A Review of Physical Simulators for Neuroendoscopy Skills Training.

BACKGROUND: Minimally invasive neurosurgical approaches reduce patient morbidity by providing the surgeon with better visualization and access to complex lesions, with minimal disruption to normal anatomy. The use of rigid or flexible neuroendoscopes, supplemented with a conventional stereoscopic operating microscope, has been integral to the adoption of these techniques. Neurosurgeons commonly use neuroendoscopes to perform the ventricular and endonasal approaches. It is challenging to learn neuroendoscopy skills from the existing apprenticeship model of surgical education. The training methods, which use simulation-based systems, have achieved wide acceptance. Physical simulators provide anatomic orientation and hands-on experience with repeatability. Our aim is to review the existing physical simulators on the basis of the skills training of neuroendoscopic procedures. METHODS: We searched Scopus, Google Scholar, PubMed, IEEE Xplore, and dblp. We used the following keywords "neuroendoscopy," "training," "simulators," "physical," and "skills evaluation." A total of 351 articles were screened based on development methods, evaluation criteria, and validation studies on physical simulators for skills training in neuroendoscopy. RESULTS: The screening of the articles resulted in classifying the physical training methods developed for neuroendoscopy surgical skills into synthetic simulators and box trainers. The existing simulators were compared based on their design, fidelity, trainee evaluation methods, and validation studies. CONCLUSIONS: The state of simulation systems demands collaborative initiatives among translational research institutes. They need improved fidelity and validation studies for inclusion in the surgical educational curriculum. Learning should be imparted in stages with standardization of performance metrics for skills evaluation.

A review of virtual reality simulators for neuroendoscopy.

Neurosurgery is a challenging surgical specialty that demands many technical and cognitive skills. The traditional surgical training approach of having a trainee coached in the operating room by the faculty is time-consuming, costly, and involves patient risk factors. Simulation-based training methods are suitable to impart the surgical skills outside the operating room. Virtual simulators allow high-fidelity repeatable environment for surgical training. Neuroendoscopy, a minimally invasive neurosurgical technique, demands additional skills for limited maneuverability and eye-hand coordination. This study provides a review of the existing virtual reality simulators for training neuroendoscopic skills. Based on the screening, the virtual training methods developed for neuroendoscopy surgical skills were classified into endoscopic third ventriculostomy and endonasal transsphenoidal surgery trainers. The study revealed that a variety of virtual reality simulators have been developed by various institutions. Although virtual reality simulators are effective for procedure-based skills training, the simulators need to include anatomical variations and variety of cases for improved fidelity. The review reveals that there should be multi-centric prospective and retrospective cohort studies to establish concurrent and predictive validation for their incorporation in the surgical educational curriculum.

Design and Validation of an Open-Source, Partial Task Trainer for Endonasal Neuro-Endoscopic Skills Development: Indian Experience.

BACKGROUND: Box trainers are ideal simulators, given they are inexpensive, accessible, and use appropriate fidelity. OBJECTIVE: The development and validation of an open-source, partial task simulator that teaches the fundamental skills necessary for endonasal skull-base neuro-endoscopic surgery. METHODS: We defined the Neuro-Endo-Trainer (NET) SkullBase-Task-GraspPickPlace with an activity area by analyzing the computed tomography scans of 15 adult patients with sellar suprasellar parasellar tumors. Four groups of participants (Group E, n = 4: expert neuroendoscopists; Group N, n =19: novice neurosurgeons; Group R, n = 11: neurosurgery residents with multiple iterations; and Group T, n = 27: neurosurgery residents with single iteration) performed grasp, pick, and place tasks using NET and were graded on task completion time and skills assessment scale score. RESULTS: Group E had lower task completion times and greater skills assessment scale scores than both Group N and R (P ≤ 0.03, 0.001). The performance of Groups N and R was found to be equivalent; in self-assessing neuro-endoscopic skill, the participants in these groups were found to have equally low pretraining scores (4/10) with significant improvement shown after NET simulation (6, 7 respectively). Angled scopes resulted in decreased scores with tilted plates compared with straight plates (30° P ≤ 0.04, 45° P ≤ 0.001). With tilted plates, decreased scores were observed when we compared the 0° with 45° endoscope (right, P ≤ 0.008; left, P ≤ 0.002). CONCLUSIONS: The NET, a face and construct valid open-source partial task neuroendoscopic trainer, was designed. Presimulation novice neurosurgeons and neurosurgical residents were described as having insufficient skills and preparation to practice neuro-endoscopy. Plate tilt and endoscope angle were shown to be important factors in participant performance. The NET was found to be a useful partial-task trainer for skill building in neuro-endoscopy.

