Glioblastoma (GBM) present with an abundant and aberrant tumor neo-vasculature. While rapid growth of solid tumors depends on the initiation of tumor angiogenesis, GBM also progress by infiltrative growth and vascular co-option. The angiogenic factor apelin (APLN) and its receptor (APLNR) are upregulated in GBM patient samples as compared to normal brain tissue. Here, we studied the role of apelin/APLNR signaling in GBM angiogenesis and growth. By functional analysis of apelin in orthotopic GBM mouse models, we found that apelin/APLNR signaling is required for in vivo tumor angiogenesis. Knockdown of tumor cell-derived APLN massively reduced the tumor vasculature. Additional loss of the apelin signal in endothelial tip cells using the APLN-knockout (KO) mouse led to a further reduction of GBM angiogenesis. Direct infusion of the bioactive peptide apelin-13 rescued the vascular loss-of-function phenotype specifically. In addition, APLN depletion massively reduced angiogenesis-dependent tumor growth. Consequently, survival of GBM-bearing mice was significantly increased when APLN expression was missing in the brain tumor microenvironment. Thus, we suggest that targeting vascular apelin may serve as an alternative strategy for anti-angiogenesis in GBM.
Background: Orally administered substances which suppress signals from gastrointestinal fluid can be used to enhance image quality in magnetic resonance cholangiopancreatography (MRCP). In daily practice, the available substances range from commercial products to regular viands such as fruit juices. Purpose: To provide an overview on the significance of and the substances used as gastrointestinal fluid signal suppressors in MRCP. Material and Methods: A systematic review of the existing literature was performed to evaluate the efficacy and efficiency of oral T2-signal suppressors in MRCP. Results: Twenty-five publications on 16 different oral contrast media were identified. The most commonly used substances were ferumoxsil, ferric ammonium citrate, and pineapple juice. Twenty-three out of 25 publications supported the use of oral signal suppressors in MRCP. Advantages of oral signal suppressors include improved visualization of the pancreatobiliary ductal system, increased help with differential diagnoses, and higher detection rates of relevant diagnoses due to a reduction of overlaying signals. Conclusion: The application of oral substances for gastrointestinal signal suppression in MRCP is recommendable. A variety of substances are used in daily routine with good but varying effectivity and patient tolerance.
1 January 2018 in European Journal of Radiology Open
Orally administered substances, which reduce image contamination by overlying gastrointestinal fluid signals, can be used to enhance the quality of MRCP images. Recently, a new standardized formula consisting of biological substances has become available. The objective of this study is to provide a first assessment of achievable MRCP image quality, taste and palatability of this new dedicated agent. In January 2015 to May 2015 practicing radiologists in Germany, Austria and Switzerland were asked to evaluate image quality as well as taste and palatability when using the new agent (LumiVision®; b.e. imaging; Baden-Baden; Germany) in MRCP questionnaire. Both criteria were rated with a 6-point Likert scale ranging from "1" (best) to "6" (worst). A total 185 of 475 radiologic institutions (39%) submitted feedback on image quality, 187 (39%) on the taste/palatability. Assessments of image quality regarding presence of disturbing gastrointestinal fluid signal resulted in a median of 2. The majority of patients rated the subjective taste as very good (median of 1). No side effects of relevance were recorded. This large survey shows that the tested product is considered effective by radiologists regarding MRCP image quality. Patients' feedback on taste and palatability was very positive.
Radiology reports can change during workflows, especially when residents draft preliminary versions that attending physicians finalize. We explored how large language models (LLMs) and embedding techniques can categorize these changes into textual, semantic, or clinically actionable types. We evaluated 400 adult CT reports drafted by residents against finalized versions by attending physicians. Changes were rated on a five-point scale from no changes to critical ones. We examined open-source LLMs alongside traditional metrics like normalized word differences, Levenshtein and Jaccard similarity, and text embedding similarity. Model performance was assessed using quadratic weighted Cohen's kappa (κ), (balanced) accuracy, F1, precision, and recall. Inter-rater reliability among evaluators was excellent (κ = 0.990). Of the reports analyzed, 1.3 % contained critical changes. The tested methods showed significant performance differences (P < 0.001). The Qwen3-235B-A22B model using a zero-shot prompt, most closely aligned with human assessments of changes in clinical reports, achieving a κ of 0.822 (SD 0.031). The best conventional metric, word difference, had a κ of 0.732 (SD 0.048), the difference between the two showed statistical significance in unadjusted post-hoc tests (P = 0.038) but lost significance after adjusting for multiple testing (P = 0.064). Embedding models underperformed compared to LLMs and classical methods, showing statistical significance in most cases. Large language models like Qwen3-235B-A22B demonstrated moderate to strong alignment with expert evaluations of the clinical significance of changes in radiology reports. LLMs outperformed embedding methods and traditional string and word approaches, achieving statistical significance in most instances. This demonstrates their potential as tools to support peer review.