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Introduction. Vagal nerve stimulation (VNS) is a therapeutical option for the treatment of drug-resistant epileptic patients. The response to VNS varies from patient to patient and is difficult to predict. The proposed study is based on our previous work, identifying relative mean power in pre-implantation EEG as a reliable marker for VNS efficacy prediction in adult patients. Our study has two main tasks. Firstly, to confirm the utility of relative mean power as a feature correlating with VNS efficacy in children. The second is to validate the applicability of our prediction classifier, Pre-X-Stim, in the pediatric population. Material and Methods. We identified a group of children with drug-resistant epilepsy. We included only children in whom EEG contained photic stimulation (Task 1) or was recorded based on the defined acquisition protocol used for development Pre-X-Stim (Task 2). Relative mean powers were calculated. VNS responders and non-responders were compared based on relative mean powers' values. In the next step, we evaluate the utility of our classifier, Pre-X-Stim, in the children population. Results: We identified 57 children treated with VNS - 17 patients were recruited for the Task 1 and 7 patients for the Task 2. When focusing on relative mean powers in EEG spectra, we observed statistically significant differences in theta range. The Pre-X-Stim algorithm was able to predict VNS efficacy correctly in 6 out of 7 patients (the accuracy 83.3%, the sensitivity 75%, the specificity 100%). Conclusions. Based on our results, it seems that children and adults share a similar pattern of EEG relative mean power changes. These changes can be used for pre-implantation prediction of VNS efficacy.
- MeSH
- dítě MeSH
- elektroencefalografie * metody MeSH
- epilepsie * terapie patofyziologie MeSH
- lidé MeSH
- mladiství MeSH
- předškolní dítě MeSH
- refrakterní epilepsie * terapie patofyziologie MeSH
- skalp MeSH
- vagová stimulace * metody MeSH
- výsledek terapie MeSH
- Check Tag
- dítě MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- předškolní dítě MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Super-resolution (SR) microscopy is a cutting-edge method that can provide detailed structural information with high resolution. However, the thickness of the specimen has been a major limitation for SR methods, and large biological structures have posed a challenge. To overcome this, the key step is to optimise sample preparation to ensure optical homogeneity and clarity, which can enhance the capabilities of SR methods for the acquisition of thicker structures. Oocytes are the largest cells in the mammalian body and are crucial objects in reproductive biology. They are especially useful for studying membrane proteins. However, oocytes are extremely fragile and sensitive to mechanical manipulation and osmotic shocks, making sample preparation a critical and challenging step. We present an innovative, simple and sensitive approach to oocyte sample preparation for 3D STED acquisition. This involves alcohol dehydration and mounting into a high refractive index medium. This extended preparation procedure allowed us to successfully obtain a unique two-channel 3D STED SR image of an entire mouse oocyte. By optimising sample preparation, it is possible to overcome current limitations of SR methods and obtain high-resolution images of large biological structures, such as oocytes, in order to study fundamental biological processes. Lay Abstract: Super-resolution (SR) microscopy is a cutting-edge tool that allows scientists to view incredibly fine details in biological samples. However, it struggles with larger, thicker specimens, as they need to be optically clear and uniform for the best imaging results. In this study, we refined the sample preparation process to make it more suitable for SR microscopy. Our method includes carefully dehydrating biological samples with alcohol and then transferring them into a mounting medium that enhances optical clarity. This improved protocol enables high-resolution imaging of thick biological structures, which was previously challenging. By optimizing this preparation method, we hope to expand the use of SR microscopy for studying large biological samples, helping scientists better understand complex biological structures.
