Imaging Beyond Seeing: Early Prognosis of Cancer Treatment. Issue 3 (18th December 2020)

• Record Type: Journal Article
• Authors: Shi, Changrong; Zhou, Zijian; Lin, Hongyu; Gao, Jinhao
• Other Names: Liu Xiang‐Yang guestEditor.; Yang Chaoyong guestEditor.; Zhou Dawang guestEditor.
• Is Part Of: Small methods. Volume 5:Issue 3(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-18
• Subjects: early prognosis -- machine learning -- molecular imaging -- precision medicine -- therapy response; Nanotechnology -- Methodology -- Periodicals; Nanotechnology -- Periodicals; Periodicals; 620.5028
• DOI: 10.1002/smtd.202001025
• Languages: English
• ISSNs: 2366-9608

Abstract

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. Abstract : In this review paper, the current development of advanced imaging technologies to predict the treatment response in cancer therapy is summarized. The noninvasive assessment of pharmacokinetic drug fates and tumor microenvironment heterogeneity by functional molecular imaging is reviewed. The practical significance of the emerging artificial intelligence technology in the applications of medical imaging is also discussed.