Artificial intelligence (AI) tools to accelerate MRI are rapidly entering clinical routine. Several techniques for MRI acceleration already exist, including compressed sensing and parallel imaging. The introduction of AI acceleration tools for MRI is therefore not fundamentally novel. However, the possibility of combining these AI tools with existing MRI acceleration techniques adds potential opportunities and complexity. This article focuses on commercially available AI tools for clinical MRI acceleration. The basic principle of AI-accelerated MRI is to shorten acquisition time-which results in noisier or lower-spatial-resolution images-then recover image quality with AI. The potential advantages of AI-accelerated MRI include increased patient comfort, shorter waiting lists, reduced motion artifacts, economic efficiencies, and environmental benefits. This article first briefly presents fundamental technical aspects of AI acceleration tools, including noise reduction and super-resolution reconstruction, summarizing available evidence. Potential errors and pitfalls, notably hallucinations (ie, invented or disappearing lesions) are serious concerns, yet they remain poorly investigated. The occurrence of hallucinations, however, is probably rare at the acceleration levels recommended for clinical practice. The downstream implications and potential challenges of AI-accelerated MRI are also discussed, including generating too many images and studies for a limited number of radiologists to interpret. Additionally, slight AI-generated modifications of image contrast could lead to systematic bias in analyses that use historical controls, such as brain volume analyses. Also, the critical question of how much acceleration is clinically useful remains unclear and needs further investigation. Finally, the logistics of implementing AI acceleration tools in routine clinical workflow are discussed, including invested time, costs, and essential medicolegal considerations. The scientific community and radiologic societies should endeavor to establish assessment criteria for this new beneficial class of MRI tools that are rapidly entering clinical practice.

With the increasing use of disease modifying therapies as treatment for multiple sclerosis, knowledge of the rare but possibly severe adverse events becomes increasingly important. We present a case of Varicella-Zoster virus associated vasculopathy in a young male multiple sclerosis patient, treated with dimethyl fumarate. We aim to address this rare but potentially deadly complication of varicella-Zoster virus infection and spread awareness about the increased risk in this patient population.

Teaching point: Meningovascular neurosyphilis is a cause of stroke in the young, and the diagnosis could be aided by black-blood MRI sequences.

Despite the advancement in computational modeling towards brain tumor segmentation, of which several models have been developed, it is evident from the computational complexity of existing models that performance and efficiency under clinical application scenarios are still limited. Therefore, this paper proposes a tumor segmentation framework. It includes a novel shallow encoder and decoder network named SEDNet for brain tumor segmentation. The highlights of SEDNet include sufficiency in hierarchical convolutional downsampling and selective skip mechanism for cost-efficient and effective brain tumor semantic segmentation, among other features. The preprocessor and optimization function approaches are devised to minimize the uncertainty in feature learning impacted by nontumor slices or empty masks with corresponding brain slices and address class imbalances as well as boundary irregularities of tumors, respectively. Through experiments, SEDNet achieved impressive dice and Hausdorff scores of 0.9308 %, 0.9451 %, and 0.9026 %, and 0.7040 mm, 1.2866 mm, and 0.7762 mm for the non-enhancing tumor core (NTC), peritumoral edema (ED), and enhancing tumor (ET), respectively. This is one of the few works to report segmentation performance on NTC. Furthermore, through transfer learning with initialized SEDNet pre-trained weights, termed SEDNetX, a performance increase is observed. The dice and Hausdorff scores recorded are 0.9336%, 0.9478%, 0.9061%, 0.6983 mm, 1.2691 mm, and 0.7711 mm for NTC, ED, and ET, respectively. With about 1.3 million parameters and impressive performance in comparison to the state-of-the-art, SEDNet(X) is shown to be computationally efficient for real-time clinical diagnosis. The code is available on GitHub.

