Kinetic features of invasive breast cancers on computer-aided diagnosis using 3T MRI data: Correlation with clinical and pathologic prognostic factors

Sung Eun Song, Kyu Ran Cho, Bo Kyoung Seo, Ok Hee Woo, Seung Pil Jung, Deuk Jae Sung

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    9 Citations (Scopus)

    Abstract

    Objective: To investigate the correlation of kinetic features of breast cancers on computer-aided diagnosis (CAD) of preoperative 3T magnetic resonance imaging (MRI) data and clinical-pathologic factors in breast cancer patients. Materials and Methods: Between July 2016 and March 2017, 85 patients (mean age, 54 years; age range, 35-81 years) with invasive breast cancers (mean, 1.8 cm; range, 0.8-4.8 cm) who had undergone MRI and surgery were retrospectively enrolled. All magnetic resonance images were processed using CAD, and kinetic features of tumors were acquired. The relationships between kinetic features and clinical-pathologic factors were assessed using Spearman correlation test and binary logistic regression analysis. Results: Peak enhancement and angio-volume were significantly correlated with histologic grade, Ki-67 index, and tumor size: r = 0.355 (p = 0.001), r = 0.330 (p = 0.002), and r = 0.231 (p = 0.033) for peak enhancement, r = 0.410 (p = 0.005), r = 0.341 (p < 0.001), and r = 0.505 (p < 0.001) for angio-volume. Delayed-plateau component was correlated with Ki-67 (r = 0.255 [p = 0.019]). In regression analysis, higher peak enhancement was associated with higher histologic grade (odds ratio [OR] = 1.004; 95% confidence interval [CI]: 1.001-1.008; p = 0.024), and higher delayed-plateau component and angio-volume were associated with higher Ki-67 (OR = 1.051; 95% CI: 1.011-1.094; p = 0.013 for delayed-plateau component, OR = 1.178; 95% CI: 1.023-1.356; p = 0.023 for angio-volume). Conclusion: Of the CAD-assessed kinetic features, higher peak enhancement may correlate with higher histologic grade, and higher delayed-plateau component and angio-volume correlate with higher Ki-67 index. These results support the clinical application of kinetic features in prognosis assessment.

    Original languageEnglish
    Pages (from-to)411-421
    Number of pages11
    JournalKorean journal of radiology
    Volume20
    Issue number3
    DOIs
    Publication statusPublished - 2019 Mar

    Keywords

    • Breast Neoplasms
    • Computer-aided diagnosis (CAD)
    • Kinetic feature
    • MRI
    • Prognostic factor

    ASJC Scopus subject areas

    • Radiology Nuclear Medicine and imaging

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