View clinical trials related to Spine Tumor.
Filter by:Cervical spine tumor is a small sample of tumor disease with low incidence, great harm, and complex anatomical structure. It is very difficult to identify and classify benign and malignant cervical spine tumors clinically. The deep learning model we constructed in the early stage has a higher accuracy rate for the image diagnosis of cervical spondylosis with a large number of cases, and a better clinical application effect, but the accuracy rate for cervical spine tumors with a small number of cases is lower. The reason may be the amount of data. With limited tasks, the traditional deep learning model is difficult to play an effective role. Based on this, we propose to build a small sample-oriented deep learning model to assist clinicians in the diagnosis of cervical spine tumors with multimodal images, and to evaluate the benign and malignant tumors.
Recently intraoperative motor evoked potential monitoring (MEP) is widely used to reduce neural damage during neurosurgery. As neuromuscular blockade(NMB) during MEP monitoring decreases the amplitude of MEP, partial NMB is usually maintained during general anesthesia. Continuous infusion of NMB agent is preferred than bolus infusion during MEP monitoring. There are a lot of NMB agents in clinical use. But there have been no reports about the effect of changing NMB agent on efficacy of MEP monitoring. Therefore, the investigators performed a randomized controlled trial to evaluate the effect of changing NMB agent on the variability of MEP amplitude during neurosurgery.
Within defined groups of primary malignant and benign bone and soft tissue spine tumors, what variables (clinical, diagnostic, therapeutic, and/or demographic) are associated with overall survival?