World Neurosurg
-
This retrospective cohort study aimed to evaluate the effectiveness of posterior long-segment fixation for thoracolumbar osteoporotic vertebral compression fractures (TLOVCFs) and identify prognosis-predicting factors. ⋯ Posterior long-segment fixation effectively improved kyphotic deformity and provided stable outcomes in patients with TLOVCFs. Open screw fixation offered better maintenance of correction with a lower risk of screw loosening compared to percutaneous methods. Therefore, further prospective studies are necessary to establish standardized treatment protocols for TLOVCFs.
-
The purpose of this study was to investigate whether the preservation of the anterior edge of the vertebral body affects the cage subsidence and clinical outcomes after anterior cervical discectomy and fusion (ACDF) using zero-profile cages. ⋯ For patients who undergo ACDF with zero-profile cages, especially those with a higher surgical segment, bone protection at the anterior edge of the vertebral body can effectively reduce the risk of zero-profile cage subsidence, but there is no difference in the final clinical effect.
-
We describe a case of a 57-year-old woman presenting initially with diplopia who later developed retro-orbital and retroauricular pain. Examination showed right abducens nerve palsy and subsequent right trigeminal nerve hyperesthesia. Neuroimaging revealed a well-defined mass confined to the right cavernous sinus, with high T2 signal intensity and homogeneous enhancement on postgadolinium T1-weighted images. ⋯ CSH is a rare benign extra-axial tumor, which is highly vascularized, and is frequently misdiagnosed as meningioma or schwannoma. The combination of very high T2 signal intensity and progressive centripetal contrast enhancement highly suggest CSH diagnosis. Given the significant risk of bleeding and mortality associated with surgical intervention, it is crucial to recognize CSH preoperatively to plan a meticulous surgical approach.
-
Review
Machine Learning Algorithms for Neurosurgical Preoperative Planning: A Comprehensive Scoping Review.
Preoperative neurosurgical planning is an important step in avoiding surgical complications, reducing morbidity, and improving patient safety. The incursion of machine learning (ML) in this domain has recently gained attention, given the notable advantages in processing large datasets and potentially generating efficient and accurate algorithms in patient care. We explored the evolving applications of ML algorithms in the preoperative planning of brain and spine surgery. ⋯ ML algorithms for preoperative neurosurgical planning are being developed for efficient, automated, and safe treatment decision-making. However, future studies are necessary to validate their objective performance across diverse clinical scenarios. Enhancing the robustness, transparency, and understanding of ML applications will be crucial for their successful integration into neurosurgical practice.