Deep brain stimulation (DBS) is an established neurosurgical treatment for Parkinson’s disease (PD), mainly targeting motor symptoms resistant to pharmacological therapy. This review examines strategies to optimize DBS using advanced anatomical, functional, and imaging approaches. The subthalamic nucleus (STN) remains the principal target for alleviating bradykinesia and rigidity, while recent evidence highlights the dentato-rubro-thalamic tract (DRTt) as an additional promising target, especially for tremor control. Clinical data demonstrate that co-stimulation of both STN and DRTt via electrode electric fields results in superior motor outcomes, including greater reductions in UPDRS-III scores and lower levodopa requirements. The review highlights the use of high-resolution MRI and diffusion tensor imaging tractography in visualizing STN and DRTt with high precision. These methods support accurate targeting and individualized treatment planning. Electric field modelling is discussed as a tool to quantify stimulation overlap with target structures and predict clinical efficacy. Anatomical variability in DRTt positioning relative to the STN is emphasized, supporting the need for patient-specific DBS approaches. Alternative and emerging DBS targets—including the pedunculopontine nucleus, zona incerta, globus pallidus internus, and nucleus basalis of Meynert—are discussed for their potential in treating axial and cognitive symptoms. The review concludes with a forward-looking discussion on network-based DBS paradigms, the integration of adaptive stimulation technologies, and the potential of multimodal imaging and electrophysiological biomarkers to guide therapy. Together, these advances support a paradigm shift from focal to network-based neuromodulation in PD management.

Background/Objectives: The rapid development of artificial intelligence is transforming the face of medicine. Due to the large number of imaging studies (pre-, intra-, and postoperative) combined with histopathological and molecular findings, its impact may be particularly significant in neurosurgery. We aimed to perform a scoping review of recent applications of deep learning in MRI-based diagnostics of brain tumors relevant to neurosurgical practice. Methods: We conducted a systematic search of scientific articles available in the PubMed database. The search was performed on 22 April 2024, using the following query: ((MRI) AND (brain tumor)) AND (deep learning). We included original studies that applied deep-learning methods to brain tumor diagnostics using MRI, with potential relevance to neuroradiology or neurosurgery. A total of 893 records were retrieved, and after title/abstract screening and full-text assessment by two independent reviewers, 229 studies met the inclusion criteria. The study was not registered and received no external funding. Results: Most included articles were published after 1 January 2022. The studies primarily focused on developing models to differentiate between specific CNS tumors. With improved radiological analysis, deep-learning technologies can support surgical planning through enhanced visualization of cerebral vessels, white matter tracts, and functional brain areas. Over half of the papers (52%) focused on gliomas, particularly their detection, grading, and molecular characterization. Conclusions: Recent advancements in artificial intelligence methods have enabled differentiation between normal and abnormal CNS imaging, identification of various pathological entities, and, in some cases, precise tumor classification and molecular profiling. These tools show promise in supporting both diagnosis and treatment planning in neurosurgery.

Malignant gliomas remain among the most formidable challenges in neuro-oncology, given their high morbidity and rising incidence worldwide. Surgical resection represents the cornerstone of treatment, typically followed by adjuvant radiotherapy and chemotherapy. Achieving maximal safe resection, however, requires advanced intraoperative guidance. A range of adjuncts are currently employed, including 5-aminolevulinic acid (5-ALA), intraoperative ultrasound, computed tomography (iCT), and intraoperative magnetic resonance imaging (iMRI). More recently, an emerging technique—virtual MRI (vMRI)—has been developed, fusing intraoperative CT with preoperative high-resolution MRI to provide real-time, MRI-like updates of brain anatomy. Beyond imaging, tumour removal itself induces reorganization of eloquent brain networks, underscoring the critical need for precision tools that balance oncological control with preservation of neurological function. In this narrative review, we highlight and synthesize the evolving armamentarium of intraoperative technologies shaping the future of precision neuro-oncology.

