University Radiology

This paper reports on the technical performance of a nonlinear "inside-out" gradient and its feasibility and safety for diffusion encoding in humans. The tested hardware is a solenoidal coil with a 10 cm diameter, positioned at the isocenter of the magnet bore, designed to generate strong gradients within the surrounding volume. Various methods were used to characterize the spatial, temporal, mechanical, and acoustic properties of the gradient coil. ADC mapping studies show the feasibility of diffusion-weighted imaging and ADC mapping in phantoms and humans. The hardware was found to generate high gradient strengths (> 200 mT/m) for expected prostate regions whilst heating, noise, and eddy currents remained within acceptable limits for human scanning. Despite its unconventional geometry and compact form factor, standard calibration methods were effective, enabling accurate ADC mapping in both phantoms and human subjects. No peripheral nerve stimulation (PNS) was reported, even at maximum slew rates and gradient amplitudes. Inside-out nonlinear gradients can be calibrated with conventional techniques, and the hardware can provide a more convenient approach to strong diffusion weighting of targeted organs.

Activating epidermal growth factor receptor (EGFR) mutations are key drivers in non-small cell lung cancer (NSCLC) and other solid tumours, predicting responses to tyrosine kinase inhibitors (TKIs). Tumour heterogeneity alongside sampling and technical factors may contribute to discordant EGFR status across biopsies, complicating treatment decisions. However, systematic evidence on prevalence and drivers of discordance remains limited. This systematic review and meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered in PROSPERO (CRD42024615727). MEDLINE, Embase, and Scopus (2004-2024) were searched for studies reporting EGFR mutation discordance in adult solid tumours. Eligible studies compared primary and metastatic tumours (tissue-tissue), tissue and liquid biopsies (tissue-liquid), or different liquid biopsies. Data extraction and QUADAS-2 risk of bias assessment were performed independently. Discordance proportions were analysed on the logit scale with Haldane-Anscombe correction when needed. Random-effects meta-analysis was conducted using the Paule-Mandel estimator with Hartung-Knapp-Sidik-Jonkman confidence intervals. Subgroup analyses and meta-regression were used to estimate pooled discordance and explore potential predictors. A total of 154 studies (15,560 patients) predominantly involving NSCLC were included. The pooled discordance rate was 16.1% (95% confidence interval 14.2-18.2). Rates were similar for tissue-tissue (16.8%) and tissue-liquid (15.5%), but higher for liquid-liquid (34.0%). Plasma was the most-studied liquid source (16.5%), while cerebrospinal fluid showed the highest discordance (35.5%). Prior TKI exposure was associated with higher discordance (25.8%) compared with treatment-naive patients (14.6%; p = 0.003). Patients who later developed resistance also had higher baseline discordance (21.0% vs 15.0%; p = 0.042). Discordance varied by metastatic site, from 15.1% in lymph nodes to 17.9% in brain/central nervous system. Meta-regression identified TKI exposure, resistance, and mutation prevalence as predictors. EGFR mutation discordance is common and clinically relevant, particularly in NSCLC, but varies substantially by sampling strategy, biofluid, treatment context, and metastatic site. Given the high between-study heterogeneity and the predominance of NSCLC and Asian cohorts, pooled estimates should be interpreted as descriptive summaries rather than universally generalisable benchmarks. These findings support integrated and context-aware sampling strategies for EGFR-targeted therapy and resistance monitoring.

Adult-type diffuse gliomas-astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and glioblastoma, IDH-wildtype-exhibit distinct prognoses and treatment responses. Accurate preoperative subtype estimation is therefore important for clinical decision-making. Proton MR spectroscopy (1H-MRS) enables noninvasive assessment of tumor metabolism. Cystathionine, detectable at 2.72 ppm, has been proposed as a metabolic marker of oligodendroglioma, but its diagnostic performance across adult-type diffuse gliomas remains incompletely defined. This study evaluated the utility of cystathionine quantification by 1H-MRS for differentiating glioma subtypes and assessed whether combined analysis with 2-hydroxyglutarate (2HG) improves diagnostic performance. Eighty-five patients with histologically and molecularly confirmed adult-type diffuse gliomas (25 oligodendrogliomas, 28 astrocytomas, 32 glioblastomas) underwent preoperative 3T MRI including single-voxel PRESS 1H-MRS (TE = 97 ms). Spectra with severe artifacts were excluded; no cases were excluded based on full width at half maximum (FWHM < 12.8 Hz, 0.1 ppm at 3T). Metabolites were quantified using LCModel, with concentrations normalized to the unsuppressed water signal and relaxation-corrected. Group comparisons of cystathionine levels were performed using Kruskal-Wallis and Bonferroni-corrected pairwise tests. The ROC analysis evaluated diagnostic performance for differentiating oligodendrogliomas from astrocytomas and glioblastomas. Supplementary analyses excluding spectra with cystathionine CRLB ≥ 50% and combined cystathionine-2HG ROC analyses were also performed. Cystathionine levels were highest in oligodendrogliomas (1.040 ± 0.908 mM), intermediate in glioblastomas, and lowest in astrocytomas (0.437 ± 0.403 mM). Oligodendrogliomas showed significantly higher levels than astrocytomas (P = 0.003), whereas no significant difference was observed between oligodendrogliomas and glioblastomas. ROC analysis showed moderate diagnostic performance (AUC = 0.69 for oligodendroglioma vs astrocytoma; AUC = 0.56 for oligodendroglioma vs glioblastoma). After CRLB-based exclusion, sensitivity increased but specificity decreased (AUC = 0.83 for oligodendroglioma vs astrocytoma). Combining cystathionine with 2HG modestly improved AUCs (0.72 and 0.61, respectively). Cystathionine quantification by 1H-MRS reflects biologically meaningful metabolic differences among adult-type diffuse gliomas, with higher levels characteristic of oligodendrogliomas compared with astrocytomas. However, overlap with glioblastomas limits its role as a stand-alone discriminator. When interpreted alongside 2HG and conventional imaging features, cystathionine may serve as a supportive metabolic marker to enhance preoperative glioma subtype classification.

