Background and Objectives: In the literature, spinal navigation and robot-assisted surgery improved screw placement accuracy, but the majority of studies only qualitatively report on screw positioning within the vertebra. We sought to evaluate screw placement accuracy in relation to a preoperative trajectory plan by three-dimensional quantification to elucidate technical benefits of navigation for lumbar pedicle screws. Materials and Methods: In 27 CT-navigated instrumentations for degenerative disease, a dedicated intraoperative 3D-trajectory plan was created for all screws. Final screw positions were defined on postoperative CT. Trajectory plans and final screw positions were co-registered and quantitatively compared computing minimal absolute differences (MAD) of screw head and tip points (mm) and screw axis (degree) in 3D-space, respectively. Differences were evaluated with consideration of the navigation target registration error. Clinical acceptability of screws was evaluated using the Gertzbein–Robbins (GR) classification. Results: Data included 140 screws covering levels L1-S1. While screw placement was clinically acceptable in all cases (GR grade A and B in 112 (80%) and 28 (20%) cases, respectively), implanted screws showed considerable deviation compared to the trajectory plan: Mean axis deviation was 6.3° ± 3.6°, screw head and tip points showed mean MAD of 5.2 ± 2.4 mm and 5.5 ± 2.7 mm, respectively. Deviations significantly exceeded the mean navigation registration error of 0.87 ± 0.22 mm (p < 0.001). Conclusions: Screw placement was clinically acceptable in all screws after navigated placement but nevertheless, considerable deviation in implanted screws was noted compared to the initial trajectory plan. Our data provides a 3D-quantitative benchmark for screw accuracy achievable by CT-navigation in routine spine surgery and suggests a framework for objective comparison of screw outcome after navigated or robot-assisted procedures. Factors contributing to screw deviations should be considered to assure optimal surgical results when applying navigation for spinal instrumentation.

Frame-based stereotactic biopsy (FBSB) is a minimally-invasive and effective procedure for the diagnosis of brain lesions and will likely gain clinical importance. Since FBSB procedures comprise a variety of imaging and sampling methods, it is necessary to compare the safety and effectiveness of individual techniques. To assess the safety and effectiveness of FBSB using 1.5T iMRI as a one-stop procedure under general anesthesia without intraoperative histological examination. In this single-center, retrospective analysis, 500 consecutive FBSBs using iMRI were compared to a historic control of 100 biopsies with traditional workflows (computed tomography (CT) with MRI image fusion). All procedures were performed under general anesthesia. Data on surgical procedures, pre- and postoperative neurologic patient status, complications and diagnostic yield were extracted from clinical records. Complication rates and diagnostic yield showed no significant differences between both groups. Mortality was 0.6%, 95% CI = [0.12%, 1.74%], in the iMRI and 0.0% [0.00%, 3.62%], in the control group with a morbidity of 5.4% [3.6%, 7.8%] and 6.0% [2.2%, 12.6%] and a diagnostic yield of 96.8% [94.9%, 98.2%] and 96.0% [90.1%, 98.9%]. Mean procedure duration was 124 [121, 127] minutes using iMRI and 112 [106, 118] minutes in the control group. FBSB using 1.5T iMRI under general anesthesia is a safe and effective procedure and is equivalent to traditional stereotactic workflows with respect to complication rate and diagnostic yield.

