Multiparameter MRI Model With DCE-MRI, DWI, and Synthetic MRI Improves the Diagnostic Performance of BI-RADS 4 Lesions

Shi Yun Sun; Yingying Ding; Zhuolin Li; Lisha Nie; Chengde Liao; Yifan Liu; Jia Zhang; Dongxue Zhang

doi:10.3389/fonc.2021.699127

Multiparameter MRI Model With DCE-MRI, DWI, and Synthetic MRI Improves the Diagnostic Performance of BI-RADS 4 Lesions

Front Oncol. 2021 Oct 15:11:699127. doi: 10.3389/fonc.2021.699127. eCollection 2021.

Authors

Shi Yun Sun¹, Yingying Ding¹, Zhuolin Li¹, Lisha Nie², Chengde Liao¹, Yifan Liu¹, Jia Zhang³, Dongxue Zhang¹

Affiliations

¹ Department of Radiology, Yunnan Cancer Center, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China.
² Magnetic Resonance Imaging Research, General Electric Healthcare (China), Beijing, China.
³ Department of Radiology, Third People's Hospital of Yunnan Province, Kunming, China.

Abstract

Objectives: To evaluate the value of synthetic magnetic resonance imaging (syMRI), diffusion-weighted imaging (DWI), DCE-MRI, and clinical features in breast imaging-reporting and data system (BI-RADS) 4 lesions, and develop an efficient method to help patients avoid unnecessary biopsy.

Methods: A total of 75 patients with breast diseases classified as BI-RADS 4 (45 with malignant lesions and 30 with benign lesions) were prospectively enrolled in this study. T1-weighted imaging (T1WI), T2WI, DWI, and syMRI were performed at 3.0 T. Relaxation time (T1 and T2), apparent diffusion coefficient (ADC), conventional MRI features, and clinical features were assessed. "T" represents the relaxation time value of the region of interest pre-contrast scanning, and "T+" represents the value post-contrast scanning. The rate of change in the T value between pre- and post-contrast scanning was represented by ΔT%.

Results: ΔT1%, T2, ADC, age, body mass index (BMI), menopause, irregular margins, and heterogeneous internal enhancement pattern were significantly associated with a breast cancer diagnosis in the multivariable logistic regression analysis. Based on the above parameters, four models were established: model 1 (BI-RADS model, including all conventional MRI features recommended by BI-RADS lexicon), model 2 (relaxation time model, including ΔT1% and T2), model 3 [multi-parameter (mp)MRI model, including ΔT1%, T2, ADC, margin, and internal enhancement pattern], and model 4 (combined image and clinical model, including ΔT1%, T2, ADC, margin, internal enhancement pattern, age, BMI, and menopausal state). Among these, model 4 has the best diagnostic performance, followed by models 3, 2, and 1.

Conclusions: The mpMRI model with DCE-MRI, DWI, and syMRI is a robust tool for evaluating the malignancies in BI-RADS 4 lesions. The clinical features could further improve the diagnostic performance of the model.

Keywords: breast cancer; mapping; quantitative imaging; relaxation time; synthetic magnetic resonance imaging (syMRI).