OBJECTIVES: Differentiating true progression or recurrence (TP/TR) from therapy-related changes (TRC) is complex in brain tumours. Amide proton transfer-weighted (APT) imaging is a chemical exchange saturation transfer (CEST) MRI technique that may improve diagnostic accuracy during radiological follow-up. This systematic review and meta-analysis elucidated the level of evidence and details of state-of-the-art imaging for APT-CEST in glioma and brain metastasis surveillance. METHODS: PubMed, EMBASE, Web of Science, and Cochrane Library were systematically searched for original articles about glioma and metastasis patients who received APT-CEST imaging for suspected TP/TR within 2 years after (chemo)radiotherapy completion. Modified Quality Assessment of Diagnostic Accuracy Studies-2 criteria were applied. A meta-analysis was performed to pool results and to compare subgroups. RESULTS: Fifteen studies were included for a narrative synthesis, twelve of which (500 patients) were deemed sufficiently homogeneous for a meta-analysis. Magnetisation transfer ratio asymmetry performed well in gliomas (sensitivity 0.88 [0.82-0.92], specificity 0.84 [0.72-0.91]) but not in metastases (sensitivity 0.64 [0.38-0.84], specificity 0.56 [0.33-0.77]). APT-CEST combined with conventional/advanced MRI rendered 0.92 [0.86-0.96] and 0.88 [0.72-0.95] in gliomas. Tumour type, TR prevalence, sex, and acquisition protocol were sources of significant inter-study heterogeneity in sensitivity (I2 = 62.25%; p < 0.01) and specificity (I2 = 66.31%; p < 0.001). CONCLUSION: A growing body of literature suggests that APT-CEST is a promising technique for improving the discrimination of TP/TR from TRC in gliomas, with limited data on metastases. CLINICAL RELEVANCE STATEMENT: This meta-analysis identified a utility for APT-CEST imaging regarding the non-invasive discrimination of brain tumour progression from therapy-related changes, providing a critical evaluation of sequence parameters and cut-off values, which can be used to improve response assessment and patient outcome. KEY POINTS: Therapy-related changes mimicking progression complicate brain tumour treatment. Amide proton imaging improves the non-invasive discrimination of glioma progression from therapy-related changes. Magnetisation transfer ratio asymmetry measurement seems not to have added value in brain metastases.
- MeSH
- amidy * MeSH
- diferenciální diagnóza MeSH
- gliom * diagnostické zobrazování patologie MeSH
- lidé MeSH
- lokální recidiva nádoru diagnostické zobrazování MeSH
- magnetická rezonanční tomografie * metody MeSH
- nádory mozku * diagnostické zobrazování sekundární MeSH
- progrese nemoci * MeSH
- protony MeSH
- senzitivita a specificita MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- metaanalýza MeSH
- systematický přehled MeSH
MR imaging-visible perivascular spaces (PVS) have been associated with disease phenotypes, risk factors, sleep measures, and overall brain health. We review avenues in the analysis of PVS quantified from brain MR imaging across dissimilar acquisition protocols, imaging modalities, scanner manufacturers and magnetic field strengths. We conduct a pilot analysis to evaluate different avenues to harmonise PVS assessments from using different parameters using brain MR imaging from 100 adult volunteers, acquired at two different magnetic field strengths with different sequence parameters. The 2024 MICCAI Enlarged Perivascular Spaces Segmentation Challenge provides a representative MRI dataset on which to test other harmonization methods.
- MeSH
- dospělí MeSH
- glymfatický systém * diagnostické zobrazování MeSH
- lidé MeSH
- magnetická rezonanční tomografie * metody MeSH
- magnetické pole MeSH
- mozek * diagnostické zobrazování MeSH
- neurozobrazování * metody MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
INTRODUCTION: Rare diseases (RDs) collectively impact over 30 million people in Europe. Most individual conditions have a low prevalence which has resulted in a lack of research and expertise in this field, especially regarding genetic newborn screening (gNBS). There is increasing recognition of the importance of incorporating patients' needs and general public perspectives into the shared decision-making process regarding gNBS. This study is part of the Innovative Medicine Initiative project Screen4Care which aims at shortening the diagnostic journey for RDs by accelerating diagnosis for patients living with RDs through gNBS and the use of digital technologies, such as artificial intelligence and machine learning. Our objective will be to assess expecting parent's perspectives, attitudes and preferences regarding gNBS for RDs in Italy and Germany. METHODS AND ANALYSIS: A mixed method approach will assess perspectives, attitudes and preferences of (1) expecting parents seeking genetic consultation and (2) 'healthy' expecting parents from the general population in two countries (Germany and Italy). Focus groups and interviews using the nominal group technique and ranking exercises will be performed (qualitative phase). The results will inform the treatment of attributes to be assessed via a survey and a discrete choice experiment (DCE). The total recruitment sample will be 2084 participants (approximatively 1000 participants in each country for the online survey). A combination of thematic qualitative and logit-based quantitative approaches will be used to analyse the results of the study. ETHICS AND DISSEMINATION: This study has been approved by the Erlangen University Ethics Committee (22-246_1-B), the Freiburg University Ethics Committee (23-1005 S1-AV) and clinical centres in Italy (University of FerraraCE: 357/2023/Oss/AOUFe and Hospedale Bambino Gesu: No.2997 of 2 November 2023, Prot. No. _902) and approved for data storage and handling at the Uppsala University (2022-05806-01). The dissemination of the results will be ensured via scientific journal publication (open access).
