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构建纳米材料作为神经胶质瘤成像的对比剂或探针。

Construction of nanomaterials as contrast agents or probes for glioma imaging.

机构信息

Zhuhai Precision Medical Center, Zhuhai Interventional Medical Center, Zhuhai People's Hospital (Affiliated With Jinan University), Zhuhai, 519000, Guangdong, China.

School of Chemical Science and Engineering, Tongji University, 1239 Siping Road, Shanghai, China.

出版信息

J Nanobiotechnology. 2021 May 3;19(1):125. doi: 10.1186/s12951-021-00866-9.

DOI:10.1186/s12951-021-00866-9
PMID:33941206
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8091158/
Abstract

Malignant glioma remains incurable largely due to the aggressive and infiltrative nature, as well as the existence of blood-brain-barrier (BBB). Precise diagnosis of glioma, which aims to accurately delineate the tumor boundary for guiding surgical resection and provide reliable feedback of the therapeutic outcomes, is the critical step for successful treatment. Numerous imaging modalities have been developed for the efficient diagnosis of tumors from structural or functional aspects. However, the presence of BBB largely hampers the entrance of contrast agents (Cas) or probes into the brain, rendering the imaging performance highly compromised. The development of nanomaterials provides promising strategies for constructing nano-sized Cas or probes for accurate imaging of glioma owing to the BBB crossing ability and other unique advantages of nanomaterials, such as high loading capacity and stimuli-responsive properties. In this review, the recent progress of nanomaterials applied in single modal imaging modality and multimodal imaging for a comprehensive diagnosis is thoroughly summarized. Finally, the prospects and challenges are offered with the hope for its better development.

摘要

恶性脑胶质瘤的治疗仍然难以治愈,主要是因为其侵袭性和浸润性,以及血脑屏障(BBB)的存在。准确诊断脑胶质瘤,旨在准确描绘肿瘤边界,指导手术切除,并为治疗效果提供可靠反馈,是成功治疗的关键步骤。已经开发了许多成像方式,从结构或功能方面来有效地诊断肿瘤。然而,BBB 的存在在很大程度上阻碍了对比剂(Cas)或探针进入大脑,使得成像性能受到严重影响。纳米材料的发展为构建纳米级 Cas 或探针提供了有前途的策略,可用于准确成像脑胶质瘤,这归因于纳米材料的 BBB 穿越能力和其他独特优势,例如高负载能力和刺激响应特性。在这篇综述中,全面总结了纳米材料在单模态成像和多模态成像中的最新进展,用于综合诊断。最后,提出了前景和挑战,希望能更好地发展。

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