Stereotactic ablative radiotherapy before resection to avoid delay for early-stage lung cancer or oligometastases during the COVID-19 pandemic: Pathologic outcomes from the SABR-BRIDGE protocol.

BACKGROUND: During coronavirus disease 2019 (COVID-19)-related operating room closures, some multidisciplinary thoracic oncology teams adopted a paradigm of stereotactic ablative radiotherapy (SABR) as a bridge to surgery, an approach called SABR-BRIDGE. This study presents the preliminary surgical and pathological results. METHODS: Eligible participants from four institutions (three in Canada and one in the United States) had early-stage presumed or biopsy-proven lung malignancy that would normally be surgically resected. SABR was delivered using standard institutional guidelines, with surgery >3 months following SABR with standardized pathologic assessment. Pathological complete response (pCR) was defined as absence of viable cancer. Major pathologic response (MPR) was defined as ≤10% viable tissue. RESULTS: Seventy-two patients underwent SABR. Most common SABR regimens were 34 Gy/1 (29%, n = 21), 48 Gy/3-4 (26%, n = 19), and 50/55 Gy/5 (22%, n = 16). SABR was well-tolerated, with one grade 5 toxicity (death 10 days after SABR with COVID-19) and five grade 2-3 toxicities. Following SABR, 26 patients underwent resection thus far (13 pending surgery). Median time-to-surgery was 4.5 months post-SABR (range, 2-17.5 months). Surgery was reported as being more difficult because of SABR in 38% (n = 10) of cases. Thirteen patients (50%) had pCR and 19 (73%) had MPR. Rates of pCR trended higher in patients operated on at earlier time points (75% if within 3 months, 50% if 3-6 months, and 33% if ≥6 months; p = .069). In the exploratory best-case scenario analysis, pCR rate does not exceed 82%. CONCLUSIONS: The SABR-BRIDGE approach allowed for delivery of treatment during a period of operating room closure and was well-tolerated. Even in the best-case scenario, pCR rate does not exceed 82%.

Brain Shift in Neuronavigation of Brain Tumors: An Updated Review of Intra-Operative Ultrasound Applications.

Neuronavigation using pre-operative imaging data for neurosurgical guidance is a ubiquitous tool for the planning and resection of oncologic brain disease. These systems are rendered unreliable when brain shift invalidates the patient-image registration. Our previous review in 2015, Brain shift in neuronavigation of brain tumours: A review offered a new taxonomy, classification system, and a historical perspective on the causes, measurement, and pre- and intra-operative compensation of this phenomenon. Here we present an updated review using the same taxonomy and framework, focused on the developments of intra-operative ultrasound-based brain shift research from 2015 to the present (2020). The review was performed using PubMed to identify articles since 2015 with the specific words and phrases: "Brain shift" AND "Ultrasound". Since 2015, the rate of publication of intra-operative ultrasound based articles in the context of brain shift has increased from 2-3 per year to 8-10 per year. This efficient and low-cost technology and increasing comfort among clinicians and researchers have allowed unique avenues of development. Since 2015, there has been a trend towards more mathematical advancements in the field which is often validated on publicly available datasets from early intra-operative ultrasound research, and may not give a just representation to the intra-operative imaging landscape in modern image-guided neurosurgery. Focus on vessel-based registration and virtual and augmented reality paradigms have seen traction, offering new perspectives to overcome some of the different pitfalls of ultrasound based technologies. Unfortunately, clinical adaptation and evaluation has not seen as significant of a publication boost. Brain shift continues to be a highly prevalent pitfall in maintaining accuracy throughout oncologic neurosurgical intervention and continues to be an area of active research. Intra-operative ultrasound continues to show promise as an effective, efficient, and low-cost solution for intra-operative accuracy management. A major drawback of the current research landscape is that mathematical tool validation based on retrospective data outpaces prospective clinical evaluations decreasing the strength of the evidence. The need for newer and more publicly available clinical datasets will be instrumental in more reliable validation of these methods that reflect the modern intra-operative imaging in these procedures.

Combining intraoperative ultrasound brain shift correction and augmented reality visualizations: a pilot study of eight cases.

We present our work investigating the feasibility of combining intraoperative ultrasound for brain shift correction and augmented reality (AR) visualization for intraoperative interpretation of patient-specific models in image-guided neurosurgery (IGNS) of brain tumors. We combine two imaging technologies for image-guided brain tumor neurosurgery. Throughout surgical interventions, AR was used to assess different surgical strategies using three-dimensional (3-D) patient-specific models of the patient's cortex, vasculature, and lesion. Ultrasound imaging was acquired intraoperatively, and preoperative images and models were registered to the intraoperative data. The quality and reliability of the AR views were evaluated with both qualitative and quantitative metrics. A pilot study of eight patients demonstrates the feasible combination of these two technologies and their complementary features. In each case, the AR visualizations enabled the surgeon to accurately visualize the anatomy and pathology of interest for an extended period of the intervention. Inaccuracies associated with misregistration, brain shift, and AR were improved in all cases. These results demonstrate the potential of combining ultrasound-based registration with AR to become a useful tool for neurosurgeons to improve intraoperative patient-specific planning by improving the understanding of complex 3-D medical imaging data and prolonging the reliable use of IGNS.

Brain shift in neuronavigation of brain tumors: A review.

