Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system (CNS). Neuropathic pain in MS is a debilitating symptom that significantly impairs the quality of life for a substantial proportion of MS patients. Neuropathic pain in MS stems primarily from demyelination, axonal loss, CNS inflammation, and direct damage to the myelin sheath, leading to pain manifestations such as ongoing extremity pain, Lhermitte's phenomenon, and trigeminal neuralgia (TN). The pathophysiological mechanisms behind MS-related neuropathic pain are explored in this review, highlighting central sensitization, neural dysfunction, spinal thalamic tract dysfunction, and inflammatory processes that exacerbate neuronal damage. Neuropathic pain in MS necessitates comprehensive assessment tools and neurophysiological tests to differentiate neuropathic pain from other MS symptoms accurately. Treatment strategies for MS-related neuropathic pain encompass pharmacological interventions, including anticonvulsants and antidepressants, and emerging therapies targeting specific inflammatory processes. The review advocates for a holistic approach to management, incorporating innovative treatments and multidisciplinary strategies to address both the physical symptoms and psychosocial aspects of this disorder. This comprehensive overview underscores the importance of ongoing research into targeted therapies to improve patient outcomes and enhance the quality of life for those affected by MS.
Soft tissue sarcomas are malignant tumors characterized by heterogeneity and are associated with a high mortality rate. Histopathological grading is considered a pivotal factor in prognostication and treatment planning. While core needle biopsy exhibits high accuracy in determining tumor histology, it fails in some cases, potentially misclassifying high-grade tumors as low-grade. Magnetic resonance imaging (MRI) has been evaluated as an adjunctive tool for predicting histopathological tumor grade. This systematic review and meta-analysis evaluated MRI features capable of distinguishing high-grade from low-grade tumors in patients with soft tissue sarcoma. A literature search was carried out in PubMed, Embase, and Cochrane Central in May 2024. The following features were evaluated for both low-grade and high-grade tumors: tumor size, heterogeneity on T2, presence of necrotic areas, margin definition on T1, and post-contrast peritumoral enhancement. Statistical analysis was conducted using the OpenMeta[Analyst] software (Providence, RI: Brown University), applying random effects models for pooled analyses with a 95% confidence interval (CI) based on the inverse variance method. A total of four studies, involving 343 patients categorized by tumor grade (high-grade or low-grade), who underwent MRI, were included in the analysis. The meta-analysis found similar incidences of tumor sizes less than 5 cm in both high-grade and low-grade tumors (22.7%; 95% CI: 10.3-25% vs. 27%; 95% CI: 2.7-51.2%) and tumor sizes greater than 5 cm (71.3%; 95% CI: 64-78.6% vs. 52%; 95% CI: 23.6-80.5%). High-grade tumors showed a higher incidence of post-contrast peritumoral enhancement compared to low-grade tumors (66%; 95% CI: 43-89% vs. 26%; 95% CI: 4.6-47.4%) as well as heterogeneity on T2 greater than 50% (72.4%; 95% CI: 49.3-95.4% vs. 25.4%; 95% CI: 5.2-56%). Additionally, high-grade tumors had a lower incidence of the absence of necrotic signal compared to low-grade tumors (28.8%; 95% CI: 8.5-49.1% vs. 68%; 95% CI: 57.5-78.6%). Our findings suggest that post-contrast peritumoral enhancement, presence of necrotic areas, and heterogeneity on T2 greater than 50% are MRI features associated with high-grade tumors in soft tissue sarcoma. Tumor size, however, does not appear to be a reliable indicator for differentiating tumor grade.