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.
Safe and accurate placement of spinal screws remains a critical step during open and minimally invasive spinal fusion surgery. We investigated the application of diffuse reflectance spectroscopy (DRS) for real-time instrument guidance during a spinal screw placement procedure. A custom-built screw probe with integrated optical fibers was inserted into a vertebra under image guidance in an ex vivo human setting. We found that fat content derived from the spectra gradually changed as the probe approached the cortical bone boundary. The results indicate that DRS integrated into surgical instruments has the potential to improve the safety and accuracy of spinal screw placement procedures.
Safe and accurate placement of screws remains a critical issue in open and minimally invasive spine surgery. We propose to use diffuse reflectance (DR) spectroscopy as a sensing technology at the tip of a surgical instrument to ensure a safe path of the instrument through the cancellous bone of the vertebrae. This approach could potentially reduce the rate of cortical bone breaches, thereby resulting in fewer neural and vascular injuries during spinal fusion surgery. In our study, DR spectra in the wavelength ranges of 400 to 1600 nm were acquired from cancellous and cortical bone from three human cadavers. First, it was investigated whether these spectra can be used to distinguish between the two bone types based on fat, water, and blood content along with photon scattering. Subsequently, the penetration of the bone by an optical probe was simulated using the Monte-Carlo (MC) method, to study if the changes in fat content along the probe path would still enable distinction between the bone types. Finally, the simulation findings were validated via an experimental insertion of an optical screw probe into the vertebra aided by x-ray image guidance. The DR spectra indicate that the amount of fat, blood, and photon scattering is significantly higher in cancellous bone than in cortical bone (p < 0.01), which allows distinction between the bone types. The MC simulations showed a change in fat content more than 1 mm before the optical probe came in contact with the cortical bone. The experimental insertion of the optical screw probe gave similar results. This study shows that spectral tissue sensing, based on DR spectroscopy at the instrument tip, is a promising technology to identify the transition zone from cancellous to cortical vertebral bone. The technology therefore has the potential to improve the safety and accuracy of spinal screw placement procedures.
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