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Uric acid is an antioxidant with neuroprotective effects in experimental models of stroke. We assessed whether uric acid therapy would improve functional outcomes at 90 days in patients with acute ischaemic stroke. URICO-ICTUS was a randomised, double-blind, placebo-controlled, phase 2b/3 trial that recruited patients with acute ischaemic stroke admitted to ten Spanish stroke centres. Patients were included if they were aged 18 years or older, had received alteplase within 4·5 h of symptom onset, and had an eligible National Institutes of Health Stroke Scale (NIHSS) score (>6 and ≤25) and premorbid (assessed by anamnesis) modified Rankin Scale (mRS) score (≤2). Patients were randomly allocated (1:1) to receive uric acid 1000 mg or placebo (both infused intravenously in 90 min during the infusion of alteplase), stratified by centre and baseline stroke severity. The primary outcome was the proportion of patients with excellent outcome (ie, an mRS score of 0–1, or 2 if premorbid score was 2) at 90 days, analysed in the target population (all randomly assigned patients who had been correctly diagnosed with ischaemic stroke and had begun study medication). The study is registered with ClinicalTrials.gov, number NCT00860366. Between July 1, 2011, and April 30, 2013, we randomly assigned 421 patients, of whom 411 (98%) were included in the target population (211 received uric acid and 200 received placebo). 83 (39%) patients who received uric acid and 66 (33%) patients who received placebo had an excellent outcome (adjusted risk ratio 1·23 [95% CI 0·96–1·56]; p=0·099). No clinically relevant or statistically significant differences were reported between groups with respect to death (28 [13%] patients who received uric acid vs 31 [16%] who received placebo), symptomatic intracerebral haemorrhage (nine [4%] vs six [3%]), and gouty arthritis (one [<1%] vs four [2%]). 516 adverse events occurred in the uric acid group and 532 in the placebo group, of which 61 (12%) and 67 (13%), respectively, were serious adverse events (p=0·703). The addition of uric acid to thrombolytic therapy did not increase the proportion of patients who achieved excellent outcome after stroke compared with placebo, but it did not lead to any safety concerns. Institute of Health Carlos III of the Spanish Ministry of Health and Fundación Doctor Melchor Colet.

BackgroundWritten medical examinations consist of multiple-choice questions and/or free-text answers. The latter require manual evaluation and rating, which is time-consuming and potentially error-prone. We tested whether natural language processing (NLP) can be used to automatically analyze free-text answers to support the review process.MethodsThe European Board of Radiology of the European Society of Radiology provided representative datasets comprising sample questions, answer keys, participant answers, and reviewer markings from European Diploma in Radiology examinations. Three free-text questions with the highest number of corresponding answers were selected: Questions 1 and 2 were “unstructured” and required a typical free-text answer whereas question 3 was “structured” and offered a selection of predefined wordings/phrases for participants to use in their free-text answer. The NLP engine was designed using word lists, rule-based synonyms, and decision tree learning based on the answer keys and its performance tested against the gold standard of reviewer markings.ResultsAfter implementing the NLP approach in Python, F1 scores were calculated as a measure of NLP performance: 0.26 (unstructured question 1, n = 96), 0.33 (unstructured question 2, n = 327), and 0.5 (more structured question, n = 111). The respective precision/recall values were 0.26/0.27, 0.4/0.32, and 0.62/0.55.ConclusionThis study showed the successful design of an NLP-based approach for automatic evaluation of free-text answers in the EDiR examination. Thus, as a future field of application, NLP could work as a decision-support system for reviewers and support the design of examinations being adjusted to the requirements of an automated, NLP-based review process.Clinical relevance statementNatural language processing can be successfully used to automatically evaluate free-text answers, performing better with more structured question-answer formats. Furthermore, this study provides a baseline for further work applying, e.g., more elaborated NLP approaches/large language models.Key points• Free-text answers require manual evaluation, which is time-consuming and potentially error-prone.• We developed a simple NLP-based approach — requiring only minimal effort/modeling — to automatically analyze and mark free-text answers.• Our NLP engine has the potential to support the manual evaluation process.• NLP performance is better on a more structured question-answer format.

