FSPGR-BRAVO (P = .062) using 1-way ANOVA with a Bonferroni adjustment. The orange line denotes the total number of ground truth lesions (n = 308).

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    Fig 2.

    Mean time for interpretation. A, Both readers had significantly reduced interpretation time using nC-MIP and oC-MIP compared with CUBE and IR-FSPGR-BRAVO, saving at least 50 seconds per case (on average). B, The use of nC-MIP and oC-MIP with the option to cross-reference an equivocal lesion to the source images (nC-MIP+XR and oC-MIP+XR, respectively) did not result in a significant change in interpretation time compared with the use of nC-MIP or oC-MIP alone. However, time for interpretation for all CUBE MIPs was significantly reduced compared with CUBE. Error bars represent the SD. One-way ANOVA with a Bonferroni adjustment. Triple asterisks indicate P < .001; ns, no significance.

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    Fig 3.

    Enhancing cerebral metastases in a 74-year-old male with metastatic tongue squamous cell carcinoma. Postcontrast T1-weighted CUBE (A), nonoverlapping CUBE MIP (nC-MIP) (B), overlapping CUBE MIP (oC-MIP) (C), and IR-FSPGR-BRAVO (D) images demonstrate enhancing metastatic lesions. The lesions appear most conspicuous with CUBE MIPs (B and C). The contrast-to-noise ratio of lesions was highest for oC-MIP (C).

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    Fig 4.

    Comparison between nonoverlapping and overlapping CUBE MIP. A small 3-mm metastasis in a 57-year-old woman with non-small cell lung cancer is seen across 4 different slices with oC-MIP but is only identified on 2 slices with nC-MIP.

Tables

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    Table 1:

    Interrater agreement using the Cohen κ coefficient for T1-weighted CUBE, nC-MIP, oC-MIP, and IR-FSPGR-BRAVO

    Image Typeκ95% Confidence IntervalAgreement
    CUBE0.2350.024–0.447Fair
    nC-MIP0.2220.069–0.374Fair
    oC-MIP0.5980.371–0.825Moderate
    IR-FSPGR-BRAVO0.4450.290–0.599Moderate
    • View popup
    Table 2:

    CNR of the smallest and largest metastases on CUBE, nC-MIP, oC-MIP, IR-FSPGR-BRAVO, and overlapping IR-FSPGR-BRAVO MIPa

    Image TypeCNR of the Smallest Lesion (<4 mm)CNR of the Largest Lesion
    CUBE2.35 ± 2.02.49 ± 1.84
    nC-MIP1.55 ± 0.532.69 ± 0.93
    oC-MIP2.35 ± 1.643.23 ± 1.92
    IR-FSPGR-BRAVO0.62 ± 0.391.45 ± 1.14
    IR-FSPGR-BRAVO MIP0.90 ± 0.781.69 ± 1.14
    • ↵a Numbers are means.

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    Table 3:

    Sensitivity, number of false-negatives, number of false-positives, and number of discrepant lesions (FN + FP) per case for CUBE, nC-MIP, oC-MIP, IR-FSPGR-BRAVO, and non-overlapping and overlapping CUBE MIPsa

    Reader 1Reader 2
    % SensitivityMean FNMean FPMean Discrepancy% SensitivityMean FNMean FPMean Discrepancy
    CUBE97.1 ± 14.80.08 ± 0.280.31 ± 0.630.40 ± 0.6593.0 ± 16.80.38 ± 0.700.38 ± 0.820.75 ± 0.93
    nC-MIP94.7 ± 20.40.08 ± 0.280.58 ± 0.980.65 ± 0.9690.2 ± 16.80.60 ± 0.960.71 ± 1.981.31 ± 2.00
    oC-MIP95.8 ± 15.40.19 ± 0.490.54 ± 0.920.73 ± 0.9495.8 ± 15.40.19 ± 0.500.33 ± 0.690.75 ± 0.93
    BRAVO91.5 ± 17.00.58 ± 0.990.21 ± 0.500.79 ± 0.9989.0 ± 19.50.85 ± 1.490.31 ± 0.591.17 ± 1.42
    nC-MIP + XR95.5 ± 9.80.33 ± 0.660.25 ± 0.700.58 ± 0.8791.2 ± 12.30.67 ± 0.930.29 ± 0.740.95 ± 1.01
    oC-MIP + XR96.6 ± 7.30.29 ± 0.620.21 ± 0.460.68 ± 0.9694.8 ± 12.30.38 ± 0.790.23 ± 0.470.60 ± 0.82
    • Note:—FN indicates false-negative; FP, false-positive.

    • ↵a With the option to cross-reference a lesion to the source images (nC-MIP+XR and oC-MIP+XR, respectively) for both readers. Numbers are means.

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American Journal of Neuroradiology: 39 (9)
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Evaluation of Thick-Slab Overlapping MIP Images of Contrast-Enhanced 3D T1-Weighted CUBE for Detection of Intracranial Metastases: A Pilot Study for Comparison of Lesion Detection, Interpretation Time, and Sensitivity with Nonoverlapping CUBE MIP, CUBE, …
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B.C. Yoon, A.F. Saad, P. Rezaii, M. Wintermark, G. Zaharchuk, M. Iv
Evaluation of Thick-Slab Overlapping MIP Images of Contrast-Enhanced 3D T1-Weighted CUBE for Detection of Intracranial Metastases: A Pilot Study for Comparison of Lesion Detection, Interpretation Time, and Sensitivity with Nonoverlapping CUBE MIP, CUBE, and Inversion-Recovery-Prepared Fast-Spoiled Gradient Recalled Brain Volume
American Journal of Neuroradiology Sep 2018, 39 (9) 1635-1642; DOI: 10.3174/ajnr.A5747

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Evaluation of Thick-Slab Overlapping MIP Images of Contrast-Enhanced 3D T1-Weighted CUBE for Detection of Intracranial Metastases: A Pilot Study for Comparison of Lesion Detection, Interpretation Time, and Sensitivity with Nonoverlapping CUBE MIP, CUBE, and Inversion-Recovery-Prepared Fast-Spoiled Gradient Recalled Brain Volume
B.C. Yoon, A.F. Saad, P. Rezaii, M. Wintermark, G. Zaharchuk, M. Iv
American Journal of Neuroradiology Sep 2018, 39 (9) 1635-1642; DOI: 10.3174/ajnr.A5747
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