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Li J, Shang C, Rong Y, Sun J, Cheng Y, He B, Wang Z, Li M, Ma J, Fu B, Ji X. Review on Laser Technology in Intravascular Imaging and Treatment. Aging Dis 2022; 13:246-266. [PMID: 35111372 PMCID: PMC8782552 DOI: 10.14336/ad.2021.0711] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 07/11/2021] [Indexed: 12/14/2022] Open
Abstract
Blood vessels are one of the most essential organs, which nourish all tissues in our body. Once there are intravascular plaques or vascular occlusion, other organs and circulatory systems will not work properly. Therefore, it is necessary to detect abnormal blood vessels by intravascular imaging technologies for subsequent vascular treatment. The emergence of lasers and fiber optics promotes the development of intravascular imaging and treatment. Laser imaging techniques can obtain deep vascular images owing to light scattering and absorption properties. Moreover, photothermal and photomechanical effects of laser make it possible to treat vascular diseases accurately. In this review, we present the research progress and applications of laser techniques in intravascular imaging and treatment. Firstly, we introduce intravascular optical coherent tomography and intravascular photoacoustic imaging, which can obtain various information of plaques. Multimodal intravascular imaging techniques provide more information about intravascular plaques, which have an essential influence on intravascular imaging. Secondly, two laser techniques including laser angioplasty and endovenous laser ablation are discussed for the treatment of arterial and venous diseases, respectively. Finally, the outlook of laser techniques in blood vessels, as well as the integration of laser imaging and treatment are prospected in the section of discussions.
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Affiliation(s)
- Jing Li
- BUAA-CCMU Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China.
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
| | - Ce Shang
- BUAA-CCMU Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China.
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
| | - Yao Rong
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.
- Medical Engineering Devices of Xuanwu Hospital, Capital Medical University, Beijing, China.
| | - Jingxuan Sun
- BUAA-CCMU Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China.
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.
| | - Yuan Cheng
- BUAA-CCMU Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China.
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.
| | - Boqu He
- BUAA-CCMU Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China.
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.
| | - Zihao Wang
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.
| | - Ming Li
- China-America Institute of Neuroscience, Xuanwu Hospital, Capital Medical University, Beijing, China.
| | - Jianguo Ma
- BUAA-CCMU Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China.
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.
| | - Bo Fu
- BUAA-CCMU Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China.
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.
- Key Laboratory of Big Data-Based Precision Medicine Ministry of Industry and Information Technology, Interdisciplinary Innovation Institute of Medicine and Engineering, Beihang University, Beijing, China.
| | - Xunming Ji
- BUAA-CCMU Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China.
- China-America Institute of Neuroscience, Xuanwu Hospital, Capital Medical University, Beijing, China.
- Neurosurgery Department of Xuanwu Hospital, Capital Medical University, Beijing, China.
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[Innovations in the endovascular treatment of peripheral arterial disease]. GEFASSCHIRURGIE 2021; 26:347-358. [PMID: 34404965 PMCID: PMC8361829 DOI: 10.1007/s00772-021-00802-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 06/29/2021] [Indexed: 11/09/2022]
Abstract
Die Kooperation von Medizinern, Ingenieuren und anderen Naturwissenschaften bringt weiterhin effektive Produkte auf den Markt, die dazu geeignet sind, die Dominanz der endovaskulären Techniken im Bereich der peripheren arteriellen Verschlusskrankheit (pAVK) weiter auszubauen. Begleitend werden zunehmend bildgebende Verfahren weiterentwickelt oder neu entwickelt, die helfen können, die Strahlenbelastung für Patient und Anwender trotz wachsender Zahlen strahlenbasierter Therapieverfahren deutlich zu reduzieren. Mittlerweile haben wir ein Materialportfolio an der Hand, das es erlaubt, jede Gefäßregion endovaskulär zu behandeln. Auf der anderen Seite dürfte das endovaskuläre Leistungsgefüge nicht flächendeckend homogen gestaltet sein und die jeweilige Ergebnisqualität dann für die Chirurgie sprechen. In diesem Übersichtsartikel sollen neue Materialien und neuere Ergebnisse vorgestellt werden, die den Bereich der endovaskulären Behandlung der pAVK in allen Gefäßsegmenten mit beeinflussen dürften.
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