Open AccessFunctional endoscopy techniques for tracking stem cell fate
Author(s) -
Yusi Miao,
Zhongping Chen,
Shengwen Calvin Li
Publication year - 2019
Publication title -
quantitative imaging in medicine and surgery
Language(s) - Uncategorized
Resource type - Journals
eISSN - 2223-4292
pISSN - 2223-4306
DOI - 10.21037/qims.2019.02.12
Subject(s) - molecular imaging , preclinical imaging , stem cell , positron emission tomography , magnetic resonance imaging , biomedical engineering , functional imaging , optical coherence tomography , optical imaging , in vivo , computer science , medicine , nuclear medicine , radiology , biology , optics , physics , microbiology and biotechnology
Tracking and monitoring implanted stem cells are essential to maximize benefits and to minimize the side effects of stem cell therapy for personalized or "precision" medicine. Previously, we proposed a comprehensive biological Global Positioning System (bGPS) to track and monitor stem cells in vivo . Magnetic resonance imaging (MRI), positron emission tomography (PET), bioluminescent imaging, fluorescence imaging, and single-photon emission computerized tomography (SPECT) have been utilized to track labeled or genetically-modified cells in vivo in rats and humans. A large amount of research has been dedicated to the design of reporter genes and molecular probes for imaging and the visualization of the biodistribution of the implanted cells in high resolution. On the other hand, optical-based functional imaging, such as photoacoustic imaging (PAI), optical coherence tomography (OCT), and multiphoton microscopy (MPM), has been implemented into small endoscopes to image cells inside the body. The optical fiber allows miniaturization of the imaging probe while maintaining high resolution due to light-based imaging. Upon summarizing the recent progress in the design and application of functional endoscopy techniques for stem cell monitoring, we offer perspectives for the future development of endoscopic molecular imaging tools for in vivo tracking of spatiotemporal changes in subclonal evolution at the single cell level.