Towards a common language in neurosurgical outcome evaluation: the NEON (NEurosurgical Outcome Network) proposal.

BACKGROUND: The aim of this study was to achieve a consensus on the minimum set of outcome measures and predictors to be used in the neurosurgical practice and on the timing of outcome assessment. METHODS: A consensus building approach was employed. All neurosurgical departments in Lombardy (Italy) were invited to participate by the Carlo Besta Neurologic Institute IRCCS Foundation. Three workshops were organized during which a multidisciplinary group called Neurosurgical Outcome Network (NEON) was created and the methodology to select outcome measures, predictors, and timing of outcome assessment was established. Eight working groups were created for the different neurosurgical diseases (neuro-oncological, skull base, vascular, traumatic, spinal, peripheral nervous system, malformation, functional) and 8 workshops were organized to identify the outcome measures and predictors specific for each of the neurosurgical diseases based on the experts' clinical practice and the existing literature. RESULTS: A total of 20 neurosurgical departments participated in this study. Specific outcome measures, predictors and the timing of outcome assessment were identified for each of the 8 neurosurgical diseases. Moreover, a list of variables common to all pathologies were identified by the NEON group as further data to be collected. CONCLUSIONS: A consensus on the minimum set of outcome measures and predictors and the timing of outcome assessments for 8 neurosurgical diseases was achieved by a group of neurosurgeons of the Lombardy region, called NEON. These sets could be used in future studies for a more homogeneous data collection and as a starting point to reach further agreement also at national and international level.

Complex Spine Pathology Simulator: An Innovative Tool for Advanced Spine Surgery Training.

Background Technical advancements in spine surgery have made possible the treatment of increasingly complex pathologies with less morbidity. Time constraints in surgeons' training have made it necessary to develop new training models for spine pathology. Objective To describe the application of a novel compound, Stratathane resin ST-504 derived polymer (SRSDP), that can be injected at different spinal target locations to mimic spinal epidural, subdural extra-axial, and intra-axial pathologies for the use in advanced surgical training. Material and Methods Fresh-frozen thoracolumbar and cervical spine segments of human and sheep cadavers were used to study the model. SRSDP is initially liquid after mixing, allowing it to be injected into target areas where it expands and solidifies, mimicking the entire spectrum of spinal pathologies. Results Different polymer concentrations have been codified to vary adhesiveness, texture, spread capability, deformability, and radiologic visibility. Polymer injection was performed under fluoroscopic guidance through pathology-specific injection sites that avoided compromising the surgical approach for subsequent excision of the artificial lesion. Inflation of a balloon catheter of the desired size was used to displace stiff cadaveric neurovascular structures to mimic pathology-related mass effect. Conclusion The traditional cadaveric training models principally only allow surgeons to practice the surgical approach. The complex spine pathology simulator is a novel educational tool that in a user-friendly, low-cost fashion allows trainees to practice advanced technical skills in the removal of complex spine pathology, potentially shortening some of the aspects of the learning curve of operative skills that may otherwise take many years to acquire.