Imaging Beyond Seeing: Early Prognosis of Cancer Treatment.

Journal: Small methods
Published Date: Dec 18, 2020

Abstract

Assessing cancer response to therapeutic interventions has been realized as an important course to early predict curative efficacy and treatment outcomes due to tumor heterogeneity. Compared to the traditional invasive tissue biopsy method, molecular imaging techniques have fundamentally revolutionized the ability to evaluate cancer response in a spatiotemporal manner. The past few years has witnessed a paradigm shift on the efforts from manufacturing functional molecular imaging probes for seeing a tumor to a vantage stage of interpreting the tumor response during different treatments. This review is to stand by the current development of advanced imaging technologies aiming to predict the treatment response in cancer therapy. Special interest is placed on the systems that are able to provide rapid and noninvasive assessment of pharmacokinetic drug fates (e.g., drug distribution, release, and activation) and tumor microenvironment heterogeneity (e.g., tumor cells, macrophages, dendritic cells (DCs), T cells, and inflammatory cells). The current status, practical significance, and future challenges of the emerging artificial intelligence (AI) technology and machine learning in the applications of medical imaging fields is overviewed. Ultimately, the authors hope that this review is timely to spur research interest in molecular imaging and precision medicine.

Authors

  • Changrong Shi
    State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics and Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China.
  • Zijian Zhou
    State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics and Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China.
  • Hongyu Lin
    State Key Laboratory of Physical Chemistry of Solid Surfaces, The Key Laboratory for Chemical Biology of Fujian Province and Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.
  • Jinhao Gao
    State Key Laboratory of Physical Chemistry of Solid Surfaces, The Key Laboratory for Chemical Biology of Fujian Province and Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.

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