Assessment of a 3D printed simulator of a lateral ventricular puncture in interns' surgical training.

PURPOSE: In this study, a simulator for training lateral ventricular puncture (LVP) was developed using three-dimensional (3D) printing technology, and its function of improving the skills of LVP in young interns was evaluated. METHODS: A virtual 3D craniocerebral simulator of a 51-year-old female patient with hydrocephalus was reconstructed with 3D printing technology. The anatomical and practical validity were assessed by all interns on a 13-item Likert scale. The usefulness of this simulator was evaluated once a week by two neurosurgeons, based on the performance of the interns, using the objective structured assessment of technical skills (OSATS) scale. RESULTS: The Likert scale showed that all participants agreed with the overall appearance of the simulator. Also, the authenticity of the skull was the best, followed by the lateral ventricles, analog generation system of intraventricular pressure, cerebrum, and the scalp. This simulator could help the participants' learning about the anatomy of the lateral ventricle, effective training, and repeating the steps of LVP. During training, the interns' ratio of success in LVP elevated gradually. At each evaluation stage, all mean performance scores for each measure based on the OSATS scale were higher than the previous. CONCLUSIONS: The 3D printed simulator for LVP training provided both anatomical and practical validity, and enabled young doctors to master the LVP procedures and skills.

Marker-less augmented reality based on monocular vision for falx meningioma localization.

BACKGROUND: The existing augmented reality (AR) based neuronavigation systems typically require markers and additional tracking devices for model registration, which causes excessive preparatory steps. METHODS: For fast and accurate intraoperative navigation, this work proposes a marker-less AR system that tracks the head features with the monocular camera. After the semi-automatic initialization process, the feature points between the captured image and the pre-loaded keyframes are matched for obtaining correspondences. The camera pose is estimated by solving the Perspective-n-Point problem. RESULTS: The localization error of AR visualization on scalp and falx meningioma is 0.417 ± 0.057 and 1.413 ± 0.282 mm, respectively. The maximum localization error is less than 2 mm. The AR system is robust to occlusions and changes in viewpoint and scale. CONCLUSIONS: We demonstrate that the developed system can successfully display the augmented falx meningioma with enough accuracy and provide guidance for neurosurgeons to locate the tumour in brain.

A virtual reality-based data analysis for optimizing freehand external ventricular drain insertion.

PURPOSE: This work exploits virtual reality technique to analyse and optimize the preoperative planning of freehand external ventricular drain (EVD) insertion. Based on the three-dimensional (3D) virtual brain models, neurosurgeons can directly observe the anatomical landmarks and complete the simulated EVD insertion. Simulation data is used to optimize preoperative planning parameters to ensure the surgical performance. METHODS: We used the computed tomography (CT) scans to construct the 3D virtual brain models. A group of EVD insertions were simulated by inserting virtual catheters at different entry points. The key parameters including the location of entry point, the catheter orientation, the catheter tip position on lateral ventricles, and the insertion depth were recorded. A data analysis method was then applied to optimize these parameters, resulting in the optimal parameters for the EVD insertion. RESULTS: When the lateral distance of entry point ranged from 2.5 to 3 cm, the success rate of 204 cases was 97.79%, which was higher than that of the classic method (59.52%). The optimal insertion angle towards the sagittal plane ranged from 10.46° to 12.73°. To prevent penetrating the lateral ventricles, the insertion depth was optimized to be 3.28 to 4.58 cm. CONCLUSIONS: The proposed data analysis method is helpful to optimize the key parameters of the preoperative planning, and provides useful references for neurosurgeons to perform the freehand EVD insertion. The EVD insertion experiments on 3D printing model had a success rate of 93.75%, which verified the effectiveness of the data analysis.

Development and evaluation of a craniocerebral model with tactile-realistic feature and intracranial pressure for neurosurgical training.

OBJECTIVE: In this article, a craniocerebral model is introduced for neurosurgical training, which is patient-specific, tactile-realistic, and with adjustable intracranial pressure. METHODS: The patient-specific feature is achieved by modeling from CT scans and magnetic resonance images (MRI). The brain tissue model is built by the hydrogel casting technique, while scalp, skull, vasculature, and lateral ventricles are all-in-one fabricated by three-dimensional (3D) printing. A closed-loop system is integrated to monitor and control the intracranial pressure. 3D measurements, mechanical tests, and simulated external ventricular drain (EVD) placement procedures are conducted on the model. RESULTS: A neurosurgical training model is completed with high accuracy (mean deviation 0.36 mm). The hydrogel brain tissue has a stiffness more similar to that of a real brain than the common 3D printed materials. The elasticity modulus of hydrogel brain tissue model is E=25.71 kPa, compared with our softest 3D printed material with E=1.14×103 kPa. Ten experienced surgeons rate the tactile realness of the neurosurgical training model at an average point of 4.25 on a scale from 1 (strongly negative) to 5 (strongly positive). The neurosurgical training model is also rated to be realistic in size (4.82), anatomy (4.70), and effective as an aid to improve blind EVD placement skills (4.65). CONCLUSIONS: The neurosurgical training model can provide trainee surgeons with realistic experience in both tactile feedbacks and craniocerebral anatomy, improving their surgical skills.