Publications by authors named "Scheel M"

To improve reliability of metabolite quantification at both, 3 T and 7 T, we propose a novel parametrized macromolecules quantification model (PRaMM) for brain H MRS, in which the ratios of macromolecule peak intensities are used as soft constraints. Full- and metabolite-nulled spectra were acquired in three different brain regions with different ratios of grey and white matter from six healthy volunteers, at both 3 T and 7 T. Metabolite-nulled spectra were used to identify highly correlated macromolecular signal contributions and estimate the ratios of their intensities.

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Purpose: To identify the impact of endovascular simulator training and shadowing in interventional radiology on medical students' self-assessed IR knowledge. Moreover, the sequence of the teaching methods and its influence on the self-assessed IR knowledge is investigated.

Materials And Methods: A total of 19 fourth-year medical students participated in this study.

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  • In NMDA receptor encephalitis, most patients have normal MRIs during acute episodes, but subtle lesions can occur; these lesions may signal overlaps with conditions like multiple sclerosis or neuromyelitis optica.
  • Other types, such as limbic encephalitis related to LGI1, CASPR2, and GAD antibodies, show specific hyperintensities in the medial temporal lobe on MRI, while GABA receptor encephalitides present different patterns of lesions, underscoring the importance of MRI in diagnosing autoimmune encephalitis and differentiating it from other disorders.
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Purpose: This observational study aims to provide a detailed clinical and imaging characterization/workup of acute intracerebral hemorrhage (ICH) due to either an underlying metastasis (mICH) or brain tumor (tICH) lesion.

Methods: We conducted a retrospective, single-center study, evaluating patients presenting with occult ICH on initial CT imaging, classified as tICH or mICH on follow-up MRI imaging according to the H-Atomic classification. Demographic, clinical and radiological data were reviewed.

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  • A study evaluated the effectiveness of open-source large language models (LLMs) in extracting clinical data from unstructured mechanical thrombectomy reports for ischemic stroke patients.
  • Three models (Mixtral, Qwen, BioMistral) were tested using data from two institutions, showing varying performance in precision and recall for clinical data categories.
  • The findings suggest that LLMs, especially when combined with a human-in-the-loop approach, can significantly improve the efficiency and accuracy of clinical data extraction, with time savings of around 65.6% per case.
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Micropollutants are increasingly prevalent in the aquatic environment. A major part of these originates from wastewater treatment plants since traditional treatment technologies do not remove micropollutants sufficiently. Moving bed biofilm reactors (MBBRs), however, have been shown to aid in micropollutant removal when applied to conventional wastewater treatment as a polishing step.

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  • The study aimed to use standardized and automated CT assessments to predict outcomes for patients who suffered out-of-hospital cardiac arrest.
  • Involving 140 unconscious patients, results showed that while qualitative assessments and various gray-white-matter ratio (GWR) models achieved 100% specificity in predicting poor outcomes, sensitivity rates varied, with automated GWR proving robust.
  • The research concluded that these CT assessment methods could reliably indicate poor functional outcomes, and automated GWR could enhance accessibility for medical centers handling cardiac arrest cases.
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  • Selective water uptake by brain cells and brain tissue swelling after cardiac arrest contribute to hypoxic-ischemic encephalopathy, with CT scans used to evaluate this condition over time.
  • This study included head CT scans from 115 cardiac arrest patients to analyze regional net water uptake (NWU) and its relationship with neurological outcomes.
  • Results showed that a significant NWU (>8%) in certain brain regions was linked to poor neurological outcomes, suggesting that NWU could be a valuable biomarker for patient prognosis after cardiac arrest.
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Objective: To establish a deep learning model for the detection of hypoxic-ischemic encephalopathy (HIE) features on CT scans and to compare various networks to determine the best input data format.

Methods: 168 head CT scans of patients after cardiac arrest were retrospectively identified and classified into two categories: 88 (52.4%) with radiological evidence of severe HIE and 80 (47.

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While subarachnoid hemorrhage is the second most common hemorrhagic stroke in epidemiologic studies, the recent DISCHARGE-1 trial has shown that in reality, three-quarters of focal brain damage after subarachnoid hemorrhage is ischemic. Two-fifths of these ischemic infarctions occur early and three-fifths are delayed. The vast majority are cortical infarcts whose pathomorphology corresponds to anemic infarcts.

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Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the interplay among these scales. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls.

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Multiple sclerosis (MS) is a chronic neuroinflammatory disease that involves both white and gray matter. Although gray matter damage is a major contributor to disability in MS patients, conventional clinical magnetic resonance imaging (MRI) fails to accurately detect gray matter pathology and establish a clear correlation with clinical symptoms. Using magnetic resonance elastography (MRE), we previously reported global brain softening in MS and experimental autoimmune encephalomyelitis (EAE).

