Sex-specific Differences in IDH1-Wildtype Glioblastoma patients in the ReSPOND Consortium.

BACKGROUND: Understanding sex-based differences in glioblastoma patients is necessary for accurate personalized treatment planning to improve patient outcomes. PURPOSE: To investigate sex-specific differences in molecular, clinical and radiological tumor parameters, as well as survival outcomes in glioblastoma, isocitrate dehydrogenase-1 wildtype (IDH1-WT), grade 4 patients. METHODS: Retrospective data of 1832 glioblastoma, IDH1-WT patients with comprehensive information on tumor parameters was acquired from the Radiomics Signatures for Precision Oncology in Glioblastoma (ReSPOND) consortium. Data imputation was performed for missing values. Sex-based differences in tumor parameters, such as, age, molecular parameters, pre-operative KPS score, tumor volumes, epicenter and laterality were assessed through non-parametric tests. Spatial atlases were generated using pre-operative MRI maps to visualize tumor characteristics. Survival time analysis was performed through log-rank tests and Cox proportional hazard analyses. RESULTS: GBM was diagnosed at a median age of 64 years in females compared to 61.9 years in males (FDR = 0.003). Males had a higher Karnofsky Performance Score (above 80) as compared to females (60.4% females Vs 69.7% males, FDR = 0.044). Females had lower tumor volumes in enhancing (16.7 cm3 Vs. 20.6 cm3 in males, FDR = 0.001), necrotic core (6.18 cm3 Vs. 7.76 cm3 in males, FDR = 0.001) and edema regions (46.9 cm3 Vs. 59.2 cm3 in males, FDR = 0.0001). Right temporal region was the most common tumor epicenter in the overall population. Right as well as left temporal lobes were more frequently involved in males. There were no significant differences in survival outcomes and mortality ratios. Higher age, unmethylated O6-methylguanine-DNAmethyltransferase (MGMT) promoter and undergoing subtotal resection increased the mortality risk in both males and females. CONCLUSIONS: Our study demonstrates significant sex-based differences in clinical and radiological tumor parameters of glioblastoma, IDH1-WT, grade 4 patients. Sex is not an independent prognostic factor for survival outcomes and the tumor parameters influencing patient outcomes are identical for males and females. ABBREVIATIONS: IDH1-WT = isocitrate dehydrogenase-1 wildtype; MGMTp = O6-methylguanine-DNA-methyltransferase promoter; KPS = Karnofsky performance score; EOR = extent of resection; WHO = world health organization; FDR = false discovery rate.

Inflammatory and tissue injury marker dynamics in pediatric acute respiratory distress syndrome.

BACKGROUNDThe molecular signature of pediatric acute respiratory distress syndrome (ARDS) is poorly described, and the degree to which hyperinflammation or specific tissue injury contributes to outcomes is unknown. Therefore, we profiled inflammation and tissue injury dynamics over the first 7 days of ARDS, and associated specific biomarkers with mortality, persistent ARDS, and persistent multiple organ dysfunction syndrome (MODS).METHODSIn a single-center prospective cohort of intubated pediatric patients with ARDS, we collected plasma on days 0, 3, and 7. Nineteen biomarkers reflecting inflammation, tissue injury, and damage-associated molecular patterns (DAMPs) were measured. We assessed the relationship between biomarkers and trajectories with mortality, persistent ARDS, or persistent MODS using multivariable mixed effect models.RESULTSIn 279 patients (64 [23%] nonsurvivors), hyperinflammatory cytokines, tissue injury markers, and DAMPs were higher in nonsurvivors. Survivors and nonsurvivors showed different biomarker trajectories. IL-1α, soluble tumor necrosis factor receptor 1, angiopoietin 2 (ANG2), and surfactant protein D increased in nonsurvivors, while DAMPs remained persistently elevated. ANG2 and procollagen type III N-terminal peptide were associated with persistent ARDS, whereas multiple cytokines, tissue injury markers, and DAMPs were associated with persistent MODS. Corticosteroid use did not impact the association of biomarker levels or trajectory with mortality.CONCLUSIONSPediatric ARDS survivors and nonsurvivors had distinct biomarker trajectories, with cytokines, endothelial and alveolar epithelial injury, and DAMPs elevated in nonsurvivors. Mortality markers overlapped with markers associated with persistent MODS, rather than persistent ARDS.FUNDINGNIH (K23HL-136688, R01-HL148054).