Abstract In this case report, we describe a 76-year-old woman, presenting with dizziness for the past 2 months, without other focal neurological signs. A magnetic resonance imaging of the brain was ordered by her GP. The MRI demonstrated multiple ring-enhancing lesions, both supratentorial and infratentorial. Lumbar puncture showed normal findings, in particular a normal cell count and culture. Because of the radiologic appearance, initially thought to be suggestive of cerebral abscesses, antibiotics were started. However, further workup revealed a new diagnosis of a stage IV (metastatic) small cell lung carcinoma, making diffuse brain metastases more likely. The patient was transferred to oncology/pneumology, where she was started on whole-brain radiotherapy, after which systemic therapy would start. However, because of further clinical deterioration, she was admitted at the palliative ward, where she died only 3 months after the initial presentation. In this case report, we emphasize the importance of keeping a broad differential diagnosis and briefly review the various possible pathologies causing ring-enhancing lesions.

We compared different LLMs, notably chatGPT, GPT4, and Google Bard and we tested whether their performance differs in subspeciality domains, in executing examinations from four different courses of the European Society of Neuroradiology (ESNR) notably anatomy/embryology, neuro-oncology, head and neck and pediatrics. Written exams of ESNR were used as input data, related to anatomy/embryology (30 questions), neuro-oncology (50 questions), head and neck (50 questions), and pediatrics (50 questions). All exams together, and each exam separately were introduced to the three LLMs: chatGPT 3.5, GPT4, and Google Bard. Statistical analyses included a group-wise Friedman test followed by a pair-wise Wilcoxon test with multiple comparison corrections. Overall, there was a significant difference between the 3 LLMs (p < 0.0001), with GPT4 having the highest accuracy (70

Commercial software based on artificial intelligence (AI) is entering clinical practice in neuroradiology. Consequently, medico-legal aspects of using Software as a Medical Device (SaMD) become increasingly important. These medico-legal issues warrant an interdisciplinary approach and may affect the way we work in daily practice. In this article, we seek to address three major topics: medical malpractice liability, regulation of AI-based medical devices, and privacy protection in shared medical imaging data, thereby focusing on the legal frameworks of the European Union and the USA. As many of the presented concepts are very complex and, in part, remain yet unsolved, this article is not meant to be comprehensive but rather thought-provoking. The goal is to engage clinical neuroradiologists in the debate and equip them to actively shape these topics in the future.

Thanks to its non-invasive nature and high-resolution imaging capabilities, magnetic resonance imaging (MRI) is a valuable diagnostic tool for pediatric patients. However, the fear and anxiety experienced by young children during MRI scans often result in suboptimal image quality and the need for sedation/anesthesia. This study aimed to evaluate the effect of a smartphone application called COSMO@home to prepare children for MRI scans to reduce the need for sedation or general anesthesia. The COSMO@home app was developed incorporating mini-games and an engaging storyline to prepare children for learning goals related to the MRI procedure. A multicenter study was conducted involving four hospitals in Belgium. Eligible children aged 4–10 years were prepared with the COSMO@home app at home. Baseline, pre-scan, and post-scan questionnaires measured anxiety evolution in two age groups (4–6 years and 7–10 years). Eighty-two children participated in the study, with 95% obtaining high-quality MRI images. The app was well-received by children and parents, with minimal technical difficulties reported. In the 4–6-year-old group (N = 33), there was a significant difference between baseline and pre-scan parent-reported anxiety scores, indicating an increase in anxiety levels prior to the scan. In the 7–10-year-old group (N = 49), no significant differences were observed between baseline and pre-scan parent-reported anxiety scores. Overall, the COSMO@home app proved to be useful in preparing children for MRI scans, with high satisfaction rates and successful image outcomes across different hospitals. The app, combined with minimal face-to-face guidance on the day of the scan, showed the potential to replace or assist traditional face-to-face training methods. This innovative approach has the potential to reduce the need for sedation or general anesthesia during pediatric MRI scans and its associated risks and improve patient experience.

Undergoing an awake MRI-scan can be very stressful for young children and bears the risk that image quality is poor due to motion artefacts. Behavioral training by an experienced trainer has shown success in preparing children before a scan, however, this approach is costly and trainer dependent. We have designed a mobile app to prepare children for an upcoming MRI-scan at home. This app was tested by 52 children in four different hospitals. First data show that children and parents appreciate the app very much and that learning goals can be reached with a digital application at home.