PURPOSE: Neuronavigation based on preoperative imaging data is a ubiquitous tool for image guidance in neurosurgery. However, it is rendered unreliable when brain shift invalidates the patient-to-image registration. Many investigators have tried to explain, quantify, and compensate for this phenomenon to allow extended use of neuronavigation systems for the duration of surgery. The purpose of this paper is to present an overview of the work that has been done investigating brain shift. METHODS: A review of the literature dealing with the explanation, quantification and compensation of brain shift is presented. The review is based on a systematic search using relevant keywords and phrases in PubMed. The review is organized based on a developed taxonomy that classifies brain shift as occurring due to physical, surgical or biological factors. RESULTS: This paper gives an overview of the work investigating, quantifying, and compensating for brain shift in neuronavigation while describing the successes, setbacks, and additional needs in the field. An analysis of the literature demonstrates a high variability in the methods used to quantify brain shift as well as a wide range in the measured magnitude of the brain shift, depending on the specifics of the intervention. The analysis indicates the need for additional research to be done in quantifying independent effects of brain shift in order for some of the state of the art compensation methods to become useful. CONCLUSION: This review allows for a thorough understanding of the work investigating brain shift and introduces the needs for future avenues of investigation of the phenomenon.

IBIS: an OR ready open-source platform for image-guided neurosurgery.

PURPOSE: Navigation systems commonly used in neurosurgery suffer from two main drawbacks: (1) their accuracy degrades over the course of the operation and (2) they require the surgeon to mentally map images from the monitor to the patient. In this paper, we introduce the Intraoperative Brain Imaging System (IBIS), an open-source image-guided neurosurgery research platform that implements a novel workflow where navigation accuracy is improved using tracked intraoperative ultrasound (iUS) and the visualization of navigation information is facilitated through the use of augmented reality (AR). METHODS: The IBIS platform allows a surgeon to capture tracked iUS images and use them to automatically update preoperative patient models and plans through fast GPU-based reconstruction and registration methods. Navigation, resection and iUS-based brain shift correction can all be performed using an AR view. IBIS has an intuitive graphical user interface for the calibration of a US probe, a surgical pointer as well as video devices used for AR (e.g., a surgical microscope). RESULTS: The components of IBIS have been validated in the laboratory and evaluated in the operating room. Image-to-patient registration accuracy is on the order of [Formula: see text] and can be improved with iUS to a median target registration error of 2.54 mm. The accuracy of the US probe calibration is between 0.49 and 0.82 mm. The average reprojection error of the AR system is [Formula: see text]. The system has been used in the operating room for various types of surgery, including brain tumor resection, vascular neurosurgery, spine surgery and DBS electrode implantation. CONCLUSIONS: The IBIS platform is a validated system that allows researchers to quickly bring the results of their work into the operating room for evaluation. It is the first open-source navigation system to provide a complete solution for AR visualization.

An analysis of tracking error in image-guided neurosurgery.

PURPOSE: This study quantifies some of the technical and physical factors that contribute to error in image-guided interventions. Errors associated with tracking, tool calibration and registration between a physical object and its corresponding image were investigated and compared with theoretical descriptions of these errors. METHODS: A precision milled linear testing apparatus was constructed to perform the measurements. RESULTS: The tracking error was shown to increase in linear fashion with distance normal to the camera, and the tracking error ranged between 0.15 and 0.6 mm. The tool calibration error increased as a function of distance from the camera and the reference tool (0.2-0.8 mm). The fiducial registration error was shown to improve when more points were used up until a plateau value was reached which corresponded to the total fiducial localization error ([Formula: see text]0.8 mm). The target registration error distributions followed a [Formula: see text] distribution with the largest error and variation around fiducial points. CONCLUSIONS: To minimize errors, tools should be calibrated as close as possible to the reference tool and camera, and tools should be used as close to the front edge of the camera throughout the intervention, with the camera pointed in the direction where accuracy is least needed during surgery.

New Protocol for Skin Landmark Registration in Image-Guided Neurosurgery: Technical Note.

BACKGROUND: Newer versions of the commercial Medtronic StealthStation allow the use of only 8 landmark pairs for patient-to-image registration as opposed to 9 landmarks in older systems. The choice of which landmark pair to drop in these newer systems can have an effect on the quality of the patient-to-image registration. OBJECTIVE: To investigate 4 landmark registration protocols based on 8 landmark pairs and compare the resulting registration accuracy with a 9-landmark protocol. METHODS: Four different protocols were tested on both phantoms and patients. Two of the protocols involved using 4 ear landmarks and 4 facial landmarks and the other 2 involved using 3 ear landmarks and 5 facial landmarks. Both the fiducial registration error and target registration error were evaluated for each of the different protocols to determine any difference between them and the 9-landmark protocol. RESULTS: No difference in fiducial registration error was found between any of the 8-landmark protocols and the 9-landmark protocol. A significant decrease (P < .05) in target registration error was found when using a protocol based on 4 ear landmarks and 4 facial landmarks compared with the other protocols based on 3 ear landmarks. CONCLUSION: When using 8 landmarks to perform the patient-to-image registration, the protocol using 4 ear landmarks and 4 facial landmarks greatly outperformed the other 8-landmark protocols and 9-landmark protocol, resulting in the lowest target registration error.