Radiogenomic biomarkers for immunotherapy in glioblastoma: A systematic review of magnetic resonance imaging studies.

Background: Immunotherapy is an effective "precision medicine" treatment for several cancers. Imaging signatures of the underlying genome (radiogenomics) in glioblastoma patients may serve as preoperative biomarkers of the tumor-host immune apparatus. Validated biomarkers would have the potential to stratify patients during immunotherapy clinical trials, and if trials are beneficial, facilitate personalized neo-adjuvant treatment. The increased use of whole genome sequencing data, and the advances in bioinformatics and machine learning make such developments plausible. We performed a systematic review to determine the extent of development and validation of immune-related radiogenomic biomarkers for glioblastoma. Methods: A systematic review was performed following PRISMA guidelines using the PubMed, Medline, and Embase databases. Qualitative analysis was performed by incorporating the QUADAS 2 tool and CLAIM checklist. PROSPERO registered: CRD42022340968. Extracted data were insufficiently homogenous to perform a meta-analysis. Results: Nine studies, all retrospective, were included. Biomarkers extracted from magnetic resonance imaging volumes of interest included apparent diffusion coefficient values, relative cerebral blood volume values, and image-derived features. These biomarkers correlated with genomic markers from tumor cells or immune cells or with patient survival. The majority of studies had a high risk of bias and applicability concerns regarding the index test performed. Conclusions: Radiogenomic immune biomarkers have the potential to provide early treatment options to patients with glioblastoma. Targeted immunotherapy, stratified by these biomarkers, has the potential to allow individualized neo-adjuvant precision treatment options in clinical trials. However, there are no prospective studies validating these biomarkers, and interpretation is limited due to study bias with little evidence of generalizability.

Optimising brain age estimation through transfer learning: A suite of pre-trained foundation models for improved performance and generalisability in a clinical setting.

Estimated age from brain MRI data has emerged as a promising biomarker of neurological health. However, the absence of large, diverse, and clinically representative training datasets, along with the complexity of managing heterogeneous MRI data, presents significant barriers to the development of accurate and generalisable models appropriate for clinical use. Here, we present a deep learning framework trained on routine clinical data (N up to 18,890, age range 18-96 years). We trained five separate models for accurate brain age prediction (all with mean absolute error ≤4.0 years, R2 ≥ .86) across five different MRI sequences (T2 -weighted, T2 -FLAIR, T1 -weighted, diffusion-weighted, and gradient-recalled echo T2 *-weighted). Our trained models offer dual functionality. First, they have the potential to be directly employed on clinical data. Second, they can be used as foundation models for further refinement to accommodate a range of other MRI sequences (and therefore a range of clinical scenarios which employ such sequences). This adaptation process, enabled by transfer learning, proved effective in our study across a range of MRI sequences and scan orientations, including those which differed considerably from the original training datasets. Crucially, our findings suggest that this approach remains viable even with limited data availability (as low as N = 25 for fine-tuning), thus broadening the application of brain age estimation to more diverse clinical contexts and patient populations. By making these models publicly available, we aim to provide the scientific community with a versatile toolkit, promoting further research in brain age prediction and related areas.

Brain Tumor Imaging without Gadolinium-based Contrast Agents: Feasible or Fantasy?