Background: This ex vivo experimental study sought to compare screw planning accuracy of a self-derived deep-learning-based (DL) and a commercial atlas-based (ATL) tool and to assess robustness towards pathologic spinal anatomy. Methods: From a consecutive registry, 50 cases (256 screws in L1-L5) were randomly selected for experimental planning. Reference screws were manually planned by two independent raters. Additional planning sets were created using the automatic DL and ATL tools. Using Python, automatic planning was compared to the reference in 3D space by calculating minimal absolute distances (MAD) for screw head and tip points (mm) and angular deviation (degree). Results were evaluated for interrater variability of reference screws. Robustness was evaluated in subgroups stratified for alteration of spinal anatomy. Results: Planning was successful in all 256 screws using DL and in 208/256 (81%) using ATL. MAD to the reference for head and tip points and angular deviation was 3.93 ± 2.08 mm, 3.49 ± 1.80 mm and 4.46 ± 2.86° for DL and 7.77 ± 3.65 mm, 7.81 ± 4.75 mm and 6.70 ± 3.53° for ATL, respectively. Corresponding interrater variance for reference screws was 4.89 ± 2.04 mm, 4.36 ± 2.25 mm and 5.27 ± 3.20°, respectively. Planning accuracy was comparable to the manual reference for DL, while ATL produced significantly inferior results (p < 0.0001). DL was robust to altered spinal anatomy while planning failure was pronounced for ATL in 28/82 screws (34%) in the subgroup with severely altered spinal anatomy and alignment (p < 0.0001). Conclusions: Deep learning appears to be a promising approach to reliable automated screw planning, coping well with anatomic variations of the spine that severely limit the accuracy of ATL systems.

Background: Routine admission to an intensive care unit (ICU) following brain tumor surgery has been a common practice for many years. Although this practice has been challenged by many authors, it has still not changed widely, mainly due to the lack of reliable data for preoperative risk assessment. Motivated by this dilemma, risk prediction scores for postoperative complications following brain tumor surgery have been developed recently. In order to improve the ICU admission policy at our institution, we assessed the applicability, performance, and safety of the two most appropriate risk prediction scores. Methods: One thousand consecutive adult patients undergoing elective brain tumor resection within 19 months were included. Patients with craniotomy for other causes, i.e., cerebral aneurysms and microvascular decompression, were excluded. The decision for postoperative ICU-surveillance was made by joint judgment of the operating surgeon and the anesthesiologist. All data and features relevant to the scores were extracted from clinical records and subsequent ICU or neurosurgical floor documentation was inspected for any postoperative adverse events requiring ICU admission. The CranioScore derived by Cinotti et al. (Anesthesiology 129(6):1111–20, 5) and the risk assessment score of Munari et al. (Acta Neurochir (Wien) 164(3):635–641, 15) were calculated and prognostic performance was evaluated by ROC analysis. Results: In our cohort, both scores showed only a weak prognostic performance: the CranioScore reached a ROC-AUC of 0.65, while Munari et al.’s score achieved a ROC-AUC of 0.67. When applying the recommended decision thresholds for ICU admission, 64% resp. 68% of patients would be classified as in need of ICU surveillance, and the negative predictive value (NPV) would be 91% for both scores. Lowering the thresholds in order to increase patient safety, i.e., 95% NPV, would lead to ICU admission rates of over 85%. Conclusion: Performance of both scores was limited in our cohort. In practice, neither would achieve a significant reduction in ICU admission rates, whereas the number of patients suffering complications at the neurosurgical ward would increase. In future, better risk assessment measures are needed.

Background: Three-dimensional (3D) visualization is thought to improve the anatomical understanding of clinicians, thus improving patient safety. Case presentation: A 58-year-old male was admitted to our hospital in April 2007 with a suspected metastasis of a sigmoid cancer in the Couinaud segment (CS) 7. The anatomical situation of this patient was analyzed using both a CT scan and 3D images. The initial CT scan revealed that the proximal part of the middle hepatic vein was completely missing and the metastasis in the CS 7 was closely attached to the right hepatic vein. After analyzing additional 3D images, it became clear that due to the close proximity of metastasis and right hepatic vein, the resection of the right hepatic vein was inevitable. Based on this 3D analysis, it was decided to perform a right-sided hemihepatectomy. In this case report, 3D visualization resulted in a faster and clearer understanding of the unique anatomical situation in a patient with complicated liver anatomy than transversal CT images. Conclusion: The here presented data shows for the first time 3D visualization of intravenous anastomoses in the human liver. The information offered by 3D visualization is not redundant but rather serves as a true source of additional information, indicating the potential benefit of 3D visualization in surgical operation planning.