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Buyck F, Vandemeulebroucke J, Ceranka J, Van Gestel F, Cornelius JF, Duerinck J, Bruneau M. Computer-vision based analysis of the neurosurgical scene - A systematic review. BRAIN & SPINE 2023; 3:102706. [PMID: 38020988 PMCID: PMC10668095 DOI: 10.1016/j.bas.2023.102706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/23/2023] [Accepted: 10/29/2023] [Indexed: 12/01/2023]
Abstract
Introduction With increasing use of robotic surgical adjuncts, artificial intelligence and augmented reality in neurosurgery, the automated analysis of digital images and videos acquired over various procedures becomes a subject of increased interest. While several computer vision (CV) methods have been developed and implemented for analyzing surgical scenes, few studies have been dedicated to neurosurgery. Research question In this work, we present a systematic literature review focusing on CV methodologies specifically applied to the analysis of neurosurgical procedures based on intra-operative images and videos. Additionally, we provide recommendations for the future developments of CV models in neurosurgery. Material and methods We conducted a systematic literature search in multiple databases until January 17, 2023, including Web of Science, PubMed, IEEE Xplore, Embase, and SpringerLink. Results We identified 17 studies employing CV algorithms on neurosurgical videos/images. The most common applications of CV were tool and neuroanatomical structure detection or characterization, and to a lesser extent, surgical workflow analysis. Convolutional neural networks (CNN) were the most frequently utilized architecture for CV models (65%), demonstrating superior performances in tool detection and segmentation. In particular, mask recurrent-CNN manifested most robust performance outcomes across different modalities. Discussion and conclusion Our systematic review demonstrates that CV models have been reported that can effectively detect and differentiate tools, surgical phases, neuroanatomical structures, as well as critical events in complex neurosurgical scenes with accuracies above 95%. Automated tool recognition contributes to objective characterization and assessment of surgical performance, with potential applications in neurosurgical training and intra-operative safety management.
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Affiliation(s)
- Félix Buyck
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), 1090, Brussels, Belgium
- Vrije Universiteit Brussel (VUB), Research group Center For Neurosciences (C4N-NEUR), 1090, Brussels, Belgium
| | - Jef Vandemeulebroucke
- Vrije Universiteit Brussel (VUB), Department of Electronics and Informatics (ETRO), 1050, Brussels, Belgium
- Department of Radiology, Universitair Ziekenhuis Brussel (UZ Brussel), 1090, Brussels, Belgium
- imec, 3001, Leuven, Belgium
| | - Jakub Ceranka
- Vrije Universiteit Brussel (VUB), Department of Electronics and Informatics (ETRO), 1050, Brussels, Belgium
- imec, 3001, Leuven, Belgium
| | - Frederick Van Gestel
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), 1090, Brussels, Belgium
- Vrije Universiteit Brussel (VUB), Research group Center For Neurosciences (C4N-NEUR), 1090, Brussels, Belgium
| | - Jan Frederick Cornelius
- Department of Neurosurgery, Medical Faculty, Heinrich-Heine-University, 40225, Düsseldorf, Germany
| | - Johnny Duerinck
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), 1090, Brussels, Belgium
- Vrije Universiteit Brussel (VUB), Research group Center For Neurosciences (C4N-NEUR), 1090, Brussels, Belgium
| | - Michaël Bruneau
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), 1090, Brussels, Belgium
- Vrije Universiteit Brussel (VUB), Research group Center For Neurosciences (C4N-NEUR), 1090, Brussels, Belgium
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Mokin M, Kan P. Balancing technical innovation and competence in the age of evidence-based medicine. J Neurointerv Surg 2022; 14:949-950. [DOI: 10.1136/jnis-2022-019579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/26/2022] [Indexed: 11/03/2022]
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Kocayiğit H, Bal NŞ. Percutaneous dilatational tracheostomy: evaluation of YouTube videos. Anaesthesist 2022; 71:219-223. [PMID: 35499614 DOI: 10.1007/s00101-022-01122-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 03/23/2022] [Accepted: 03/31/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND OBJECTIVE In today's rapidly changing world, the technology of social media is widely used for educational purposes. Our aim in this study was to investigate the accuracy and efficacy of video presentations of percutaneous dilatational tracheostomy procedures available on the international video sharing website YouTube. METHODS On 1 December 2020, the terms "percutaneous dilatational tracheostomy" and "percutaneous tracheostomy" were entered into the search feature of YouTube ( www.youtube.com ). The evaluation was made in three categories; general information about percutaneous tracheostomy, performing percutaneous tracheostomy steps and demographic features of videos. RESULTS The median number of viewings of the videos on the date our data were collected was 1342 (IQR, 237-8052), and the most watched video had been viewed 325,170 times. Surgical site cleaning was explained in 46 (65.7%) videos and incision site detection in 55 (78.6%) videos. Needle aspiration into the trachea, insertion of the Seldinger guidewire, dilatation, and tracheal tube placement were covered in all videos (70; 100%). Confirmation of the location of the tracheal tube with end tidal capnography, the last step of the procedure, is available in 34 videos (48.6%). CONCLUSION The use of inexpensive or freely available teaching materials is possible but should always be checked before use with respect to the completeness and correctness of the content conveyed. The unreflected adoption of such content can lead to serious treatment errors.
