Internally Responsive Nanomaterials for Activatable Multimodal Imaging of Cancer. Issue 5 (21st July 2020)

• Record Type: Journal Article
• Authors: Rosenkrans, Zachary T.; Ferreira, Carolina A.; Ni, Dalong; Cai, Weibo
• Other Names: Hou Yanglong guestEditor.; Bu Wenbo guestEditor.; Ai Hua guestEditor.; Lu Zheng‐Rong guestEditor.; Lammers Twan guestEditor.
• Is Part Of: Advanced healthcare materials. Volume 10:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-07-21
• Subjects: bioresponsive materials -- internally responsive materials -- multimodal imaging -- nanomedicine; Biomedical materials -- Periodicals; 610.28
• DOI: 10.1002/adhm.202000690
• Languages: English
• ISSNs: 2192-2640

Abstract

Abstract: Advances in technology and nanomedicine have led to the development of nanoparticles that can be activated for multimodal imaging of cancer, where a stimulus induces a material modification that enhances image contrast. Multimodal imaging using nanomaterials with this capability can combine the advantages and overcome the limitations of any single imaging modality. When designed with stimuli‐responsive abilities, the target‐to‐background ratio of multimodal imaging nanoprobes increases because specific stimuli in the tumor enhance the signal. Several aspects of the tumor microenvironment can be exploited as an internal stimulus response for multimodal imaging applications, such as the pH gradient, redox processes, overproduction of various enzymes, or combinations of these. In this review, design strategies are discussed and an overview of the recent developments of internally responsive multimodal nanomaterials is provided. Properly implementing this approach improves noninvasive cancer diagnosis and staging as well as provides a method to monitor drug delivery and treatment response. Abstract : Internally responsive nanomaterials that respond to low pH, redox gradients, overexpressed enzymes, or combinations for activatable multimodal imaging have significantly advanced the nanomedicine field in recent years. Designs using this strategy maximize disease‐to‐background signals while simultaneously providing anatomical and biological information for improved disease diagnosis, treatment monitoring, or image‐guided surgical resection of diseased tissue.