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In Vivo Photoacoustic Sentinel Lymph Node Imaging Using Clinically-Approved Carbon Nanoparticles

前哨淋巴结 吲哚青绿 活检 医学 医学物理学 放射科 病理 癌症 内科学 乳腺癌
作者
Songde Liu,Hang Wang,Chenxi Zhang,Jiangning Dong,Shengchun Liu,Ronald X. Xu,Chao Tian
出处
期刊:IEEE Transactions on Biomedical Engineering [Institute of Electrical and Electronics Engineers]
卷期号:: 1-1 被引量:30
标识
DOI:10.1109/tbme.2019.2953743
摘要

Objective: Breast cancer is the most common type of invasive cancer and one of the leading causes of cancer death in women worldwide. Correct staging of breast cancer is critical to the survival rate of the patients. Sentinel lymph node (SLN) biopsy (SLNB), currently the gold standard technique for breast cancer staging, requires preoperative and intraoperative image guidance for noninvasive SLN identification and minimal surgical invasion. However, existing image guidance techniques suffer from a variety of limitations, such as ionizing radiation, high cost, and poor imaging depth. To address the clinical challenges, new methodology has to be developed. Methods: We developed a photoacoustic (PA) imaging procedure for noninvasive and nonradioactive SLN identification and biopsy guidance enhanced with a clinically-approved lymphatic tracer, i.e., carbon nanoparticles (CNPs) suspension injection. Results: In vivo experiments show that the proposed procedure could sensitively identify the SLN and provide high-contrast image guidance for fine-needle aspiration simulation. In addition, we demonstrated that CNPs have significantly better performance than other commonly-used contrast agents, such as methylene blue and indocyanine green. Conclusion: PA imaging technique using clinically-approved CNPs as the contrast agent is capable for noninvasive and nonradioactive SLN identification and high-contrast biopsy guidance, and should be considered as a new tool for assisting SLNB in breast cancer staging. Significance: The proposed CNPs-enhanced PA imaging technique provides a practical way for SLN identification and biopsy guidance for breast cancer patients and paves the way for clinical translation of PA SLN imaging.
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