Optical and Photoacoustic Imaging.

Q3 Medicine
Joanna Napp, Andrea Markus, Frauke Alves
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引用次数: 0

Abstract

Optical imaging is crucial in preclinical evaluation of tumor development, progression, and therapies, due to its low cost, versatility, sensitivity, and capability of real-time monitoring. The main in vivo imaging techniques include fluorescence, bioluminescence, and photoacoustic imaging. Although all three applications are limited by relatively low tissue penetration due to absorption and scattering of light in biological tissues, each application has its own benefits. Fluorescence imaging is technically the simplest method to perform and using near infrared fluorescent (NIRF) probes can enhance depth capability. Moreover, novel activatable probes, lifetime imaging, and multimodal imaging strategies have extended its utility to endoscopic and surgical procedures. Bioluminescence imaging boasts high sensitivity and signal-to-noise ratio, as light emission originates at the target from enzymatic reactions. However, it requires genetic modification to express luciferases, restricting its use in humans. Photoacoustic imaging offers better depth penetration compared to purely optical methods by utilizing ultrasound signals. Leveraging endogenous contrast from chromophores, it assists in vascular imaging and tumor identification without external labels. Due to the use of safe, non-ionizing radiation, it reduces the risk to subjects and allows repeated imaging, and is thus most suited for clinical translation. All three applications continuously benefit from the development of three-dimensional imaging techniques and deep learning algorithms.

光学和光声成像。
光学成像由于其低成本、多功能性、灵敏度和实时监测能力,在肿瘤发生、进展和治疗的临床前评估中至关重要。主要的体内成像技术包括荧光、生物发光和光声成像。尽管这三种应用都受到生物组织中光的吸收和散射导致的相对较低的组织穿透性的限制,但每种应用都有自己的优点。荧光成像是技术上最简单的方法,使用近红外荧光(NIRF)探针可以增强深度能力。此外,新型可激活探针、终身成像和多模态成像策略已将其应用于内窥镜和外科手术。生物发光成像具有高灵敏度和高信噪比,因为光发射源于酶促反应的目标。然而,它需要基因改造来表达荧光素酶,限制了它在人类中的应用。光声成像利用超声信号提供了比纯光学方法更好的深度穿透。利用来自发色团的内源性对比,它有助于血管成像和肿瘤识别,而无需外部标签。由于使用安全的非电离辐射,它降低了受试者的风险,并允许重复成像,因此最适合临床转译。这三种应用都不断受益于三维成像技术和深度学习算法的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.60
自引率
0.00%
发文量
0
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