Background: Neurosurgical procedures are complex and require years of training and experience. Traditional training on human cadavers is expensive, requires facilities and planning, and raises ethical concerns. Therefore, the use of anthropomorphic phantoms could be an excellent substitute. The aim of the study was to design and develop a patient-specific 3D-skull and brain model with realistic CT-attenuation suitable for conventional and augmented reality (AR)-navigated neurosurgical simulations. Methods: The radiodensity of materials considered for the skull and brain phantoms were investigated using cone beam CT (CBCT) and compared to the radiodensities of the human skull and brain. The mechanical properties of the materials considered were tested in the laboratory and subsequently evaluated by clinically active neurosurgeons. Optimization of the phantom for the intended purposes was performed in a feedback cycle of tests and improvements. Results: The skull, including a complete representation of the nasal cavity and skull base, was 3D printed using polylactic acid with calcium carbonate. The brain was cast using a mixture of water and coolant, with 4 wt% polyvinyl alcohol and 0.1 wt% barium sulfate, in a mold obtained from segmentation of CBCT and T1 weighted MR images from a cadaver. The experiments revealed that the radiodensities of the skull and brain phantoms were 547 and 38 Hounsfield units (HU), as compared to real skull bone and brain tissues with values of around 1300 and 30 HU, respectively. As for the mechanical properties testing, the brain phantom exhibited a similar elasticity to real brain tissue. The phantom was subsequently evaluated by neurosurgeons in simulations of endonasal skull-base surgery, brain biopsies, and external ventricular drain (EVD) placement and found to fulfill the requirements of a surgical phantom. Conclusions: A realistic and CT-compatible anthropomorphic head phantom was designed and successfully used for simulated augmented reality-led neurosurgical procedures. The anatomic details of the skull base and brain were realistically reproduced. This phantom can easily be manufactured and used for surgical training at a low cost. @en

Purpose: This review provides an overview of the patent literature on posteriorly placed intrapedicular bone anchors. Conventional pedicle screws are the gold standard to create a fixation in the vertebra for spinal fusion surgery but may lack fixation strength, especially in osteoporotic bone. The ageing population demands new bone anchors that have an increased fixation strength, that can be placed safely, and, if necessary, can be removed without damaging the surrounding tissue. Methods: The patent search was conducted using a classification search in the Espacenet patent database. Only patents with a Cooperative Patent Classification of A61B17/70 or A61B17/7001 concerning spinal positioners and stabilizers were eligible for inclusion. The search query resulted in the identification of 731 patents. Based on preset inclusion criteria, a total of 56 unique patents on different anchoring methods were included, reviewed and categorized in this study. Results: Five unique fixation methods were identified; (1) anchors that use threading, (2) anchors that utilize a curved path through the vertebra, (3) anchors that (partly) expand, (4) anchors that use cement and (5) anchors that are designed to initiate bone ingrowth. Of the anchor designs included in this study, eight had a corresponding commercial product, six of which were evaluated in clinical trials. Conclusion: This review provides insights into worldwide patented intrapedicular bone anchors that aim to increase the fixation strength compared to the conventional pedicle screw. The identified anchoring methods and their working principles can be used for clinical decision-making and as a source of inspiration when designing novel bone anchors.

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Glial tumors grow diffusely in the brain. Survival is correlated to the extent of tumor removal, but tumor borders are often invisible. Resection beyond the borders as defined by conventional methods may further improve prognosis. In this proof-of-concept study, we evaluate diffuse reflectance spectroscopy (DRS) for discrimination between glial tumors and normal brain ex vivo. DRS spectra and histology were acquired from 22 tumor samples and nine brain tissue samples retrieved from 30 patients. The content of biological chromophores and scattering features were estimated by fitting a model derived from diffusion theory to the DRS spectra. DRS parameters differed significantly between tumor and normal brain tissue. Classification using random forest yielded a sensitivity and specificity for the detection of low-grade gliomas of 82.0% and 82.7%, respectively, and the area under curve (AUC) was 0.91. Applied in a hand-held probe or biopsy needle, DRS has the potential to provide intra-operative tissue analysis.

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OBJECTIVE The aim of this study was to evaluate the accuracy (deviation from the target or intended path) and efficacy (insertion time) of an augmented reality surgical navigation (ARSN) system for insertion of biopsy needles and external ventricular drains (EVDs), two common neurosurgical procedures that require high precision. METHODS The hybrid operating room-based ARSN system, comprising a robotic C-arm with intraoperative conebeam CT (CBCT) and integrated video tracking of the patient and instruments using nonobtrusive adhesive optical markers, was used. A 3D-printed skull phantom with a realistic gelatinous brain model containing air-filled ventricles and 2-mm spherical biopsy targets was obtained. After initial CBCT acquisition for target registration and planning, ARSN was used for 30 cranial biopsies and 10 EVD insertions. Needle positions were verified by CBCT. RESULTS The mean accuracy of the biopsy needle insertions (n = 30) was 0.8 mm ± 0.43 mm. The median path length was 39 mm (range 16-104 mm) and did not correlate to accuracy (p = 0.15). The median device insertion time was 149 seconds (range 87-233 seconds). The mean accuracy for the EVD insertions (n = 10) was 2.9 mm ± 0.8 mm at the tip with a 0.7° ± 0.5° angular deviation compared with the planned path, and the median insertion time was 188 seconds (range 135-400 seconds). CONCLUSIONS This study demonstrated that ARSN can be used for navigation of percutaneous cranial biopsies and EVDs with high accuracy and efficacy.

