Achala Vagal

Summary: Children with sickle cell disease (SCD) have enlarged perivascular spaces (ePVS) in their basal ganglia (BG) and centrum semiovale (CSO) visible on magnetic resonance imaging (MRI). ePVS are dilated fluid‐filled spaces around penetrating arterioles and venules of the brain parenchyma and are a marker of cerebral small vessel disease in adults. We used the T2‐weighted MRI from the Silent Cerebral Infarct Transfusion Trial to (1) quantify the ePVS burden in children with the severe SCD genotypes and (2) evaluate for an association between ePVS burden and silent cerebral infarcts (SCIs) adjusted for laboratory/imaging measures of SCD severity. The study included 929/1191 (78%) of participants with a median age of 8.9 (5–15) years, 48% female, and 48% had a high ePVS burden in at least one region. More children with a higher ePVS burden in the BG and whole brain had at least one SCI, whereas there was no difference in SCI based on ePVS burden status in the CSO. In multivariable logistic regression, high ePVS burden was associated with the presence of SCI in the BG and whole brain only. ePVS may become a useful neuroimaging biomarker of SCD‐related neurological disease.

This study aimed to assess the trends in contribution of neuroradiologists as clinician-scientists advancing research through NIH-funded research. Between 2012 and 2025, neuroradiologists accounted for 29.2% of principal investigators in radiology, 33.6% of grants and 41.1% of cumulative funding to all clinician-scientists in radiology. Neuroradiology lead across all funding metrics of NIH-funded research in radiology.

Approximately one-fourth of all strokes are recurrent, which is associated with a higher risk of morbidity/death. Identifying stroke survivors at greatest risk of recurrence could help direct secondary prevention efforts, but prior models based on clinical data have limited predictive ability. Neuroimaging markers of brain health may be uniquely able to capture the duration and severity of traditional and nontraditional risk factors for recurrence, and we examined whether they could improve the prediction of stroke recurrence beyond clinical factors alone using advanced machine-learning techniques. Using a well-validated approach, all ischemic strokes and TIAs during 2015 were ascertained in a representative population of the United States. Standard-of-care neuroimaging was collected for all patients across 18 different hospitals and centrally read/analyzed for more than 20 different measures of brain health. Only patients who underwent standard of care MRI were included. Patients were then followed for 3 years to assess for stroke recurrence. Using both clinical and neuroimaging variables, prediction models of recurrence at 90-days and 3-years were built using random survival forests. A total of 1999 patients (46.6% male and 21.2% Black) had sufficient clinical and imaging data to be included in the final study population, including 275 (13.8%) patients who experienced a recurrent stroke event. Models that included clinical and imaging variables outperformed those with clinical data alone at 90 days (C-statistics increased from 0.63 with 95% CI 0.520–0.740 , to 0.667 with 95% CI 0.567–0.767; P=0.0498) and at 3 years (C-statistics increased from 0.618 with 95% CI 0.572–0.663 to 0.683 with 95% CI 0.637–0.729; P<0.001).Among imaging variables, global cortical atrophy scale, microbleed count, deep white matter hyperintensities (WMH), and baseline CT ASPECTS were highly important variables at both time points. Neuroimaging data can improve the prediction of stroke recurrence but only moderately improves discriminative ability. Other strategies will be needed to better identify stroke patients at highest risk of recurrence, including dynamic prediction models or other non-imaging biomarkers.