Objectives This study aims to assess the accuracy of generative pre-trained transformer 4o (GPT-4o) in answering multiple response questions from the European Diploma in Radiology (EDiR) examination, comparing its performance to that of human candidates. Materials and methods Results from 42 EDiR candidates across Europe were compared to those from 26 fourth-year medical students who answered exclusively using the ChatGPT-4o in a prospective study (October 2024). The challenge consisted of 52 recall or understanding-based EDiR multiple-response questions, all without visual inputs. Results The GPT-4o achieved a mean score of 82.1 ± 3.0%, significantly outperforming the EDiR candidates with 49.4 ± 10.5% ( p  < 0.0001). In particular, chatGPT-4o demonstrated higher true positive rates while maintaining lower false positive rates compared to EDiR candidates, with a higher accuracy rate in all radiology subspecialties ( p  < 0.0001) except informatics ( p  = 0.20). There was near-perfect agreement between GPT-4 responses (κ = 0.872) and moderate agreement among EDiR participants (κ = 0.334). Exit surveys revealed that all participants used the copy-and-paste feature, and 73% submitted additional questions to clarify responses. Conclusions GPT-4o significantly outperformed human candidates in low-order, text-based EDiR multiple-response questions, demonstrating higher accuracy and reliability. These results highlight GPT-4o’s potential in answering text-based radiology questions. Further research is necessary to investigate its performance across different question formats and candidate populations to ensure broader applicability and reliability. Critical relevance statement GPT-4o significantly outperforms human candidates in factual radiology text-based questions in the EDiR, excelling especially in identifying correct responses, with a higher accuracy rate compared to radiologists. Key Points In EDiR text-based questions, ChatGPT-4o scored higher (82%) than EDiR participants (49%). Compared to radiologists, GPT-4o excelled in identifying correct responses. GPT-4o responses demonstrated higher agreement (κ = 0.87) compared to EDiR candidates (κ = 0.33). Graphical Abstract

The number of circulating monocytes increases after stroke. In this study, we assessed the time course and phenotype of monocyte subsets and their relationship with the clinical course and outcome in 46 consecutive stroke patients and 13 age-matched controls. The proportion of the most abundant ‘classical’ CD14highCD16 monocytes did not change after stroke, whereas that of CD14highCD16+ monocytes increased and CD14dimCD16+ monocytes decreased. CD14highCD16 + monocytes had the highest expression of TLR2, HLA-DR and the angiogenic marker, Tie-2; CD14dimCD16+ monocytes had the highest expression of costimulatory CD86 and adhesion molecule CD49d. Platelet-monocyte interactions were highest in CD14highCD16 monocytes and lowest in CD14dimCD16+ monocytes. In adjusted models, 1/CD14highCD16 monocytes were associated with poor outcome (OR: 1.38), higher mortality (OR: 1.40) and early clinical worsening (OR: 1.29); 2/CD14highCD16+ monocytes were inversely related to mortality (OR: 0.32); and 3/CD14dimCD16+ monocytes were inversely related to poor outcome (OR: 0.74) and infarction size (r= 0.45; P = 0.02). These results illustrate that the predominant monocyte subtype conveys harmful effects after stroke, which include stronger interaction with platelets. Alternatively, rarer subpopulations of monocytes are beneficial with a phenotype that could promote tissue repair and angiogenesis. Therefore, monitoring of monocyte subtypes may emerge as a useful tool at the bedside for stroke patients.

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual-energy imaging remains relatively untapped, possibly due to its intricate workflow and the intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is necessary for an appropriate clinical use. The aims of this paper are to review the physical and technical bases of DECT acquisition and analysis, to discuss the advantages and limitations of DECT in different clinical scenarios, to review the technical constraints in material labeling and quantification, and to evaluate the cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radiogenomics.

