Keywords
Breast cancer
Neoadjuvant chemotherapy
Ultrasonography
Submitted : 2024-05-21
Accepted : 2024-06-05
Published : 2024-06-20
Abstract
Breast cancer is a malignant tumor with the highest incidence in women. In recent years, the incidence of breast cancer has shown an increasing trend, especially in younger patients, which seriously threatens the life and health of women. In order to improve the treatment effect of breast cancer, neoadjuvant chemotherapy has become a reliable strategy to cooperate with surgical treatment and improve the prognosis of advanced breast cancer, which is conducive to quickly and accurately curbing the growth of cancer cells, controlling the patients’ condition, reducing their pain, and improving the cure rate of breast cancer patients. This paper analyzes the development history of ultrasound radiomics, explores its application in the evaluation and prediction of neoadjuvant chemotherapy for breast cancer, and clarifies the research results of multimodal ultrasound radiomics in the analysis of high-order characteristics of breast cancer tumors and the evaluation of tumor heterogeneity, so as to provide references for the clinical treatment of breast cancer.
References
Breast Cancer Committee of Chinese Anti-Cancer Association, 2017, Chinese Anti-Cancer Association Guidelines and Standards for Diagnosis and Treatment of Breast Cancer (2017 Edition). Chin J Cancer, (9): 695–759.
Wang H, Chen S, Li J, et al., 2021, Consensus and Controversy of Neoadjuvant Chemotherapy for Breast Cancer. Chin J Cancer, 42(4): 504–509.
Breast Cancer Committee of Chinese Anti-Cancer Association. 2019, Chinese Anti-Cancer Association Guidelines and Standards for Diagnosis and Treatment of Breast Cancer (2019 Edition). Chin J Cancer, 238(8): 56–127.
Lambin P, Rios Velazquez E, Leijenaar R, et al., 2012, Radiomics: Extracting More Information from Medical Images Using Advanced Feature Analysis. European Journal of Cancer, 48(4): 441–446.
Liu T, Sheng X, Gao Y, et al., 2021, Application Progress of MR Radiomics in Neoadjuvant Chemotherapy of Breast Cancer. Magnetic Resonance Imaging, 11(7): 117420.
Ma M, Qin G, Chen W, 2020, Application Status and Research Progress of Radiomics in Molecular Subtyping of Breast Cancer. Chin J Med Radiology, 43(4): 452–456.
Jain KK, 2017, Biomarkers of Cancer, The Handbook of Biomarkers, Springer, New York, 1648.
Valdora F, Houssami N, Rossi F, et al., 2018, Rapid Review: Radiomics and Breast Cancer. Breast Cancer Research and Breast Cancer Research and Treatment, 169(2): 217–229.
Li J, Shi Z, Guo Y, 2017, Predictive Value of Ultrasound Radiomics on Hormone Receptor Expression in Invasive Breast Cancer. Oncological Imaging, 26(2): 128–135.
Zha H, Pan J, Liu W, et al., 2021, Prediction of Lymphatic Vascular Invasion in Invasive Breast Cancer Based on Ultrasound Radiomics Model. Oncological Imaging, 30(1): 6–15.
Filiz C, Nur PK, Cetin O, et al., 2015, The Role of Ultrasonographic Findings to Predict Molecular Subtype, Histologic Grade. Diagnostic and Interventional Radiology, 21(6): 448–453.
Cui H, Zhang D, Peng F, et al., 2020, Identifying Ultrasound Features of Positive Expression of Ki67 and P53 in Breast Cancer Using Radiomics. Asia-Pacific Journal of Clinical Oncology, 17(5): 176–184.
Braman NM, Etesami M, Prasanna P, et al., 2017, Intratumoral and Peritumoral Radiomics for the Pretreatment Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy Based on Breast DCE-MRI. Breast Cancer Res, 19(57): 1–14.
Zhao Q, Ji X, Shi K, 2021, Research Progress of Contrast-Enhanced Ultrasound and Elastography in Evaluating the Effect of Neoadjuvant Chemotherapy for Breast Cancer. Chin J Ultrasound Imaging, 30(3): 272–276.
Yang XJ, Wang F, Tieliewuha N, 2016, Value of Contrast-Enhanced Ultrasound to the Efficacy Evaluation of Neoadjuvant Chemotherapy of Breast Cancer. Journal of Chinese Practical Diagnosis and Therapy, 30(4): 396–398.
Sun J, Zhang L, Cui H, et al., 2021, Clinical Application Value of Ultrasound in Evaluating the Pathological Complete Response of Breast Cancer After Neoadjuvant Chemotherapy. Chin J Ultrasound Imaging, 30(5): 420425.
Lee YJ, Kim SH, Kang BJ, et al., 2019, Contrast-Enhanced Ultrasound for Early Prediction of Response of Breast Cancer to Neoadjuvant Chemotherapy. Senologie Zeitschrift fiur Mammadiagnostikund d-Therapie, 16(4): 302–312.
Virkkunen I, Koskinen T, Jessen JO, et al., 2021, Augmented Ultrasonic Data for Machine Learning. Journal of Nondestructive Evaluation, 40(4): 19.
Jiang M, Li CL, Luo XM, et al., 2021, Ultrasound Based Deep Learning Radiomics in the Assessment of Pathological Complete Response to Neoadjuvant Chemotherapy in Local Advanced Breast Cancer. European Journal of Cancer, 147(2): 95–105.
Mishra AK, Roy P, Bandyopadhyay S, et al., 2021, Breast Ultrasound Tumour Classification: A Machine Learning-Radiomics Based Approach. Expert Systems, 38(7): 12713.