An Update in Imaging Evaluation of Histopathological Grade of Soft Tissue Sarcomas Using Structural and Quantitative Imaging and Radiomics

J Magn Reson Imaging. 2022 May;55(5):1357-1375. doi: 10.1002/jmri.27954. Epub 2021 Oct 12.

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.

Keywords: functional magnetic resonance imaging; histopathological grade; radiomics; soft tissue sarcomas; structural magnetic resonance imaging.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence
  • Diffusion Magnetic Resonance Imaging / methods
  • Humans
  • Magnetic Resonance Imaging / methods
  • Retrospective Studies
  • Sarcoma* / diagnostic imaging
  • Sarcoma* / pathology
  • Soft Tissue Neoplasms* / pathology