High Hypoperfusion Intensity Ratio Is Independently Associated with Very Poor Outcomes in Large Ischemic Core Stroke.

BACKGROUND: Recent advances have highlighted the efficacy of endovascular thrombectomy (EVT) in patients with large ischemic core stroke, yet a significant portion still experience very poor outcomes, defined as a 90-day modified Rankin Score (mRS) of 5-6. This study aims to investigate the hypoperfusion intensity ratio (HIR) as a prognostic imaging parameter for these outcomes. METHODS: In a multicenter retrospective cohort study, data from consecutive patients undergoing EVT for acute ischemic stroke with large vessel occlusion (AIS-LVO) at two comprehensive stroke centers were analyzed. The study included patients with an Alberta Stroke Program Early CT Score (ASPECTS) of 5 or less and utilized pretreatment perfusion imaging to calculate HIR. The primary outcome was very poor outcomes (90 days mRS 5-6). RESULTS: Among 102 patients included, 59 (57.8%) had very poor outcome (90 days mRS 5-6). Multivariable logistic regression analysis adjusting for multiple covariates including admission National Institutes of Health Stroke Scale (NIHSS) and EVT revealed that higher admission NIHSS (adjusted odds ratio [aOR] 1.224, 95% CI 1.089-1.374, p = 0.001) and HIR (aOR per 0.1 incremental change, 1.34, 95% CI 1.02-1.82, P = 0.042) were independently associated with very poor outcomes. CONCLUSION: This study demonstrates that admission NIHSS and HIR are independently associated with very poor outcome (90 days mRS 5-6) in patients with large ischemic core strokes. These findings highlight the importance of collateral status and perfusion imaging in predicting outcomes in this patient population, suggesting a potential role for HIR in the triage and management of large core stroke patients.

Prediction of Ischemic Stroke Functional Outcomes from Acute-Phase Noncontrast CT and Clinical Information.

Background Clinical outcome prediction based on acute-phase ischemic stroke data is valuable for planning health care resources, designing clinical trials, and setting patient expectations. Existing methods require individualized features and often involve manually engineered, time-consuming postprocessing activities. Purpose To predict the 90-day modified Rankin Scale (mRS) score with a deep learning (DL) model fusing noncontrast-enhanced CT (NCCT) and clinical information from the acute phase of stroke. Materials and Methods This retrospective study included data from six patient datasets from four multicenter trials and two registries. The DL-based imaging and clinical model was trained by using NCCT data obtained 1-7 days after baseline imaging and clinical data (age; sex; baseline and 24-hour National Institutes of Health Stroke Scale scores; and history of hypertension, diabetes, and atrial fibrillation). This model was compared with models based on either NCCT or clinical information alone. Model-specific mRS score prediction accuracy, mRS score accuracy within 1 point of the actual mRS score, mean absolute error (MAE), and performance in identifying unfavorable outcomes (mRS score, >2) were evaluated. Results A total of 1335 patients (median age, 71 years; IQR, 60-80 years; 674 female patients) were included for model development and testing through sixfold cross validation, with distributions of 979, 133, and 223 patients across training, validation, and test sets in each of the six cross-validation folds, respectively. The fused model achieved an MAE of 0.94 (95% CI: 0.89, 0.98) for predicting the specific mRS score, outperforming the imaging-only (MAE, 1.10; 95% CI: 1.05, 1.16; P < .001) and the clinical information-only (MAE, 1.00; 95% CI: 0.94, 1.05; P = .04) models. The fused model achieved an area under the receiver operating characteristic curve (AUC) of 0.91 (95% CI: 0.89, 0.92) for predicting unfavorable outcomes, outperforming the clinical information-only model (AUC, 0.88; 95% CI: 0.87, 0.90; P < .001) and the imaging-only model (AUC, 0.85; 95% CI: 0.84, 0.87; P < .001). Conclusion A fused DL-based NCCT and clinical model outperformed an imaging-only model and a clinical-information-only model in predicting 90-day mRS scores. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Lee in this issue.

Academic Radiology Physician Financial Compensation in the United States: Trends and Distribution.

