Why No Signals? Cerebral Anatomy Predicts Success of Intraoperative Neuromonitoring During Correction of Scoliosis Secondary to Cerebral Palsy

Intraoperative neurophysiological monitoring in scoliosis surgery: literature review of the last 10 years

INTRODUCTION

Patients with spinal deformities undergoing corrective surgery are at risk for iatrogenic spinal cord injury (SCI) and subsequent neurological deficit. Intraoperative neurophysiological monitoring (IONM) allows early detection of SCI which enables early intervention resulting in a better prognosis. The primary aim of this literature review was to search if there are threshold values of TcMEP and SSEP in the literature that are widely accepted as alert during IONM. The secondary aim was to update knowledge concerning IONM during scoliosis surgery.

METHOD

PubMed/MEDLINE and Cochrane library electronic databases were used to search publication from 2012 to 2022. The following keywords were used: evoked potential, scoliosis, surgery, intraoperative monitoring and neurophysiological. We included all studies dealing with SSEP and TcMEP monitoring during scoliosis surgery. Two authors reviewed all titles and abstracts to identify studies that met the inclusion criteria.

RESULTS

We included 43 papers. Rates of IONM alert and neurological deficit varied from 0.56 to 64% and from 0.15 to 8.3%, respectively. Threshold values varied from a loss of 50 to 90% for TcMEP amplitude, whereas it seems that a loss of 50% in amplitude and/or an increase of 10% of latency is widely accepted for SSEP. Causes of IONM changes most frequently reported were surgical maneuver.

CONCLUSION

Concerning SSEP, a loss of 50% in amplitude and/or an increase of 10% of latency is widely accepted as an alert. For TcMEP, it seems that the use of highest threshold values can avoid unnecessary surgical procedure for the patient without increasing risk of neurological deficit.

Spinal Fusion with Sacral Alar Iliac Pelvic Fixation in Severe Neuromuscular Scoliosis

Neuromuscular scoliosis is characterized by rapid progression of curvature during growth and may continue to progress following skeletal maturity. Posterior spinal fusion in patients with cerebral palsy and severe scoliosis results in substantial improvements in health-related quality of life¹. Correction of pelvic obliquity can greatly improve sitting balance, reduce pain, and decrease skin breakdown. The sacral alar iliac (SAI) technique has key advantages over prior techniques, including the Galveston and iliac-screw techniques. The SAI technique eliminates the need for subcutaneous muscle dissection over the iliac crest, does not require the use of connectors from the rod to the iliac screw, and decreases the risk of implant prominence².

Description

We demonstrate how to perform posterior spinal fusion with SAI pelvic fixation in a patient with cerebral palsy. In correcting the scoliosis, we utilize the segmental 3-dimensional technique, which includes compression, distraction, transverse approximation to 1 rod at a time, and derotation around 2 rods. We also demonstrate SAI pelvic fixation with identification of the screw starting point on the lateral-caudal border of the first sacral foramen and trajectory toward the anterior inferior iliac spine.

Alternatives

Nonoperative alternatives include bracing, trunk support, contouring of sitting surfaces (such as wheelchairs), and physical therapy to slow curve progression during growth periods and delay the need for surgical treatment^3,4. Decision-making is shared with the family following education about the risks and benefits. Families who are satisfied with the function of the child at baseline should not be persuaded into pursuing surgical treatment.

Rationale

Neuromuscular scoliosis can include difficulty sitting secondary to increased pelvic obliquity, along with poor trunk control and balance. Surgical intervention is considered in patients with curves exceeding approximately 50°, as these curves will often continue to progress even after maturity⁵. In patients with neuromuscular scoliosis, indications for pelvic fixation include pelvic obliquity of >15°, poor control of the trunk as indicated by lack of independent sitting or standing, and location of the apex of the curve in the lumbar spine. SAI screws are utilized as a low-profile option for pelvic fixation to avoid implant prominence and an increased risk of skin breakdown and infection, which are associated with traditional sacroiliac screws^2,6.

Expected Outcomes

Miyanji et al. reported quality outcomes in patients with cerebral palsy and Gross Motor Function Classification Scores of ≥4¹. In that study, caregivers completed a validated disease-specific questionnaire grading the health-related quality of life of the patient preoperatively and at 1, 2, and 5 years postoperatively. Complication data were prospectively collected for each patient and preoperative outcome scores were compared at each of the postoperative time points. Survey scores at 1, 2, and 5 years postoperatively were significantly higher compared with baseline preoperative values.Sponseller et al. compared the 2-year postoperative radiographic parameters of 32 pediatric patients who underwent SAI fixation and 27 patients who underwent pelvic fixation with the sacroiliac technique². Among patients who underwent SAI fixation, the mean correction of pelvic obliquity was 20° ± 11° (70% correction) and the mean Cobb angle 42° ± 25° (67%). Among patients who underwent pelvic fixation with the sacroiliac technique, those values were 10° ± 9° (50%) and 46° ± 16° (60%), respectively. SAI screws provided significantly better pelvic obliquity correction (p = 0.002) but no difference in Cobb correction or complications compared with other traditional techniques.

Important Tips

Family discussion prior to surgical treatment is paramount.Perform preoperative neurologic examination⁷.Examine the cranium carefully for a ventriculoperitoneal shunt or prior cranial reconstruction prior to cranial traction.Transcranial neuromonitoring may be useful. Use descending neural motor evoked potentials when no signals from transcranial monitoring are obtained⁸.Sink the SAI screw until it lines up with the S1 screw. Bury the SAI screw so it is not prominent.Measure rods longer in order to ensure adequate length for compression and distraction in correction of the pelvic obliquity.Use a T-square to verify adequate spinopelvic alignment⁹.Postoperatively, the use of incisional vacuum-assisted closure can decrease soiling in these patients.

Acronyms and Abbreviations

SAI = Sacral alar iliacCP = Cerebral palsyAIS = Adolescent idiopathic scoliosisSMA = Spinal muscular atrophyIONM = Intraoperative neuromonitoringGMFCS = Gross Motor Functional Classification SystemDNMEP = Descending neural motor evoked potentialTXA = Tranexamic acidFFP = Fresh frozen plasmaASIS = Anterior superior iliac spineAIIS = Anterior inferior iliac spinePJK = Proximal junctional kyphosis.

Multivariate Analysis and Machine Learning in Cerebral Palsy Research

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.