Gadolinium-based contrast agents (GBCAs) form the cornerstone of current primary brain tumor MRI protocols at all stages of the patient journey. Though an imperfect measure of tumor grade, GBCAs are repeatedly used for diagnosis and monitoring. In practice, however, radiologists will encounter situations where GBCA injection is not needed or of doubtful benefit. Reducing GBCA administration could improve the patient burden of (repeated) imaging (especially in vulnerable patient groups, such as children), minimize risks of putative side effects, and benefit costs, logistics, and the environmental footprint. On the basis of the current literature, imaging strategies to reduce GBCA exposure for pediatric and adult patients with primary brain tumors will be reviewed. Early postoperative MRI and fixed-interval imaging of gliomas are examples of GBCA exposure with uncertain survival benefits. Half-dose GBCAs for gliomas and T2-weighted imaging alone for meningiomas are among options to reduce GBCA use. While most imaging guidelines recommend using GBCAs at all stages of diagnosis and treatment, non-contrast-enhanced sequences, such as the arterial spin labeling, have shown a great potential. Artificial intelligence methods to generate synthetic postcontrast images from decreased-dose or non-GBCA scans have shown promise to replace GBCA-dependent approaches. This review is focused on pediatric and adult gliomas and meningiomas. Special attention is paid to the quality and real-life applicability of the reviewed literature.

Biosynthesis of the Azoxy Compound Azodyrecin from Streptomyces mirabilis P8-A2.

Azoxy compounds are a distinctive group of bioactive secondary metabolites characterized by a unique RN═N+(O-)R moiety. The azoxy moiety is present in various classes of metabolites that exhibit various biological activities. The enzymatic mechanisms underlying azoxy bond formation remain enigmatic. Azodyrecins are cytotoxic azoxy metabolites produced by Streptomyces mirabilis P8-A2. Here, we cloned and confirmed the putative azd biosynthetic gene cluster through CATCH cloning followed by expression and production of azodyrecins in two heterologous hosts, S. albidoflavus J1074 and S. coelicolor M1146, respectively. We explored the function of 14 enzymes in azodyrecin biosynthesis through gene knockout using CRISPR-Cas9 base editing in the native producer, S. mirabilis P8-A2. The key intermediates were analyzed in the mutants through MS/MS fragmentation studies, revealing azoxy bond formation via the conversion of hydrazine to an azo compound followed by further oxygenation. Enzymes involved in modifications of the precursor could be postulated based on their predicted function and the intermediates identified in the knockout strains. Moreover, the distribution of the azoxy biosynthetic gene clusters across Streptomyces spp. genomes is explored, highlighting the presence of these clusters in over 20% of the Streptomyces spp. genomes and revealing that azoxymycin and valanimycin are scarce, while azodyrecin and KA57A-like clusters are widely distributed across the phylogenetic tree.

Detection of chromosomal aneuploidy in ancient genomes.

Ancient DNA is a valuable tool for investigating genetic and evolutionary history that can also provide detailed profiles of the lives of ancient individuals. In this study, we develop a generalised computational approach to detect aneuploidies (atypical autosomal and sex chromosome karyotypes) in the ancient genetic record and distinguish such karyotypes from contamination. We confirm that aneuploidies can be detected even in low-coverage genomes ( ~ 0.0001-fold), common in ancient DNA. We apply this method to ancient skeletal remains from Britain to document the first instance of mosaic Turner syndrome (45,X0/46,XX) in the ancient genetic record in an Iron Age individual sequenced to average 9-fold coverage, the earliest known incidence of an individual with a 47,XYY karyotype from the Early Medieval period, as well as individuals with Klinefelter (47,XXY) and Down syndrome (47,XY, + 21). Overall, our approach provides an accessible and automated framework allowing for the detection of individuals with aneuploidies, which extends previous binary approaches. This tool can facilitate the interpretation of burial context and living conditions, as well as elucidate past perceptions of biological sex and people with diverse biological traits.

Glioblastoma and Radiotherapy: a multi-center AI study for Survival Predictions from MRI (GRASP study).