Anterior communicating artery (AcoA) aneurysms may project in different directions - anterior, posterior, superior, or inferior - each of which can substantially alter intra-aneurysmal flow patterns and potentially influence rupture risk. The present study investigates the impact of aneurysm projection direction on hemodynamic characteristics associated with rupture and thrombosis. Transient computational fluid dynamics (CFD) simulations were performed using idealized, parametric models of AcoA aneurysms with four defined projection types: anterior (toward the frontal lobe), posterior (toward the optic chiasm), superior (toward the hypothalamus), and inferior (toward the skull base). Two aneurysm sizes were analyzed. Blood was modeled as a non-Newtonian, shear-thinning fluid under pulsatile flow conditions representative of physiological cerebral circulation. Key hemodynamic parameters, including wall shear stress and its spatial gradient, pressure, velocity, vorticity, relative residence time, viscosity, and blood washout were evaluated over multiple cardiac cycles. While global cerebral flow distribution remained unchanged, aneurysm projection produced marked differences in intra-aneurysmal hemodynamics. Anteriorly projecting aneurysms exhibited higher velocities, stronger vortical structures, elevated wall shear stress, and rapid blood washout, indicating a rupture-prone flow environment. In contrast, inferiorly projecting aneurysms demonstrated low velocity, high viscosity, reduced vorticity, and prolonged blood residence time, consistent with conditions favoring intrasaccular thrombosis. These projection-dependent patterns were preserved across both aneurysm sizes. Aneurysm projection direction is a critical determinant of AcoA aneurysm hemodynamics, independent of size. Anterior projections are associated with flow conditions linked to increased rupture risk, whereas inferior projections promote flow stagnation and thrombotic potential. These findings highlight the importance of incorporating projection-specific hemodynamic assessment into aneurysm risk stratification beyond size-based criteria.

Background: Cerebral arteriovenous malformations (AVMs) are high-flow shunts in which abnormal arteriovenous connections expose draining veins to venous hypertension, arterialization, and altered oxygenation. While digital subtraction angiography (DSA) remains the reference standard for dynamic angioarchitecture, it does not directly characterize venous oxygenation or microhemorrhagic tissue changes. Objective: To synthesize current evidence on susceptibility-based MRI-susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM) for characterization, risk-related features, and treatment monitoring in cerebral AVMs. Methods: Narrative review of the foundational and contemporary literature on AVM pathophysiology, SWI and QSM technical principles, and clinical applications including venous drainage depiction, microhemorrhage detection, oxygenation-related biomarkers, and post-treatment surveillance. Results: SWI provides high-resolution, non-contrast depiction of venous drainage and perinidal hemorrhagic/calcific components, improving visualization of draining veins and microhemorrhages compared with conventional MRI and complementing TOF-MRA. Arterialized draining veins may show altered SWI signal consistent with elevated venous oxygen saturation, though interpretation is indirect and influenced by flow and orientation. QSM extends susceptibility imaging by quantifying tissue susceptibility and enabling indirect estimation of venous oxygenation (SvO₂), offering a potential physiological biomarker of shunt severity and treatment response after radiosurgery or embolization. Key limitations include lack of dynamic flow timing, flow-related artifacts, orientation dependence, confounding from hemorrhage/calcification, and limited standardization and prospective validation. Conclusions: Susceptibility-based MRI does not replace DSA but meaningfully enriches multimodal AVM assessment by adding structural and physiological information-particularly venous mapping, microhemorrhage detection, and oxygenation-sensitive biomarkers. Standardized acquisition/reconstruction and prospective studies are needed to validate susceptibility-derived metrics for risk stratification and longitudinal monitoring.

Delayed cerebral ischemia (DCI) is a major complication of aneurysmal subarachnoid hemorrhage (aSAH), strongly associated with neurological deterioration and poor outcomes. Its pathophysiology remains incompletely understood and involves multiple interacting processes. Increasing evidence highlights the role of redox imbalance triggered by hemoglobin breakdown and the subsequent generation of reactive species, leading to vascular dysfunction, impaired nitric oxide signaling, and inflammatory activation This review aims to summarize current knowledge on redox-related mechanisms involved in DCI and to explore the potential role of the peroxiredoxin (PRDX) family in this setting. A narrative review of experimental and preclinical studies was performed, focusing on molecular pathways associated with vascular regulation, cellular injury, and antioxidant defense. Particular attention was given to the distribution and biological functions of PRDX isoforms within the central nervous system. This work addresses a topic not previously systematically discussed, the potential involvement of PRDX proteins in aSAH-related complications. By integrating available data, it provides a conceptual framework linking PRDX to mechanisms relevant for DCI. The manuscript serves as a starting point for future research, particularly translational and clinical studies in humans, which are necessary to verify the relevance of these findings and to better understand their potential clinical implications.