Cranial neurosurgical procedures are especially delicate considering that the surgeon must localize the subsurface anatomy with limited exposure and without the ability to see beyond the surface of the surgical field. Surgical accuracy is imperative as even minor surgical errors can cause major neurological deficits. Traditionally surgical precision was highly dependent on surgical skill. However, the introduction of intraoperative surgical navigation has shifted the paradigm to become the current standard of care for cranial neurosurgery.
Intra-operative image guided navigation systems are currently used to allow the surgeon to visualize the three-dimensional subsurface anatomy using pre-acquired computed tomography (CT) or magnetic resonance (MR) images. The patient anatomy is fused to the pre-acquired images using various registration techniques and surgical tools are typically localized using optical tracking methods. Although these techniques positively impact complication rates, surgical accuracy is limited by the accuracy of the navigation system and as such quantification of surgical error is required. While many different measures of registration accuracy have been presented true navigation accuracy can only be quantified post-operatively by comparing a ground truth landmark to the intra-operative visualization.
In this study we quantified the accuracy of cranial neurosurgical procedures using a novel optical surface imaging navigation system to visualize the three-dimensional anatomy of the surface anatomy. A tracked probe was placed on the screws of cranial fixation plates during surgery and the reported position of the centre of the screw was compared to the co-ordinates of the post-operative CT or MR images, thus quantifying cranial neurosurgical error.
Non-melanoma skin cancer (NMSC) is considered the most commonly diagnosed cancer in the United States and Canada. Treatment options include radiotherapy, surgical excision, radiotherapy, topical therapies, electrocautery, and cryotherapy. For patients undergoing fractionated orthovoltage radiation therapy or photodynamic therapy (PDT), the lesions are typically delineated by clinical markup prior to treatment without providing any information about the underlying tissue thus increasing the risk of geographic miss.
The development of biomarkers for response in NMSC is imperative considering the current treatment paradigm is based on clinical examination and biopsy confirmation. Therefore, a non-invasive image-based evaluation of skin structure would allow for faster and potentially more comprehensive microscopic evaluation of the treated region at the point of care. To address this, our group is investigating the use of optical coherence tomography (OCT) for pre- and post- treatment evaluation of NMSC lesions during radiation therapy and PDT.
Localization of the OCT probe for follow-up is complex, especially in the context of treatment response where the lesion is not present, precluding accurate delineation of the planning treatment area. Further, comparison to standard white light pre-treatment images is limited by the scale of the OCT probe (6 mm X 6 mm) relative to target region.
In this study we compare the set-up accuracy of a typical OCT probe to detect a theoretical lesion on a patient’s hand. White light images, optical surface imaging (OSI) and OCT will be obtained at baseline and used for probe set up on subsequent scans. Set-up error will be quantified using advanced image processing techniques.
Surgical navigation has been more actively deployed in open spinal surgeries due to the need for improved precision during procedures. This is increasingly difficult in minimally invasive surgeries due to the lack of visual cues caused by smaller exposure sites, and increases a surgeon’s dependence on their knowledge of anatomical landmarks as well as the CT or MRI images.
The use of augmented reality (AR) systems and registration technologies in spinal surgeries could allow for improvements to techniques by overlaying a 3D reconstruction of patient anatomy in the surgeon’s field of view, creating a mixed reality visualization. The AR system will be capable of projecting the 3D reconstruction onto a field and preliminary object tracking on a phantom. Dimensional accuracy of the mixed media will also be quantified to account for distortions in tracking.
In this paper, a multi-beam optical coherence tomography (OCT) was used to reconstruct the microvascular image of human skin in vivo with phase resolved Doppler OCT (PRDOCT), phase resolved Doppler variance (PRDV) and speckle variance OCT (svOCT), in which the blood flow image was calculated by averaging the four blood flow images obtained by the four beams. In PRDOCT method, it is difficult to detect the blood flow perpendicular to optical axis of the probe beam for single beam OCT, but the multi-beam scanning method can solve this because the input angles of the four probe beams are slightly different from each other. The proposed method can further improve the signal-to-noise ratio (SNR) of the blood flow signals extracted by the three methods mentioned above.