BACKGROUND: The aim was to predict survival of glioblastoma at eight months after radiotherapy (a period allowing for completing a typical course of adjuvant temozolomide), by applying deep learning to the first brain MRI after radiotherapy completion. METHODS: Retrospective and prospective data were collected from 206 consecutive glioblastoma, IDH-wildtype patients diagnosed between March 2014-February 2022 across 11 UK centers. Models were trained on 158 retrospective patients from three centers. Holdout test sets were retrospective (n=19; internal validation), and prospective (n=29; external validation from eight distinct centers).Neural network branches for T2-weighted and contrast-enhanced T1-weighted inputs were concatenated to predict survival. A non-imaging branch (demographics/MGMT/treatment data) was also combined with the imaging model. We investigated the influence of individual MR sequences; non-imaging features; and weighted dense blocks pretrained for abnormality detection. RESULTS: The imaging model outperformed the non-imaging model in all test sets (area under the receiver-operating characteristic curve, AUC p=0.038) and performed similarly to a combined imaging/non-imaging model (p>0.05). Imaging, non-imaging, and combined models applied to amalgamated test sets gave AUCs of 0.93, 0.79, and 0.91. Initializing the imaging model with pretrained weights from 10,000s of brain MRIs improved performance considerably (amalgamated test sets without pretraining 0.64; p=0.003). CONCLUSIONS: A deep learning model using MRI images after radiotherapy, reliably and accurately determined survival of glioblastoma. The model serves as a prognostic biomarker identifying patients who will not survive beyond a typical course of adjuvant temozolomide, thereby stratifying patients into those who might require early second-line or clinical trial treatment.

An individual with Sarmatian-related ancestry in Roman Britain.

In the second century CE the Roman Empire had increasing contact with Sarmatians, nomadic Iranian speakers occupying an area stretching from the Pontic-Caspian steppe to the Carpathian mountains, both in the Caucasus and in the Danubian borders of the empire.1,2,3 In 175 CE, following their defeat in the Marcomannic Wars, emperor Marcus Aurelius drafted Sarmatian cavalry into Roman legions and deployed 5,500 Sarmatian soldiers to Britain, as recorded by contemporary historian Cassius Dio.4,5 Little is known about where the Sarmatian cavalry were stationed, and no individuals connected with this historically attested event have been identified to date, leaving its impact on Britain largely unknown. Here we document Caucasus- and Sarmatian-related ancestry in the whole genome of a Roman-period individual (126-228 calibrated [cal.] CE)-an outlier without traceable ancestry related to local populations in Britain-recovered from a farmstead site in present-day Cambridgeshire, UK. Stable isotopes support a life history of mobility during childhood. Although several scenarios are possible, the historical deployment of Sarmatians to Britain provides a parsimonious explanation for this individual's extraordinary life history. Regardless of the factors behind his migrations, these results highlight how long-range mobility facilitated by the Roman Empire impacted provincial locations outside of urban centers.

Factors affecting the labelling accuracy of brain MRI studies relevant for deep learning abnormality detection.

Unlocking the vast potential of deep learning-based computer vision classification systems necessitates large data sets for model training. Natural Language Processing (NLP)-involving automation of dataset labelling-represents a potential avenue to achieve this. However, many aspects of NLP for dataset labelling remain unvalidated. Expert radiologists manually labelled over 5,000 MRI head reports in order to develop a deep learning-based neuroradiology NLP report classifier. Our results demonstrate that binary labels (normal vs. abnormal) showed high rates of accuracy, even when only two MRI sequences (T2-weighted and those based on diffusion weighted imaging) were employed as opposed to all sequences in an examination. Meanwhile, the accuracy of more specific labelling for multiple disease categories was variable and dependent on the category. Finally, resultant model performance was shown to be dependent on the expertise of the original labeller, with worse performance seen with non-expert vs. expert labellers.

Outcome study of the Pipeline Vantage Embolization Device (second version) in unruptured (and ruptured) aneurysms (PEDVU(R) study).

