Recent therapeutic advances in metastatic melanoma have led to improved overall survival (OS) rates, with consequently an increased incidence of brain metastases (BM). The role of BM resection in the era of targeted and immunotherapy should be reassessed. In the current study we analysed the role of residual intracranial tumour load in a cohort of melanoma BM patients. Retrospective single-centre analysis of a prospective registry of resected melanoma BM from 2013 to 2021. Correlations of residual tumour volume and outcome were determined with respect to patient, tumour and treatment regimens characteristics. 121 individual patients (66% male, mean age 59.9 years) were identified and included in the study. Pre- and postoperative systemic treatments included BRAF/MEK inhibitors, as well as combination or monotherapy of immune-checkpoint inhibitors (ICIs). Median OS of the entire cohort was 20 months. Cox proportional-hazard analysis revealed postoperative anti-CTLA4+anti-PD-1 therapy (HR 0.07, p = .01) and postoperative residual intracranial tumour burden (HR 1.4, p = .027) as significant predictors for OS. Further analysis revealed that ICI-naïve patients with residual tumour volume ≤3.5 cm³ and postoperative ICI showed significantly prolonged OS compared to patients with residual volume >3.5 cm³ (p < .0001). Subgroup analysis of ICI-naïve patients showed steroid intake postoperatively to be negatively associated with OS, however residual tumour volume ≤3.5 cm³ remained independently correlated with superior OS (HR 0.14, p < .001). Besides known predictive factors like postoperative ICI, a maximal intracranial tumour burden reduction seems to be beneficial, especially in ICI-naïve patients. This highlights the importance of local CNS control and the need to further investigating the role of initial surgical tumour load reduction in randomised clinical trials.

Hypoxia-powered blood oxygen level-dependent (BOLD) MRI probes the BOLD response to a controlled transient hypoxic stimulus. We developed GLIODISSECT, an operational voxel-wise framework that separates relative response arrival, descending and recovery transitions, and threshold-defined steady state amplitude. Twenty healthy controls underwent 3-T BOLD MRI during a double hypoxic-step challenge, and three patients with newly diagnosed glioblastoma were included as proof-of-concept cases. Full-record cross-correlation and first-step 10% landmarks yielded one refined voxel-wise lag that was reused downstream. Alternative 5%/95% and 20%/80% thresholds preserved steady state map patterns (median within-subject spatial r 0.9987-0.9998), while timing measures were more threshold-dependent. Numerical criteria were satisfied in 97.789% and 97.682% of evaluable delay-to-plateau (DTP) estimates and in all evaluable delay-to-return (DTR) estimates. Leave-one-subject-out validation of the global-response-adjusted steady state model yielded a median voxel-wise Q ² of 0.345 and reduced pooled prediction error by 16.0%, improving 19 of 20 controls. In the three illustrative cases, component and deviation maps displayed spatially heterogeneous timing and steady state patterns that could not be represented by one response-amplitude summary. GLIODISSECT supports component-specific mapping and voxel-wise normative interpretation. Biological and clinical validation remain required.

Objective: Traumatic brain injury (TBI) significantly reduces the quality of life for millions of survivors worldwide, causing persistent brain tissue damage and cognitive impairments, with no established therapeutic interventions currently available. Slow‐wave activity, a hallmark of deep sleep, has been implicated in recovery after TBI, but pharmacological approaches to enhance it lack specificity and scalability, complicating efforts to identify slow‐wave activity as a direct mechanistic contributor and severely limiting clinical translation. Methods: To overcome these limitations, we developed a preclinical closed‐loop auditory stimulation (CLAS) paradigm that targets sleep's slow waves, enabling highly specific and temporally precise enhancement of slow‐wave activity. Therefore, we delivered 30‐ms sound triggers targeting the up‐phase of real‐time detected slow‐waves (upCLAS: TBI n = 8), or no sound stimulation (mockCLAS: non‐TBI n = 8, TBI n = 7) during sleep to healthy controls (non‐TBI) or brain injured (TBI) rats. Concomitantly, we assessed the ability of upCLAS‐enhanced sleep to counteract brain tissue damage (primary outcome) and symptomatic sequelae (secondary outcome) of TBI. Results: Bayesian analysis revealed that sound‐mediated slow‐wave activity enhancement: (1) reduces diffuse axonal injury, with TBI mockCLAS posterior estimates falling outside the 95% confidence intervals of both other groups, whereas the posterior distributions of TBI upCLAS and non‐TBI groups largely overlapped (~13% posterior differences >0), consistent with a negligible effect size between groups; (2) decreases demyelination, with approximately 97% posterior differences >0 between TBI mockCLAS and TBI upCLAS groups, compared to approximately 60% between non‐TBI and TBI upCLAS groups; and (3) preserves cognitive ability, with recognition indexes in the novel object recognition test significantly above chance level in non‐TBI (* p = 0.031) and TBI upCLAS (* p = 0.026) groups, in contrast to mockCLAS‐treated TBI rats ( p = 0.156), presenting pronounced cognitive deficit. Furthermore, microglial response to brain injury was increased by deep sleep enhancement, with reduced ionized calcium‐binding adaptor molecule 1+ area coverage in TBI upCLAS rats (* p = 0.0445) compared to non‐TBI ones. Interpretation: These results unambiguously demonstrate slow‐wave activity enhancement confers robust disease modification following TBI while overcoming major limitations of other preclinical approaches. Our findings constitute proof‐of‐concept that boosted sleep intensity mitigates histopathological and cognitive sequelae of brain trauma, suggesting that a clinically relevant, nonobtrusive, sleep‐based therapy may represent a novel therapeutic intervention for TBI survivors. ANN NEUROL 2026

