Quantitative assessment of metabolic tumor burden in molecular subtypes of primary breast cancer with FDG PET/CT
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    Breast Imaging - Original Article
    P: 336-341
    November 2018

    Quantitative assessment of metabolic tumor burden in molecular subtypes of primary breast cancer with FDG PET/CT

    Diagn Interv Radiol 2018;24(6):336-341
    1. Department of Molecular Imaging and Nuclear Medicine Tianjin Medical University Cancer Institute and Hospital; National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy Tianjin, China
    2. Key Laboratory of Cancer Prevention and Therapy Tianjin, China
    3. Department of Molecular Imaging and Nuclear Medicine Tianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy Tianjin, China
    4. Department of Molecular Imaging and Nuclear Medicine and Radiation Oncology Tianjin Medical University Cancer Institute and Hospital; Key Laboratory of Cancer Prevention and Therapy Tianjin, China
    No information available.
    No information available
    Received Date: 17.09.2017
    Accepted Date: 23.05.2018
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    ABSTRACT

    PURPOSE:

    We aimed to quantitatively evaluate volumetric metabolic tumor burden including metabolic tumor volume and total lesion glycolysis in different molecular subtypes of breast cancer using 18F-fluorodeoxyglucose (FDG) positron emission tomography/ computed tomography (PET/CT).

    METHODS:

    This study involved 99 female patients with pathologic diagnosis of primary breast cancer, who underwent 18F-FDG PET/CT before any therapy. Patients were divided into subtypes of luminal A, luminal B, ERBB2+, and basal-like based on the immunohistochemistry results. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) before and after correction for lean body mass were achieved and compared. Correlations between metabolic tumor burden and Ki-67 were analyzed and diagnostic performances of volumetric metabolic parameters were evaluated.

    RESULTS:

    TLG values were significantly different between each molecular subtype, while MTV values were not. Values of TLG were significantly reduced after normalizing for lean body mass in each subtype. Both of them showed correlations with Ki-67 and presented high diagnostic ability in identifying patients with basal-like breast cancer from the rest. TLGs before and after normalizing for the lean body mass had similar diagnostic performances in differentiating patients of basal-like subtype from the rest.

    CONCLUSION:

    Metabolic tumor burden could comprehensively reflect tumor metabolic differences of molecular subtypes of breast cancer, and it can serve to help differentiate patients with basal-like breast cancer.

    References

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