Abstract The ITER Wide Angle Viewing System (WAVS) relies on in-vessel metallic first mirrors (FM) to transport optical signals from the plasma to out-of-vessel diagnostics. Under the conditions of ITER, energetic plasma particles induce sputtering of plasma-facing components, and the resulting sputtered material can re-deposit on these mirrors, resulting in reflectivity degradation. In-situ plasma removal using radio-frequency (RF) capacitively coupled plasma discharges is one of the proposed methods to mitigate this issue. Experiments were conducted in a 3 T homogeneous magnetic field using a medical magnetic resonance imaging (MRI) system at the University Hospital of Basel. The WAVS First Mirror Unit consists of two mirror electrodes (M1 and M2), one or both of which can be powered with RF, while the remaining surfaces act as grounded areas. Systematic measurements of the self-bias voltage were performed for varying discharge conditions, including gas species (argon and helium), pressure (0.1–10 Pa) and mirror capacitance, as well as the angle θ between the mirror surface and magnetic field. The results revealed a strong dependence of the self-bias on the grounded-to-powered area ratio A g / A p , which is affected by the magnetic confinement. Erosion and deposition patterns were examined in cases where one or both mirrors were powered. Erosion occurred primarily where a powered mirror faces a grounded surface, whereas overlapping discharges in the dual-powered case resulted in low ion kinetic energy and preferential net deposition at the overlapping area. These observations were supported by one-dimensional simulations of plasma potential evolution under representative conditions. These results provide critical insight into RF plasma behaviour in fully magnetised, geometrically asymmetric discharges and support the development of robust in-situ cleaning strategies for ITER optical diagnostics.

Speech-language pathology assistants (SLPAs) have been utilized to address the shortage of speech-language pathologists (SLPs). However, the training is primarily put on the shoulders of the SLP. Currently, there is no research addressing the confidence and education of SLPAs. The current study aimed to investigate the self-perceived confidence and educational background of SLPAs. In this study, 68 participants responded to a survey. Descriptive statistics and the results of a regression analysis were used to analyze the data. The results indicate a variation of confidence across different areas of speech-language pathology. Language was the area in which the SLPAs felt the most confident, while swallowing was identified as the area where they felt the least confident. Moreover, preservice education is only a predictive factor in three of the 10 clinical areas.

Pediatric cardiovascular imaging plays an important role in the diagnosis, monitoring, and management of congenital and acquired heart diseases. Although echocardiography remains the most widely used modality in pediatric cardiology, cross-sectional imaging techniques such as cardiac magnetic resonance imaging (MRI) and computed tomography (CT) provide complementary anatomic and functional information. However, time-consuming diagnostic processes and patient-specific characteristics remain major limitations to early and precise diagnosis, as well as optimal clinical outcomes. With technological advancements, artificial intelligence (AI) has been increasingly integrated into cardiovascular magnetic resonance imaging (MRI) and computed tomography (CT) to enhance image acquisition, segmentation, interpretation, and diagnosis, and to facilitate predictive modeling of clinical outcomes. This review summarizes current and emerging AI applications in pediatric cardiovascular MRI and CT, emphasizing workflow optimization, diagnostic automation, and quantitative analysis. Emerging frontiers include multimodal data integration for risk stratification, clinical decision-making support, digital twin models, three-dimensional virtual modeling, and the application of computational fluid dynamics, as well as the potential of AI to improve access to care in low-resource settings.