BACKGROUND: The Pipeline Vantage Embolization Device (PEDV) is the fourth-generation pipeline flow diverter for intracranial aneurysm treatment. There are no outcome studies for the second PEDV version. We aimed to evaluate safety and efficacy outcomes. Primary and secondary objectives were to determine outcomes for unruptured and ruptured cohorts, respectively. METHODS: In this multicenter retrospective and prospective study, we analyzed outcome data from eight centers using core laboratory assessments. We determined 30-day and ≥3-month mortality and morbidity rates, and 6- and 18-month radiographic aneurysm occlusion rates for procedures performed during the period July 2021-March 2023. RESULTS: We included 121 consecutive patients with 131 aneurysms. The adequate occlusion rate for the unruptured cohort at short-term and medium-term follow up, and also for the ruptured cohort at short-term follow up, was >90%. Two aneurysms (1.5%) underwent retreatment. When mortality attributed to a palliative case in the unruptured cohort, or subarachnoid hemorrhage in the ruptured cohort, was excluded then the overall major adverse event rate in respective cohorts was 7.5% and 23.5%, with 0% mortality rates for each. When all event causes were included on an intention-to-treat basis, the major adverse event rates in respective cohorts were 8.3% and 40.9%, with 0.9% and 22.7% mortality rates. CONCLUSIONS: For unruptured aneurysm treatment, the second PEDV version appears to have a superior efficacy and similar safety profile to previous-generation PEDs. These are acceptable outcomes in this pragmatic and non-industry-sponsored study. Analysis of ruptured aneurysm outcomes is limited by cohort size. Further prospective studies, particularly for ruptured aneurysms, are needed.

Artificial intelligence in the autonomous navigation of endovascular interventions: a systematic review.

Background: Autonomous navigation of catheters and guidewires in endovascular interventional surgery can decrease operation times, improve decision-making during surgery, and reduce operator radiation exposure while increasing access to treatment. Objective: To determine from recent literature, through a systematic review, the impact, challenges, and opportunities artificial intelligence (AI) has for the autonomous navigation of catheters and guidewires for endovascular interventions. Methods: PubMed and IEEEXplore databases were searched to identify reports of AI applied to autonomous navigation methods in endovascular interventional surgery. Eligibility criteria included studies investigating the use of AI in enabling the autonomous navigation of catheters/guidewires in endovascular interventions. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), articles were assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). PROSPERO: CRD42023392259. Results: Four hundred and sixty-two studies fulfilled the search criteria, of which 14 studies were included for analysis. Reinforcement learning (RL) (9/14, 64%) and learning from expert demonstration (7/14, 50%) were used as data-driven models for autonomous navigation. These studies evaluated models on physical phantoms (10/14, 71%) and in-silico (4/14, 29%) models. Experiments within or around the blood vessels of the heart were reported by the majority of studies (10/14, 71%), while non-anatomical vessel platforms "idealized" for simple navigation were used in three studies (3/14, 21%), and the porcine liver venous system in one study. We observed that risk of bias and poor generalizability were present across studies. No procedures were performed on patients in any of the studies reviewed. Moreover, all studies were limited due to the lack of patient selection criteria, reference standards, and reproducibility, which resulted in a low level of evidence for clinical translation. Conclusion: Despite the potential benefits of AI applied to autonomous navigation of endovascular interventions, the field is in an experimental proof-of-concept stage, with a technology readiness level of 3. We highlight that reference standards with well-identified performance metrics are crucial to allow for comparisons of data-driven algorithms proposed in the years to come. Systematic review registration: identifier: CRD42023392259.

Robotically facilitated parafasicular microsurgery to a brain arteriovenous malformation in a paediatric patient.

