Journal
MAGNETIC RESONANCE IMAGING
Volume 85, Issue -, Pages 262-270Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.mri.2021.10.027
Keywords
Breast cancer; MRI; IVIM; Histogram; Molecular prognostic factors
Funding
- Lanzhou Talent Innovation and Entrepreneurship Project of Gansu Province [2017-RC-76]
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The study found that the ADC 10th percentile had the highest ROC value in ER-negative breast cancer patients, with a cut-off value of 0.788 x 10(-3) mm(2)/s. The negative correlation between lymph node metastasis status and ADC standard deviation was significant. Positive correlations were observed between ER and PR expression with ADC or perfusion fraction metrics.
Objective: To explore the efficacy of the quantitative parameter histogram analysis of intravoxel incoherent motion (IVIM) for different molecular prognostic factors of breast cancer. Materials and methods: A total of 72 patients with breast cancer who were confirmed by surgical pathology and underwent preoperative magnetic resonance imaging (MRI) were analyzed retrospectively. A region of interest (ROI) was drawn in each slice of the IVIM images. Whole-tumor histogram parameters were obtained with Firevoxel's software by accumulating all ROIs. Next, Kolmogorov-Smirnov test, Student's t-test, Mann-Whitney U test, receiver operating characteristic curve analysis and spearman rank correlation analysis were used to assess the relationship between histogram parameters and molecular prognostic factors of breast cancer. Results: Among estrogen receptor (ER)-negative ROCs, the apparent diffusion coefficient (ADC) 10th percentile had the highest ROC of 0.792, with a cut-off value of 0.788 x 10(-3) mm(2)/s, and sensitivity and specificity of 0.714 and 0.867, respectively. The negative correlation between lymph node metastasis status and ADC standard deviation was significant (rho = -0.44, the correlation coefficients was represented by rho). Positive correlations were observed between hormonal expression of ER and progesterone receptor (PR) with heterogeneity metrics of ADC or perfusion fraction (f), such as ADC inhomogeneity (rho = 0.37, rho = 0.29) and f skewness (rho = 0.32, rho = 0.28). Negative correlations were observed with numerical metrics, such as the ADC median (rho = -0.31, rho = -0.34) and f 45th percentile (rho = -0.35, rho = -0.28). The positive correlations between human epidermal receptor factor-2 (HER2) and pseudo-diffusivity (Dp) numerical metrics, Ki-67 expression, and heterogeneity metrics of Dp were high. Conclusions: The ADC 10th percentile had the largest area under the curve in the ER-negative ROC analysis, and the ADC standard deviation was the most valuable in the correlation analysis of lymph node metastasis. Whole-lesion quantitative histogram parameters of IVIM could, therefore, provide a scientific basis for radiomics to further guide clinical practice in the prognosis of breast cancer.
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