Literature DB >> 28478644

The role of MRI in predicting Ki-67 in breast cancer: preliminary results from a prospective study.

Corrado Caiazzo1, Rosa Di Micco2, Emanuela Esposito2, Viviana Sollazzo2, Maria Cervotti2, Carlo Varelli3, Pietro Forestieri2, Gennaro Limite2.   

Abstract

PURPOSE: In the last decade contrast-enhanced magnetic resonance imaging (MRI) has gained a growing role as a complementary tool for breast cancer diagnosis. Currently the relationship between the kinetic features of a breast lesion and pathologic prognostic factors has become a popular field of research. Our aim is to verify whether breast MRI could be considered a useful tool to predict Ki-67 score, thus resulting as a breast cancer prognosis indicator.
METHODS: From June to December 2014, we enrolled patients with breast cancer who underwent preoperative dynamic contrast-enhanced MRI at the local health agency. We analyzed the time-signal intensity curves calculating the mean values of the following parameters: the basal enhancement (Ebase), the enhancement ratio (ENHratio), the maximum enhancement (Emax), and the steepest slope of the contrast enhancement curve (Smax). Scatterplots and Pearson correlation test were used to investigate the eventual associations among these parameters.
RESULTS: A total of 27 patients underwent breast MRI during the study period. The mean ± SD Ki-67 percentage was 27.03 ± 16.8; the mean Emax, Smax, Ebase, and ENHratio were 433.9 ± 120.2, 267.3 ± 96.8, 165.5 ± 77.1, and 187.1 ± 94.8, respectively. Scatterplots suggest a positive correlation between Ki-67 and both Emax and Smax. The correlation tests between Ki-67 and Emax, Ki-67 and Smax showed statistical significance.
CONCLUSIONS: Our preliminary data suggest that enhancement pattern is closely linked to breast cancer proliferation, thus proving the relationship between more proliferating tumors and more rapidly enhanced lesions. This is hypothesis-generating for further studies aimed at promoting breast MRI in the early estimation of cancer prognosis and tumor in vivo response to chemotherapy.

Entities:  

Keywords:  Breast cancer; Magnetic resonance imaging; Prognostic factors

Mesh:

Substances:

Year:  2018        PMID: 28478644     DOI: 10.5301/tj.5000619

Source DB:  PubMed          Journal:  Tumori        ISSN: 0300-8916            Impact factor:   2.098


  4 in total

1.  Development and validation of novel radiomics-based nomograms for the prediction of EGFR mutations and Ki-67 proliferation index in non-small cell lung cancer.

Authors:  Yinjun Dong; Zekun Jiang; Chaowei Li; Shuai Dong; Shengdong Zhang; Yunhong Lv; Fenghao Sun; Shuguang Liu
Journal:  Quant Imaging Med Surg       Date:  2022-05

2.  Computer-Aided Diagnosis Parameters of Invasive Carcinoma of No Special Type on 3T MRI: Correlation with Pathologic Immunohistochemical Markers.

Authors:  Jinho Jeong; Chang Suk Park; Jung Whee Lee; Kijun Kim; Hyeon Sook Kim; Sun-Young Jun; Se-Jeong Oh
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2021-09-15

3.  Radiomic signatures based on multiparametric MR images for predicting Ki-67 index expression in medulloblastoma.

Authors:  Lili Zhou; Hong Peng; Qiang Ji; Bo Li; Lexin Pan; Feng Chen; Zishan Jiao; Yali Wang; Mengqian Huang; Gaifen Liu; Yaou Liu; Wenbin Li
Journal:  Ann Transl Med       Date:  2021-11

Review 4.  Breast Cancer Subtypes and Quantitative Magnetic Resonance Imaging: A Systemic Review.

Authors:  Toshiki Kazama; Taro Takahara; Jun Hashimoto
Journal:  Life (Basel)       Date:  2022-03-28
  4 in total

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