Background The overall trends in academic radiology physician compensation are not well studied. Purpose To assess recent trends in academic radiology financial compensation and distribution based on rank, gender, race/ethnicity, and geography in U.S. medical schools. Materials and Methods This secondary analysis used deidentified data from the Association of American Medical Colleges (AAMC) Faculty Salary Report, which collects information for full-time faculty at U.S. medical schools. Financial compensation data for full-time academic radiology faculty was collected from 2017 to 2023, stratified by rank, gender, race/ethnicity, and geography. The faculty salary report includes median, 25th, and 75th percentile compensation values for each rank, which were used to analyze trends with linear regression. Median compensation values were used to compare groups based on gender, race/ethnicity, and region. Results The AAMC Faculty Salary Report data for 2023 included responses for 5847 faculty members across all radiology departments, including 306 instructors, 2758 assistant professors, 1409 associate professors, 1004 full professors, 226 chiefs, and 144 chairs. On average, median faculty compensation increased by 2.6%-4.4% per year from 2017 to 2023, with the greatest increase (by 4.4% per year) at the instructor level and smaller increases (3.4%-2.6%) at the more senior ranks. Male faculty members were consistently compensated more than women at all ranks throughout the study period. The overall salary gap remained at 6% ($455 000 for women vs $483 000 for men) throughout the study period but increased numerically from $24 000 in 2019 to $28 000 in 2023. Black/African American faculty had a lower median compensation compared with White faculty (by 4% overall; $452 000 for Black/African American faculty vs $472 000 for White faculty) at all ranks except at professor rank. Instructor compensation in the Northeast region was substantially higher (by $278 000) than other regions, but this geographic differential did not exceed $35 000 at other ranks. Conclusion This study summarized the trends of full-time academic radiology faculty compensation and showed persistent salary inequities that should be addressed as part of a broader drive to increase diversity, equity, and inclusion. © RSNA, 2024 Supplemental material is available for this article.

Adjunctive Intravenous Argatroban or Eptifibatide for Ischemic Stroke.

BACKGROUND: Intravenous thrombolysis is a standard treatment of acute ischemic stroke. The efficacy and safety of combining intravenous thrombolysis with argatroban (an anticoagulant agent) or eptifibatide (an antiplatelet agent) are unclear. METHODS: We conducted a phase 3, three-group, adaptive, single-blind, randomized, controlled clinical trial at 57 sites in the United States. Patients with acute ischemic stroke who had received intravenous thrombolysis within 3 hours after symptom onset were assigned to receive intravenous argatroban, eptifibatide, or placebo within 75 minutes after the initiation of thrombolysis. The primary efficacy outcome, the utility-weighted 90-day modified Rankin scale score (range, 0 to 10, with higher scores reflecting better outcomes), was assessed by means of centralized adjudication. The primary safety outcome was symptomatic intracranial hemorrhage within 36 hours after randomization. RESULTS: A total of 514 patients were assigned to receive argatroban (59 patients), eptifibatide (227 patients), or placebo (228 patients). All the patients received intravenous thrombolysis (70% received alteplase, and 30% received tenecteplase), and 225 patients (44%) underwent endovascular thrombectomy. At 90 days, the mean (±SD) utility-weighted modified Rankin scale scores were 5.2±3.7 with argatroban, 6.3±3.2 with eptifibatide, and 6.8±3.0 with placebo. The posterior probability that argatroban was better than placebo was 0.002 (posterior mean difference in utility-weighted modified Rankin scale score, -1.51±0.51) and that eptifibatide was better than placebo was 0.041 (posterior mean difference, -0.50±0.29). The incidence of symptomatic intracranial hemorrhage was similar in the three groups (4% with argatroban, 3% with eptifibatide, and 2% with placebo). Mortality at 90 days was higher in the argatroban group (24%) and the eptifibatide group (12%) than in the placebo group (8%). CONCLUSIONS: In patients with acute ischemic stroke treated with intravenous thrombolysis within 3 hours after symptom onset, adjunctive treatment with intravenous argatroban or eptifibatide did not reduce poststroke disability and was associated with increased mortality. (Funded by the National Institute of Neurological Disorders and Stroke; MOST ClinicalTrials.gov number, NCT03735979.).

Artificial Intelligence-Generated Editorials in Radiology: Can Expert Editors Detect Them?

