Robot Versus Fluoroscopy-Assisted Vertebroplasty and Kyphoplasty for Osteoporotic Vertebral Compression Fractures: A Systematic Review and Meta-analysis

Zhang, Yu; Peng, Qing; Sun, Chenhao; Kang, Xiaohe; Hu, Man; Zhao, Wei; Liu, Xin; Meng, Bo; Yang, Shiwen; Feng, Xiaoshan; Zhang, Liang

doi:10.1016/j.wneu.2022.07.083

Cited by 8 publications

(2 citation statements)

References 29 publications

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“…Being robot-assisted navigation a new technological tool, it could be possible to hypothesize that surgeons will become more confident with time, with shorten of the length of surgery compared to FA-PVA. Interestingly, clinical outcome reported using VAS (Visual Analog Score) and ODI (Oswestry Disability Index) had similar results ( 23 ).…”

mentioning

confidence: 79%

Percutaneous vertebral augmentation—pearls and pitfalls

Espahbodinea¹,

Ku²,

Alves³

et al. 2023

J Spine Surg

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mentioning

confidence: 79%

Percutaneous vertebral augmentation—pearls and pitfalls

Espahbodinea¹,

Ku²,

Alves³

et al. 2023

J Spine Surg

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“…In our meta-analysis, we also found that robotassisted surgery resulted in less radiation exposure than fluoroscopy-assisted surgery and reduced bone cement leakage. 35 Spinal surgery usually requires delicate manipulation of key structures, often accessed through minimally invasive channels. The application of image-guided robot-assisted spinal surgery enables surgeons to visualize and navigate complex anatomical structures during the planning…”

Section: Accepted Manuscriptmentioning

confidence: 99%

A Bibliometric Analysis of Artificial Intelligence Applications in Spine Care

Zhang

Zhao

et al. 2023

J Neurol Surg A Cent Eur Neurosurg

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Background With the rapid development of science and technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis analysis of various spine diseases. It has been proved that AI has a broad prospect in the accurate diagnosis and treatment of spine field. Methods On May 07, 2022, the Web of Science (WOS) Core Collection database was used to identify the documents on the application of AI in spine field. HistCite and VOSviewer softwares were used for citation analysis and visualization mapping. Results A total of 693 documents were included in the final analysis. The most prolific authors were Karhade AV and Schwab JH. The USA was the most productive country. The leading journal was Spine. The most frequently used keyword was spinal. The most prolific institution was Northwestern Univ. Network visualization map showed that USA was the largest network of international cooperation. The keyword “machine learning” had the strongest total link strengths (TLS) and largest number of occurrences. The latest trends suggest that AI for the diagnosis of spine diseases may receive widespread attention in the future. Conclusions AI has a wide range of application prospect in the subject of spine field, and an increasing number of scholars are committed to the research of AI in spine field. Bibliometric analysis in the field of AI and spine provides an overall perspective, and the appreciation and research of these influential publications are useful for future research.

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