Objective: This study aimed to evaluate whether modifying the post-processing algorithm of Twin-Spiral Dual-Energy computed tomography (DECT) improves infarct detection compared to conventional Dual-Energy CT (DECT) and Single-Energy CT (SECT) following endovascular therapy (EVT) for large vessel occlusion (LVO). Methods: We retrospectively analyzed 52 patients who underwent Twin-Spiral DECT after endovascular stroke therapy. Ten patients were used to generate a device-specific parameter (“y”) using an AI-based neural network (SynthSR). This parameter was integrated into the post-processing algorithm for edema map generation. Quantitative Hounsfield unit (HU) measurements were used to assess density differences in ischemic brain tissue across conventional virtual non-contrast (VNC) images and edema maps. Results: The median HU of infarcted tissue in conventional mixed DECT was 33.73 ± 4.58, compared to 22.96 ± 3.81 in default VNC images. Edema maps with different smoothing filter settings showed values of 14.39 ± 4.96, 14.50 ± 3.75, and 15.05 ± 2.65, respectively. All edema maps demonstrated statistically significant HU differences of infarcted tissue compared to conventional VNC images ($p<0.001$) while maintaining the density values of non-infarcted brain tissue. Conclusions: Enhancing the post-processing algorithm of conventional virtual non-contrast imaging improves infarct detection compared to standard mixed or virtual non-contrast reconstructions in Dual-Energy CT.

Background/Objectives: Several imaging scores have been developed for subarachnoid hemorrhage (SAH), but their prognostic performance for long-term functional outcome and post-hospital complications remains insufficiently characterized. We evaluated whether five admission imaging scores (modified Fisher, Claassen, Hijdra, Graeb, IVH) independently predict 12-month functional outcome and major secondary endpoints. Methods: We performed a retrospective cohort study of 479 consecutive patients with atraumatic SAH recorded in a prospectively maintained institutional registry. Admission CT/MRI was scored by two board-certified neuroradiologists blinded to clinical outcomes. The primary endpoint was unfavorable functional outcome at 12 months (modified Rankin scale [mRS] 4–6). Secondary endpoints included 12-month mortality, delayed cerebral ischemia (DCI), post-hemorrhagic epilepsy, shunt-dependent hydrocephalus, return to work, and patient-reported health. Receiver operating characteristic (ROC) analyses and multivariable logistic regression adjusted for established predictors were conducted. Results: All imaging scores were significantly associated with the primary endpoint and demonstrated adequate discrimination (area under the curve [AUC] ~0.70–0.74), with the Graeb and IVH scores performing highest for long-term functional outcome, mortality, and shunt dependence. Associations with DCI and epilepsy were modest. In multivariable analyses, all imaging scores remained independently associated with mRS 4–6. Subgroup analyses showed stronger prognostic performance in good-grade SAH, aneurysmal SAH, and cases with concomitant intraventricular hemorrhage. Conclusions: Admission imaging burden independently predicts 12-month functional outcome, mortality, and shunt dependence after SAH. Incorporating IVH-oriented measures alongside established clinical grading may improve individualized risk stratification, particularly in good-grade and aneurysmal SAH.

Introduction: Tenecteplase is increasingly adopted as an alternative to alteplase for intravenous thrombolysis in acute ischemic stroke. However, real-world data describing complete institutional transitions, particularly in extended treatment windows and off-label clinical scenarios, remain limited. Methods: We conducted a retrospective cohort study of consecutive patients treated with intravenous thrombolysis during the 12 months before and after a complete institutional transition from alteplase to tenecteplase (June 2023–May 2025). Primary endpoints were in-hospital workflow metrics (door-to-needle, door-to-imaging, imaging-to-needle, door-to-groin, and door-to-recanalization times). Safety outcomes included any intracranial hemorrhage and symptomatic intracranial hemorrhage according to the SITS-MOST definition. Outcomes were analyzed in the overall cohort, in patients treated beyond 4.5 h after symptom onset, and in patients receiving oral anticoagulation. Multivariable-adjusted and propensity score–based analyses, including augmented inverse probability of treatment weighting, were applied to account for baseline differences. Results: Among 591 thrombolyzed patients (rt-PA n = 278; TNK n = 313), 31% were treated beyond 4.5 h and 14% under oral anticoagulation. Tenecteplase was associated with significantly shorter door-to-needle times (31 vs. 35 min; p = 0.004), primarily driven by reduced imaging-to-needle intervals (13 vs. 16 min; p = 0.004). Door-to-groin times were numerically shorter with tenecteplase but did not differ significantly (70 vs. 76 min; p = 0.07). Rates of any intracranial hemorrhage (8% vs. 7%; p = 0.61) and symptomatic intracranial hemorrhage (3% vs. 1%; p = 0.34) were comparable. Similar safety findings were observed in patients treated beyond 4.5 h after symptom onset and in those receiving oral anticoagulation, with consistent results across multivariable-adjusted and propensity score–based analyses. Conclusion: Institutional transition to tenecteplase was associated with improved in-hospital workflow without evidence of increased hemorrhagic complications. These findings support the feasibility of implementing tenecteplase as the standard thrombolytic agent in routine comprehensive stroke center practice, including in extended treatment windows and selected off-label clinical scenarios.

Objective: This study aimed to evaluate whether modifying the post-processing algorithm of twin-spiral dual-energy computed tomography (DECT) improves infarct detection compared to conventional dual-energy or single-energy CT (DECT/SECT) following endovascular therapy (EVT) for large vessel occlusion (LVO). Methods: We retrospectively analyzed 52 patients who underwent twin-spiral DECT after endovascular stroke therapy. Ten patients were used to generate a device-specific parameter (“y”) using an AI-based neural network (SynthSR). This parameter was integrated into the post-processing algorithm for edema map generation. Quantitative Hounsfield unit (HU) measurements were used to assess density differences in ischemic brain tissue across conventional virtual non-contrast (VNC) images and edema maps. Results: The median HU of infarcted tissue in conventional mixed DECT was 33.73 ± 4.58, compared to 22.96 ± 3.81 in default VNC images. Edema maps with different smoothing filter settings showed values of 14.39 ± 4.96, 14.50 ± 3.75, and 15.05 ± 2.65, respectively. All edema maps demonstrated statistically significant HU differences of infarcted tissue compared to conventional VNC images (p<0.001) while maintaining the density values of non-infarcted brain tissue. Conclusion: Enhancing the post-processing algorithm of conventional virtual non-contrast imaging improves infarct detection compared to standard mixed or virtual non-contrast reconstructions in dual-energy CT.