BACKGROUND AND PURPOSE: We aimed to evaluate GPT-4's ability to write radiology editorials and to compare these with human-written counterparts, thereby determining their real-world applicability for scientific writing. MATERIALS AND METHODS: Sixteen editorials from eight journals were included. To generate the AI-written editorials, the summary of 16 human-written editorials was fed into GPT-4. Six experienced editors reviewed the articles. First, an unpaired approach was used. The raters were asked to evaluate the content of each article using a 1-5 Likert scale across specified metrics. Then, they determined whether the editorials were written by humans or AI. The articles were then evaluated in pairs to determine which article was generated by AI and which should be published. Finally, the articles were analyzed with an AI detector and for plagiarism. RESULTS: The human-written articles had a median AI probability score of 2.0%, whereas the AI-written articles had 58%. The median similarity score among AI-written articles was 3%. 58% of unpaired articles were correctly classified regarding authorship. Rating accuracy was increased to 70% in the paired setting. AI-written articles received slightly higher scores in most metrics. When stratified by perception, human-written perceived articles were rated higher in most categories. In the paired setting, raters strongly preferred publishing the article they perceived as human-written (82%). CONCLUSIONS: GPT-4 can write high-quality articles that iThenticate does not flag as plagiarized, which may go undetected by editors, and that detection tools can detect to a limited extent. Editors showed a positive bias toward human-written articles. ABBREVIATIONS: AI = Artificial intelligence; LLM = large language model; SD = standard deviation.

Perfusion imaging predicts short-term clinical outcome in isolated posterior cerebral artery occlusion stroke.

BACKGROUND AND PURPOSE: Ischemic strokes due to isolated posterior cerebral artery (PCA) occlusions represent 5% of all strokes but have significant impacts on patients' quality of life, primarily due to visual deficits and thalamic involvement. Current guidelines for acute PCA occlusion management are sparse, and the prognostic value of perfusion imaging parameters remains underexplored. METHODS: We conducted a retrospective analysis of 32 patients with isolated PCA occlusions treated at Johns Hopkins Medical Institutions between January 2017 and March 2023. Patients underwent pretreatment perfusion imaging, with perfusion parameters analyzed using RAPID software. The primary outcome was short-term clinical outcome as measured by the National Institutes of Health Stroke Scale (NIHSS) at discharge. RESULTS: The median age of the cohort was 70 years, with 34% female and 66% male. Significant correlations were found between NIHSS at discharge and various perfusion parameters, including time-to-maximum (Tmax) >6 seconds (ρ = .55, p = .004), Tmax >8 seconds (ρ = .59, p = .002), Tmax >10 seconds (ρ = .6, p = .001), mismatch volume (ρ = .51, p = .008), and cerebral blood volume (CBV) < 34% (ρ = .59, p = .002). CONCLUSIONS: Tmax and CBV volumes significantly correlated with discharge NIHSS with marginal superiority of Tmax >10 seconds and CBV <42% volumes. These findings suggest that CT and MR perfusion imaging can play a crucial role in the acute management of PCA strokes, though larger, standardized studies are needed to validate these results and refine imaging thresholds specific to posterior circulation infarcts.

The Impact of MRI-Based Advanced Neuroimaging on Neurooncologists' Clinical Decision-Making in Patients With Posttreatment High-Grade Glioma: A Prospective Survey-Based Study.

Background: Advanced MRI-based neuroimaging techniques, such as perfusion and spectroscopy, have been increasingly incorporated into routine follow-up protocols in patients treated for high-grade glioma (HGG), to help differentiate tumor progression from treatment effect. However, these techniques' influence on clinical management remains poorly understood. Objective: To evaluate the impact of MRI-based advanced neuroimaging on clinical decision-making in patients with HGG in the posttreatment setting. Methods: This prospective study, performed at a comprehensive cancer center from March 1, 2017, to October 31, 2020, included adult patients treated by chemoradiation for WHO grade 4 diffuse glioma who underwent MRIbased advanced neuroimaging (comprising multiple perfusion imaging sequences and spectroscopy) to further evaluate findings on conventional MRI equivocal for tumor progression versus treatment effect. The ordering neuro-oncologists completed surveys before and after each advanced neuroimaging session. The percent of care episodes with a change between the intended and actual management plan on the surveys conducted before and after advanced neuroimaging, respectively, was computed and compared with a previously published percent using the Wald test for independent samples proportions. Results: The study included 63 patients (mean age, 55±13 years; 36 women, 27 men) who underwent 70 advanced neuroimaging sessions. Ordering neuro-oncologists' intended and actual management plans on the surveys completed before and after advanced neuroimaging, respectively, differed in 44% (31/70, [95% CI: 33-56%]) of episodes, which differed from the previously published frequency of 8.5% (5/59) (p<.001). These management plan changes included selection of a different plan for 6/8 episodes with an intended plan to enroll patients in a clinical trial, 12/19 episodes with an intended plan to change chemotherapeutic agents, 4/8 episodes with an intended plan of surgical intervention, and 1/2 episodes with an intended plan of re-irradiation. The ordering neuro-oncologists found advanced neuroimaging to be helpful in 93% (95% CI: 87%-99%) (65/70) of episodes. Conclusion: Neuro-oncologists' management plans changed in a substantial fraction of adult patients with HGG who underwent advanced neuroimaging to further evaluate conventional MRI findings equivocal for tumor progression versus treatment effect. Clinical Impact: The findings support incorporation of advanced neuroimaging into HGG posttreatment monitoring protocols.

