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光声成像作为一种用于评估脑部疾病的高效且精确的成像策略。

Photoacoustic imaging as a highly efficient and precise imaging strategy for the evaluation of brain diseases.

作者信息

Qiu Ting, Lan Yintao, Gao Weijian, Zhou Mengyu, Liu Shiqi, Huang Wenyan, Zeng Sujuan, Pathak Janak L, Yang Bin, Zhang Jian

机构信息

Department of Biomedical Engineering, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China.

Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China.

出版信息

Quant Imaging Med Surg. 2021 May;11(5):2169-2186. doi: 10.21037/qims-20-845.

Abstract

Photoacoustic imaging (PAI) is an emerging imaging strategy with a unique combination of rich optical contrasts, high ultrasound spatial resolution, and deep penetration depth without ionizing radiation. Taking advantage of the features mentioned above, PAI has been widely applied to preclinical studies in diverse fields, such as vascular biology, cardiology, neurology, ophthalmology, dermatology, gastroenterology, and oncology. Among various biomedical applications, photoacoustic brain imaging has great importance due to the brain's complex anatomy and the variability of brain disease. In this review, we aimed to introduce a novel and effective imaging modality for diagnosing brain diseases. Firstly, a brief overview of two major types of PAI system was provided. Then, PAI's major preclinical applications in brain diseases were introduced, including early diagnosis of brain tumors, subtle changes in the chemotherapy response, epileptic activity and brain injury, foreign body, and brain plaque. Finally, a perspective of the remaining challenges of PAI was given for future advancements.

摘要

光声成像(PAI)是一种新兴的成像策略,它独特地结合了丰富的光学对比度、高超声空间分辨率以及无电离辐射的深穿透深度。利用上述特性,PAI已广泛应用于血管生物学、心脏病学、神经学、眼科、皮肤科、胃肠病学和肿瘤学等不同领域的临床前研究。在各种生物医学应用中,由于大脑复杂的解剖结构和脑部疾病的变异性,光声脑成像具有重要意义。在本综述中,我们旨在介绍一种用于诊断脑部疾病的新型有效成像方式。首先,简要概述了PAI系统的两种主要类型。然后,介绍了PAI在脑部疾病中的主要临床前应用,包括脑肿瘤的早期诊断、化疗反应的细微变化、癫痫活动和脑损伤、异物以及脑斑块。最后,对PAI未来发展中尚存的挑战进行了展望。

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