Intraoperative Neurophysiological Monitoring in Spine Surgery

Intraoperative neurophysiological monitoring (IONM) has become an integral component of modern spine surgery, offering real-time assessment of the functional integrity of neural pathways. By employing a combination of somatosensory evoked potentials, motor evoked potentials and electromyography, the surgical team receives continuous feedback on spinal cord and nerve root function during instrumentation, tumour resection and deformity correction. The principal aim is to detect impending neurological injury at an early, reversible stage, enabling immediate adjustment of surgical manoeuvres or anaesthetic parameters. Modalities are often used in a multimodal fashion: somatosensory evoked potentials track ascending dorsal column pathways, motor evoked potentials assess descending corticospinal tracts, and spontaneous or triggered electromyography identifies nerve root irritation. In specialised centres, D-wave recordings provide direct measurements of spinal cord output with high sensitivity. IONM has demonstrated utility across a spectrum of procedures—from cervical decompression to complex deformity correction and intramedullary tumour excision—contributing to reduced rates of postoperative motor and sensory deficits. However, its efficacy depends on close cooperation among surgeon, anaesthetist and neurophysiologist, meticulous attention to anaesthetic regimens and prompt interpretation of warning criteria. As techniques evolve, IONM supports safer surgical practice, enhancing patient outcomes and informing evidence-based protocols worldwide.

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Intraoperative Neurophysiological Monitoring in Spine Surgery publication trend

The graph below shows the total number of articles in intraoperative neurophysiological monitoring in spine surgery across all publications each year (not limited to Nature Index journals).

Technical terms

Somatosensory evoked potentials (SSEPs): Neurophysiological responses recorded over the cortex or spinal cord following peripheral sensory nerve stimulation, used to assess dorsal column integrity.

Motor evoked potentials (MEPs): Muscle responses elicited by transcranial electrical or magnetic stimulation of the motor cortex, reflecting corticospinal tract function.

Electromyography (EMG): Recording of electrical activity in peripheral muscles, either spontaneous or in response to nerve stimulation, to detect nerve root irritation or injury.

D-wave recording: Direct measurement of descending spinal cord action potentials via epidural electrodes, offering high sensitivity for motor pathway monitoring.

Explainable artificial intelligence (XAI): Computational methods that not only predict outcomes from data but also provide human-interpretable insights into the features driving those predictions.

Random forest classifier: An ensemble machine-learning algorithm using multiple decision trees to improve predictive accuracy and control overfitting.

References

1. Explainable AI for Intraoperative Motor-Evoked Potential Muscle Classification in Neurosurgery: Bicentric Retrospective Study. Journal of Medical Internet Research (2025).
2. Opportunities and challenges of supervised machine learning for the classification of motor evoked potentials according to muscles. BMC Medical Informatics and Decision Making (2023).
3. Multimodal Intraoperative Neurophysiological Monitoring in Intramedullary Spinal Cord Tumors: A 10-Year Single Center Experience. Cancers (2023).