Diagnostic Performance of ASL-MRI and FDG-PET in Frontotemporal Dementia: A Systematic Review and Meta-Analysis.

BACKGROUND: While the diagnosis of frontotemporal dementia (FTD) is based mostly on clinical features, [18F]-FDG PET has been investigated as a potential imaging golden standard in ambiguous cases, with arterial spin labeling (ASL) MRI gaining recent interest. PURPOSE: The purpose of this study is to conduct a systematic review and meta-analysis on the diagnostic performance of ASL MRI in FTD patients and compare it to that of [18F]-FDG PET. DATA SOURCES: A systematic search of PubMed, Scopus and EMBASE was conducted until March 13, 2024. STUDY SELECTION: Inclusion criteria were: original articles, patients with FTD and/or its variants, use of ASL MR perfusion imaging with or without [18F]-FDG PET, presence of sufficient diagnostic performance data. Exclusion criteria were: meeting abstracts, comments, summaries, protocols, letters and guidelines, longitudinal studies, overlapping cohorts. DATA ANALYSIS: The quality of eligible studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) for [18F]-FDG PET and ASL MRI were calculated, and a summary receiver operating characteristic curve was plotted. DATA SYNTHESIS: Seven eligible studies were identified, which included a total of 102 FTD patients. Aside from some of the studies showing at worst an unclear risk of bias in patient selection, index test, flow and timing, all studies showed low risk of bias and applicability concerns in all categories. Data from 4 studies was included in our meta-analysis for ASL MRI and 3 studies for [18F]-FDG PET. Pooled sensitivity, specificity and DOR were 0.70 (95% CI: 0.59-0.79), 0.81 (95% CI: 0.71-0.88) and 8.00 (95% CI: 3.74-17.13) for ASL MRI, and 0.88 (95% CI: 0.71-0.96), 0.89 (95% CI: 0.43-0.99) and 47.18 (95% CI: 10.77-206.75) for [18F]-FDG PET. LIMITATIONS: The number of studies was relatively small, with a small sample size. The studies used different scanning protocols as well as a mix of diagnostic metrics, all of which might have introduced heterogeneity in the data. CONCLUSIONS: While ASL MRI performed worse than [18F]-FDG PET in the diagnosis of FTD, it exhibited a decent diagnostic performance to justify its further investigation as a quicker and more convenient alternative. ABBREVIATIONS: 3DPCASL, 3D pseudocontinuous ASL; AD, Alzheimer's disease; ASL, arterial spin labeling; AUC, area under the curve; CI, confidence interval; DOR, diagnostic odds ratio; FN, false negative; FP, false positive; FTD, frontotemporal dementia; LE, limbic encephalitis; NLR, negative likelihood ratio; PASL, pulsed ASL; PLD, post-label delay; PLR, positive likelihood ratio; PRISMA, PSP, progressive supranuclear palsy; Preferred Reporting Items for Systematic Reviews and Meta-Analysis; SROC, summary receiver operative characteristic; TN, true negative; TP, true positive; QUADAS-2, Quality Assessment of Diagnostic Accuracy Studies-2.

Pulsed focused ultrasound alters the proteomic profile of the tumor microenvironment in a syngeneic mouse model of glioblastoma.

PURPOSE: Glioblastoma (GBM), a lethal primary adult malignancy, is difficult to treat because of the restrictive nature of the blood-brain barrier (BBB), blood-tumor barrier (BTB), and the immunosuppressive tumor microenvironment (TME). Since pulsed focused ultrasound (pFUS) is currently used to improve therapeutic deliveries across these barriers, this study aims to characterize the impact of pFUS on the TME proteomics upon opening the BBB and BTB. METHODS: We utilized MRI-guided, pFUS with ultrasound contrast microbubbles (termed 'pFUS' herein) to selectively and transiently open the BBB and BTB investigating proteomic modifications in the TME. Utilizing an orthotopically-allografted mouse GL26 GBM model (Ccr2RFP/wt - Cx3cr1GFP/wt), pFUS's effect on glioma proteomics was evaluated using a Luminex 48-plex assay. RESULTS: pFUS treated tumors exhibited increases in pro-inflammatory cytokines, chemokines, and trophic factors (CCTFs). Proteomic changes in tumors tend to peak at 24 h after single pFUS session (1x), with levels then plateauing or declining over the subsequent 24 h. Tumors receiving three pFUS sessions (3x) showed elevated CCTFs levels peaking as early as 6 h after the third session. CONCLUSIONS: pFUS together with microbubbles induces a sterile inflammatory response in the TME of a mouse GBM tumor. Moreover, this proinflammatory shift can be sustained and perhaps primed for more rapid responses upon multiple sessions of pFUS. These findings raise the intriguing potential that pFUS-induced BBB and BTB opening may not only be effective in facilitating the therapeutic agent delivery, but also be harnessed to modify the TME to assist immunotherapies in overcoming immune evasion in GBM.

