AUTHOR=Huang Xiaodan , Wang Xiangyu , Lan Xinxin , Deng Jinhuan , Lei Yi , Lin Fan 

TITLE=The role of radiomics with machine learning in the prediction of muscle-invasive bladder cancer: A mini review

JOURNAL=Frontiers in Oncology

VOLUME=12

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.990176

DOI=10.3389/fonc.2022.990176

ISSN=2234-943X

ABSTRACT=<p>Bladder cancer is a common malignant tumor in the urinary system. Depending on whether bladder cancer invades muscle tissue, it is classified into non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). It is crucial to accurately diagnose the muscle invasion of bladder cancer for its clinical management. Although imaging modalities such as CT and multiparametric MRI play an important role in this regard, radiomics has shown great potential with the development and innovation of precision medicine. It features outstanding advantages such as non-invasive and high efficiency, and takes on important significance in tumor assessment and laor liberation. In this article, we provide an overview of radiomics in the prediction of muscle-invasive bladder cancer and reflect on its future trends and challenges.</p>