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  • By Author: Sciubba, Daniel M. x
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Camilo A. Molina, Nicholas Theodore, A. Karim Ahmed, Erick M. Westbroek, Yigal Mirovsky, Ran Harel, Emanuele Orru’, Majid Khan, Timothy Witham and Daniel M. Sciubba

OBJECTIVE

Augmented reality (AR) is a novel technology that has the potential to increase the technical feasibility, accuracy, and safety of conventional manual and robotic computer-navigated pedicle insertion methods. Visual data are directly projected to the operator’s retina and overlaid onto the surgical field, thereby removing the requirement to shift attention to a remote display. The objective of this study was to assess the comparative accuracy of AR-assisted pedicle screw insertion in comparison to conventional pedicle screw insertion methods.

METHODS

Five cadaveric male torsos were instrumented bilaterally from T6 to L5 for a total of 120 inserted pedicle screws. Postprocedural CT scans were obtained, and screw insertion accuracy was graded by 2 independent neuroradiologists using both the Gertzbein scale (GS) and a combination of that scale and the Heary classification, referred to in this paper as the Heary-Gertzbein scale (HGS). Non-inferiority analysis was performed, comparing the accuracy to freehand, manual computer-navigated, and robotics-assisted computer-navigated insertion accuracy rates reported in the literature. User experience analysis was conducted via a user experience questionnaire filled out by operators after the procedures.

RESULTS

The overall screw placement accuracy achieved with the AR system was 96.7% based on the HGS and 94.6% based on the GS. Insertion accuracy was non-inferior to accuracy reported for manual computer-navigated pedicle insertion based on both the GS and the HGS scores. When compared to accuracy reported for robotics-assisted computer-navigated insertion, accuracy achieved with the AR system was found to be non-inferior when assessed with the GS, but superior when assessed with the HGS. Last, accuracy results achieved with the AR system were found to be superior to results obtained with freehand insertion based on both the HGS and the GS scores. Accuracy results were not found to be inferior in any comparison. User experience analysis yielded “excellent” usability classification.

CONCLUSIONS

AR-assisted pedicle screw insertion is a technically feasible and accurate insertion method.

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Wataru Ishida, Joshua Casaos, Arun Chandra, Adam D’Sa, Seba Ramhmdani, Alexander Perdomo-Pantoja, Nicholas Theodore, George Jallo, Ziya L. Gokaslan, Jean-Paul Wolinsky, Daniel M. Sciubba, Ali Bydon, Timothy F. Witham and Sheng-Fu L. Lo

OBJECTIVE

With the advent of intraoperative electrophysiological neuromonitoring (IONM), surgical outcomes of various neurosurgical pathologies, such as brain tumors and spinal deformities, have improved. However, its diagnostic and therapeutic value in resecting intradural extramedullary (ID-EM) spinal tumors has not been well documented in the literature. The objective of this study was to summarize the clinical results of IONM in patients with ID-EM spinal tumors.

METHODS

A retrospective patient database review identified 103 patients with ID-EM spinal tumors who underwent tumor resection with IONM (motor evoked potentials, somatosensory evoked potentials, and free-running electromyography) from January 2010 to December 2015. Patients were classified as those without any new neurological deficits at the 6-month follow-up (group A; n = 86) and those with new deficits (group B; n = 17). Baseline characteristics, clinical outcomes, and IONM findings were collected and statistically analyzed. In addition, a meta-analysis in compliance with the PRISMA guidelines was performed to estimate the overall pooled diagnostic accuracy of IONM in ID-EM spinal tumor resection.

RESULTS

No intergroup differences were discovered between the groups regarding baseline characteristics and operative data. In multivariate analysis, significant IONM changes (p < 0.001) and tumor location (thoracic vs others, p = 0.018) were associated with new neurological deficits at the 6-month follow-up. In predicting these changes, IONM yielded a sensitivity of 82.4% (14/17), specificity of 90.7% (78/86), positive predictive value (PPV) of 63.6% (14/22), negative predictive value (NPV) of 96.3% (78/81), and area under the curve (AUC) of 0.893. The diagnostic value slightly decreased in patients with schwannomas (AUC = 0.875) and thoracic tumors (AUC = 0.842). Among 81 patients who did not demonstrate significant IONM changes at the end of surgery, 19 patients (23.5%) exhibited temporary intraoperative exacerbation of IONM signals, which were recovered by interruption of surgical maneuvers; none of these patients developed new neurological deficits postoperatively. Including the present study, 5 articles encompassing 323 patients were eligible for this meta-analysis, and the overall pooled diagnostic value of IONM was a sensitivity of 77.9%, a specificity of 91.1%, PPV of 56.7%, and NPV of 95.7%.

CONCLUSIONS

IONM for the resection of ID-EM spinal tumors is a reasonable modality to predict new postoperative neurological deficits at the 6-month follow-up. Future prospective studies are warranted to further elucidate its diagnostic and therapeutic utility.