Overestimation of the Ischemic Core Is Associated With Higher Core Lesion Volume and Degree of Reperfusion After Thrombectomy.

Background CT perfusion (CTP)-derived baseline ischemic core volume (ICV) can overestimate the true extent of infarction, which may result in exclusion of patients with ischemic stroke from endovascular treatment (EVT). Purpose To determine whether ischemic core overestimation is associated with larger ICV and degree of recanalization. Materials and Methods This retrospective multicenter cohort study included patients with acute ischemic stroke triaged at multimodal CT who underwent EVT between January 2015 and January 2022. The primary outcome was ischemic core overestimation, which was assumed when baseline CTP-derived ICV was larger than the final infarct volume at follow-up imaging. The secondary outcome was functional independence defined as modified Rankin Scale scores of 0-2 90 days after EVT. Successful vessel recanalization was defined as extended Thrombolysis in Cerebral Infarction score of 2b or higher. Categorical variables were compared between patients with ICV of 50 mL or less versus large ICV greater than 50 mL with use of the χ2 test. Adjusted multivariable logistic regression analyses were used to assess the primary and secondary outcomes. Results In total, 721 patients (median age, 76 years [IQR, 64-83 years]; 371 female) were included, of which 162 (22%) demonstrated ischemic core overestimation. Core overestimation occurred more often in patients with ICV greater than 50 mL versus 50 mL or less (48% vs 16%; P < .001) and those with successful versus unsuccessful vessel recanalization (26% vs 13%; P < .001). In an adjusted model, successful recanalization after EVT (odds ratio [OR], 3.14 [95% CI: 1.65, 5.95]; P < .001) and larger ICV (OR, 1.03 [95% CI: 1.02, 1.04]; P < .001) were independently associated with core overestimation, while the time from symptom onset to imaging showed no association (OR, 0.99; P = .96). Core overestimation was independently associated with functional independence (adjusted OR, 2.83 [95% CI: 1.66, 4.81]; P < .001) after successful recanalization. Conclusion Ischemic core overestimation occurred more frequently in patients presenting with large CTP-derived ICV and successful vessel recanalization compared with those with unsuccessful recanalization. © RSNA, 2024 Supplemental material is available for this article.

Artificial intelligence/machine learning for neuroimaging to predict hemorrhagic transformation: Systematic review/meta-analysis.

BACKGROUND AND PURPOSE: Early and reliable prediction of hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) is crucial for treatment decisions and early intervention. The purpose of this study was to conduct a systematic review and meta-analysis on the performance of artificial intelligence (AI) and machine learning (ML) models that utilize neuroimaging to predict HT. METHODS: A systematic search of PubMed, EMBASE, and Web of Science was conducted until February 19, 2024. Inclusion criteria were as follows: patients with AIS who received reperfusion therapy; AI/ML algorithm using imaging to predict HT; or presence of sufficient data on the predictive performance. Exclusion criteria were as follows: articles with less than 20 patients; articles lacking algorithms that operate solely on images; or articles not detailing the algorithm used. The quality of eligible studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 and Checklist for Artificial Intelligence in Medical Imaging. Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated using a random-effects model, and a summary receiver operating characteristic curve was constructed using the Reitsma method. RESULTS: We identified six eligible studies, which included 1640 patients. Aside from an unclear risk of bias regarding flow and timing identified in two of the studies, all studies showed low risk of bias and applicability concerns in all categories. Pooled sensitivity, specificity, and DOR were .849, .878, and 45.598, respectively. CONCLUSION: AI/ML models can reliably predict the occurrence of HT in AIS patients. More prospective studies are needed for subgroup analyses and higher clinical certainty and usefulness.

Standardized reporting for Head CT Scans in patients suspected of traumatic brain injury (TBI): An international expert endeavor.

