The histogram features of quantitative parameters from synthetic MRI in predicting the expression of human epithelial growth factor receptor 2 in breast invasive ductual carcinoma
10.3760/cma.j.cn112149-20210620-00584
- VernacularTitle:合成MRI参数直方图特征预测乳腺浸润性导管癌人表皮生长因子受体2表达状态的研究
- Author:
Qin LI
1
;
Yan HUANG
;
Meng YANG
;
Qinghuan CHAI
;
Puye WU
;
Yajia GU
Author Information
1. 复旦大学附属肿瘤医院放射诊断科 复旦大学上海医学院肿瘤学系 200032
- Keywords:
Breast neoplasms;
Magnetic resonance imaging;
Histogram;
Human epithelial growth factor receptor 2
- From:
Chinese Journal of Radiology
2021;55(12):1294-1300
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate the application value of the histogram features of quantitative parameters from synthetic MRI in predicting the expression of human epidermal growth factor receptor 2 (HER2) in breast invasive ductal carcinoma (IDC) and to compare the prediction efficiency with that of ADC histogram parameters.Methods:A total of 195 patients with breast lesions were prospectively enrolled in the Fudan University Cancer Hospital, from January 2020 to September 2020. All patients underwent preoperative synthetic MRI, DWI and dynamic contrast-enhanced MRI (DCE-MRI). All surgical specimens were confirmed by pathology. The histogram features of the quantitative parameters [T 1, T 2, and proton density (PD)] and ADC values were extracted by PyRadiomics software. Student t test or Mann-Whitney U test were used to compare the histogram characteristics of quantitative parameters (T 1, T 2, and PD) and ADC values between HER2-positive and HER2-negative breast cancers. The diagnostic efficacy of the variables in predicting HER2 expression state was evaluated using the area under curve (AUC) value of ROC. Results:A total of 122 patients with breast IDC were included into analysis, with 31 of HER2-positive and 91 of HER2-negative. There was no significant difference in the clinicopathological characteristics between HER2-positive and HER2-negative breast IDC patients. Univariate analysis showed that there was statistically significant difference in PD-median [79.80 (75.90, 83.90)ms vs. 76.56 (72.59, 79.09) ms, Z=-3.46, P<0.01], PD-mean [78.89 (74.80, 84.01) ms vs. 75.99 (71.70, 78.63) ms, Z=-2.61, P=0.01], PD-Kurtosis [6.45(3.45, 7.54) vs. 5.04 (3.55, 5.58), Z=-2.21, P=0.03], T 1-10 th percentile [731.52 (668.50, 975.39) ms vs. 726.51 (588.38, 852.19) ms, Z=-2.54, P=0.01], T 1-mean [1 161.97 (1 063.56, 1 253.78) ms vs. 1 072.75 (989.39, 1 154.04)ms, Z=-2.21, P=0.03] and ADC-Kurtosis [4.75 (2.72, 5.91) vs. 3.82 (2.69, 4.39), Z=-2.43, P=0.02] between HER2 positive and negative breast IDC patients. Multivariate analysis showed that PD-median ( P=0.004) and T 1-mean ( P=0.004) were independent risk factors for HER2 expression. The ROC curve of HER2 expression predicted by this model showed an AUC was 0.853(95%CI 0.779-0.926), with a sensitivity of 71% and a specificity of 81%. The ROC curve of ADC-Kurtosis for predicting the expression of HER2 showed that the AUC was 0.714 (95%CI 0.611-0.817), with the sensitivity of 45%, and the specificity of 85%. DeLong test showed that the diagnostic efficacy of quantitative parameters from synthetic MRI in predicting the status of HER2 was higher than that of ADC histogram parameters ( Z=2.18, P=0.04). Conclusion:Histogram features of synthetic MRI quantitative parameters contribute to the prediction of HER2 expression status in IDC and may therefore contribute to the determination of individualized anti-HER2 targeted therapy strategies.
