Preoperative ultrasound radiomics analysis for expression of multiple molecular biomarkers in mass type of breast ductal carcinoma in situ.

Abstract

BACKGROUND:

The molecular biomarkers of breast ductal carcinoma in situ (DCIS) have important guiding significance for individualized precision treatment. This study was intended to explore the significance of radiomics based on ultrasound images to predict the expression of molecular biomarkers of mass type of DCIS.

METHODS:

116 patients with mass type of DCIS were included in this retrospective study. The radiomics features were extracted based on ultrasound images. According to the ratio of 7:3, the data sets of molecular biomarkers were split into training set and test set. The radiomics models were developed to predict the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), Ki67, p16, and p53 by using combination of multiple feature selection and classifiers. The predictive performance of the models were evaluated using the area under the curve (AUC) of the receiver operating curve.

RESULTS:

The investigators extracted 5234 radiomics features from ultrasound images. 12, 23, 41, 51, 31 and 23 features were important for constructing the models. The radiomics scores were significantly (P < 0.05) in each molecular marker expression of mass type of DCIS. The radiomics models showed predictive performance with AUC greater than 0.7 in the training set and test set: ER (0.94 and 0.84), PR (0.90 and 0.78), HER2 (0.94 and 0.74), Ki67 (0.95 and 0.86), p16 (0.96 and 0.78), and p53 (0.95 and 0.74), respectively.

CONCLUSION:

Ultrasonic-based radiomics analysis provided a noninvasive preoperative method for predicting the expression of molecular markers of mass type of DCIS with good accuracy.

• Authors: Linyong Wu, Yujia Zhao, Peng Lin, Hui Qin, Yichen Liu, Da Wan, Xin Li, Yun He, Hong Yang
• Journal: BMC medical imaging (BMC Med Imaging) Vol. 21 Issue 1 Pg. 84 (05 17 2021) ISSN: 1471-2342 [Electronic] England
• PMID: 34001017 (Publication Type: Journal Article)

Chemical References

• Biomarkers, Tumor
• CDKN2A protein, human
• Cyclin-Dependent Kinase Inhibitor p16
• Ki-67 Antigen
• MKI67 protein, human
• Receptors, Estrogen
• Receptors, Progesterone
• Tumor Suppressor Protein p53
• ERBB2 protein, human
• Receptor, ErbB-2

Topics

• Adult
• Aged
• Aged, 80 and over
• Biomarkers, Tumor (analysis)
• Breast Neoplasms (chemistry, diagnostic imaging)
• Carcinoma, Intraductal, Noninfiltrating (chemistry, diagnostic imaging)
• Cyclin-Dependent Kinase Inhibitor p16 (analysis)
• Female
• Humans
• Ki-67 Antigen (analysis)
• Middle Aged
• Receptor, ErbB-2 (analysis)
• Receptors, Estrogen (analysis)
• Receptors, Progesterone (analysis)
• Retrospective Studies
• Tumor Suppressor Protein p53 (analysis)
• Ultrasonography (methods)