Generalized Flows for Optimal Inference in Higher Order MRF-MAP.

Use of higher order clique potentials in MRF-MAP problems has been limited primarily because of the inefficiencies of the existing algorithmic schemes. We propose a new combinatorial algorithm for computing optimal solutions to 2 label MRF-MAP problems with higher order clique potentials. The algorithm runs in time O(2(k)n(3)) in the worst case (k is size of clique and n is the number of pixels). A special gadget is introduced to model flows in a higher order clique and a technique for building a flow graph is specified. Based on the primal dual structure of the optimization problem, the notions of the capacity of an edge and a cut are generalized to define a flow problem. We show that in this flow graph, when the clique potentials are submodular, the max flow is equal to the min cut, which also is the optimal solution to the problem. We show experimentally that our algorithm provides significantly better solutions in practice and is hundreds of times faster than solution schemes like Dual Decomposition [1], TRWS [2] and Reduction [3], [4], [5]. The framework represents a significant advance in handling higher order problems making optimal inference practical for medium sized cliques.

Quantitative analysis of the Kawase versus the modified Dolenc-Kawase approach for middle cranial fossa lesions with variable anteroposterior extension.

OBJECT: The surgical corridor to the upper third of the clivus and ventral brainstem is hindered by critical neurovascular structures, such as the cavernous sinus, petrous apex, and tentorium. The traditional Kawase approach provides a 10 × 5-mm fenestration at the petrous apex of the temporal bone between the 5th cranial nerve and internal auditory canal. Due to interindividual variability, sometimes this area proves to be insufficient as a corridor to the posterior cranial fossa. The authors describe a modification to the technique of the extradural anterior petrosectomy consisting of additional transcavernous exploration and medial mobilization of the cisternal component of the trigeminal nerve. This approach is termed the modified Dolenc-Kawase (MDK) approach. METHODS: The authors describe a volumetric analysis of temporal bones with 3D laser scanning of dry and drilled bones for respective triangles and rhomboid areas, and they compare the difference of exposure with traditional versus modified approaches on cadaver dissection. Twelve dry temporal bones were laser scanned, and mesh-based volumetric analysis was done followed by drilling of the Kawase triangle and MDK rhomboid. Five cadaveric heads were drilled on alternate sides with both approaches for evaluation of the area exposed, surgical freedom, and angle of approach. RESULTS: The MDK approach provides an approximately 1.5 times larger area and 2.0 times greater volume of bone at the anterior petrous apex compared with the Kawase's approach. Cadaver dissection objectified the technical feasibility of the MDK approach, providing nearly 1.5-2 times larger fenestration with improved view and angulation to the posterior cranial fossa. Practical application in 6 patients with different lesions proves clinical applicability of the MDK approach. CONCLUSIONS: The larger fenestration at the petrous apex achieved with the MDK approach provides greater surgical freedom at the Dorello canal, gasserian ganglion, and prepontine area and better anteroposterior angulation than the traditional Kawase approach. Additional anterior clinoidectomy and transcavernous exposure helps in dealing with basilar artery aneurysms.

Quantitative analysis of variable extent of anterior clinoidectomy with intradural and extradural approaches: 3-dimensional analysis and cadaver dissection.

BACKGROUND: Drilling of the anterior clinoid process (ACP) is an integral component of surgical approaches for central and paracentral skull base lesions. The technique to drill ACP has evolved from pure intradural to extradural and combined techniques. OBJECTIVE: To describe the computerized morphometric evaluation of exposure of optic nerve and internal carotid artery with proposed tailored intradural (IDAC) and complete extradural (EDAC) anterior clinoidectomy. METHODS: We describe a morphometric subdivision of ACP into 4 quadrangles and 1 triangle on the basis of fixed bony landmarks. Computerized volumetric analysis with 3-dimensional laser scanning of dry-drilled bones for respective tailored IDAC and EDAC was performed. Both approaches were compared for the area and length of the optic nerve and internal carotid artery. Five cadaver heads were dissected on alternate sides with intradural and extradural techniques to evaluate exposure, surgical freedom, and angulation of approach. RESULTS: Complete anterior clinoidectomy provides a 2.5-times larger area and 2.7-times larger volume of ACP. Complete clinoidectomy deroofed the optic nerve to an equal extent as by proposed the partial tailored clinoidectomy approach. Tailored IDAC exposes only the distal dural ring, whereas complete EDAC exposes both the proximal and distal dural rings with complete exposure of the carotid cave. CONCLUSION: Quantitative comparative evaluation provides details of exposure and surgical ease with both techniques. We promote hybrid/EDAC technique for vascular pathologies because of better anatomic orientation. Extradural clinoidectomy is the preferred technique for midline cranial neoplasia. An awareness of different variations of clinoidectomy can prevent dependency on any particular approach and facilitate flexibility.