Automated intracranial hemorrhage (ICH) detection tools are widespread, yet data are limited regarding their performance in real-world practice. We retrospectively analyzed noncontrast CT head images of consecutive code stroke patients from January 2022 to February 2023 at a comprehensive stroke center. Patients were included if their indication was stroke, and images were assessed by the automated platform. Radiology reports were considered the gold standard. The primary outcome was the performance of the automated software tool compared with that of board-certified radiologists in ICH detection. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated using SAS software. Of 1,434 code stroke CT scans, 1,402 (98%) were analyzed using the automated detection tool. Thirty-two studies were considered nondiagnostic because of severe motion degradation, and these were excluded. The mean patient age was 67 ± 16 years, with 51% of patients being women and 65% of patients being White. The software tool accurately identified 105 of 129 ICH cases (81%) and 1,255 of the 1,273 non-ICH cases (99%). The sensitivity, specificity, positive predictive value, and negative predictive value with 95% CIs were 81% (74%-88%), 99% (98%-99%), 85% (78%-91%), and 98% (97%-99%), respectively. Automated software sensitivity was highest for intra-axial hemorrhage (IAH) at 94%. Extra-axial hemorrhage (EAH) had a sensitivity of just 43%. Sensitivity of mixed IAH and EAH was 89%, representing a significant increase from isolated EAH. Automated ICH detection software demonstrates high accuracy in detecting ICH in real-world practice. Sensitivity for IAH is particularly high, with detection of EAH reaching acceptable parameters when co-presenting with IAH but lacking in isolation.

Artificial intelligence (AI) is rapidly transforming medical imaging, yet its integration into neuroradiology remains uneven. This survey-based study assesses AI usage, tools, applications, barriers, and future expectations among U.S. neuroradiology departments. This cross-sectional survey questionnaire comprised 19 items, blending multiple-choice, multi-select, and open-ended formats. Descriptive statistics were used to identify patterns in data. Most departments (81%) reported AI use, primarily for stroke-related applications, with smaller numbers using tools for report generation, segmentation, and image quality enhancement. Most clinical tools were FDA-approved. AI had minimal perceived impact on workload, and performance was viewed as variable, with concerns about accuracy and false positives. Cost, integration challenges, and limited efficacy evidence were the main barriers to adoption. Despite these limitations, most respondents anticipated increased AI use over the next five years. Findings underscore the need for clinician-vendor collaboration to realize AI's potential in reducing workload and improving outcomes.

Background: Several observational studies have supported the use of conscious sedation (CS) for endovascular thrombectomy in patients with acute ischemic stroke and associated general anesthesia (GA) with poor functional outcomes. Recently, few randomized controlled trials have shown no difference in the functional outcomes between GA and CS. The aim of this paper is to compare the outcomes of GA versus CS in patients with acute ischemic stroke undergoing mechanical thrombectomy in the MOST (Multi‐arm Optimization of Stroke Thrombolysis) trial. Methods: Patients who underwent mechanical thrombectomy for acute ischemic stroke under GA or CS in the MOST trial were included. The primary outcome of interest was the utility weighted modified Rankin Scale (mRS) score at 90 days after stroke. The secondary outcomes were mRS score ≤1, ≤2 at 90 days, 90‐day mRS score, thrombolysis in cerebral infarction 2B or better, 24‐hour National Institutes of Health Stroke Scale score, 24‐hour change in National Institutes of Health Stroke Scale score, and 90‐day mortality. Results: A total of 219 patients underwent mechanical thrombectomy with 101 patients receiving GA and 118 patients receiving CS. Our analysis showed that GA was associated with a lower average utility weighted mRS score at 90 days compared with CS ( P ≤0.02). Similarly, GA was associated with higher odds of worse outcomes on 90‐day mRS 0 to 2 ( P P P P <0.001). A sensitivity analysis of patients with anterior stroke alone also favored better neurologic outcomes in the CS group compared with the GA group. Conclusions: In patients undergoing endovascular thrombectomy in the MOST trial, GA was associated with poorer functional outcomes compared with CS.

