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.
- Klíčová slova
- Cerebral small vessel disease, ComBat, Image processing, MR imaging, Perivascular spaces, Virchow-robin spaces, Visual rating, Z-scores,
- 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
Neuroimaging investigations are fundamental in the diagnosis of patients with epilepsy. The International League Against Epilepsy (ILAE) harmonized neuroimaging of epilepsy structural sequences (HARNESS-MRI) protocol was intended as a generalizable structural MRI protocol. The European Reference Network for Rare and Complex Epilepsies, EpiCARE, includes 50 centers, across 26 countries, with expertise in epilepsy. We investigated adherence to the HARNESS-MRI protocol across EpiCARE. A survey on the clinical use of imaging and postprocessing methods in epilepsy patients was distributed among the centers. A descriptive analysis was performed, and results were compared to existing guidelines, as well as a previous survey in 2016. 79% of centers were adhering to the HARNESS-MRI protocol in all epilepsy patients. All centers were acquiring 3D T1-weighted sequences, 90% were acquiring 3D FLAIR and 87% were acquiring high in-plane 2D coronal T2 MRI sequences in all epilepsy patients. In comparison, in 2016, only 50% of centers were following MRI recommendations at the time. Across European expert epilepsy centers, there has been increased harmonization of MRI sequences since the introduction of the HARNESS-MRI protocol. This standardization supports optimal radiological review at individual centers as well as enabling harmonization of multicenter datasets for research. PLAIN LANGUAGE SUMMARY: Neuroimaging investigations are a fundamental component of epilepsy diagnosis. The International League Against Epilepsy (ILAE) has created guidelines about what MRI images to obtain in all epilepsy patients. In this study, we assessed the adherence of expert European epilepsy centers to these guidelines and found that 79% are acquiring the minimum set of MRI scans in all epilepsy patients. Standardization of MRI imaging serves to improve epilepsy diagnosis across Europe.
- Klíčová slova
- epilepsy, magnetic resonance imaging, postprocessing,
- MeSH
- dodržování směrnic MeSH
- epilepsie * diagnostické zobrazování MeSH
- lidé MeSH
- magnetická rezonanční tomografie * normy metody MeSH
- mozek * diagnostické zobrazování MeSH
- neurozobrazování * normy metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- Geografické názvy
- Evropa MeSH
Longitudinal neuroimaging studies offer valuable insight into brain development, ageing, and disease progression over time. However, prevailing analytical approaches rooted in our understanding of population variation are primarily tailored for cross-sectional studies. To fully leverage the potential of longitudinal neuroimaging, we need methodologies that account for the complex interplay between population variation and individual dynamics. We extend the normative modelling framework, which evaluates an individual's position relative to population standards, to assess an individual's longitudinal change compared to the population's standard dynamics. Using normative models pre-trained on over 58,000 individuals, we introduce a quantitative metric termed 'z-diff' score, which quantifies a temporal change in individuals compared to a population standard. This approach offers advantages in flexibility in dataset size and ease of implementation. We applied this framework to a longitudinal dataset of 98 patients with early-stage schizophrenia who underwent MRI examinations shortly after diagnosis and 1 year later. Compared to cross-sectional analyses, showing global thinning of grey matter at the first visit, our method revealed a significant normalisation of grey matter thickness in the frontal lobe over time-an effect undetected by traditional longitudinal methods. Overall, our framework presents a flexible and effective methodology for analysing longitudinal neuroimaging data, providing insights into the progression of a disease that would otherwise be missed when using more traditional approaches.
