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Updated: Jun 15, 2026
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
Published on: August 16, 2020
Detecting metastasis of lymph nodes and predicting aggressiveness in patients with breast carcinomas
Qiufang Ouyang1, Liwu Chen, Hongjia Zhao
1Department of Ultrasonography, Second Affiliated People's Hospital of Fujian Traditional Chinese Medicine, Fuzhou, China.
Objective:
The purpose of this study was to evaluate the contrast-enhanced ultrasonographic (CEUS) characteristics of metastatic lymph nodes (LNs) and to determine the correlation of CEUS parameters with the tumor aggressiveness in patients with breast cancer.
Methods:
Real-time gray scale CEUS of axillary LNs was preoperatively performed in 51 consecutive patients with breast carcinoma who were scheduled for axillary lymph node dissection. The CEUS characteristics assessed by a direct visualization method and quantification software were compared with pathologic findings. Expression of human epidermal growth factor receptor 2 (HER-2/neu) in the primary tumor was detected by immunohistochemical analysis. Correlation analysis of CEUS parameters with HER-2/neu expression and the LN stage was performed.
Results:
Of the LNs examined, 27 were metastatic, and 25 were diagnosed as reactive hyperplasia. Lymph nodes with metastasis were characterized by centripetal progress (66.7%) and a heterogeneous pattern (55.6%) or no or scarce perfusion (25.9%). However, LNs with nonmetastases were characterized by with centrifugal enhancement (56.0%) and a homogeneous pattern (80.0%). The difference between the hyperintense and hypointense regions was higher in metastatic LNs than nonmetastatic ones (P < .001). No significant differences were found in the arrival time, time to peak intensity, and peak intensity between the two groups. A histopathologic diagnosis could be predicted with sensitivity, specificity, and accuracy of 92.6%, 76.0%, and 84.6% respectively, by a standardized difference between maximum and minimum signal intensity (SI(max)-SI(min)) value of 28. Human epidermal growth factor receptor 2 expression and the LN histopathologic stage were significantly associated with the SI(max)-SI(min). In metastatic LNs, the relationship between the diagnostic sensitivity of CEUS and the transverse diameter of LNs remained statistically significant (P < .05).
Conclusions:
Noninvasive CEUS can play a role in discriminating metastatic from nonmetastatic LNs and predicting the aggressiveness in patients with breast cancer.
