(1) Background: Spinal cord injury (SCI) represents a major health challenge, often leading to significant and permanent sensorimotor and autonomic dysfunctions. This study reviews the evolving role of epidural spinal cord stimulation (eSCS) in treating chronic SCI, focusing on its efficacy and safety. The objective was to analyze how eSCS contributes to the recovery of neurological functions in SCI patients. (2) Methods: We utilized the PRISMA guidelines and performed a comprehensive search across MEDLINE/PubMed, Embase, Web of Science, and IEEE Xplore databases up until September 2023. We identified studies relevant to eSCS in SCI and extracted assessments of locomotor, cardiovascular, pulmonary, and genitourinary functions. (3) Results: A total of 64 studies encompassing 306 patients were identified. Studies investigated various stimulation devices, parameters, and rehabilitation methods. Results indicated significant improvements in motor function: 44% of patients achieved assisted or independent stepping or standing; 87% showed enhanced muscle activity; 65% experienced faster walking speeds; and 80% improved in overground walking. Additionally, eSCS led to better autonomic function, evidenced by improvements in bladder and sexual functions, airway pressures, and bowel movements. Notable adverse effects included device migration, infections, and post-implant autonomic dysreflexia, although these were infrequent. (4) Conclusion: Epidural spinal cord stimulation is emerging as an effective and generally safe treatment for chronic SCI, particularly when combined with intensive physical rehabilitation. Future research on standardized stimulation parameters and well-defined therapy regimens will optimize benefits for specific patient populations.

Spine surgery has significantly progressed due to innovations in surgical techniques, technology, and a deeper understanding of spinal pathology. However, numerous challenges persist, complicating successful outcomes. Anatomical intricacies at transitional junctions demand precise surgical expertise to avoid complications. Technical challenges, such as underestimation of the density of fixed vertebrae, individual vertebral characteristics, and the angle of pedicle inclination, pose additional risks during surgery. Patient anatomical variability and prior surgeries add layers of difficulty, often necessitating thorough pre- and intraoperative planning. Technological challenges involve the integration of artificial intelligence (AI) and advanced visualization systems. AI offers predictive capabilities but is limited by the need for large, high-quality datasets and the “black box” nature of machine learning models, which complicates clinical decision making. Visualization technologies like augmented reality and robotic surgery enhance precision but come with operational and cost-related hurdles. Patient-specific challenges include managing postoperative complications such as adjacent segment disease, hardware failure, and neurological deficits. Effective patient outcome measurement is critical, yet existing metrics often fail to capture the full scope of patient experiences. Proper patient selection for procedures is essential to minimize risks and improve outcomes, but criteria can be inconsistent and complex. There is the need for continued technological innovation, improved patient-specific outcome measures, and enhanced surgical education through simulation-based training. Integrating AI in preoperative planning and developing comprehensive databases for spinal pathologies can aid in creating more accurate, generalizable models. A holistic approach that combines technological advancements with personalized patient care and ongoing education is essential for addressing these challenges and improving spine surgery outcomes.

Traumatic spinal cord injury (SCI) remains a devastating condition, with limited functional recovery despite advancements in clinical management and understanding of its mechanisms. SCI pathophysiology involves primary mechanical trauma and secondary neuroimmune and structural changes, leading to neuronal death and chronic functional deficits. Through a comprehensive literature review of articles published in the PubMed, MEDLINE, Embase, and Cochrane Reviews Library databases, this article provides an update on the current management of traumatic SCI with a focus on these emerging therapeutic strategies that hold potential for future advancements in the field. Current management strategies include pre-hospital care, acute clinical interventions, surgical decompression and spine destabilization, and neurorehabilitation. Despite these interventions, SCI patients often fail to fully restore lost functions. Emerging therapies focus on neuroprotection, neuroregeneration, and neuromodulation, leveraging advances in molecular biomarkers, imaging techniques, and cell-based treatments. Neuroprotective agents, including the sodium-glutamate antagonist riluzole, aim to keep cells alive through the secondary injury phase, while regenerative strategies utilize neurotrophic factors and stem cell transplantation or approaches to target inhibitor molecules such as NOGO or RGMa to regenerate new cells, axons, and neural circuits. Neuromodulation techniques, such as electrical and magnetic field stimulation, offer promising avenues for functional recovery. Combining these novel therapies with traditional neurorehabilitation holds potential for improved outcomes. While significant strides have been made in understanding the mechanisms underlying SCI and in developing novel therapeutic approaches, the challenge and opportunity will be to tailor treatments to fit the heterogenous clinical presentation of patients with SCI and to better understand the heterogeneity in clinical trajectories.

Background/Objectives: Hemodynamic stressors, including abnormal wall shear stress (low or high) or oscillatory shear index are recognized as contributors to the pathogenesis, growth, and rupture of intracranial aneurysms (IAs). Computational fluid dynamics (CFD) has therefore become an essential tool for their quantitative assessment. This systematic review aimed to identify the most frequently analyzed hemodynamic and morphological parameters in recent CFD studies and summarize the methodological strategies employed. Methods: A systematic review was conducted following the PRISMA guidelines, including original studies published between 2019 and 2024 in PubMed, Scopus, Web of Science, and Embase databases. Eligible studies applied CFD to human saccular aneurysms addressing rupture or growth. Exclusion criteria comprised stent-assisted treatments, idealized or phantom models, and non-human or in vitro analyses. Extracted data included study characteristics, CFD software, meshing and solver approaches, and reported parameters. Results: Thirty-five studies met the eligibility criteria. Commercial software predominated across the segmentation, meshing, and solver stages. The most frequently evaluated wall shear stress metrics were the oscillatory shear index (OSI, 91.43%), time-averaged wall shear stress (TAWSS, 71.43%), low shear area ratio (LSAR, 60.00%), normalized wall shear stress (NWSS, 51.43%), and relative residence time (RRT, 45.71%). Morphological parameters such as the aspect ratio (AR, 74.29%), size ratio (SR, 68.57%), and volume (42.86%), reflecting aneurysm shape and relative size, were the most consistently evaluated and demonstrated strong associations with rupture and growth. Conclusions: A core set of morphological and hemodynamic parameters (AR, SR, TAWSS, OSI, RRT, and LSAR) was consistently identified as potential discriminators for the rupture and growth of intracranial aneurysms. However, substantial methodological heterogeneity and the absence of unified standards hinder reproducibility and clinical translation. Future research must urgently standardize computational frameworks, parameter definitions, and boundary conditions to enhance the consistency, comparability, and clinical applicability of CFD in aneurysm risk assessment.