- Klíčová slova
- MRI, human, neuroimaging, neuroscience, normative modelling, psychosis, schizophrenia,
- MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- longitudinální studie MeSH
- magnetická rezonanční tomografie MeSH
- mozek * diagnostické zobrazování MeSH
- neurozobrazování * metody MeSH
- průřezové studie MeSH
- schizofrenie * diagnostické zobrazování patologie MeSH
- šedá hmota diagnostické zobrazování patologie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND AND OBJECTIVES: Frontotemporal lobar degeneration (FTLD) as the second most common dementia encompasses a range of syndromes and often shows overlapping symptoms with other subtypes or neurodegenerative diseases, which poses a significant clinical diagnostic challenge. Recent advancements in artificial intelligence (AI), specifically the application of machine learning (ML) algorithms to neuroimaging, have significantly progressed in addressing this challenge. This study aims to assess the diagnostic and predictive efficacy of neuroimaging feature-based AI algorithms for FTLD. METHODS: We conducted a systematic review and meta-analysis following PRISMA guidelines. We searched Pubmed, Scopus, and Web of Science for English-language, peer-reviewed studies using the following three umbrella terms: artificial intelligence, frontotemporal lobar degeneration, and neuroimaging modality. Our survey focused on computer-aided diagnosis for FTLD, employing machine/deep learning with neuroimaging radiomic features. RESULTS: The meta-analysis includes 75 articles with 20,601 subjects, including 8,051 FTLD patients. The results reveal that FTLD can be automatically classified against healthy controls (HC) with pooled sensitivity and specificity of 86% and 89%, respectively. Likewise, FTLD versus Alzheimer's disease (AD) classification exhibits pooled sensitivity and specificity of 84% and 81%, while FTLD versus Parkinson's disease (PD) demonstrates pooled sensitivity and specificity of 84% and 75%, respectively. Classification performance distinguishing FTLD from atypical Parkinsonian syndromes (APS) showed pooled sensitivity and specificity of 84% and 79%, respectively. Multiclass classification sensitivity ranges from 42% to 100%, with lower sensitivity occurring in higher class distinctions (e.g., 5-class and 11-class). DISCUSSION: Our study demonstrates the effectiveness of utilizing neuroimaging features to distinguish FTLD from HC, AD, APS, and PD in binary classification. Utilizing deep learning with multimodal neuroimaging data to differentiate FTLD subtypes and perform multiclassification among FTLD and other neurodegenerative disease holds promise for expediting diagnosis. In sum, the meta-analysis supports translation of machine learning tools in combination with imaging to clinical routine paving the way to precision medicine.
- Klíčová slova
- Artificial Intelligence, Frontotemporal lobar degeneration, Machine Learning, Meta-analysis, Neuroimaging,
- MeSH
- frontotemporální lobární degenerace * diagnostické zobrazování diagnóza MeSH
- lidé MeSH
- neurozobrazování * metody MeSH
- strojové učení MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- metaanalýza MeSH
- systematický přehled MeSH
OBJECTIVES: This evidence implementation project aimed to assess and improve compliance with evidence-based neuroimaging criteria for adult patients with suspected stroke. INTRODUCTION: Stroke is the second leading cause of mortality and severe disability, requiring timely and accurate diagnosis. Clinical guidelines recommend brain imaging within 60 minutes of hospital arrival for suspected stroke patients. This project involved hospitals in North West Anglia NHS Foundation Trust, UK, serving 850,000 people with over 800 admissions annually. METHODS: The JBI Evidence Implementation Framework was used to guide this project. JBI software, the Practical Application of Clinical Evidence System (PACES), as well as JBI's Getting Research into Practice (GRiP) approach, were used to conduct the audit and implementation phases. The project followed three stages: (1) implementation planning, (2) baseline assessment and implementation, and (3) impact evaluation. Three audit criteria were used to represent best practices for diagnosing suspected stroke patients. RESULTS: The baseline audit revealed low compliance with the first criterion, with only 2.9% (1/35) of patients receiving a CT head scan within 1 hour of admission. In the follow-up audit, compliance improved to 45.2% (14/31). The other two criteria, diagnosis by a trained health care professional and baseline ECG assessment, had already achieved 100% compliance in the baseline audit. CONCLUSIONS: Compliance with evidence-based neuroimaging criteria improved after implementing targeted educational strategies and training. The rate of CT scans conducted within 1 hour increased, although door-to-imaging times remain suboptimal compared with achievable benchmarks of ≤ 20 minutes. Ongoing education and training are crucial for sustaining high compliance and improving stroke patient outcomes. SPANISH ABSTRACT: http://links.lww.com/IJEBH/A324.