OBJECTIVES: Accurate detection of metastatic brain lesions (MBL) is critical due to advances in radiosurgery. We compared the results of three readers in detecting MBL using T1-weighted 2D spin echo (SE) and sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) sequences with whole-brain coverage at both 1.5 T and 3 T. METHODS: Fifty-six patients evaluated for MBL were included and underwent a standard protocol (1.5 T, n = 37; 3 T, n = 19), including postcontrast T1-weighted SE and SPACE. The rating was performed by three raters in two sessions > six weeks apart. The true number of MBL was determined using all available imaging including follow-up. Intraclass correlations for intra-rater and inter-rater agreement were calculated. Signal intensity ratios (SIR; enhancing lesion, white matter) were determined on a subset of 46 MBL > 4 mm. A paired t-test was used to evaluate postcontrast sequence order and SIR. Reader accuracy was evaluated by the coefficient of determination. RESULTS: A total of 135 MBL were identified (mean/subject 2.41, SD 6.4). The intra-rater agreement was excellent for all 3 raters (ICC = 0.97-0.992), as was the inter-rater agreement (ICC = 0.995 SE, 0.99 SPACE). Subjective qualitative ratings were lower for SE images; however, signal intensity ratios were higher in SE sequences. Accuracy was high in all readers for both SE (R2 0.95-0.96) and SPACE (R2 0.91-0.96) sequences. CONCLUSIONS: Although SE sequences are superior to gradient echo sequences in the detection of small MBL, they have long acquisition times and frequent artifacts. We show that T1-weighted SPACE is not inferior to standard thin-slice SE sequences in the detection of MBL at both imaging fields. CRITICAL RELEVANCE STATEMENT: Our results show the suitability of 3D T1-weighted turbo spin echo (TSE) sequences (SPACE, CUBE, VISTA) in the detection of brain metastases at both 1.5 T and 3 T. KEY POINTS: • Accurate detection of brain metastases is critical due to advances in radiosurgery. • T1-weighted SE sequences are superior to gradient echo in detecting small metastases. • T1-weighted 3D-TSE sequences may achieve high resolution and relative insensitivity to artifacts. • T1-weighted 3D-TSE sequences have been recommended in imaging brain metastases at 3 T. • We found T1-weighted 3D-TSE equivalent to thin-slice SE at 1.5 T and 3 T.
- Publikační typ
- časopisecké články MeSH
The spinal cord plays a pivotal role in the central nervous system, providing communication between the brain and the body and containing critical motor and sensory networks. Recent advancements in spinal cord MRI data acquisition and image analysis have shown a potential to improve the diagnostics, prognosis, and management of a variety of pathological conditions. In this review, we first discuss the significance of standardized spinal cord MRI acquisition protocol in multi-center and multi-manufacturer studies. Then, we cover open-access spinal cord MRI datasets, which are important for reproducible science and validation of new methods. Finally, we elaborate on the recent advances in spinal cord MRI data analysis techniques implemented in the open-source software package Spinal Cord Toolbox (SCT).