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Background: Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity.

Methods: We have analysed a prospective multi-centric cohort of 322 MS patients and 98 healthy controls from four MS centres, collecting disability scales at baseline and 2 years later. Imaging data included brain MRI and optical coherence tomography, and omics included genotyping, cytomics and phosphoproteomic data from peripheral blood mononuclear cells.

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Bone material contains a hierarchical network of micro- and nano-cavities and channels, known as the lacuna-canalicular network (LCN), that is thought to play an important role in mechanobiology and turnover. The LCN comprises micrometer-sized lacunae, voids that house osteocytes, and submicrometer-sized canaliculi that connect bone cells. Characterization of this network in three dimensions is crucial for many bone studies.

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Purpose: To improve reliability of metabolite quantification at both, 3 T and 7 T, we propose a novel parametrized macromolecules quantification model (PRaMM) for brain H MRS, in which the ratios of macromolecule peak intensities are used as soft constraints.

Methods: Full- and metabolite-nulled spectra were acquired in three different brain regions with different ratios of grey and white matter from six healthy volunteers, at both 3 T and 7 T. Metabolite-nulled spectra were used to identify highly correlated macromolecular signal contributions and estimate the ratios of their intensities.

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Introduction: Restricted retinal diffusion (RDR) has recently been recognized as a frequent finding on standard diffusion-weighted imaging (DWI) in central retinal artery occlusion (CRAO). However, data on early DWI signal evolution are missing.

Patients And Methods: Consecutive CRAO patients with DWI performed within 24 h after onset of visual impairment were included in a bicentric, retrospective cross-sectional study.

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Permafrost soils store a substantial part of the global soil carbon and nitrogen. However, global warming causes abrupt erosion and gradual thaw, which make these stocks vulnerable to microbial decomposition into greenhouse gases. Here, we investigated the microbial response to abrupt in situ permafrost thaw.

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Advances in high-throughput sequencing (HTS) technologies and their increasing affordability have fueled environmental DNA (eDNA) metabarcoding data generation from freshwater, marine and terrestrial ecosystems. Research institutions worldwide progressively employ HTS for biodiversity assessments, new species discovery and ecological trend monitoring. Moreover, even non-scientists can now collect an eDNA sample, send it to a specialized laboratory for analysis and receive in-depth biodiversity record from a sampling site.

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In DISCHARGE-1, a recent Phase III diagnostic trial in aneurysmal subarachnoid haemorrhage patients, spreading depolarization variables were found to be an independent real-time biomarker of delayed cerebral ischaemia. We here investigated based on prospectively collected data from DISCHARGE-1 whether delayed infarcts in the anterior, middle, or posterior cerebral artery territories correlate with (i) extravascular blood volumes; (ii) predefined spreading depolarization variables, or proximal vasospasm assessed by either (iii) digital subtraction angiography or (iv) transcranial Doppler-sonography; and whether spreading depolarizations and/or vasospasm are mediators between extravascular blood and delayed infarcts. Relationships between variable groups were analysed using Spearman correlations in 136 patients.

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Article Synopsis
  • Optic neuritis (ON) often signals the onset of multiple sclerosis (MS) and other related disorders, with high-dose corticosteroids recommended for treatment but not adequately studied regarding timing and patient antibodies.
  • The Acute Optic Neuritis Network (ACON) aims to investigate how the timing of corticosteroid treatment affects visual outcomes 6 months post-ON onset by enrolling patients who present within 30 days of initial symptoms.
  • The study will collect extensive data on various ON subtypes and factors like visual acuity, imaging results, and patient-reported outcomes from 28 hospitals globally, targeting a recruitment of 200 patients across different ON classifications.
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The gravitational wave strain emitted by a perturbed black hole (BH) ringing down is typically modeled analytically using first-order BH perturbation theory. In this Letter, we show that second-order effects are necessary for modeling ringdowns from BH merger simulations. Focusing on the strain's (ℓ,m)=(4,4) angular harmonic, we show the presence of a quadratic effect across a range of binary BH mass ratios that agrees with theoretical expectations.

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In this study, we hypothesised that the actual development stage (i.e., current age of the ecosystem) is a determining factor for the magnitude of methane production and emissions in young, northern high-latitude peatlands.

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Synchrotron X-rays micro-computed tomography was applied to visualize and quantify 3D ice crystal changes into a model sponge cake after freezing and subsequent frozen storage. Model sponge cake samples were submitted to two different freezing rates (fast: 17.2 °C min and slow: 0.

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  • The study looked at how MRI and special tools called QReports can help doctors diagnose and understand multiple sclerosis (MS) better.
  • They reviewed different QReports to see how well they work and if they have been tested properly.
  • They found that while some tools were well-tested, many haven't been checked enough by doctors who actually use them in real situations.
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