PURPOSE: We report what we believe is the first application of robotically constrained image-guided surgery to approach a fistulous micro-arteriovenous malformation in a highly eloquent location. Drawing on institutional experience with a supervisory-control robotic system, a series of steps were devised to deliver a tubular retractor system to a deeply situated micro-arteriovenous malformation. The surgical footprint of this procedure was minimised along with the neurological morbidity. We hope that our contribution will be of assistance to others in integrating such systems given a similar clinical problem. CLINICAL PRESENTATION: A right-handed 9-year old girl presented to her local emergency department after a sudden onset of severe headache accompanied by vomiting. An intracranial haemorrhage centred in the right centrum semiovale with intraventricular extension was evident and she was transferred urgently to the regional paediatric neurosurgical centre, where an external ventricular drain (EVD) was sited. A digital subtraction angiogram demonstrated a small right hemispheric arteriovenous shunt irrigated by peripheral branches of the middle cerebral artery & a robotically facilitated parafasicular microsurgical approach was performed to disconnect the arteriovenous malformation. CONCLUSION: We describe the successful microsurgical in-situ disconnection of a deeply-situated, fistulous micro-AVM via a port system itself delivered directly to the target with a supervisory-control robotic system. This minimised the surgical disturbance along a relatively long white matter trajectory and demonstrates the feasibility of this approach for deeply located arteriovenous fistulae or fistulous AVMs.

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium.

PURPOSE: While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas. METHODS: Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS). RESULTS: One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p < 0.001), tumor centered in frontal lobe (OR 3.842, [2.361, 6.251], p < 0.001), absence of multicentricity (OR 0.173, [0.049, 0.612], p = 0.007), and presence of cystic (OR 6.596, [3.023, 14.391], p < 0.001) or non-enhancing solid components (OR 6.069, [3.371, 10.928], p < 0.001). Multivariate Cox analysis demonstrated cystic components (p = 0.024) and non-enhancing solid components (p = 0.003) were associated with longer OS, while older age (p < 0.001), frontal lobe center (p = 0.008), multifocality (p < 0.001), and multicentricity (p < 0.001) were associated with shorter OS. CONCLUSION: Partial T2-FLAIR mismatch sign is highly specific for IDH mutation in WHO grade 4 gliomas.

Comparative verification of control methodology for robotic interventional neuroradiology procedures.

PURPOSE: The use of robotics is emerging for performing interventional radiology procedures. Robots in interventional radiology are typically controlled using button presses and joystick movements. This study identified how different human-robot interfaces affect endovascular surgical performance using interventional radiology simulations. METHODS: Nine participants performed a navigation task on an interventional radiology simulator with three different human-computer interfaces. Using Simulation Open Framework Architecture we developed a simulation profile of vessels, catheters and guidewires. We designed and manufactured a bespoke haptic interventional radiology controller for robotic systems to control the simulation. Metrics including time taken for navigation, number of incorrect catheterisations, number of catheter and guidewire prolapses and forces applied to vessel walls were measured and used to characterise the interfaces. Finally, participants responded to a questionnaire to evaluate the perception of the controllers. RESULTS: Time taken for navigation, number of incorrect catheterisations and the number of catheter and guidewire prolapses, showed that the device-mimicking controller is better suited for controlling interventional neuroradiology procedures over joystick control approaches. Qualitative metrics also showed that interventional radiologists prefer a device-mimicking controller approach over a joystick approach. CONCLUSION: Of the four metrics used to compare and contrast the human-robot interfaces, three conclusively showed that a device-mimicking controller was better suited for controlling interventional neuroradiology robotics.

Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection.