- MeSH
- časové faktory MeSH
- cévní mozková příhoda * diagnostické zobrazování diagnóza MeSH
- dodržování směrnic MeSH
- dospělí MeSH
- lékařská praxe založená na důkazech MeSH
- lidé MeSH
- neurozobrazování * metody normy MeSH
- počítačová rentgenová tomografie MeSH
- směrnice pro lékařskou praxi jako téma MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Spojené království MeSH
Botulinum neurotoxins (BoNTs) and tetanus toxin (TeTX) are the deadliest biological substances that cause botulism and tetanus, respectively. Their astonishing potency and capacity to enter neurons and interfere with neurotransmitter release at presynaptic terminals have attracted much interest in experimental neurobiology and clinical research. Fused with reporter proteins or labelled with fluorophores, BoNTs and TeTX and their non-toxic fragments also offer remarkable opportunities to visualize cellular processes and functions in neurons and synaptic connections. This study presents the state-of-the-art optical probes derived from BoNTs and TeTX and discusses their applications in molecular and synaptic biology and neurodevelopmental research. It reviews the principles of the design and production of probes, revisits their applications with advantages and limitations and considers prospects for future improvements. The versatile characteristics of discussed probes and reporters make them an integral part of the expanding toolkit for molecular neuroimaging, promoting the discovery process in neurobiology and translational neurosciences.
- Klíčová slova
- Advanced biomaterials, Fluorescent probes, Fusion proteins, Molecular trafficking, Optical imaging, Retrograde transport, SNARE proteins,
- MeSH
- botulotoxiny chemie MeSH
- fluorescenční barviva chemie MeSH
- lidé MeSH
- molekulární sondy chemie MeSH
- neurony * metabolismus MeSH
- neurotoxiny * MeSH
- neurozobrazování * metody MeSH
- synapse * metabolismus MeSH
- tetanový toxin * chemie MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
- Názvy látek
- botulotoxiny MeSH
- fluorescenční barviva MeSH
- molekulární sondy MeSH
- neurotoxiny * MeSH
- tetanový toxin * MeSH
Assessing imaging biomarker in the prodromal and early phases of Parkinson's disease (PD) is of great importance to ensure an early and safe diagnosis. In the last decades, imaging modalities advanced and are now able to assess many different aspects of neurodegeneration in PD. MRI sequences can measure iron content or neuromelanin. Apart from SPECT imaging with Ioflupane, more specific PET tracers to assess degeneration of the dopaminergic system are available. Furthermore, metabolic PET patterns can be used to anticipate a phenoconversion from prodromal PD to manifest PD. In this regard, it is worth mentioning that PET imaging of inflammation will gain significance. Molecular imaging of neurotransmitters like serotonin, noradrenaline and acetylcholine shed more light on non-motor symptoms. Outside of the brain, molecular imaging of the heart and gut is used to measure PD-related degeneration of the autonomous nervous system. Moreover, optical coherence tomography can noninvasively detect degeneration of retinal fibers as a potential biomarker in PD. In this review, we describe these state-of-the-art imaging modalities in early and prodromal PD and point out in how far these techniques can and will be used in the future to pave the way towards a biomarker-based staging of PD.
- Klíčová slova
- MRI, PET, Parkinson’s disease, biomarker, diagnosis, neuroimaging, prodromal, progression,
- MeSH
- biologické markery * metabolismus analýza MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- neurozobrazování metody MeSH
- optická koherentní tomografie metody MeSH
- Parkinsonova nemoc * diagnostické zobrazování metabolismus diagnóza MeSH
- pozitronová emisní tomografie MeSH
- prodromální symptomy * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
- Názvy látek
- biologické markery * MeSH
The application of artificial intelligence (AI) in neurology is a growing field offering opportunities to improve accuracy of diagnosis and treatment of complicated neuronal disorders, plus fostering a deeper understanding of the aetiologies of these diseases through AI-based analyses of large omics data. The most common neurodegenerative disease, Alzheimer's disease (AD), is characterized by brain accumulation of specific pathological proteins, accompanied by cognitive impairment. In this review, we summarize the latest progress on the use of AI in different AD-related fields, such as analysis of neuroimaging data enabling early and accurate AD diagnosis; prediction of AD progression, identification of patients at higher risk and evaluation of new treatments; improvement of the evaluation of drug response using AI algorithms to analyze patient clinical and neuroimaging data; the development of personalized AD therapies; and the use of AI-based techniques to improve the quality of daily life of AD patients and their caregivers.
