0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Designing Smart Iron Oxide Nanoparticles for MR Imaging of Tumors

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Iron oxide nanoparticles (IONPs) possess unique magnetism and good biocompatibility, and they have been widely applied as contrast agents (CAs) for magnetic resonance imaging (MRI). Traditional CAs typically show a fixed enhanced signal, thus exhibiting the limitations of low sensitivity and a lack of specificity. Nowadays, the progress of stimulus-responsive IONPs allows alteration of the relaxation signal in response to internal stimuli of the tumor, or external stimuli, thus providing an opportunity to overcome those limitations. This review summarizes the current status of smart IONPs as tumor imaging MRI CAs that exhibit responsiveness to endogenous stimuli, such as pH, hypoxia, glutathione, and enzymes, or exogenous stimuli, such as magnets, light, and so on. We discuss the challenges and future opportunities for IONPs as MRI CAs and comprehensively illustrate the applications of these stimuli-responsive IONPs. This review will help provide guidance for designing IONPs as MRI CAs and further promote the reasonable design of magnetic nanoparticles and achieve early and accurate tumor detection.

          Related collections

          Most cited references171

          • Record: found
          • Abstract: found
          • Article: not found

          Radiomics: Images Are More than Pictures, They Are Data

          This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Cancer metabolism: looking forward

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Artificial intelligence in cancer imaging: Clinical challenges and applications

              Abstract Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.
                Bookmark

                Author and article information

                Journal
                Chem Biomed Eng
                Chem Biomed Eng
                im
                cbihbp
                Chemical & Biomedical Imaging
                Nanjing University and American Chemical Society
                2832-3637
                04 May 2023
                24 July 2023
                : 1
                : 4
                : 315-339
                Affiliations
                []CAS Key Laboratory for Biomedical Effects of Nanoparticles and Nanosafety & CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology , Beijing 100190, China
                []Department of Radiology, Beijing Tongren Hospital, Capital Medical University , Beijing 100730, China
                [§ ]University of Chinese Academy of Sciences , Beijing 100049, China
                []Research Unit of Nanoscience and Technology, Chinese Academy of Medical Sciences , Beijing 100021, China
                []The GBA National Institute for Nanotechnology Innovation , Guangzhou 510700, China
                [# ]Guangdong Provincial Development and Reform Commission , Guangzhou 510031, China
                Author notes
                Author information
                https://orcid.org/0000-0001-6210-0566
                https://orcid.org/0000-0002-6027-0315
                Article
                10.1021/cbmi.3c00026
                10369497
                37501794
                6e1fc9c3-d98e-49c5-8770-975d2e7df75f
                © 2023 The Authors. Co-published by Nanjing University and American Chemical Society

                Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works ( https://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 13 February 2023
                : 21 April 2023
                : 14 April 2023
                Funding
                Funded by: Guangdong Province Introduction of Innovative R&D Team, doi 10.13039/100012540;
                Award ID: 2019B090917011
                Funded by: Beijing Municipal Administration of Hospitals, doi 10.13039/501100009601;
                Award ID: DFL20190203
                Funded by: Chinese Academy of Medical Sciences, doi 10.13039/501100005150;
                Award ID: CIFMS 2019-I2M-5-018
                Funded by: Ministry of Science and Technology of the People''s Republic of China, doi 10.13039/501100002855;
                Award ID: 2021YFA1200900
                Funded by: Chinese Academy of Sciences, doi 10.13039/501100002367;
                Award ID: ZDBS-LY-SLH039
                Funded by: Chinese Academy of Sciences, doi 10.13039/501100002367;
                Award ID: XDB36000000
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Award ID: 32000983
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Award ID: 22027810
                Categories
                Review
                Custom metadata
                im3c00026
                im3c00026

                iron oxide nanoparticles,magnetic resonance imaging,contrast agent,tumor imaging,stimuli-responsive nanomaterials,internal stimuli,external stimuli,dual-mode imaging

                Comments

                Comment on this article