Abstract: In this case report we describe the case of a 66-year old man with subacute gait difficulties, with a progression to confusion coma with multiple generalised epileptic seizures during the following days. Biochemical analysis showed hyperglycaemia, cerebrospinal fluid (CSF) testing showed a mild lymphocytic pleocytosis and an elevated protein and lactate. Broad-spectrum antibiotics and antiviral therapy where initiated. However, all other CSF testing remained negative. Magnetic resonance imaging of the brain showed remarkably symmetric hyperintense T2 white matter lesions most noticable in the corpus callosum. The lesion pattern was suggestive of a metabolic or toxic encephalopathy, the preponderance for the corpus callosum was furthermore suggestive for Marchiafava-Bignami disease (MDB), as was the clinical course since admission of the patient. A high dose IV substitution of vitamin B1, B6 and B12 was started and antibiotic and antiviral therapy was discontinued. After one day the patient showed progressive regaining of consciousness and he returned to premorbid functioning in a matter of 1-2 weeks. MRI of the brain after 1 week showed notable improvement of the white matter lesions. At routine follow-up two weeks later he presented with icterus and a diagnosis of Epstein-Barr virus (EBV) hepatitis was made, lymph node biopsies showed an EBV positive diffuse large cell B-cell lymphoma (DLCBL). MDB is mostly associated with severe alcoholism, with malnourishment being the second leading cause, however there are case reports describing MDB in patients with chronically poorly controlled diabetes mellitus. We hypothesize that his condition may have been precipitated by his poorly controlled diabetes mellitus. However it is also possible that weight loss (probably related to the DLCBL diagnosis) might have contributed to a state of malnourishment and therefore played a role in the aetiology as well.

The suprahyoid neck extends from the hyoid bone inferiorly to the skull base, excluding the orbit, sinonasal and oral cavity. The suprahyoid neck is anatomically complex but can be organized into different spaces based on the fascial planes. Multiple systems with slightly different namings are adapted. As a consensus, 5 principal spaces and 2 posterior midline spaces can be recognized. Each space contains unique contents which are subject to a predictable set of disease processes. Localization of lesions to a particular space allows the generation of a limited radiologic differential diagnosis. This is termed a "space-specific diagnosis". The anatomy and related pathology of the pharyngeal mucosal, the parapharyngeal, the carotid space, the masticator space, the parotid space, the retropharyngeal space, and the perivertebral space will be discussed. After the presentation, participants will be able to comprehend the anatomy of the suprahyoid neck, understand the concept of a space- specific diagnosis and formulate a (differential) diagnosis when encountering pathology in the suprahyoid neck region.

Artificial intelligence (AI)-based tools are gradually blending into the clinical neuroradiology practice. Due to increasing complexity and diversity of such AI tools, it is not always obvious for the clinical neuroradiologist to capture the technical specifications of these applications, notably as commercial tools very rarely provide full details. The clinical neuroradiologist is thus confronted with the increasing dilemma to base clinical decisions on the output of AI tools without knowing in detail what is happening inside the "black box" of those AI applications. This dilemma is aggravated by the fact that currently, no established and generally accepted rules exist concerning best clinical practice and scientific and clinical validation nor for the medico-legal consequences in cases of wrong diagnoses. The current review article provides a practical checklist of essential points, intended to aid the user to identify and double-check necessary aspects, although we are aware that not all this information may be readily available at this stage, even for certified and commercially available AI tools. Furthermore, we therefore suggest that the developers of AI applications provide this information.

Twelve pairs of cranial nerves control the sensory and motor functions of the head and neck region, with exception of the tenth nerve, the vagus nerve which also is responsible for the parasympathetic and viscerosensory innervation of the thoracoabdominal organs. MRI is the cornerstone in the study of cranial nerves. Next to the traditional sequences that depict general anatomical findings and pathological changes, two additional sequences should be included in every imaging protocol for cranial nerves. High-resolution steady-state free precession is important for the visualization of the cisternal courses of the cranial nerves. These sequences have a high spatial resolution and additionally show dark cranial nerves against a background of bright CSF. Threedimensional T1-weighted GE sequences, preferentially with fat suppression, provide a good evaluation of nerve enhancement. The twelve cranial nerves are individually discussed from the intra-axial segments to the distal extracranial branches. There is a specific emphasis on the connections between different cranial nerves. Finally, new imaging techniques are highlighted.

