| Summary: | Spinal tumor metastases are secondary tumors in the bone of the vertebral column that arise from primary cancers from other areas of the body. Metastatic neoplasms in the spine have significant implications for the overall quality of life of patients with all cancer types. Bone is one of the most common sites for metastases to develop, and the spine is the most common osseous site for metastatic disease. Accurate and early diagnosis is critical in order to prevent irreversible spinal cord damage. MRI is the standard for diagnostic imaging, and various techniques to employ key imaging findings are discussed. Treating spinal tumor metastases requires an interdisciplinary approach involving close collaboration between oncologists, neurosurgeons, radiologists and orthopedic surgeons. The Neurological, Oncological, Mechanical instability and Systemic disease (NOMS) decision-making framework has been developed to assess these four pillars in order to facilitate complex decision-making across specialties to improve treatment for secondary spinal tumors. One of the major advantages of NOMS is its ability to incorporate the most recent clinical data available in the decision framework. Each component of NOMS has various methods for standardizing prognostication and recommending treatment options, but the reliability of these methods is questioned by the literature. Standardized prognostication and treatment planning have high potential for improving treatment outcomes, but more research on their accuracy is imperative for optimal application. Creating a common language across medical disciplines can help streamline the treatment process and prevent unnecessary complications. As the revolutionary advancements in cancer treatment continue to unfold and more cancer patients achieve long term survival, the incidence of spinal tumor metastases will increase for patients with advanced metastatic cancers. This thesis will discuss the utility of current diagnostic standards, assess the value of prognostic scoring systems, and evaluate the decision-making framework used to synthesize treatment recommendations based on diagnostic and prognostic data.
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