The Effect of Training, Used-Hand, and Experience on Endoscopic Surgery Skills in an Educational Computer-Based Simulation Environment (ECE) for Endoneurosurgery Training

Çağıltay, Nergiz Ercil; Ozcelik, Erol; Işıkay, İlkay; Hanalıoğlu, Şahin; Süslü, Ahmet Emre; Yücel, Taşkın; Berker, Mustafa

doi:10.1177/1553350619861563

Cited by 13 publications

(12 citation statements)

References 26 publications

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“…Also, cadaveric dissection is the gold standard for training neurosurgeons because it allows surgical techniques to be demonstrated, provides a unique experience with a wide range of sensory inputs, and creates necessary surgical skills ( 12 , 13 ). These skills include depth perception, 2D and 3D vision orientation, sensitive movements in limited environments ( 14 ), bimanual coordination, and hand-eye coordination ( 15 , 16 ). In fields such as chess, music, sports, and mathematics, studies on human performance have shown that attaining an expert performance level requires about 10,000 hours of focused practice ( 17 , 18 ).…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Novel Methodological Pipeline to Integrate Neuroimaging and Photogrammetry for Immersive 3D Cadaveric Neurosurgical Simulation

et al. 2022

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BackgroundVisualizing and comprehending 3-dimensional (3D) neuroanatomy is challenging. Cadaver dissection is limited by low availability, high cost, and the need for specialized facilities. New technologies, including 3D rendering of neuroimaging, 3D pictures, and 3D videos, are filling this gap and facilitating learning, but they also have limitations. This proof-of-concept study explored the feasibility of combining the spatial accuracy of 3D reconstructed neuroimaging data with realistic texture and fine anatomical details from 3D photogrammetry to create high-fidelity cadaveric neurosurgical simulations.MethodsFour fixed and injected cadaver heads underwent neuroimaging. To create 3D virtual models, surfaces were rendered using magnetic resonance imaging (MRI) and computed tomography (CT) scans, and segmented anatomical structures were created. A stepwise pterional craniotomy procedure was performed with synchronous neuronavigation and photogrammetry data collection. All points acquired in 3D navigational space were imported and registered in a 3D virtual model space. A novel machine learning-assisted monocular-depth estimation tool was used to create 3D reconstructions of 2-dimensional (2D) photographs. Depth maps were converted into 3D mesh geometry, which was merged with the 3D virtual model’s brain surface anatomy to test its accuracy. Quantitative measurements were used to validate the spatial accuracy of 3D reconstructions of different techniques.ResultsSuccessful multilayered 3D virtual models were created using volumetric neuroimaging data. The monocular-depth estimation technique created qualitatively accurate 3D representations of photographs. When 2 models were merged, 63% of surface maps were perfectly matched (mean [SD] deviation 0.7 ± 1.9 mm; range −7 to 7 mm). Maximal distortions were observed at the epicenter and toward the edges of the imaged surfaces. Virtual 3D models provided accurate virtual measurements (margin of error <1.5 mm) as validated by cross-measurements performed in a real-world setting.ConclusionThe novel technique of co-registering neuroimaging and photogrammetry-based 3D models can (1) substantially supplement anatomical knowledge by adding detail and texture to 3D virtual models, (2) meaningfully improve the spatial accuracy of 3D photogrammetry, (3) allow for accurate quantitative measurements without the need for actual dissection, (4) digitalize the complete surface anatomy of a cadaver, and (5) be used in realistic surgical simulations to improve neurosurgical education.

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Section: Discussionmentioning

confidence: 99%

Development and Validation of a Novel Methodological Pipeline to Integrate Neuroimaging and Photogrammetry for Immersive 3D Cadaveric Neurosurgical Simulation

et al. 2022

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“…For this study, two scenarios were used which were developed for endoneurosurgery training programs ( Cagiltay et al, 2019 ). Each scenario includes some user tasks intended to improve certain endoscopic surgical skills like depth perception, left–right hand coordination and eye-hand coordination in a 3D simulated environment.…”

