Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study
Abstract 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...
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Nature Portfolio
2021
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oai:doaj.org-article:50ca524a075a42ba86b159a9b55637d52021-12-02T15:55:13ZKinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study10.1038/s41598-021-89380-42045-2322https://doaj.org/article/50ca524a075a42ba86b159a9b55637d52021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89380-4https://doaj.org/toc/2045-2322Abstract 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.Ayane YamaguchiMaya HondaHiroshi IshiguroMasako KataokaTatsuki R. KataokaHanako ShimizuMasae ToriiYukiko MoriNobuko Kawaguchi-SakitaKentaro UenoMasahiro KawashimaMasahiro TakadaEiji SuzukiYuji NakamotoKosuke KawaguchiMasakazu ToiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021) |
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Medicine R Science Q 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 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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Abstract 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. |
format |
article |
author |
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 |
author_facet |
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 |
author_sort |
Ayane Yamaguchi |
title |
Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study |
title_short |
Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study |
title_full |
Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study |
title_fullStr |
Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study |
title_full_unstemmed |
Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study |
title_sort |
kinetic information from dynamic contrast-enhanced mri enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/50ca524a075a42ba86b159a9b55637d5 |
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