IMAGING SCIENCE AND PHOTOCHEMISTRY ›› 2022, Vol. 40 ›› Issue (5): 1077-1082.DOI: 10.7517/issn.1674-0475.220115

• Review and Articles • Previous Articles     Next Articles

Application of 1.5T MR Dynamic Enhanced Image Features and Parameters in the Diagnosis of Breast Cancer

CHENG Yu, ZHANG Yayun, LI Mengshuang   

  1. Department of Imaging, The First People's Hospital of Lianyungang, Lianyungang 222000, Jiangsu, P. R. China
  • Received:2022-01-14 Published:2022-09-13

Abstract: This paper explored the application value of 1.5T magnetic resonance dynamic enhanced image features and parameters in the diagnosis of breast cancer. 100 patients with breast cancer were selected as the observation group, and 60 patients with benign breast tumors treated in the same period were selected as the control group. All patients underwent magnetic resonance dynamic enhanced examination. The results showed, compared with the control group that there were statistically significant differences on the lesion morphology, edge, internal enhancement and ring enhancement in the observation group (P<0.05). In the observation group the Kep and Ktrans were higher than those in the control group (P<0.05). The AUC of Kep, Ktrans combined diagnosis was 0.861, which was higher than the single diagnostic value of each index. The lesion morphology, edge, internal enhancement and ring enhancement in patients with poor prognosis were compared with those in patients with good prognosis (P<0.05). Kep and Ktrans of patients with poor prognosis were higher than those with good prognosis (P<0.05). The lesion morphology, edge, internal enhancement, annular enhancement, Kep, Ktrans were independently correlated with the prognosis of breast cancer patients (P<0.05). 1.5T MRI dynamic enhancement image features of breast cancer patients are mainly irregular in shape, edge burr, internal inhomogeneous enhancement and annular enhancement, and the quantitative parameters Kep and Ktrans are at high levels, which could be clinically enhanced by MRI dynamic enhancement imaging features and parameters to diagnose breast cancer and predict prognosis.

Key words: breast cancer, dynamic magnetic resonance image enhancement, image features, quantitative parameters, prognosis