PURPOSE: Most studies evaluating artificial intelligence (AI) models that detect abnormalities in neuroimaging are either tested on unrepresentative patient cohorts or are insufficiently well-validated, leading to poor generalisability to real-world tasks. The aim was to determine the diagnostic test accuracy and summarise the evidence supporting the use of AI models performing first-line, high-volume neuroimaging tasks. METHODS: Medline, Embase, Cochrane library and Web of Science were searched until September 2021 for studies that temporally or externally validated AI capable of detecting abnormalities in first-line computed tomography (CT) or magnetic resonance (MR) neuroimaging. A bivariate random effects model was used for meta-analysis where appropriate. This study was registered on PROSPERO as CRD42021269563. RESULTS: Out of 42,870 records screened, and 5734 potentially eligible full texts, only 16 studies were eligible for inclusion. Included studies were not compromised by unrepresentative datasets or inadequate validation methodology. Direct comparison with radiologists was available in 4/16 studies and 15/16 had a high risk of bias. Meta-analysis was only suitable for intracranial hemorrhage detection in CT imaging (10/16 studies), where AI systems had a pooled sensitivity and specificity 0.90 (95% confidence interval [CI] 0.85-0.94) and 0.90 (95% CI 0.83-0.95), respectively. Other AI studies using CT and MRI detected target conditions other than hemorrhage (2/16), or multiple target conditions (4/16). Only 3/16 studies implemented AI in clinical pathways, either for pre-read triage or as post-read discrepancy identifiers. CONCLUSION: The paucity of eligible studies reflects that most abnormality detection AI studies were not adequately validated in representative clinical cohorts. The few studies describing how abnormality detection AI could impact patients and clinicians did not explore the full ramifications of clinical implementation.

Early Outcomes of the Pipeline Vantage Flow Diverter : A Multicentre Study.

PURPOSE: The recently introduced Pipeline Vantage Embolization Device with Shield Technology is the fourth generation of Pipeline flow diverter devices. Due to the relatively high rate of intraprocedural technical complications, modifications were subsequently made to the device after a limited release of the device in 2020. This study aimed to evaluate the safety and efficacy of the modified version of this device. METHODS: This was a multicentre retrospective series. The primary efficacy endpoint was aneurysm occlusion in the absence of retreatment. The primary safety endpoint was any neurological morbidity or death. Ruptured and unruptured aneurysms were included in the study. RESULTS: A total of 52 procedures were performed for 60 target aneurysms. Treatment was performed on 5 patients with ruptured aneurysms. The technical success rate was 98%. The mean clinical follow-up time was 5.5 months. In patients presenting with unruptured aneurysms there were no deaths, 3 (6.4%) major complications and 7 (13%) minor complications. In the five patients presenting with subarachnoid haemorrhage there were 2 (40%) major complications with 1 (20%) of these resulting in death, and 1 (20%) minor complication. Of the patients 29 (56%) had undergone 6­monthly postprocedural angiographic imaging with a mean time of 6.6 months demonstrating that 83% of patients had achieved adequate occlusion (RROC1/2) of the aneurysm. CONCLUSIONS: In this non-industry-sponsored study, the occlusion rates and safety outcomes were similar to those seen in previously published studies with flow diverter devices and earlier generation Pipeline devices. Modifications to the device appear to have improved ease of deployment.

Yersinia pestis genomes reveal plague in Britain 4000 years ago.

Extinct lineages of Yersinia pestis, the causative agent of the plague, have been identified in several individuals from Eurasia between 5000 and 2500 years before present (BP). One of these, termed the 'LNBA lineage' (Late Neolithic and Bronze Age), has been suggested to have spread into Europe with human groups expanding from the Eurasian steppe. Here, we show that the LNBA plague was spread to Europe's northwestern periphery by sequencing three Yersinia pestis genomes from Britain, all dating to ~4000 cal BP. Two individuals were from an unusual mass burial context in Charterhouse Warren, Somerset, and one individual was from a single burial under a ring cairn monument in Levens, Cumbria. To our knowledge, this represents the earliest evidence of LNBA plague in Britain documented to date. All three British Yersinia pestis genomes belong to a sublineage previously observed in Bronze Age individuals from Central Europe that had lost the putative virulence factor yapC. This sublineage is later found in Eastern Asia ~3200 cal BP. While the severity of the disease is currently unclear, the wide geographic distribution within a few centuries suggests substantial transmissibility.