World Neurosurg
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To develop and validate natural language processing-driven artificial intelligence (AI) models for the diagnosis of lumbar disc herniation (LDH) with L5 and S1 radiculopathy using electronic health records (EHRs). ⋯ This study provides preliminary validation of the concept that natural language processing-driven AI models can be used for the diagnosis of lumbar disease using EHRs. This study could pave the way for future research that may develop more comprehensive and clinically impactful AI-driven diagnostic systems.
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Bertolotti syndrome (BS) is characterized by chronic pain and functional impairment associated with lumbosacral transitional vertebrae (LSTVs). The study aimed to investigate the histologic characteristics of the pseudoarticulation between the enlarged transverse process and sacrum seen in Castellvi 2a LSTV and explore the involvement of nervous tissue in pain generation. ⋯ The study findings suggest that nerve tissue is not involved in the nociceptive mechanisms underlying pain in BS. The histologic similarities between the pseudoarticulation and osteoarthritic joints indicate that pseudoarticulation itself may be a significant source of pain in BS. These insights contribute to our understanding of the pathophysiology of BS and support treatment paradigms prioritizing pain control with medications such as NSAIDs before considering surgical intervention. Future studies with larger sample sizes and in vivo models are needed to further validate these findings and explore the changes in joint histology under biomechanical forces in LSTVs.
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Introducing a preoperative image simulation technique to streamline the visualization of the foramen ovale in percutaneous microcompression. ⋯ Based on our initial findings, the application of preoperative image simulation shows significant referential value in achieving accurate visualization of the foramen ovale in percutaneous microcompression for trigeminal neuralgia.
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Tubular retractors in minimally invasive lumbar stenosis permit surgeons to achieve satisfactory neural decompression while minimizing the morbidity of the surgical access.1-3 Transtubular lumbar decompression requires intraoperative image guidance and microscopic magnification to achieve precise and reproductible surgical results. Use of 2-dimensional image guidance in transtubular lumbar decompression has a major limitation due to the lack of multiplanar orientation. Consequently, there is a risk of incomplete decompression and excessive bone removal resulting in iatrogenic instability. ⋯ This tailors the bone resection to achieve adequate neural decompression while minimizing the risks of potential spine instability. After precise placement of the tubular retractor, bone removal and neural decompression are accomplished under robotic exoscope magnification with 4k 3D images. Using a 3D robotic exoscope (Modus V, Synaptive, Toronto, Canada) allows better tissue magnification and improves surgeon ergonomics during lumbar decompression through tubular retractors.5,6.
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Microsurgical interventions involve the interaction of numerous variables, making objective analysis of skill proficiency challenging. This difficulty is even more pronounced in low-resource contexts. Continuous improvement methodologies such as Kaizen-planning, doing, checking, acting (PDCA) and micromovements science (MMS) can address this issue. This study aimed to demonstrate the advantages of designing and implementing microsurgical training programs using these methodologies. ⋯ The training program and methodology effectively assessed, facilitated, and demonstrated the acquisition of microsurgical skills. Kaizen-PDCA and MMS enabled the effective use of expert experience, detailed evaluation of microsurgical procedures, and integration into a continuous improvement cycle. The program structure could also be valuable for teaching, evaluating, and enhancing similar surgical procedures.