An Update in Imaging Evaluation of Histopathological Grade of Soft Tissue Sarcomas Using Structural and Quantitative Imaging and Radiomics. Issue 5 (12th October 2021)

• Record Type: Journal Article
• Authors: Fang, Shaobo; Yang, Yanyu; Xu, Nan; Tu, Yun; Yin, Zhenzhen; Zhang, Yu; Liu, Yajie; Duan, Zhiqing; Liu, Wenyu; Wang, Shaowu
• Is Part Of: Journal of magnetic resonance imaging. Volume 55:Issue 5(2022)
• Page Start: 1357
• Page End: 1375
• Publication Date: 2021-10-12
• Subjects: structural magnetic resonance imaging -- functional magnetic resonance imaging -- radiomics -- soft tissue sarcomas -- histopathological grade; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.27954
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Over the past two decades, considerable efforts have been made to develop non‐invasive methods for determining tumor grade or surrogates for predicting the biological behavior, aiding early treatment decisions, and providing prognostic information. The development of new imaging tools, such as diffusion‐weighted imaging, diffusion kurtosis imaging, perfusion imaging, and magnetic resonance spectroscopy have provided leverage in the diagnosis of soft tissue sarcomas. Artificial intelligence is a new technology used to study and simulate human thinking and abilities, which can extract and analyze advanced and quantitative image features from medical images with high throughput for an in‐depth characterization of the spatial heterogeneity of tumor tissues. This article reviews the current imaging modalities used to predict the histopathological grade of soft tissue sarcomas and highlights the advantages and limitations of each modality. Level of Evidence: 5 Technical Efficacy: Stage 2