- MeSH
- Alzheimerova nemoc * diagnóza farmakoterapie metabolismus MeSH
- klinické zkoušky jako téma MeSH
- lidé MeSH
- neurozobrazování metody MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
BACKGROUND: Subjective cognitive decline (SCD) is a risk factor for future cognitive impairment and dementia. It is uncertain whether the neurodegeneration of the cholinergic system is already present in SCD individuals. We aimed to review the current evidence about the association between SCD and biomarkers of degeneration in the cholinergic system. METHOD: Original articles were extracted from three databases: Pubmed, Web of Sciences, and Scopus, in January 2023. Two researchers screened the studies independently. RESULTS: A total of 11 research articles were selected. SCD was mostly based on amnestic cognitive complaints. Cholinergic system biomarkers included neuroimaging markers of basal forebrain volume, functional connectivity, transcranial magnetic stimulation, or biofluid. The evidence showed associations between basal forebrain atrophy, poorer connectivity of the cholinergic system, and SCD CONCLUSIONS: Degenerative changes in the cholinergic system can be present in SCD. Subjective complaints may help when identifying individuals with brain changes that are associated with cognitive impairment. These findings may have important implications in targeting individuals that may benefit from cholinergic-target treatments at very early stages of neurodegenerative diseases.
- Klíčová slova
- Basal forebrain, Basal nucleus of Meynert, Ch(4), Cholinergic system, Subjective cognitive impairment, Subjective memory complaints,
- MeSH
- Alzheimerova nemoc * MeSH
- biologické markery MeSH
- cholinergní látky MeSH
- kognitivní dysfunkce * diagnostické zobrazování MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- neurozobrazování metody MeSH
- pars basalis telencephali * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- systematický přehled MeSH
- Názvy látek
- biologické markery MeSH
- cholinergní látky MeSH
The objective was to determine the optimal combination of multimodal imaging methods (IMs) for localizing the epileptogenic zone (EZ) in patients with MR-negative drug-resistant epilepsy. Data from 25 patients with MR-negative focal epilepsy (age 30 ± 10 years, 16M/9F) who underwent surgical resection of the EZ and from 110 healthy controls (age 31 ± 9 years; 56M/54F) were used to evaluate IMs based on 3T MRI, FDG-PET, HD-EEG, and SPECT. Patients with successful outcomes and/or positive histological findings were evaluated. From 38 IMs calculated per patient, 13 methods were selected by evaluating the mutual similarity of the methods and the accuracy of the EZ localization. The best results in postsurgical patients for EZ localization were found for ictal/ interictal SPECT (SISCOM), FDG-PET, arterial spin labeling (ASL), functional regional homogeneity (ReHo), gray matter volume (GMV), cortical thickness, HD electrical source imaging (ESI-HD), amplitude of low-frequency fluctuation (ALFF), diffusion tensor imaging, and kurtosis imaging. Combining IMs provides the method with the most accurate EZ identification in MR-negative epilepsy. The PET, SISCOM, and selected MRI-post-processing techniques are useful for EZ localization for surgical tailoring.
- MeSH
- dospělí MeSH
- elektroencefalografie MeSH
- epilepsie * diagnostické zobrazování chirurgie MeSH
- fluorodeoxyglukosa F18 * MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- mladý dospělý MeSH
- neurozobrazování metody MeSH
- zobrazování difuzních tenzorů MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladý dospělý MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- fluorodeoxyglukosa F18 * MeSH
