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Zhuang YD, Li RJ, Wu JJ, He XW, Zou WB, Xu XC, Lu SQ, Chen CM. Multi-angle laser device improves novice learning of C-arm fluoroscopy for lumbar spine surgery. PLoS One 2024; 19:e0299273. [PMID: 38452128 PMCID: PMC10919629 DOI: 10.1371/journal.pone.0299273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 02/07/2024] [Indexed: 03/09/2024] Open
Abstract
PURPOSE This study aims to evaluate the efficacy and satisfaction of using a multi-angle laser device (MLD) for C-arm fluoroscopy to assist novice learners during lumbar spine surgery. METHODS Forty novice learners were randomly assigned to Group A using an MLD-equipped C-arm or Group B using a traditional C-arm. Both groups performed X-ray fluoroscopy on a lumbar spine model in supine and rotated positions. Time, number of shots, and deviation from the target were compared. A questionnaire was used to assess the learning experience. RESULTS Group A required less time (13.66 vs. 25.63 min), and fewer shots (15.05 vs. 32.50), and had a smaller deviation (22.9% vs. 61.5%) than Group B (all p<0.05). The questionnaire revealed higher scores in Group A for comfort, efficiency, and knowledge mastery (all p<0.05). CONCLUSION The MLD significantly improves novice learning of C-arm fluoroscopy during lumbar spine surgery.
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Affiliation(s)
- Yuan-Dong Zhuang
- Department of Neurosurgery, Fujian Institute of Neurosurgery, Fujian Medical University Union Hospital, Gulou District, Fuzhou, Fujian, China
| | - Rui-Jin Li
- Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Jia-Jun Wu
- Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Xue-Wei He
- Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Wen-Bin Zou
- Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Xu-Chu Xu
- Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Si-Qi Lu
- Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Chun-Mei Chen
- Department of Neurosurgery, Fujian Institute of Neurosurgery, Fujian Medical University Union Hospital, Gulou District, Fuzhou, Fujian, China
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Müller PC, Haslebacher C, Steinemann DC, Müller-Stich BP, Hackert T, Peterhans M, Eigl B. Image-guided minimally invasive endopancreatic surgery using a computer-assisted navigation system. Surg Endosc 2020; 35:1610-1617. [PMID: 32253555 DOI: 10.1007/s00464-020-07540-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 03/31/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND Minimally invasive endopancreatic surgery (EPS), performing a pancreatic resection from inside the pancreatic duct, has been proposed as an experimental alternative to duodenum-preserving pancreatic head resection in benign diseases such as chronic pancreatitis, but is complicated by difficult spatial orientation when trying to reach structures of interest. This study assessed the feasibility and potential benefits of image-guided EPS using a computer-assisted navigation system in artificial pancreas silicon model. METHODS A surgical navigation system displayed a 3D reconstruction of the original computed tomography (CT) scan and the endoscope in relation to a selected target structure. In a first step, different surface landmark (LM)-based and intraparenchymal LM-based approaches for image-to-physical space registration were evaluated. The accuracy of registration was measured as fiducial registration error (FRE). Subsequently, intrapancreatic lesions (n = 8) that were visible on preoperative imaging, but not on the endoscopic view, were targeted with a computer-assisted, image-guided endopancreatic resection technique in pancreas silicon models. After each experiment, a CT scan was obtained for measurement of the shortest distance from the resection cavity to the centre of the lesion. RESULTS Intraparenchymal LM registration [FRE 2.24 mm (1.40-2.85)] was more accurate than surface LM registration [FRE 3.46 mm (2.25-4.85); p = 0.035], but not more accurate than combined registration of intraparenchymal and surface LM [FRE 2.46 mm (1.60-3.35); p = 0.052]. Using image-guided EPS, six of seven lesions were successfully targeted. The median distance from the resection cavity to the centre of the lesion on CT was 1.52 mm (0-2.4). In one pancreas, a lesion could not be resected due to the fragility of the pancreas model. CONCLUSION Image-guided minimally invasive EPS using a computer-assisted navigation system enabled successful targeting of pancreatic lesions that were invisible on the endoscopic image, but detectable on preoperative imaging. In the clinical setting, this tool could facilitate complex minimally invasive and robotic pancreatic procedures.
