学位论文详细信息
Development of multi-modality polymer-coated quantum dots for cancer imaging
Quantum dots;Multi-modality;Cancer imaging;Hyaluronic Acid
Wang, Hening ; Ren, Qiushi Nie, Shuming Biomedical Engineering (Joint GT/Emory Department) Li, Changhui Xi, Peng Liu, Xiaodong ; Ren, Qiushi
University:Georgia Institute of Technology
Department:Biomedical Engineering (Joint GT/Emory Department)
关键词: Quantum dots;    Multi-modality;    Cancer imaging;    Hyaluronic Acid;   
Others  :  https://smartech.gatech.edu/bitstream/1853/55611/1/WANG-DISSERTATION-2016.pdf
美国|英语
来源: SMARTech Repository
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【 摘 要 】

Cancer has become a large threat to people’s health and lives in the world. It is very important if we can achieve the early diagnosis of cancer, which can significantly reduce cancer mortality and improve the life quality of patients. Nanotechnology is currently widely used in cancer diagnosis and treatment. Nanometer-sized Quantum Dots have intrinsic optical, electronic, and structural properties therefore they have found many applications in the bio-medical imaging field. For better applications, we need the QDs to have excellent water-stability, biocompatibility and even targeting ability. Here, we design and develop novel biocompatible Hyaluronic acid polymer coated QDs for CD44+ cancer targeted imaging. The resulted QDs not only have good water solubility, biocompatibility, strong stability, but also achieved CD44 receptor targeted cancer cell imaging. The development of multi-modal imaging equipment requires the design for multi-modality imaging probes. We synthesized DTPA and DOTA chelating agent conjugated hyaluronic acid, which can couple magnetic resonance imaging elements-Gd, and PET isotopes-Cu respectively to make a NIR / MR or NIR / PET dual-modality imaging probes. The multi-modality imaging probe holds the ability for fluorescence imaging, magnetic resonance imaging and PET imaging which can complement the advantages of different imaging modality and help to enhance tumor identification and diagnostic capabilities. We expect our novel method to have broad applications in biomedical imaging research, for the realization of precise diagnosis of tumors, as well as to promote personalized medicine.

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