BACKGROUND AND PURPOSE: Traumatic brain injury (TBI) is a major source of health loss and disability worldwide. Accurate and timely diagnosis of TBI is critical for appropriate treatment and management of the condition. Neuroimaging plays a crucial role in the diagnosis and characterization of TBI. Computed tomography (CT) is the first-line diagnostic imaging modality typically utilized in patients with suspected acute mild, moderate and severe TBI. Radiology reports play a crucial role in the diagnostic process, providing critical information about the location and extent of brain injury, as well as factors that could prevent secondary injury. However, the complexity and variability of radiology reports can make it challenging for healthcare providers to extract the necessary information for diagnosis and treatment planning. METHODS/RESULTS/CONCLUSION: In this article, we report the efforts of an international group of TBI imaging experts to develop a clinical radiology report template for CT scans obtained in patients suspected of TBI and consisting of fourteen different subdivisions (CT technique, mechanism of injury or clinical history, presence of scalp injuries, fractures, potential vascular injuries, potential injuries involving the extra-axial spaces, brain parenchymal injuries, potential injuries involving the cerebrospinal fluid spaces and the ventricular system, mass effect, secondary injuries, prior or coexisting pathology).

Simplifying venous outflow: Prolonged venous transit as a novel qualitative marker correlating with acute stroke outcomes.

BACKGROUND: Prolonged venous transit (PVT), defined as presence of time-to-maximum ≥ 10 s within the superior sagittal sinus (SSS) and/or torcula, is a novel, qualitatively assessed computed tomography perfusion surrogate parameter of venous outflow with potential utility in pretreatment acute ischemic stroke imaging for neuroprognostication. We aim to characterize the correlation between PVT and neurological functional outcomes in thrombectomy-treated patients. METHODS: A prospectively-collected database of large vessel occlusion acute ischemic stroke patients treated with thrombectomy was retrospectively analyzed. Spearman's rank correlation coefficient and point-biserial correlations were performed between PVT status (i.e., no region, either SSS or torcula, or both), 90-day modified Rankin score (mRS), mortality (mRS 6), and poor functional outcome (mRS 4-6 vs 0-3). RESULTS: Of 128 patients, correlation between PVT and 90-day mRS (ρ = 0.35, p < 0.0001), mortality (r = 0.26, p = 0.002), and poor functional outcome (r = 0.27, p = 0.002) were significant. CONCLUSION: There is a modest, significant correlation between PVT and severity of neurological functional outcome. Consequently, PVT is an easily-ascertained, qualitative metric that may be useful as an adjunct for anticipating a patient's clinical course. Future analyses will determine the significance of incorporating PVT in clinical decision-making.

Personalized brain circuit scores identify clinically distinct biotypes in depression and anxiety.

There is an urgent need to derive quantitative measures based on coherent neurobiological dysfunctions or 'biotypes' to enable stratification of patients with depression and anxiety. We used task-free and task-evoked data from a standardized functional magnetic resonance imaging protocol conducted across multiple studies in patients with depression and anxiety when treatment free (n = 801) and after randomization to pharmacotherapy or behavioral therapy (n = 250). From these patients, we derived personalized and interpretable scores of brain circuit dysfunction grounded in a theoretical taxonomy. Participants were subdivided into six biotypes defined by distinct profiles of intrinsic task-free functional connectivity within the default mode, salience and frontoparietal attention circuits, and of activation and connectivity within frontal and subcortical regions elicited by emotional and cognitive tasks. The six biotypes showed consistency with our theoretical taxonomy and were distinguished by symptoms, behavioral performance on general and emotional cognitive computerized tests, and response to pharmacotherapy as well as behavioral therapy. Our results provide a new, theory-driven, clinically validated and interpretable quantitative method to parse the biological heterogeneity of depression and anxiety. Thus, they represent a promising approach to advance precision clinical care in psychiatry.

Probabilistic Presurgical Language fMRI Atlas of Patients with Brain Tumors.