Background We compared the performance, confidence, and response consistency of five chatbots powered by large language models in solving European Diploma in Radiology (EDiR) text-based multiple-response questions. Methods ChatGPT-4o, ChatGPT-4o-mini, Copilot, Gemini, and Claude 3.5 Sonnet were tested using 52 text-based multiple-response questions from two previous EDiR sessions in two iterations. Chatbots were prompted to evaluate each answer as correct or incorrect and grade its confidence level on a scale of 0 (not confident at all) to 10 (most confident). Scores per question were calculated using a weighted formula that accounted for correct and incorrect answers (range 0.0–1.0). Results Claude 3.5 Sonnet achieved the highest score per question (0.84 ± 0.26, mean ± standard deviation) compared to ChatGPT-4o (0.76 ± 0.31), ChatGPT-4o-mini (0.64 ± 0.35), Copilot (0.62 ± 0.37), and Gemini (0.54 ± 0.39) ( p  < 0.001). A self-reported confidence in answering the questions was 9.0 ± 0.9 for Claude 3.5 Sonnet followed by ChatGPT-4o (8.7 ± 1.1), compared to ChatGPT-4o-mini (8.2 ± 1.3), Copilot (8.2 ± 2.2), and Gemini (8.2 ± 1.6, p  < 0.001). Claude 3.5 Sonnet demonstrated superior consistency, changing responses in 5.4% of cases between the two iterations, compared to ChatGPT-4o (6.5%), ChatGPT-4o-mini (8.8%), Copilot (13.8%), and Gemini (18.5%). All chatbots outperformed human candidates from previous EDiR sessions, achieving a passing grade from this part of the examination. Conclusion Claude 3.5 Sonnet exhibited superior accuracy, confidence, and consistency, with ChatGPT-4o performing nearly as well. The variation in performance among the evaluated models was substantial. Relevance statement Variation in performance, consistency, and confidence among chatbots in solving EDiR test-based questions highlights the need for cautious deployment, particularly in high-stakes clinical and educational settings. Key Points Claude 3.5 Sonnet outperformed other chatbots in accuracy and response consistency. ChatGPT-4o ranked second, showing strong but slightly less reliable performance. All chatbots surpassed EDiR candidates in text-based EDiR questions. Graphical Abstract

Immunotherapy, particularly immune checkpoint inhibitors, plays a crucial role in the treatment of brain metastases in various primary cancers. Response assessment encompasses atypical patterns, including pseudoprogression, hyperprogression, or dissociated response, which present greater complexity than classical patterns defined by standardized response assessment criteria. Additionally, intracranial adverse events like hypophysitis or encephalitis may resemble tumor progression. Accurate evaluation and management of brain metastases during immunotherapy requires that radiologists are familiar with both classical and atypical response patterns, as well as potential intracranial adverse events. Brain MRI and advanced imaging techniques serve as essential tools for this purpose. Critical relevance statement Assessing brain metastases response to immunotherapy accurately is fundamental for therapeutic decision-making. Radiologists must recognize classical and atypical responses and adverse events associated with immunotherapy to ensure optimal patient management. Key Points Immunotherapy response assessment in brain metastases is complex due to atypical patterns including pseudoprogression, hyperprogression, and dissociated responses. Immunotherapy-induced intracranial adverse events, such as hypophysitis and encephalitis, must be accurately identified. Brain MRI, complemented by advanced imaging techniques (perfusion MRI, MRS, and amino acid PET), is crucial for distinguishing these complex scenarios. Graphical Abstract