Purpose: Hypoxia-targeted blood oxygen level–dependent (BOLD) MRI is an emerging non-contrast imaging technique for characterizing tumor biology in isocitrate dehydrogenase-wildtype glioblastoma. Beyond the magnitude of BOLD signal changes, signal heterogeneity may provide valuable information about tumor aggressiveness and microenvironmental complexity. The aim was to assess both the magnitude and heterogeneity of hypoxia-targeted BOLD signal changes across subregions of glioblastomas. Methods: In this prospective pilot study, hypoxia-targeted BOLD MRI data from 12 patients with histopathologically confirmed glioblastoma were analyzed. Tumor subregions were defined using an automated segmentation framework (Oncohabitats) based on conventional MRI and dynamic susceptibility contrast (DSC) MR perfusion imaging. Voxel-wise BOLD signal changes were calculated within the following volumes of interest: highly angiogenic tumor (HAT), low angiogenic tumor (LAT), peritumoral edema, and mirrored contralateral control tissue (mCET). The magnitude of BOLD signal changes was assessed using median BOLD signal changes, while heterogeneity was quantified using interquartile ranges (IQR), and kernel density estimation-derived entropy. Friedman tests with Dunn post-hoc tests were used to assess parameter differences between the VOIs. Results: HAT demonstrated the largest BOLD signal changes compared with LAT, edema, and mCET (all FDR-adjusted p ≤ 0.017). Heterogeneity metrics revealed significantly increased IQR and entropy in HAT compared with edema and mCET (all FDR-adjusted p < 0.008), with LAT showing intermediate values. Conclusion: Hypoxia-targeted BOLD MRI reveals both greater BOLD signal changes and elevated intratumoral heterogeneity in highly angiogenic and likely aggressive glioblastoma subregions. These findings suggest that heterogeneity metrics may provide complementary information to BOLD signal magnitude alone.

Background: Postoperative outcome assessment is often based on discrete follow-up visits, limiting characterization of individual recovery trajectories, and the timely identification of adverse events (AEs). Longitudinal smartphone-based monitoring may overcome these limitations by enabling frequent, resource-efficient collection of patient-reported outcomes and complications throughout recovery. Such data may provide a more patient-centered understanding of the postoperative course and complement conventional clinical surveillance. Objective: This study aimed to evaluate the feasibility of smartphone-based longitudinal monitoring of quality of life, subjective well-being, and AEs after elective neurosurgery and compare postoperative recovery trajectories and agreement between patient- and clinician-reported AEs. Methods: This interim analysis of a prospective cohort study included adult patients undergoing elective lumbar decompression, lumbar fusion, supratentorial craniotomy, or infratentorial craniotomy at a Swiss tertiary referral center between June 2023 and January 2025. Participants used a smartphone app to longitudinally report subjective well-being (Subjective Well-Being Index; 0‐10), quality of life (EQ-5D-5L), and AEs for up to 1 year postoperatively. Complications were self-reported using the Therapy-Disability-Neurology (TDN) classification and retrospectively adjudicated by physicians. Descriptive analyses assessed data density, engagement, and concordance between patient- and clinician-reported events. Mixed-effects models were used to evaluate factors associated with postoperative well-being. Results: Of the 100 enrolled patients (median age 64.0, IQR 52.95‐71.6 years; n=45, 45% women), 86 (86%) provided postoperative data. During a median follow-up of 3.2 (IQR 0.2‐11.3) months, participants submitted 4354 longitudinal well-being entries. Patients reported 22 unique AEs, whereas physicians identified 44 AEs, with overlap for 9 (20.5%) events. Most physician-reported AEs were mild (30/44, 68.2%; TDN grade 1‐2), and no grade 4 or 5 events occurred. Patient-reported AEs primarily reflected symptomatic and functional impairments, whereas physician-reported events more often included clinically detected or subclinical findings. In mixed-effects models, time since surgery was associated with improved well-being, and no other factors were statistically significant. Conclusions: Smartphone-based postoperative monitoring was feasible in this elective neurosurgical cohort and generated dense longitudinal patient-reported data beyond routine follow-up. Patient and clinician AE reporting captured partly distinct aspects of postoperative recovery, suggesting that smartphone-based self-reporting may complement rather than replace clinical surveillance.

Background/Objectives: Carotid endarterectomy (CEA) is a standard surgical treatment for high-grade symptomatic and asymptomatic internal carotid artery (ICA) stenosis. The Transit Time Flowmeter (TTF) provides an easy-to-use tool to quantify intraoperative ICA blood flow in mL/min. This study aimed to (1) describe post-CEA ICA flow quantified with TTF, (2) identify predictors of post-CEA ICA flow, and (3) examine its association with contralateral steno-occlusive disease. Methods: We queried data from our prospective registry of patients who underwent a CEA between January 2019 and July 2024 and had intraoperative registered post-CEA ICA flow measurements using TTF. Preoperative ICA stenosis was graded according to the NASCET criteria. The clinical data was retrospectively collected. Results: Data from 196 CEAs in 190 patients (median age 74 [67–81]; 25% female) were included. Most patients (86%) had a symptomatic ICA stenosis. The median post-CEA ICA flow was 170 mL/min [IQR 140–242; range 40–800]. Post-CEA ICA flow was not associated with age, sex, comorbidities, symptomatic stenosis, left ventricular ejection fraction (LVEF), or ipsilateral stenosis severity but was significantly higher in patients requiring intraluminal shunt placement during CEA (p = 0.010) as well as in those with contralateral steno-occlusive disease (p < 0.001). Conclusions: TTF is a practical intraoperative tool for quantitative flow assessment during CEA. Higher post-CEA ICA flow in patients with an intraoperative shunt placement or with contralateral steno-occlusive disease may reflect a compensatory hyperperfusion, as the ipsilateral ICA serves as a key supplier when collateral pathways are incomplete.