2023 VOLUME 3 ISSUE 4
RESEARCH ARTICLE
Progress on radiomics and radiogenomics and their applications in breast cancer: A survey
AUTHOR
Xuan Cao, Ming Fan, Lihua Li
ABSTRACT
Radiomics is an emerging analytical approach in the medical field that extracts high-throughput quantitative features from multiple imaging data and builds models for cancer diagnosis, prognosis, and treatment by machine learning or deep learning. Radiomics allows radiologists to obtain a more complete picture of the tumor in a noninvasive way than by reading radiographs. Radiogenomics incorporates genomics on top of radiomics to analyze the potential relationship between imaging features and tumor genetic status, enabling biological profiling of the causes of tumor heterogeneity, and its development of biomarkers will be of great help for personalized treatment. Breast cancer is the most prevalent cancer among women worldwide today, and this survey aims to summarize the progress on radiomics and radiogenomics, their applications in breast cancer, and discuss the issues that need to be addressed before radiomics and radiogenomics can be used in clinic. From the literature, it can be concluded that radiomics and radiogenomics have a high potential for differentiating malignant and benign breast lesions to assess breast cancer types and lymph node status, as well as to predict neoadjuvant chemotherapy response, risk of recurrence and survival outcomes, especially in the context of the rapid development of artificial intelligence technologies, promising early realization of precision medicine.
KEYWORDS
Radiomics; Radiogenomics; Breast cancer; Application; Medical image