BACKGROUND AND PURPOSE: Patients with brain tumors have high intersubject variation in putative language regions, which may limit the utility of straightforward application of healthy subject brain atlases in clinical scenarios. The purpose of this study was to develop a probabilistic functional brain atlas that consolidates language functional activations of sentence completion and Silent Word Generation language paradigms using a large sample of patients with brain tumors. MATERIALS AND METHODS: The atlas was developed using retrospectively collected fMRI data from patients with brain tumors who underwent their first standard-of-care presurgical language fMRI scan at our institution between July 18, 2015, and May 13, 2022. Three hundred seventeen patients (861 fMRI scans) were used to develop the language functional atlas. An independent presurgical language fMRI data set of 39 patients with brain tumors from a previous study was used to evaluate our atlas. Family-wise error-corrected binary functional activation maps from sentence completion, letter fluency, and category fluency presurgical fMRI were used to create probability overlap maps and pooled probabilistic overlap maps in Montreal Neurological Institute standard space. The Wilcoxon signed-rank test was used to determine a significant difference in the maximum Dice coefficient for our atlas compared with a meta-analysis-based template with respect to expert-delineated primary language area activations. RESULTS: Probabilities of activating the left anterior primary language area and left posterior primary language area in the temporal lobe were 87.9% and 91.5%, respectively, for sentence completion, 88.5% and 74.2%, respectively, for letter fluency, and 83.6% and 67.6%, respectively, for category fluency. Maximum Dice coefficients for templates derived from our language atlas were significantly higher than the meta-analysis-based template in the left anterior primary language area (0.351 and 0.326, respectively, P < .05) and the left posterior primary language area in the temporal lobe (0.274 and 0.244, respectively, P < .005). CONCLUSIONS: Brain tumor patient- and paradigm-specific probabilistic language atlases were developed. These atlases had superior spatial agreement with fMRI activations in individual patients compared with the meta-analysis-based template.

Evidence of varicella zoster virus (VZV) reactivation in children with arterial ischemic stroke: Results of the VIPS II Study.

Background: Varicella zoster virus (VZV) has been associated with focal cerebral arteriopathy (FCA) and arterial ischemic stroke (AIS) in childhood. The Vascular effects of Infection in Pediatric Stroke (VIPS) II study aimed to examine this relationship in the modern era when most children in North America and Australia receive VZV vaccination with live, attenuated virus. Methods: This 22-center prospective cohort study enrolled 205 children (28 days-18 years) with AIS (2017-2022), collected baseline [hyperacute (≤72 hours; n=194) and acute (4-6 days; n=181)] and convalescent (1-6 weeks; n=74) serum samples. Sites enrolled 95 stroke-free controls with single serum samples. A virology research laboratory measured VZV IgM and IgG titers by an in-house enzyme-linked immunosorbent assay (ELISA). Baseline IgG seropositivity indicated prior exposure (vaccination/infection) and elevated IgM titers indicated recent reactivation. Results: Median (IQR) age was 11.6 (5.5-15.6) years for cases and 11.8 (6.8-15.3) years for controls. Baseline serologies indicated prior VZV exposure in 198 cases (97%) and all controls. Parents of cases reported VZV vaccination in 160 (78%) and remote chicken pox in three (1.4%). Twenty cases (9.8%) and three controls (3.1%) had serologic evidence of recent VZV reactivation (p=0.06); all had remote VZV exposure (vaccination in 19 cases and all controls) and all were asymptomatic. Recent VZV reactivation was seen in similar proportions in arteriopathic, cardioembolic, and idiopathic stroke. Of 32 cases of FCA, 4 (12.5%) had recent VZV reactivation, versus no cases of arterial dissection (n=10) or moyamoya (n=16). Conclusions: Serologic evidence of recent VZV reactivation (≈1-6 weeks prior to stroke) was present in one in 10 cases of childhood AIS, including those without arteriopathy. Clinically silent VZV reactivation may be a childhood stroke trigger despite widespread vaccination. These cases could represent waning immunity with reactivation of either vaccine virus or wild-type virus after an unrecognized secondary VZV infection.

Carotid artery calcium score: Definition, classification, application, and limits.

INTRODUCTION: In the current paper, the "carotid artery calcium score" method is presented with the target to offer a metric method to quantify the amount of calcification in the carotid artery. MODEL AND DEFINITION: The Volume of Interest (VOI) should be extracted and those voxels, with a Hounsfield Unit (HU) value ≥130, should be considered. The total weight value is determined by calculating the sum of the HU attenuation values of all voxels with values ≥130 HU. This value should be multiplied by the conversion factor ("or voxel size") and divided by a weighting factor, the attenuation threshold to consider a voxel as calcified (and therefore 130 HU): this equation determines the Carotid Artery Calcium Score (CACS). RESULTS: In order to provide the demonstration of the potential feasibility of the model, the CACS was calculated in 131 subjects (94 males; mean age 72.7 years) for 235 carotid arteries (in 27 subjects, unilateral plaque was present) considered. The CACS value ranged from 0.67 to 11716. A statistically significant correlation was found (rho value = 0.663, p value = .0001) between the CACS in the right and left carotid plaques. Moreover, a statistically significant correlation between the age and the total CACS was present (rho value = 0.244, p value = .005), whereas no statistically significant difference was found in the distribution of CACS by gender (p = .148). The CACS was also tested at baseline and after contrast and no statistically significant difference was found. CONCLUSION: In conclusion, this method is of easy application, and it weights at the same time the volume and the degree of calcification in a unique parameter. This method needs to be tested to verify its potential utility, similar to the coronary artery calcium score, for the risk stratification of the occurrence of cerebrovascular events of the anterior circulation. Further studies using this new diagnostic tool to determine the prognostic value of carotid calcium quantification are needed.