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Affiliation(s)
- Philip C Müller
- Department of Visceral and Transplant Surgery, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland.
| | | | - Daniel C Steinemann
- Department of Surgery, Clarunis, University Hospital Basel, Basel, Switzerland
| | - Beat P Müller-Stich
- Department of General, Visceral and Transplantation Surgery, University Hospital Heidelberg, Heidelberg, Germany
| | - Thilo Hackert
- Department of General, Visceral and Transplantation Surgery, University Hospital Heidelberg, Heidelberg, Germany
| | | | - Benjamin Eigl
- CAScination AG, Bern, Switzerland.,ARTORG Center for Computer-Aided Surgery, University of Bern, Bern, Switzerland
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Dias RD, Ngo-Howard MC, Boskovski MT, Zenati MA, Yule SJ. Systematic review of measurement tools to assess surgeons' intraoperative cognitive workload. Br J Surg 2018; 105:491-501. [PMID: 29465749 PMCID: PMC5878696 DOI: 10.1002/bjs.10795] [Citation(s) in RCA: 108] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Revised: 10/09/2017] [Accepted: 11/17/2017] [Indexed: 12/25/2022]
Abstract
BACKGROUND Surgeons in the operating theatre deal constantly with high-demand tasks that require simultaneous processing of a large amount of information. In certain situations, high cognitive load occurs, which may impact negatively on a surgeon's performance. This systematic review aims to provide a comprehensive understanding of the different methods used to assess surgeons' cognitive load, and a critique of the reliability and validity of current assessment metrics. METHODS A search strategy encompassing MEDLINE, Embase, Web of Science, PsycINFO, ACM Digital Library, IEEE Xplore, PROSPERO and the Cochrane database was developed to identify peer-reviewed articles published from inception to November 2016. Quality was assessed by using the Medical Education Research Study Quality Instrument (MERSQI). A summary table was created to describe study design, setting, specialty, participants, cognitive load measures and MERSQI score. RESULTS Of 391 articles retrieved, 84 met the inclusion criteria, totalling 2053 unique participants. Most studies were carried out in a simulated setting (59 studies, 70 per cent). Sixty studies (71 per cent) used self-reporting methods, of which the NASA Task Load Index (NASA-TLX) was the most commonly applied tool (44 studies, 52 per cent). Heart rate variability analysis was the most used real-time method (11 studies, 13 per cent). CONCLUSION Self-report instruments are valuable when the aim is to assess the overall cognitive load in different surgical procedures and assess learning curves within competence-based surgical education. When the aim is to assess cognitive load related to specific operative stages, real-time tools should be used, as they allow capture of cognitive load fluctuation. A combination of both subjective and objective methods might provide optimal measurement of surgeons' cognition.
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Affiliation(s)
- R D Dias
- STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Boston, Massachusetts, USA,Harvard Medical School, Boston, Massachusetts, USA
| | - M C Ngo-Howard
- Department of Otolaryngology – Head and Neck Surgery, Boston University School of Medicine, Boston, Massachusetts, USA,Medical Robotics and Computer Assisted Surgery Laboratory, Division of Cardiac Surgery, Veterans Affairs Boston Healthcare System, West Roxbury, Massachusetts, USA
| | - M T Boskovski
- Department of Surgery, Brigham and Women's Hospital, Boston, Massachusetts, USA,Harvard Medical School, Boston, Massachusetts, USA
| | - M A Zenati
- Harvard Medical School, Boston, Massachusetts, USA,Medical Robotics and Computer Assisted Surgery Laboratory, Division of Cardiac Surgery, Veterans Affairs Boston Healthcare System, West Roxbury, Massachusetts, USA
| | - S J Yule
- STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Boston, Massachusetts, USA,Center for Surgery and Public Health, Brigham and Women's Hospital, Boston, Massachusetts, USA,Department of Surgery, Brigham and Women's Hospital, Boston, Massachusetts, USA,Harvard Medical School, Boston, Massachusetts, USA,Correspondence to: Dr S. J. Yule, STRATUS Center for Medical Simulation, Brigham and Women's Hospital, 10 Vining Street, Boston, Massachusetts 02115, USA (e-mail: ; @RogerDaglius; @BWH_STRATUS)
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