Background/Objectives: The objective of our study was to quantify the annual costs, from a societal perspective, encompassing direct health care costs, direct non-health care costs, and labor productivity losses associated with spinal muscular atrophy (SMA) patients in Bulgaria and their caregivers. Methods: We applied a prevalence-based, bottom-up costing methodology to assess the socio-economic burden of SMA from a societal perspective. We evaluated and summed up all costs for health services (diagnosis, treatment, follow-up, and rehabilitation), educational and social services, and formal and informal care in the community, as well as indirect costs due to the loss of productivity and work capacity of the SMA patients’ caregivers. Results: Nine parents of SMA patients provided consent and completed the study’s questionnaire. Two children had SMA type III, and seven had SMA type II. The median annual socio-economic burden per SMA patient was EUR 254,968.80. The high direct costs, primarily driven by drug expenses, and the substantial indirect costs resulting from the loss of productivity among informal caregivers were the primary causes. We found no utilization of social care and educational services. Conclusions: We emphasize the need for careful consideration of long-term outcomes, real-world data collection, and performance-based reimbursement. An ideal scenario could achieve these objectives in synergy. A second layer of policy actions and measures must address the unmet needs of SMA patients and their families using a holistic approach. The indirect costs associated with SMA, particularly the productivity loss of informal caregivers, underscore the need for comprehensive support programs.

Background/Objectives: Artificial intelligence (AI) tools are increasingly integrated into acute stroke imaging workflows, but real-world performance for ischemia detection on non-contrast CT (NCCT) remains incompletely validated by investigators independent of the developer. This study externally validated the BrainScan AI system in an unselected, consecutively enrolled emergency cohort. Methods: Consecutive adult patients undergoing NCCT under the routine acute stroke protocol at a single tertiary centre between January and December 2025 were prospectively enrolled. The reference standard was the post-consensus radiological diagnosis, supplemented where available by follow-up imaging and clinical course. Primary outcomes were diagnostic accuracy for ischemia and intracranial haemorrhage detection, assessed by sensitivity, specificity, predictive values, likelihood ratios, and area under the ROC curve (AUC; DeLong). Pre-specified secondary analyses included regional sensitivity, confidence-score behaviour, artefact robustness, threshold sensitivity, a cluster-robust bootstrap for within-patient correlation, and a quantitative bias analysis under non-differential reference-standard misclassification. Sample size adequacy was assessed using a precision-based framework. Results: A total of 1419 NCCT examinations from 1260 patients were analysed. Ischemia sensitivity was 59.2% (95% CI 52.1–66.1) and specificity was 99.8% (99.4–100), with an AUC of 0.930 (0.906–0.954). The Youden-optimal threshold (0.055) recovered sensitivity to 86.1% with negligible specificity loss, reflecting a markedly bimodal score distribution. Regional sensitivity was lower in infratentorial structures. Bias-corrected estimates were stable across all reference-standard parameters consistent with the data. Haemorrhage detection performed substantially better (sensitivity 96.7%; AUC 0.983). Conclusions: The system shows excellent specificity and strong discrimination but moderate sensitivity for ischemia, supporting its role as a rule-in adjunct rather than a stand-alone tool, pending multicentre validation and site-specific threshold recalibration.

Background: The sphenoid sinus occupies a strategically central position at the base of the skull, in close proximity to critical neurovascular structures including the pituitary gland, optic nerves, internal carotid arteries, and the cavernous sinus. Its complex anatomical configuration and pronounced individual variability render it a structure of paramount clinical importance in transsphenoidal approaches to the sellar and parasellar regions. Methods: A narrative review of the literature was conducted in accordance with the SANRA (Scale for the Assessment of Narrative Review Articles) guidelines for narrative reviews. A comprehensive search was performed across four electronic databases—PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar—covering publications from January 2000 through March 2026, with the final search update completed in March 2026. An initial pool of 826 articles was identified. Following title and abstract screening, 421 articles were retained for full-text assessment; of these, 307 contributed to the conceptual synthesis, and 100 are directly cited in the manuscript. The literature selection process followed a structured flow diagram consistent with PRISMA reporting principles for identification and screening stages. Results: We synthesise current evidence on the embryological development, macroscopic and microscopic anatomy, morphological classifications, and epidemiological distribution of anatomical variations in the sphenoid sinus, with emphasis on radiological assessment and surgical relevance. The spectrum of pneumatization patterns—from the conchal type through presellar and sellar variants to the postsellar, clival, and lateral types—is reviewed alongside population-level prevalence data. Common and rare variations are examined, including intrasinus septation, Onodi cells, and bony dehiscences overlying the internal carotid artery and optic nerve. The comparative diagnostic capabilities of computed tomography and magnetic resonance imaging are evaluated, alongside emerging modalities such as three-dimensional reconstruction, virtual reality, and augmented reality. Conclusions: Detailed morphological knowledge of the sphenoid sinus plays an important role in surgical strategy, instrument selection, and risk mitigation in skull base surgery. Individualised preoperative imaging—integrating CT, MRI, and, where available, immersive digital technologies—is essential for safe transsphenoidal planning and cannot be replaced by standard anatomical templates.