Clinical Application of Computer-Assisted Second Near-Infrared Window Fluorescence Angiography in Surgical Creation of Hemodialysis Access

被引:0
|
作者
Li Lingbing [1 ,2 ]
Fu Lidan [2 ,3 ]
Shi Xiaojing [2 ]
Wang Yuanda [4 ]
Wang Zhijun [1 ,4 ,5 ]
Hu Zhenhua [2 ,5 ]
机构
[1] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 2, Beijing 100853, Peoples R China
[2] Chinese Acad Sci, Inst Automat, Beijing Key Lab Mol Imaging, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
[3] Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
[4] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Beijing 100853, Peoples R China
[5] Chinese Peoples Liberat Army Gen Hosp, Natl Key Lab Kidney Dis, Beijing 100853, Peoples R China
来源
关键词
medical optics; NIR-II fluorescence; fluorescence angiography; indocyanine green; artificial intelligence; computational simulation; TISSUE PERFUSION;
D O I
10.3788/CJL231471
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Objective Vascular imaging is crucial for medical diagnosis, and it facilitates disease diagnosis, disease progression monitoring, surgical planning and navigation, and patient prognosis evaluation. However, conventional imaging methods encounter challenges in rapid and noninvasively imaging of superficial blood vessels because of the similarities in texture and color with surrounding tissues. In clinical surgery, preoperative superficial vascular imaging and intraoperative vascular display are beneficial for reducing bleeding, facilitating surgical navigation and path planning, and promoting postoperative blood supply recovery. Methods A fluorescent imaging system in the second near- infrared window (NIR-II) to capture images of the forearm vascular network in patients was used in this study. The research involved 12 patients, with indocyanine green serving as a contrast agent for obtaining NIR-II images of the forearm blood vessels. These images were used to observe the anatomical structure of the venous vascular network. Furthermore, computer- aided analysis was employed to improve image quality, support surgical path planning and prognosis prediction, and provide valuable guidance for clinical practitioners. Results and Discussions High-resolution and high-contrast images are captured using NIR-II fluorescence angiography. The clarity of these images are enhanced using artificial intelligence techniques. Computer simulation was employed to simulate venous network reflux. The agreement between the measurement results obtained from this technique and ultrasound was evaluated using the Bland Altman plot and consistency measurements. Conclusions The acquired images are used to examine the anatomical structure of the venous vascular network and combined with blood flow simulation. This integration aims to assist clinicians in determining optimal surgical trajectories and predicting outcomes. The application of NIR-II fluorescence imaging and computational simulation techniques has potential in providing valuable support for surgeons in performing various vascular procedures in the future.
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页数:7
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