Magnetic Resonance Imaging (MRI) has revolutionized our ability to non-invasively study the brain's structural and functional properties. However, detecting myelin, a crucial component of white matter, remains challenging due to its indirect visibility on conventional MRI scans. Myelin plays a vital role in neural signal transmission and is associated with various neurological conditions. Understanding myelin distribution and content is crucial for insights into brain development, aging, and neurological disorders. Although specialized MRI sequences can estimate myelin content, these are time-consuming. Also, many patients sent to specialized neurological centers have an MRI of the brain already scanned. In this study, we focused on techniques utilizing standard MRI T1-weighted (T1w) and T2 weighted (T2w) sequences commonly used in brain imaging protocols. We evaluated the applicability of the T1w/T2w ratio in assessing myelin content by comparing it to quantitative T1 mapping (qT1). Our study included 1 healthy adult control and 7 neurologic patients (comprising both pediatric and adult populations) with epilepsy originating from focal epileptogenic lesions visible on MRI structural scans. Following image acquisition on a 3T Siemens Vida scanner, datasets were co registered, and segmented into anatomical regions using the Fastsurfer toolbox, and T1w/T2w ratio maps were calculated in Matlab software. We further assessed interhemispheric differences in volumes of individual structures, their signal intensity, and the correlation of the T1w/T2w ratio to qT1. Our data demonstrate that in situations where a dedicated myelin-sensing sequence such as qT1 is not available, the T1w/T2w ratio provides significantly better information than T1w alone. By providing indirect information about myelin content, this technique offers a valuable tool for understanding the neurobiology of myelin-related conditions using basic brain scans.
Umělá inteligence (AI) se stále více zapojuje do medicíny včetně gastroenterologie, což otevírá nové možnosti pro diagnostiku a léčbu onemocnění trávicího traktu. ChatGPT, AI model založený na architektuře GPT-4, má potenciál zrychlit diagnostiku a léčbu, personalizovat léčbu, vzdělávat a školit zdravotníky, podporovat rozhodování a zlepšovat komunikaci s pacienty. Avšak s využitím AI přicházejí i výzvy, jako omezená schopnost AI nahradit lidský úsudek, chyby v datech, otázky související s bezpečností a ochranou osobních údajů a náklady na implementaci. Budoucnost ChatGPT v gastroenterologii závisí na schopnosti zpracovávat a analyzovat velké množství dat pro identifikaci vzorů a tvorbu individuálních léčebných plánů. ChatGPT se díky pokroku v AI a strojovém učení stává přesnějším a efektivnějším, což umožní rychlejší diagnostiku a léčbu gastroenterologických onemocnění. V oblasti vzdělávání bude ChatGPT sloužit jako neocenitelný zdroj informací o nejnovějších výzkumných článcích a postupech. Přes výhody AI v gastroenterologii je důležité řešit otázky etiky, ochrany dat a spolupráce mezi AI a zdravotnickými odborníky. Zajištění správných protokolů a postupů umožní bezpečné a etické využití AI v medicíně. Ačkoli AI přináší významný potenciál pro zlepšení kvality péče, je třeba řešit výzvy spojené s ochranou dat, bezpečností a etikou.
Artificial intelligence (AI) is increasingly being incorporated into medicine, including gastroenterology, opening new possibilities for the diagnosis and treatment of digestive tract diseases. ChatGPT, an AI model based on the GPT-4 architecture, has the potential to accelerate diagnosis and treatment, personalize care, educate, and train healthcare professionals, support decision-making, and improve communication with patients. However, with the use of AI come challenges such as the limited ability of AI to replace human judgment, data errors, issues related to security and personal data protection, and implementation costs. The future of ChatGPT in gastroenterology depends on its ability to process and analyze large amounts of data to identify patterns and create individual treatment plans. Thanks to advancements in AI and machine learning, ChatGPT is becoming more accurate and efficient, enabling faster diagnosis and treatment of gastroenterological diseases. In the field of education, ChatGPT will serve as an invaluable source of information on the latest research articles and procedures. Despite the benefits of AI in gastroenterology, it is essential to address issues of ethics, data protection, and collaboration between AI and healthcare professionals. Ensuring proper protocols and procedures will enable the safe and ethical use of AI in medicine. Although AI offers significant potential for improving the quality of care, it is necessary to address challenges associated with data protection, security, and ethics.
- Klíčová slova
- ChatGPT,
- MeSH
- algoritmy MeSH
- analýza dat MeSH
- gastroenterologie * MeSH
- lidé MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