Section: Methodsmentioning

confidence: 99%

A user task design notation for improved software design

Özcan¹,

Topalli

Tokdemir

et al. 2021

PeerJ Computer Science

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System design is recognized as one of the most critical components of a software system that bridges system requirements and coding. System design also has a significant impact on testing and maintenance activities, and on further improvements during the lifespan of the software system. Software design should reflect all necessary components of the requirements in a clear and understandable manner by all stakeholders of the software system. To distinguish system elements, separation of concerns in software design is suggested. In this respect, identification of the user tasks, i.e., the tasks that need to be performed by the user, is not currently reflected explicitly in system design documents. Our main assumption in this study is that software quality can be improved significantly by clearly identifying the user tasks from those that need to be performed by the computer system itself. Additionally, what we propose has the potential to better reflect the user requirements and main objectives of the system on the software design and thereby to improve software quality. The main aim of this study is to introduce a novel notation for software developers in the frame of UML Activity Diagram (UML-AD) that enables designers to identify the user tasks and define them separately from the system tasks. For this purpose, an extension of UML-AD, named UML-ADE (UML-Activity Diagram Extended) was proposed. Afterwards, it was implemented in a serious game case for which the specification of user tasks is extremely important. Finally, its effectiveness was analyzed and compared to UML-AD experimentally with 72 participants. The defect detection performance of the participants on both diagrams with two real-life serious game scenarios was evaluated. Results show a higher level of understandability for those using UML-ADE, which in turn may indicate a better design and higher software quality. The results encourage researchers to develop specific design representations dedicated to task design to improve system quality and to conduct further evaluations of the impact of these design on each of the above mentioned potential benefits for the software systems.

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“…Four different scenarios simulating different surgical procedures in a virtual environment were designed in accordance with the feedback of expert surgeons from Hacettepe University Medical School with more than 30 years' experience in skull base surgery. Their educational evaluations including these scenarios also show some encouraging results for supporting surgical education programmes [23]. Each scenario contained different tasks to be performed to develop different skills among surgical residents, such as eye-hand coordination, fast tracking of objects, depth perception, effective use of surgical instruments, and simultaneous use of both hands.…”

Section: Rq2 Do the Algorithms Form Different Clusters?mentioning

confidence: 97%

“…Besides, several studies have been undertaken to investigate eye movements in order to support surgical training programmes, specifically to improve surgical simulations and needle insertion simulations to represent real-life environments, such as soft tissues [17]- [21]. These improvements on the techniques used for surgical simulations have several potential benefits for surgical training programmes in terms of providing support for skill assessment procedures [22] and helping candidate surgeons acquire the necessary skills [23]. Additionally, there is some evidence showing the benefits of better understanding the eye-movement events of surgical residents while they are performing surgical tasks in computer-based simulation environments [24].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Ten Open-Source Eye-Movement Classification Algorithms in Simulated Surgical Scenarios

Dalveren

Çağıltay

2019

IEEE Access

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Despite providing several insights into visual attention and evidence regarding certain brain states and psychological functions, classifying eye movements is a highly demanding process. Currently, there are several algorithms to classify eye movement events which use different approaches. However, to date, only a limited number of studies have assessed these algorithms under specific conditions, such as those required for surgical training programmes. This study presents an investigation of ten open-source eye-movement classification algorithms using the Eye Tribe eye-tracker. The algorithms were tested on the eye-movement records obtained from 23 surgical residents, who performed computer-based surgical simulation tasks under different hand conditions. The aim was to offer data for the improvement of surgical training programmes. According to the results, due to the different classification methods and default threshold values, the ten algorithms produced different results. Considering the fixation duration, the only common event for all of the investigated algorithms, the binocular-individual threshold (BIT) algorithm resulted in a different clustering compared to the other algorithms. Based on the other set of common events, three clusters were determined by eight algorithms (except BIT and event detection (ED)), distinguishing dispersion-based, velocity-based and modified versions of velocity-based algorithms. Accordingly, it was concluded that dispersion-based and velocity-based algorithms provided different results. Additionally, as it individually specifies the threshold values for the eye-movement data, when there is no consensus about the threshold values to be set, the BIT algorithm can be selected. Especially for such cases like simulation-based surgical skill-training, the use of individualised threshold values in the BIT algorithm can be more beneficial in classifying the raw eye data and thus evaluating the individual progress levels of trainees based on their eye movement behaviours. In conclusion, the threshold values had a critical effect on the algorithm results. Since default values may not always be suitable for the unique features of different data sets, guidelines should be developed to indicate how the threshold values are set for each algorithm. INDEX TERMS Eye-movement classification algorithms, eye-movement events, eye-tracking.

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The Effect of Training, Used-Hand, and Experience on Endoscopic Surgery Skills in an Educational Computer-Based Simulation Environment (ECE) for Endoneurosurgery Training

Cited by 13 publications

References 26 publications

Development and Validation of a Novel Methodological Pipeline to Integrate Neuroimaging and Photogrammetry for Immersive 3D Cadaveric Neurosurgical Simulation

Development and Validation of a Novel Methodological Pipeline to Integrate Neuroimaging and Photogrammetry for Immersive 3D Cadaveric Neurosurgical Simulation

A user task design notation for improved software design

Evaluation of Ten Open-Source Eye-Movement Classification Algorithms in Simulated Surgical Scenarios

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