Preoperative Prediction Power of Radiomics for Breast Cancer: A Systemic Review and Meta-Analysis

Zhenkai Li; Juan Ye; Hongdi Du; Ying Cao; Ying Wang; Desen Liu; Feng Zhu; Hailin Shen

doi:10.3389/fonc.2022.837257

Preoperative Prediction Power of Radiomics for Breast Cancer: A Systemic Review and Meta-Analysis

Front Oncol. 2022 Mar 1:12:837257. doi: 10.3389/fonc.2022.837257. eCollection 2022.

Authors

Zhenkai Li¹, Juan Ye¹, Hongdi Du¹, Ying Cao², Ying Wang¹, Desen Liu³, Feng Zhu¹, Hailin Shen¹

Affiliations

¹ Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, China.
² Department of Radiotherapy, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, China.
³ Department of Thoracic Surgery, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, China.

Abstract

Background: To evaluate the preoperative predictive value of radiomics in the diagnosis of breast cancer (BC).

Methods: By searching PubMed and Embase libraries, our study identified 19 eligible studies. We conducted a meta-analysis to assess the differential value in the preoperative assessment of BC using radiomics methods.

Results: Nineteen radiomics studies focusing on the diagnostic efficacy of BC and involving 5865 patients were enrolled. The integrated sensitivity and specificity were 0.84 (95% CI: 0.80-0.87, I ^{2 =} 76.44%) and 0.83 (95% CI: 0.78-0.87, I ^{2 =} 81.79%), respectively. The AUC based on the SROC curve was 0.91, indicating a high diagnostic value.

Conclusion: Radiomics has shown excellent diagnostic performance in the preoperative prediction of BC and is expected to be a promising method in clinical practice.

Keywords: breast cancer; cancer prediction; meta-analysis; radiomics; systematic review.

Publication types

Systematic Review