The use of standardized imaging protocols is paramount in order to facilitate comparable, reproducible images and, consequently, to optimize patient care. Standardized MR protocols are lacking when studying head and neck pathologies in the pediatric population. We propose an international, multicenter consensus paper focused on providing the best combination of acquisition time/technical requirements and image quality. Distinct protocols for different regions of the head and neck and, in some cases, for specific pathologies or clinical indications are recommended. This white paper is endorsed by several international scientific societies and it is the result of discussion, in consensus, among experts in pediatric head and neck imaging.

BACKGROUND:Histologically classified glioblastomas (GBM) can have different clinical behavior and response to therapy, for which molecular subclassifications have been proposed. We evaluated the relationship of epigenetic GBM subgroups with immune cell infiltrations, systemic immune changes during radiochemotherapy, and clinical outcome.METHODS:450K genome-wide DNA methylation was assessed on tumor tissue from 93 patients with newly diagnosed GBM, treated with standard radiochemotherapy and experimental immunotherapy. Tumor infiltration of T cells, myeloid cells, and Programmed cell death protein 1 (PD-1) expression were evaluated. Circulating immune cell populations and selected cytokines were assessed on blood samples taken before and after radiochemotherapy.RESULTS:Forty-two tumors had a mesenchymal, 27 a receptor tyrosine kinase (RTK) II, 17 RTK I, and 7 an isocitrate dehydrogenase (IDH) DNA methylation pattern. Mesenchymal tumors had the highest amount of tumor-infiltrating CD3+ and CD8+ T cells and IDH tumors the lowest. There were no significant differences for CD68+ cells, FoxP3+ cells, and PD-1 expression between groups. Systemically, there was a relative increase of CD8+ T cells and CD8+ PD-1 expression and a relative decrease of CD4+ T cells after radiochemotherapy in all subgroups except IDH tumors. Overall survival was the longest in the IDH group (median 36 mo), intermediate in RTK II tumors (27 mo), and significantly lower in mesenchymal and RTK I groups (15.5 and 16 mo, respectively).CONCLUSIONS:Methylation based stratification of GBM is related to T-cell infiltration and survival, with IDH and mesenchymal tumors representing both ends of a spectrum. DNA methylation profiles could be useful in stratifying patients for immunotherapy trials.

Subacute combined degeneration of the spinal cord is a neurologic complication of vitamin B12 deficiency. It presents as a potentially reversible demyelination of the posterior and lateral columns of the cervical and dorsal spinal cord. We present the case of a 40-year-old male with progressive sensory and motor deficit from the lower extremities ascending to the mid-thoracic region. A combination of laboratory tests and magnetic resonance imaging confirmed the diagnosis of subacute degeneration of the spinal cord due to vitamin B12 deficiency.

Navigation systems used during minimally invasive spine procedures have evolved from uniplanar, two-dimensional C-arm fluoroscopy to multiplanar, 3D intraoperative computed tomography (iCT). In this study, the radiation exposure to the patient and operating room staff in posterior intervertebral lumbar fusion procedures is compared between iCT and C-arm fluoroscopy. The effective dose of the surgeon, operating nurse, and anesthesiologist was measured during surgery with personal dosimeters, and the effective dose of the patient was measured with GafchromicTM films. The time efficiency of the procedure was evaluated by recording the duration of pedicle screw fixation and the duration of the total surgery time. A total of 75 patients participated in the study; 30 patients had surgery guided by iCT and 45 by C-arm fluoroscopy. The radiation dose of the surgeon, the operating nurse, and the anesthesiologist was thirteen fold lower with surgeries assisted by iCT compared to C-arm fluoroscopy. In contrast, the effective dose of the patient significantly increased with iCT. Using iCT, radiation exposure of the operating room staff can be significantly reduced. iCT increases the effective dose of the patient and prolongs the operative time.