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Neurosurgical training is performed on human cadavers and simulation models, such as VR platforms, which have several drawbacks. Head phantoms could solve most of the issues related to these trainings. The aim of this study was to design a realistic and CT-compatible head phantom, with a specific focus on endo-nasal skull-base surgery and brain biopsy. A head phantom was created by segmenting an image dataset from a cadaver. The skull, which includes a complete structure of the nasal cavity and detailed skull-base anatomy, is 3D printed using PLA with calcium, while the brain is produced using a PVA mixture. The radiodensity and mechanical properties of the phantom were tested and adjusted in material choice to mimic real-life conditions. Surgeons find the skull, the structures at the skull-base and the brain realistically reproduced. The head phantom can be employed for neurosurgical education, training and surgical planning, and can be successfully used for simulating surgeries.

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Background: The increased popularity of minimally invasive spinal surgery calls for a revision of guidance techniques to prevent injuries of nearby neural and vascular structures. Lipid content has previously been proposed as a distinguishing criterion for different bone tissues to provide guidance along the interface of cancellous and cortical bone. This study aims to investigate how fat is distributed throughout the spinal column to confirm or refute the suitability of lipid content for guidance purposes. Results: Proton density fat fraction (PDFF) was assessed over all vertebral levels for six human cadavers between 53 and 92 years of age, based on fat and water MR images. According to their distance to the vertebra contour, the data points were grouped in five regions of interest (ROIs): cortical bone (−1 mm to 0 mm), pre-cortical zone (PCZ) 1–3 (0–1 mm; 1–2 mm; 2–3 mm), and cancellous bone (≥ 3 mm). For PCZ1 vs. PCZ2, a significant difference in mean PDFF of between −7.59 pp and −4.39 pp on average was found. For cortical bone vs. PCZ1, a significant difference in mean PDFF of between −27.09 pp and −18.96 pp on average was found. Conclusion: A relationship between distance from the cortical bone boundary and lipid content could be established, paving the way for guidance techniques based on fat fraction detection for spinal surgery.

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BACKGROUND: The safe and accurate placement of pedicle screws remains a critical step in open and minimally invasive spine surgery, emphasizing the need for intraoperative guidance techniques. Diffuse reflectance spectroscopy (DRS) is an optical sensing technology that may provide intraoperative guidance in pedicle screw placement. PURPOSE: The study presents the first in vivo minimally invasive procedure using DRS sensing at the tip of a Jamshidi needle with an integrated optical K-wire. We investigate the effect of tissue perfusion and probe-handling conditions on the reliability of fat fraction measurements for breach detection in vivo. METHODS: A Jamshidi needle with an integrated fiber-optic K-wire was gradually inserted into the vertebrae under intraoperative image guidance. The fiber-optic K-wire consisted of two optical fibers with a fiber-to-fiber distance of 1.024 mm. DRS spectra in the wavelength range of 450 to 1600 nm were acquired at several positions along the path inside the vertebrae. Probe-handling conditions were varied by changing the amount of pressure exerted on the probe within the vertebrae. Continuous spectra were recorded as the probe was placed in the center of the vertebral body while the porcine specimen was sacrificed via a lethal injection. RESULTS: A typical insertion of the fiber-optic K-wire showed a drop in fat fraction during an anterior breach as the probe transitioned from cancellous to cortical bone. Fat fraction measurements were found to be similar irrespective of the amount of pressure exerted on the probe (p = 0.65). The 95% confidence interval of fat fraction determination was found in the narrow range of 1.5-3.6% under various probe-handling conditions. The fat fraction measurements remained stable during 70 min of decreased blood flow after the animal was sacrificed. DISCUSSIONS: These findings indicate that changes in tissue perfusion and probe-handling conditions have a relatively low measureable effect on the DRS signal quality and thereby on the determination of fat fraction as a breach detection signal. CONCLUSIONS: Fat fraction quantification for intraoperative pedicle screw breach detection is reliable, irrespective of changes in tissue perfusion and probe-handling conditions.

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In neurosurgery, technical solutions for visualizing the border between healthy brain and tumor tissue is of great value, since they enable the surgeon to achieve gross total resection while minimizing the risk of damage to eloquent areas. By using real-time non-ionizing imaging techniques, such as hyperspectral imaging (HSI), the spectral signature of the tissue is analyzed allowing tissue classification, thereby improving tumor boundary discrimination during surgery. More particularly, since infrared penetrates deeper in the tissue than visible light, the use of an imaging sensor sensitive to the near-infrared wavelength range would also allow the visualization of structures slightly beneath the tissue surface. This enables the visualization of tumors and vessel boundaries prior to surgery, thereby preventing the damaging of tissue structures. In this study, we investigate the use of Diffuse Reflectance Spectroscopy (DRS) and HSI for brain tissue classification, by extracting spectral features from the near infra-red range. The applied method for classification is the linear Support Vector Machine (SVM). The study is conducted on ex-vivo porcine brain tissue, which is analyzed and classified as either white or gray matter. The DRS combined with the proposed classification reaches a sensitivity and specificity of 96%, while HSI reaches a sensitivity of 95% and specificity of 93%. This feasibility study shows the potential of DRS and HSI for automated tissue classification, and serves as a fjrst step towards clinical use for tumor detection deeper inside the tissue.

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