Impact of Multimodal Intraoperative Monitoring During Surgery for Spine Deformity and Potential Risk Factors for Neurological Monitoring Changes

Feng, Bin; Qiu, Guixing; Shen, Jianxiong; Zhang, Jianguo; Tian, Ye; Li, Shugang; Zhao, Hong; Zhao, Yu

doi:10.1097/bsd.0b013e31824d2a2f

Cited by 80 publications

(74 citation statements)

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“…For the first step, 10 candidate variables were investigated using univariable logistic regression models. These candidates were selected based on clinical relevance and previous literature [6][7][8][9][10][11][12][13][14][15][16][17]. In the second step, all these variables were entered in a multivariable logistic regression model using backward selection with a retention criterion of p-value of less than .25.…”

Section: Discussionmentioning

confidence: 99%

“…For instance, spinal osteotomy for rigid deformity is generally believed to be a high-risk procedure, and the severity of the deformity has also been found to be predictive of intraoperative spinal cord monitoring events in a recent study [6]. Only a few modern studies in the literature have documented the risk factors [6][7][8][9][10][11][12][13][14][15][16][17]. The objective of the present study was to elucidate the risk factors associated with neurologic decline after surgical correction of complex ASD.…”

Section: Introductionmentioning

confidence: 99%

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Incidence and risk factors of postoperative neurologic decline after complex adult spinal deformity surgery: results of the Scoli-RISK-1 study

et al. 2018

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Incidence and risk factors of postoperative neurologic decline after complex adult spinal deformity surgery: results of the Scoli-RISK-1 study

et al. 2018

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“…17,18,35 The use of intraoperative neuromonitoring allows the surgical team the potential for real-time identification of neural element dysfunction and the possibility to remedy reversible causes, including hypotension, ongoing cord compression, or overcorrection of deformity. 21,31,40 Due to the strong relationship between anesthetic administration and the effectiveness of monitoring, [12][13][14]36,45,49 which can result in false-positive monitoring alerts, 32 effective teamwork and communication between the anesthesia, neuromonitoring, and surgical teams is necessary to determine the cause and to institute corrective action in response to monitoring alerts.…”

Section: 2941mentioning

confidence: 99%

The design, development, and implementation of a checklist for intraoperative neuromonitoring changes

Ziewacz¹,

Berven

Mummaneni³

et al. 2012

FOC

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Object The purpose of this study was to provide an evidence-based algorithm for the design, development, and implementation of a new checklist for the response to an intraoperative neuromonitoring alert during spine surgery. Methods The aviation and surgical literature was surveyed for evidence of successful checklist design, development, and implementation. The limitations of checklists and the barriers to their implementation were reviewed. Based on this review, an algorithm for neurosurgical checklist creation and implementation was developed. Using this algorithm, a multidisciplinary team surveyed the literature for the best practices for how to respond to an intraoperative neuromonitoring alert. All stakeholders then reviewed the evidence and came to consensus regarding items for inclusion in the checklist. Results A checklist for responding to an intraoperative neuromonitoring alert was devised. It highlights the specific roles of the anesthesiologist, surgeon, and neuromonitoring personnel and encourages communication between teams. It focuses on the items critical for identifying and correcting reversible causes of neuromonitoring alerts. Following initial design, the checklist draft was reviewed and amended with stakeholder input. The checklist was then evaluated in a small-scale trial and revised based on usability and feasibility. Conclusions The authors have developed an evidence-based algorithm for the design, development, and implementation of checklists in neurosurgery and have used this algorithm to devise a checklist for responding to intraoperative neuromonitoring alerts in spine surgery.

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“…Several types of surgery can be performed on scoliotic patients to reduce their spinal deformations. Precise positioning of hooks and screws on vertebrae attached to a rod, using anterior or posterior approach, to bring back the normal curvature of the spine is an example [1,2]. For patient with stiff curvature, a disk resection is often required to be able to properly attach instrumentations to the rod and optimise the results of the surgery [3,4].…”

Section: Introductionmentioning

confidence: 99%

Quantitative evaluation of an automatic segmentation method for 3D reconstruction of intervertebral scoliotic disks from MR images

et al. 2012

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Background: For some scoliotic patients the spinal instrumentation is inevitable. Among these patients, those with stiff curvature will need thoracoscopic disk resection. The removal of the intervertebral disk with only thoracoscopic images is a tedious and challenging task for the surgeon. With computer aided surgery and 3D visualisation of the interverterbral disk during surgery, surgeons will have access to additional information such as the remaining disk tissue or the distance of surgical tools from critical anatomical structures like the aorta or spinal canal. We hypothesized that automatically extracting 3D information of the intervertebral disk from MR images would aid the surgeons to evaluate the remaining disk and would add a security factor to the patient during thoracoscopic disk resection. Methods: This paper presents a quantitative evaluation of an automatic segmentation method for 3D reconstruction of intervertebral scoliotic disks from MR images. The automatic segmentation method is based on the watershed technique and morphological operators. The 3D Dice Similarity Coefficient (DSC) is the main statistical metric used to validate the automatically detected preoperative disk volumes. The automatic detections of intervertebral disks of real clinical MR images are compared to manual segmentation done by clinicians. Results: Results show that depending on the type of MR acquisition sequence, the 3D DSC can be as high as 0.79 (±0.04). These 3D results are also supported by a 2D quantitative evaluation as well as by robustness and variability evaluations. The mean discrepancy (in 2D) between the manual and automatic segmentations for regions around the spinal canal is of 1.8 (±0.8) mm. The robustness study shows that among the five factors evaluated, only the type of MRI acquisition sequence can affect the segmentation results. Finally, the variability of the automatic segmentation method is lower than the variability associated with manual segmentation performed by different physicians. Conclusions: This comprehensive evaluation of the automatic segmentation and 3D reconstruction of intervertebral disks shows that the proposed technique used with specific MRI acquisition protocol can detect intervertebral disk of scoliotic patient. The newly developed technique is promising for clinical context and can eventually help surgeons during thoracoscopic intervertebral disk resection.

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Impact of Multimodal Intraoperative Monitoring During Surgery for Spine Deformity and Potential Risk Factors for Neurological Monitoring Changes

Cited by 80 publications

References 0 publications

Incidence and risk factors of postoperative neurologic decline after complex adult spinal deformity surgery: results of the Scoli-RISK-1 study

Incidence and risk factors of postoperative neurologic decline after complex adult spinal deformity surgery: results of the Scoli-RISK-1 study

The design, development, and implementation of a checklist for intraoperative neuromonitoring changes

Quantitative evaluation of an automatic segmentation method for 3D reconstruction of intervertebral scoliotic disks from MR images

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