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Affiliation(s)
- Havva Kocayiğit
- Department of Anaesthesiology and Reanimation, Sakarya University Education and Research Hospital, Adnan Menderes Caddesi Saglik Sokak., 54100, Sakarya, Turkey.
| | - Nevcihan Şahutoğlu Bal
- Department of Anaesthesiology and Reanimation, Yıldırım Bayezit University Yenimahalle Education and Research Hospital, Sakarya, Turkey
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Wu H, Wang Z, Li M, Sun P, Zhang L, Zhang C, Wei S, Xie B, Lou C, Qiao Z, Liu Y, Bai T, Bai H. The Current State of Vascular Surgery Presence in Bilibili Video Platform of China. Front Surg 2022; 9:874113. [PMID: 35574551 PMCID: PMC9096722 DOI: 10.3389/fsurg.2022.874113] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 04/06/2022] [Indexed: 11/13/2022] Open
Abstract
Background With the development of the Internet, more and more patients search for disease-related information on video platforms during the treatment process, and physicians also look for learning materials through these video platforms. Bilibili is one of the most popular video platforms in China. This study evaluated information on various interesting topics, and related surgical procedures searched through Bilibili. Method The Bilibili platform was independently queried for 12 common vascular diseases or related surgical procedures between October and November 2021 by two independent authors using the Baidu search engine. Information about the video and uploader was collected, and descriptive analyses of the overall and first-page results were performed. Results A total of 3,998 search results were retrieved by searching 12 vascular-related topics, of which 2,225 actual videos (55.7%) were finally confirmed to be related to medicine. Videos for the public accounted for 84.8% of these 2,225 videos. In addition, 50.5% of the video results were uploaded by vascular surgeons, 12.4% by other specialties, 17.7% by organizations, and 19.4% by other individuals. The total number of videos searched for varicose vein and peripheral vascular diseases was the largest, and the total number of leg amputation videos was the smallest. The largest number of videos for medical professionals was about pulmonary embolism, and the smallest was about leg amputation. On the first pages, 168 results (70.0%) were actually medically relevant, and only 7.7% of the videos were uploaded by vascular surgeons. Conclusion On the Bilibili platform, videos about vascular diseases are extensive but not comprehensive. The videos uploaded by vascular surgeons are rare, and the results searched are not precise. The online presence of vascular surgeons needs to be improved, which may partially solve the problem of low-quality videos due to the lack of strict management and censorship.
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Affiliation(s)
- Haoliang Wu
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
- Key Vascular Physiology and Applied Research Laboratory of Zhengzhou City, Henan, China
| | - Zhiwei Wang
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Mingxing Li
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Peng Sun
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Liwei Zhang
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Cong Zhang
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Shunbo Wei
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Boao Xie
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Chunyang Lou
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Zhentao Qiao
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Yuanfeng Liu
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Tao Bai
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
| | - Hualong Bai
- Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Henan, China
- Key Vascular Physiology and Applied Research Laboratory of Zhengzhou City, Henan, China
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Kanmounye US. Commentary: Step-by-Step Guide on How to Make a 2-Dimensional Operative Neurosurgical Video: Microsurgical Resection of Right Lateral Ventricle Subependymoma via Anterior Interhemispheric Transcallosal Approach. Oper Neurosurg (Hagerstown) 2022; 22:e120-e121. [PMID: 35042226 DOI: 10.1227/ons.0000000000000081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 10/03/2021] [Indexed: 11/19/2022] Open
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Pojskić M, Nguyen VN, Gienapp AJ, Arnautović KI. Step-by-Step Guide on How to Make a 2-Dimensional Operative Neurosurgical Video: Microsurgical Resection of a Right Lateral Ventricle Subependymoma by an Anterior Interhemispheric Transcallosal Approach. Oper Neurosurg (Hagerstown) 2022; 22:165-170. [PMID: 35042224 DOI: 10.1227/ons.0000000000000073] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 09/13/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Digital video recordings are increasingly used across various medical and surgical disciplines with advances in computer hardware and software technologies. The creation of high-quality surgical video footage requires a basic understanding of key technical considerations, together with creativity and sound aesthetic judgment. Online operative videos have become a core resource within neurosurgical education. OBJECTIVE To provide a step-by-step description for making operative videos using a video from a real case as an example. METHODS We recorded an operative video of the microsurgical resection of a right lateral ventricle subependymoma performed by an anterior interhemispheric transcallosal approach. The patient consented to surgical resection of the subependymoma and to publication of this operative video. With the video, we explain the step-by-step process the authors used for developing the raw video into a publishable surgical video. RESULTS The patient depicted in our video tolerated the surgery well and made a complete recovery. The final video produced from the surgery illustrated elements that Operative Neurosurgery, Neurosurgery, and other journals require in surgical videos. CONCLUSION Although more than 1200 peer-reviewed (PubMed) neurosurgical operative videos have been published so far, there has not been a single publication that describes the step-by-step process of producing an operative video. To the best of our knowledge, this is the first published detailed description of editing of an educational operative video in neurosurgery and the first video case report of a microsurgical resection of subependymoma of the lateral ventricle in the peer-reviewed English literature.
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Affiliation(s)
- Mirza Pojskić
- Department of Neurosurgery, University of Marburg, Marburg, Germany.,Faculty of Medicine, Josip Juraj Strossmayer University, Osijek, Croatia
| | - Vincent N Nguyen
- Semmes Murphey Neurologic and Spine Institute, Memphis, Tennessee, USA.,Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Andrew J Gienapp
- Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, Tennessee, USA.,Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, Tennessee, USA
| | - Kenan I Arnautović
- Semmes Murphey Neurologic and Spine Institute, Memphis, Tennessee, USA.,Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, Tennessee, USA
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