Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study

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作者
Ayane Yamaguchi
Maya Honda
Hiroshi Ishiguro
Masako Kataoka
Tatsuki R. Kataoka
Hanako Shimizu
Masae Torii
Yukiko Mori
Nobuko Kawaguchi-Sakita
Kentaro Ueno
Masahiro Kawashima
Masahiro Takada
Eiji Suzuki
Yuji Nakamoto
Kosuke Kawaguchi
Masakazu Toi
机构
[1] Kyoto University Graduate School of Medicine,Department of Breast Surgery
[2] Kyoto University Graduate School of Medicine,Department of Diagnostic Imaging and Nuclear Medicine
[3] Saitama Medical University International Medical Center,Breast Oncology Service
[4] Iwate Medical University,Department of Molecular Diagnostic Pathology
[5] Japanese Red Cross Wakayama Medical Center,Department of Breast Surgery
[6] Kyoto University Hospital,Department of Therapeutic Oncology
[7] Kyoto University Hospital,Department of Clinical Oncology
[8] Kyoto University Graduate School of Medicine,Department of Biomedical Statistics and Bioinformatics
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This study aimed to evaluate the predictions of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for prognosis of triple-negative breast cancer (TNBC), especially with residual disease (RD) after preoperative chemotherapy. This retrospective analysis included 74 TNBC patients who received preoperative chemotherapy. DCE-MRI findings from three timepoints were examined: at diagnosis (MRIpre), at midpoint (MRImid) and after chemotherapy (MRIpost). These findings included cancer lesion size, washout index (WI) as a kinetic parameter using the difference in signal intensity between early and delayed phases, and time-signal intensity curve types. Distant disease-free survival was analysed using the log-rank test to compare RD group with and without a fast-washout curve. The diagnostic performance of DCE-MRI findings, including positive predictive value (PPV) for pathological responses, was also calculated. RD without fast washout curve was a significantly better prognostic factor, both at MRImid and MRIpost (hazard ratio = 0.092, 0.098, p < 0.05). PPV for pathological complete remission at MRImid was 76.7% by the cut-off point at negative WI value or lesion size = 0, and 66.7% at lesion size = 0. WI and curve types derived from DCE-MRI at the midpoint of preoperative chemotherapy can help not only assess tumour response but also predict prognosis.
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