The Los Angeles motor scale (LAMS) is independently associated with CT perfusion collateral status markers.

BACKGROUND AND AIM: The Los Angeles Motor Scale (LAMS) is an objective tool that has been used to rapidly assess and predict the presence of large vessel occlusion (LVO) in the pre-hospital setting successfully in several studies. However, studies assessing the relationship between LAMS score and CT perfusion collateral status (CS) markers such as cerebral blood volume (CBV) index, and hypoperfusion intensity ratio (HIR) are sparse. Our study therefore aims to assess the association of admission LAMS score with established CTP CS markers CBV Index and HIR in AIS-LVO cases. MATERIALS AND METHODS: In this prospectively collected, retrospectively reviewed analysis, inclusion criteria were as follows: a) CT angiography (CTA) confirmed anterior circulation LVO from 9/1/2017 to 10/01/2023, and b) diagnostic CT perfusion (CTP). Logistic regression analysis was performed to assess the relationship between admission LAMS with CTP CS markers HIR and CBV Index. p ≤ 0.05 was considered significant. RESULTS: In total, 285 consecutive patients (median age = 69 years; 56 % female) met our inclusion criteria. Multivariable logistic regression analysis adjusting for sex, age, ASPECTS, tPA, premorbid mRS, admission NIH stroke scale, prior history of TIA, stroke, atrial fibrillation, diabetes mellitus, hyperlipidemia, coronary artery disease and hypertension, admission LAMS was found to be independently associated with CBV Index (adjusted OR:0.82, p < 0.01), and HIR (adjusted OR:0.59, p < 0.05). CONCLUSION: LAMS is independently associated with CTP CS markers, CBV index and HIR. This finding suggests that LAMS may also provide an indirect estimate of CS.

Assessing the Performance of Artificial Intelligence Models: Insights from the American Society of Functional Neuroradiology Artificial Intelligence Competition.

BACKGROUND AND PURPOSE: Artificial intelligence models in radiology are frequently developed and validated using data sets from a single institution and are rarely tested on independent, external data sets, raising questions about their generalizability and applicability in clinical practice. The American Society of Functional Neuroradiology (ASFNR) organized a multicenter artificial intelligence competition to evaluate the proficiency of developed models in identifying various pathologies on NCCT, assessing age-based normality and estimating medical urgency. MATERIALS AND METHODS: In total, 1201 anonymized, full-head NCCT clinical scans from 5 institutions were pooled to form the data set. The data set encompassed studies with normal findings as well as those with pathologies, including acute ischemic stroke, intracranial hemorrhage, traumatic brain injury, and mass effect (detection of these, task 1). NCCTs were also assessed to determine if findings were consistent with expected brain changes for the patient's age (task 2: age-based normality assessment) and to identify any abnormalities requiring immediate medical attention (task 3: evaluation of findings for urgent intervention). Five neuroradiologists labeled each NCCT, with consensus interpretations serving as the ground truth. The competition was announced online, inviting academic institutions and companies. Independent central analysis assessed the performance of each model. Accuracy, sensitivity, specificity, positive and negative predictive values, and receiver operating characteristic (ROC) curves were generated for each artificial intelligence model, along with the area under the ROC curve. RESULTS: Four teams processed 1177 studies. The median age of patients was 62 years, with an interquartile range of 33 years. Nineteen teams from various academic institutions registered for the competition. Of these, 4 teams submitted their final results. No commercial entities participated in the competition. For task 1, areas under the ROC curve ranged from 0.49 to 0.59. For task 2, two teams completed the task with area under the ROC curve values of 0.57 and 0.52. For task 3, teams had little-to-no agreement with the ground truth. CONCLUSIONS: To assess the performance of artificial intelligence models in real-world clinical scenarios, we analyzed their performance in the ASFNR Artificial Intelligence Competition. The first ASFNR Competition underscored the gap between expectation and reality; and the models largely fell short in their assessments. As the integration of artificial intelligence tools into clinical workflows increases, neuroradiologists must carefully recognize the capabilities, constraints, and consistency of these technologies. Before institutions adopt these algorithms, thorough validation is essential to ensure acceptable levels of performance in clinical settings.