Free-access open-source e-learning in comprehensive neurosurgery skills training.

BACKGROUND: Since the end of last century, technology has taken a front seat in dispersion of medical education. Advancements of technology in neurosurgery and traditional training methods are now being challenged by legal and ethical concerns of patient safety, resident work-hour restriction and cost of operating-room time. To supplement the existing neurosurgery education pattern, various e-learning platforms are introduced as structured, interactive learning system. MATERIALS AND METHODS: This study focuses on the concept, formulation, development and impact of web based learning platforms dedicated to neurosurgery discipline to disseminate education, supplement surgical knowledge and improve skills of neurosurgeons. 'Neurosurgery Education and Training School (NETS), e-learning platform' has integration of web-based technologies like 'Content Management System' for organizing the education material and 'Learning Management System' for updating neurosurgeons. NETS discussion forum networks neurosurgeons, neuroscientists and neuro-technologists across the globe facilitating collaborative translational research. RESULTS: Multi-authored neurosurgical e-learning material supplements the deficiencies of regular time-bound education. Interactive open-source, global, free-access e-learning platform of NETS has around 1) 425 visitors/month from 73 countries; ratio of new visitors to returning visitors 42.3; 57.7 (2); 64,380 views from 190 subscribers for surgical videos, 3-D animation, graphics based training modules (3); average 402 views per post. CONCLUSION: The e-Learning platforms provide updated educational content that make them "quick, surf, find and extract" resources. e-Learning tools like web-based education, social interactive platform and question-answer forum will save unnecessary expenditure of time and travel of neurosurgeons seeking knowledge. The need for free access platforms is more pronounced for the neurosurgeons and patients in developing nations.

On efficient learning machine with root-power mean neuron in complex domain.

This paper describes an artificial neuron structure and an efficient learning procedure in the complex domain. This artificial neuron aims at incorporating an improved aggregation operation on the complex-valued signals. The aggregation operation is based on the idea underlying the weighted root-power mean of input signals. This aggregation operation allows modeling the degree of compensation in a natural manner and includes various aggregation operations as its special cases. The complex resilient propagation algorithm ([Formula: see text]-RPROP) with error-dependent weight backtracking step accelerates the training speed significantly and provides better approximation accuracy. Finally, performance evaluation of the proposed complex root-power mean neuron with the [Formula: see text]-RPROP learning algorithm on various typical examples is given to understand the motivation.

Space-time super-resolution using graph-cut optimization.

We address the problem of super-resolution­obtaining high-resolution images and videos from multiple low-resolution inputs. The increased resolution can be in spatial or temporal dimensions, or even in both. We present a unified framework which uses a generative model of the imaging process and can address spatial super-resolution, space-time super-resolution, image deconvolution, single-image expansion, removal of noise, and image restoration. We model a high-resolution image or video as a Markov random field and use maximum a posteriori estimate as the final solution using graph-cut optimization technique. We derive insights into what super-resolution magnification factors are possible and the conditions necessary for super-resolution. We demonstrate spatial super-resolution reconstruction results with magnifications higher than predicted limits of magnification. We also formulate a scheme for selective super-resolution reconstruction of videos to obtain simultaneous increase of resolutions in both spatial and temporal directions. We show that it is possible to achieve space-time magnification factors beyond what has been suggested in the literature by selectively applying super-resolution constraints. We present results on both synthetic and real input sequences.

A computational skin model: fold and wrinkle formation.

This paper presents a computational model for studying the mechanical properties of skin with aging. In particular, attention is given to the folding capacity of skin, which may be manifested as wrinkles. The simulation provides visual results demonstrating the form and density of folds under the various conditions. This can help in the consideration of proper measures for a cosmetic product for the skin.