IntroductionIn recent years, there has been a notable increase of migratory movements into Europe with the arrival of not (reliably) documented young individuals within EU-Member States. Accordingly, the need for forensic age assessments likewise increased in order to administratively differentiate along the legally relevant cut-off age of 18 completed years. The objective of our study was to analyse the expert reports of forensic age estimation issued in Barcelona between 2011 and 2018.MethodIn all cases, data on the medical history, physical examination, radiology of the left hand and orthopantomography were collected. In cases without third molars and a complete ossification of the hand, a CT scan of the clavicles was also performed.ResultsA total of 2754 expert reports were evaluated; 96.7% were males, the majority were of North African origin, mainly from Morocco (63.6%), and 19.6% were sub-Saharan Africans; 65.4% had a level of bone maturation corresponding to the last three standards of Greulich and Pyle. Most cases had mineralization of the third molar corresponding to the F, G or H stages of Demirjian.In 85.9%, there was a correspondence between bone and dental age. A total of 28.8% of the subjects were evaluated as being aged over 18 years; 86.2% of North Africans were considered to be younger than 18, and 82% of sub-Saharan Africans were considered to be over 18 years old.ConclusionsIn Barcelona, most of the subjects evaluated were male and North African, and 71.2% of the cases were considered to be minors.

Background: Extracranial metastasis (EM) from glioblastoma (GB), IDH-wildtype (WHO CNS 2021 grade 4) is rare and often under-recognized, yet it has immediate implications for staging and management. We report a case series integrating advanced neuroimaging, whole-body imaging, and pathology/biomarkers to characterize imaging–pathology correlates of EM and highlight practical clinical triggers that should prompt systemic evaluation. Case presentation: We report three patients with adult-type, IDH-wildtype GB who developed EM confirmed by cytology/histology and/or concordant multimodality imaging. Brain MRI (1.5T/3T) demonstrated aggressive primary tumors with qualitative elevation of DSC-perfusion and frequent tumor–surface contact (dural, ependymal/leptomeningeal contact). Intratumoral susceptibility signal reached grade 3 where assessed. All patients underwent surgical resection followed by temozolomide-based chemoradiation; two received fotemustine and bevacizumab, and one underwent re-irradiation. EM presented with clinical triggers including severe axial/back pain, palpable cervical masses, and/or cytopenias. Initial EM sites were bone marrow/vertebrae (n = 1) and cervical lymph nodes (n = 2); staging revealed additional osseous disease in both nodal cases and a small pulmonary nodule in one. Nodal and osseous lesions were FDG-avid on 18F-FDG PET/CT. OLIG2-positive cytology confirmed cervical nodal metastases, and bone marrow aspiration with GFAP/OLIG2 positivity confirmed medullary infiltration. All tumors shared a molecular profile of TERT-promoter mutation, ATRX wild-type, TP53 mutation, and MGMT-promoter methylation. Despite attempts at second- and third-line therapies, disease progression was rapid, and all patients succumbed within 8–16 months of diagnosis. Discussion: This series underscores that EM can occur despite MGMT-promoter methylation and supports the concept of heterogeneous metastatic phenotypes in GB. Our cases reinforce that new axial/back pain or hematologic abnormalities may signal osseous or marrow involvement, and necrotic cervical lymphadenopathy in GB patients warrants dedicated imaging and tissue confirmation with glial markers. Integrating brain MRI features (high perfusion, surface contact, susceptibility burden) with FDG-PET/CT and targeted cytology/pathology can expedite diagnosis and inform multidisciplinary care. Conclusions: EM can arise despite MGMT-promoter methylation in IDH-wildtype GBM. Imaging red flags (high perfusion, surface contact, necrotic/FDG-avid cervical nodes) and clinical cues (axial pain, cytopenias, neck masses) should prompt early systemic staging (CT/PET-CT) and targeted tissue confirmation to advance management.

Abnormal metabolism is a key tumor hallmark. Proton magnetic resonance spectroscopy (1H-MRS) allows measurement of metabolite concentration that can be utilized to characterize tumor metabolic changes. 1H-MRS measurements of specific metabolites have been implemented in the clinic. This article performs a systematic review of image acquisition and interpretation of 1H-MRS for cancer evaluation, evaluates its strengths and limitations, and correlates metabolite peaks at 1H-MRS with diagnostic and prognostic parameters of cancer in different tumor types.