BACKGROUND: Recent randomized trials showed no benefit of mechanical thrombectomy (MT) for ischemic stroke due to distal medium vessel occlusion (DMVO). We sought to understand the use of MT for DMVO stroke treatment before and after the publication of these trials. METHODS: We conducted an email survey of 47 comprehensive stroke centers across the United States, which are participating in a National Institutes of Health–funded randomized controlled trial (RCT; Unique identifier: NCT05948566). The questionnaire was developed and modified with expert feedback. Site principal investigators were asked to discuss the DMVO RCT results with their local clinical teams and to subsequently respond to survey questions in a manner that reflected team-based decision-making regarding MT for DMVO before and after the publication of the RCTs, considering the location of the vessel occlusion (nondominant M2 versus M3/M4/A1/A2). If the site principal investigator was responsible for >1 site with the same stroke team, only 1 survey response was tallied. RESULTS: Of the 43 site principal investigators surveyed representing 47 unique sites, 40 (93%) representing 44 unique sites completed the survey. Before the DMVO RCTs, 95% of respondents were treating nondominant M2 occlusions with MT. Only 15% will continue to be treated with MT, while 57.5% said that treatment was dependent on at least ≥1 variable following presentation of the DMVO RCTs. For all other anterior circulation DMVOs, 50% were treating DMVOs with MT before RCT results’ presentation. Only 7.5% will continue to treat with MT, while 32.5% said that treatment was dependent on at least 1 other variable following presentation of the DMVO RCTs. The most common variable named by survey respondents as important to treatment decision was symptom severity. CONCLUSIONS: In this survey of comprehensive stroke centers, the DMVO RCT results created a significant practice change in how stroke teams approach anterior circulation DMVO stroke with MT.

BACKGROUND: Minimally invasive surgical evacuation improved outcomes for patients with acute, spontaneous, lobar intracerebral hemorrhage (ICH) in the ENRICH trial (Early Minimally Invasive Removal of ICH). We determined the percentage of patients with ICH in a US population–based study eligible for minimally invasive surgical evacuation and projected the annual number of patients with ICH in the United States in 2020 eligible for this therapy. METHODS: We ascertained adults (aged ≥18 years) with acute (International Classification of Diseases codes, clinical data abstracted, and physician adjudicated. Location and volume of ICH were centrally adjudicated by neuroradiologists. We applied ENRICH trial criteria to calculate conservative and liberal estimates of the percentage of patients with (1) all ICH at any location and (2) lobar ICH eligible for minimally invasive surgical evacuation. We extrapolated our estimates to the 2020 US adult population using 2020 US census data. RESULTS: We identified 196 patients in Greater Cincinnati/Northern Kentucky in 2015 with acute, spontaneous ICH. After applying all criteria, 2.0% (n=5) of all patients with acute ICH (5.1%; n=5 lobar ICH) were eligible for minimally invasive surgical evacuation. The most common exclusion criteria were ICH volume 1 (52%). In liberal estimates, 2.6% to 3.6% (n=4–7) of all patients with acute ICH (4.1%–7.1% of lobar ICH) were eligible. We projected 1066 to 1848 patients of an estimated 72 283 adult patients with ICH in the United States in 2020 met eligibility criteria. CONCLUSIONS: Approximately 2% to 4% of patients with ICH in our population were eligible for minimally invasive surgical evacuation based on ENRICH criteria, which extrapolates to 1066 to 1848 patients with ICH in the United States annually. Future research is needed to determine whether indications for effective surgical therapy for ICH can be expanded.

Purpose Healthcare costs in large vessel occlusion acute ischemic stroke (AIS-LVO) patients vary widely despite achieving successful reperfusion. Prolonged venous transit (PVT+) is a new marker of poor venous outflow on pretreatment perfusion imaging associated with various patient outcomes. We aim to explore the relationship between PVT + and acute care cost estimates for AIS-LVO. Methods Adult AIS-LVO patients achieving successful reperfusion with thrombectomy at three centers in the United States were retrospectively reviewed. Cost estimates were derived from national averages for services in the Centers for Medicare and Medicaid Services data (2025). The primary outcome was total cost estimates for acute intervention, imaging, and post-treatment inpatient care until discharge. Estimates were compared between PVT + and PVT- cohorts. Results In 109 included patients, the median age was 71 years (IQR 62–80). The cost estimates for total acute stroke care were significantly greater by $11787 in PVT + patients (median $36601 [IQR $24814-$72944] than PVT- patients (median $24814 [IQR $16956-$48388], p = 0.03). Cost of post-treatment care was significantly greater in PVT + patients than PVT- patients (p = 0.03). Conclusion PVT + demonstrates potential as a useful, versatile pretreatment biomarker, in conjunction with other clinical data, to anticipate in-hospital resources and costs associated with acute stroke care.