Training Performance Assessment for Intracranial Aneurysm Clipping Surgery Using a Patient-Specific Mixed-Reality Simulator: A Learning Curve Study.

BACKGROUND AND OBJECTIVES: The value of simulation-based training in medicine and surgery has been widely demonstrated. This study investigates the introduction and use of a new mixed-reality neurosurgical simulator in aneurysm clipping surgery, focusing on the learning curve and performance improvement. METHODS: Five true-scale craniotomy head models replicating patient-specific neuroanatomy, along with a mixed-reality simulator, a neurosurgical microscope, and a set of microsurgical instruments and clips, were used in the operation theater to simulate aneurysm microsurgery. Six neurosurgical residents participated in five video-recorded simulation sessions over 4 months. Complementary learning modalities were implemented between sessions. Thereafter, three blinded analysts reported on residents' use of the microscope, quality of manipulation, aneurysm occlusion, clipping techniques, and aneurysm rupture. Data were also captured regarding training time and clipping attempts. RESULTS: Over the course of training, clipping time and number of clipping attempts decreased significantly (P = .018, P = .032) and the microscopic skills improved (P = .027). Quality of manipulation and aneurysm occlusion scoring improved initially although the trend was interrupted because the spacing between sessions increased. Significant differences in clipping time and attempts were observed between the most and least challenging patient models (P = .005, P = .0125). The least challenging models presented higher rates of occlusion based on indocyanine green angiography evaluation from the simulator. CONCLUSION: The intracranial aneurysm clipping learning curve can be improved by implementing a new mixed-reality simulator in dedicated training programs. The simulator and the models enable comprehensive training under the guidance of a mentor.

Dynamic Mixed-Reality Patient-Specific Aneurysm Clipping Simulation for Two Cases-A Feasibility Study.

BACKGROUND AND OBJECTIVE: Intracranial aneurysm (IA) clipping is a complex neurosurgical procedure which demands advanced technology to minimize risks and maximize patient outcomes. This study aims to evaluate the feasibility of training patient-specific microsurgical clipping procedures using a mixed-reality physical neurosurgical simulator for unruptured IA. METHODS: Two board-certified neurosurgeons were asked to simulate surgery in 2 patient-specific left-side unruptured middle cerebral artery-bifurcation IA models. The study was conducted in the operation theater under realistic conditions using a mixed-reality physical neurosurgical simulator. Time, procedural, and outcome-related information was collected. The participating neurosurgeons were encouraged to attempt all possible clipping strategies, even those deemed suboptimal, reporting the outcome of each strategy. Finally, to evaluate the feasibility and added value of integrating indocyanine green fluorescence angiography (ICG-FA) with the simulator, the ICG-FA videos for each clipping strategy were analyzed and compared with the reported clipping outcomes. RESULTS: Between 4 and 8, different clipping strategies were applied per aneurysm model; the number of strategies was higher in Patient Model 1 (6.5 ± 1.5) (more complex aneurysm) than in Patient Model 2 (5.0 ± 1.0). The clipping strategies differed between surgeons. At most, 53.5 minutes were necessary to complete each training session, but more than double the time was spent on the more complex aneurysm. Up to 53.8% (Patient Model 1) and 50% (Patient Model 2) of the attempted strategies were discarded by the neurosurgeons during the simulation. Evaluation of aneurysm occlusion through ICG-FA was specific, although sensitivity was poor. CONCLUSION: The present mixed-reality patient-specific simulator allows testing, anticipating, and discarding different aneurysm microsurgical clipping strategies regardless of the pathology complexity. Specific limitations should be considered regarding ICG-FA aneurysm inspection after clipping.

Simulation training approaches in intracranial aneurysm surgery-a systematic review.

BACKGROUND: With the increasing complexity and decreasing exposure to intracranial aneurysm surgery, training and maintenance of the surgical skills have become challenging. This review elaborated on simulation training for intracranial aneurysm clipping. METHODS: A systematic review was performed according to the PRISMA guidelines to identify studies on aneurysm clipping training using models and simulators. The primary outcome was the identification of the predominant modes of the simulation process, models, and training methods associated with a microsurgical learning curve. The secondary outcomes included assessments of the validation of such simulators and the learning capability from the use of such simulators. RESULTS: Of the 2068 articles screened, 26 studies met the inclusion criteria. The chosen reports used a wide range of simulation approaches including ex vivo methods (n = 6); virtual reality (VR) platforms (n = 11); and static (n = 6) and dynamic (n = 3) 3D-printed aneurysm models (n = 6). The ex vivo training methods have limited availability, VR simulators lack haptics and tactility, while 3D static models lack important microanatomical components and the simulation of blood flow. 3D dynamic models including pulsatile flow are reusable and cost-effective but miss microanatomical components. CONCLUSIONS: The existing training methods are heterogenous and do not realistically simulate the complete microsurgical workflow. The current simulations lack certain anatomical features and crucial surgical steps. Future research should focus on developing and validating a reusable, cost-effective training platform. No systematic validation method exists for the different training models, so there is a need to build homogenous assessment tools and validate the role of simulation in education and patient safety.

3D-Printed Head Model in Patient's Education for Micro-Neurosurgical Aneurysm Clipping Procedures.

BACKGROUND: Computed tomography (CT), Magnetic resonance imaging (MRI), and 3D reconstruction from Digital Subtraction Angiography (DSA) are currently used in clinical consultations for patients diagnosed with intracranial aneurysms; however, they have limitations in helping patients understand the disease and possible treatments. This study investigates the use of a 3D-printed model of the patients' neurosurgical anatomy and vascular pathology as an educational tool in outpatient clinics. METHODS: A 3D-printed model of a middle cerebral artery aneurysm was created for use during patient consultations to discuss microsurgical treatment of unruptured cerebral aneurysms. In total, 38 patients and 5 neurosurgeons were included in the study. After the consultation, the patients and neurosurgeons received a questionnaire to assess the effectiveness of the 3D-printed model as an educational tool. RESULTS: The 3D model improved the patients' understanding of the diagnosis, the aneurysm's relationship to the parent artery; the treatment process as well as the risks if left untreated. The patients found the 3D model to be an interesting tool (97%). The neurosurgeons were satisfied with the 3D-printed model as a patient encounter tool, they found the model effective during consultation (87%) and better than the conventional education tools used during consultations (97%). CONCLUSIONS: Using a 3D model improves communication, enhances the patient's understanding of the pathology and its treatment and potentially facilitates the informed consent process in patients undergoing intracranial aneurysm surgery.