Computer-assisted navigation is used by surgeons in spine procedures to guide pedicle screws to improve placement
accuracy and in some cases, to better visualize patient’s underlying anatomy. Intraoperative registration is performed to
establish a correlation between patient’s anatomy and the pre/intra-operative image. Current algorithms rely on seeding
points obtained directly from the exposed spinal surface to achieve clinically acceptable registration accuracy. Registration
of these three dimensional surface point-clouds are prone to various systematic errors. The goal of this study was to
evaluate the robustness of surgical navigation systems by looking at the relationship between the optical density of an
acquired 3D point-cloud and the corresponding surgical navigation error. A retrospective review of a total of 48
registrations performed using an experimental structured light navigation system developed within our lab was conducted.
For each registration, the number of points in the acquired point cloud was evaluated relative to whether the registration
was acceptable, the corresponding system reported error and target registration error. It was demonstrated that the number
of points in the point cloud neither correlates with the acceptance/rejection of a registration or the system reported error.
However, a negative correlation was observed between the number of the points in the point-cloud and the corresponding
sagittal angular error. Thus, system reported total registration points and accuracy are insufficient to gauge the accuracy
of a navigation system and the operating surgeon must verify and validate registration based on anatomical landmarks
prior to commencing surgery.
Computer-assisted navigation (CAN) may guide spinal surgeries, reliably reducing screw breach rates. Definitions of
screw breach, if reported, vary widely across studies. Absolute quantitative error is theoretically a more precise and
generalizable metric of navigation accuracy, but has been computed variably and reported in fewer than 25% of clinical
studies of CAN-guided pedicle screw accuracy. We reviewed a prospectively-collected series of 209 pedicle screws
placed with CAN guidance to characterize the correlation between clinical pedicle screw accuracy, based on postoperative
imaging, and absolute quantitative navigation accuracy. We found that acceptable screw accuracy was
achieved for significantly fewer screws based on 2mm grade vs. Heary grade, particularly in the lumbar spine. Inter-rater
agreement was good for the Heary classification and moderate for the 2mm grade, significantly greater among
radiologists than surgeon raters. Mean absolute translational/angular accuracies were 1.75mm/3.13° and 1.20mm/3.64°
in the axial and sagittal planes, respectively. There was no correlation between clinical and absolute navigation accuracy,
in part because surgeons appear to compensate for perceived translational navigation error by adjusting screw
medialization angle. Future studies of navigation accuracy should therefore report absolute translational and angular
errors. Clinical screw grades based on post-operative imaging, if reported, may be more reliable if performed in multiple
by radiologist raters.
Spinal surgery is particularly challenging for surgeons, requiring a high level of expertise and precision
without being able to see beyond the surface of the bone. Accurate insertion of pedicle screws is critical
considering perforation of the pedicle can result in profound clinical consequences including spinal cord,
nerve root, arterial injury, neurological deficits, chronic pain, and/or failed back syndrome.
Various navigation systems have been designed to guide pedicle screw fixation. Computed tomography
(CT)-based image guided navigation systems increase the accuracy of screw placement allowing for 3-
dimensional visualization of the spinal anatomy. Current localization techniques require extensive
preparation and introduce spatial deviations. Use of near infrared (NIR) optical tracking allows for realtime
navigation of the surgery by utilizing spectral domain multiplexing of light, greatly enhancing the
surgeon’s situation awareness in the operating room. While the incidence of pedicle screw perforation and
complications have been significantly reduced with the introduction of modern navigational technologies,
some error exists. Several parameters have been suggested including fiducial localization and registration
error, target registration error, and angular deviation. However, many of these techniques quantify error
using the pre-operative CT and an intra-operative screenshot without assessing the true screw trajectory.
In this study we quantified in-vivo error by comparing the true screw trajectory to the intra-operative
trajectory. Pre- and post- operative CT as well as intra-operative screenshots were obtained for a cohort of
patients undergoing spinal surgery. We quantified entry point error and angular deviation in the axial and
sagittal planes.
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