A5082185261- Nuclear Physics and Applications
- X-ray Spectroscopy and Fluorescence Analysis
- Dementia and Cognitive Impairment Research
- Medical Imaging Techniques and Applications
- Advanced X-ray and CT Imaging
- Ion-surface interactions and analysis
- Alzheimer's disease research and treatments
- Electron and X-Ray Spectroscopy Techniques
- Advanced Neuroimaging Techniques and Applications
- MRI in cancer diagnosis
- Health, Environment, Cognitive Aging
- Pancreatitis Pathology and Treatment
- Radiation Detection and Scintillator Technologies
- Statistical Methods in Clinical Trials
- Nuclear reactor physics and engineering
- Tuberculosis Research and Epidemiology
- Radiomics and Machine Learning in Medical Imaging
- Functional Brain Connectivity Studies
- Infectious Diseases and Tuberculosis
- Orthopedic Infections and Treatments
- Pancreatic and Hepatic Oncology Research
- Radioactivity and Radon Measurements
- Advanced MRI Techniques and Applications
- Lanthanide and Transition Metal Complexes
- Artificial Intelligence in Healthcare and Education
King's College London
2019-2024
Guy's and St Thomas' NHS Foundation Trust
2024
London School of Hygiene & Tropical Medicine
2024
University of Naples Federico II
2022-2023
Collaborative Group (United States)
2023
University College London
2014-2017
MRC Unit for Lifelong Health and Ageing
2017
University of Lisbon
2013-2015
TARH (Portugal)
2013
Instituto Superior Técnico
2013
The aim was to predict survival of glioblastoma at 8 months after radiotherapy (a period allowing for completing a typical course adjuvant temozolomide), by applying deep learning the first brain MRI completion.
Increasing age is the biggest risk factor for dementia, of which Alzheimer’s disease commonest cause. The pathological changes underpinning are thought to develop at least a decade prior onset symptoms. Molecular positron emission tomography and multi-modal magnetic resonance imaging allow key processes cognitive impairment – including β-amyloid depostion, vascular disease, network breakdown atrophy be assessed repeatedly non-invasively. This enables potential determinants dementia...
Abstract INTRODUCTION The Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized (CT) data and are influenced by scanner differences, we investigated the transformation with from Insight 46 acquired PET/magnetic resonanceimaging (MRI). METHODS We transformed standardized uptake value ratios (SUVRs) 432 florbetapir PET/MRI scans processed whole cerebellum (WC) white...
Objective To summarise the incidental findings detected on brain imaging and blood tests during first wave of data collection for Insight 46 study. Design Prospective observational sub-study a birth cohort. Setting Single-day assessment at research centre in London, UK. Participants 502 individuals were recruited from MRC National Survey Health Development (NSHD), 1946 British cohort, based pre-specified eligibility criteria; mean age was 70.7 (SD: 0.7) 49% female. Outcome measures Data...
Abstract Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient for accurate prognosis other outcomes, especially when impacted by co-morbidities HIV infection. Brain magnetic resonance imaging (MRI) characterises extent and severity disease may enable more prediction complications poor outcomes. We analysed clinical brain MRI data from a prospective longitudinal study 216 adults with TBM; 73 (34%)...
ABSTRACT Purpose The Centiloid scale provides a systematic means of harmonising amyloid-β PET measures across different acquisition and processing methodologies. This work explores the transformation [ 18 F]florbetapir data acquired on combined PET/MR scanner processed with methods that differ from standard pipeline. Methods Standard PiB Florbetapir Calibration datasets were using standardised uptake value ratio (SUVR) pipeline MRI parcellations Geodesic Information Flow (GIF) algorithm in...
Abstract Introduction Tuberculous meningitis (TBM) leads to high mortality, especially amongst individuals with HIV. Predicting the incidence of disease-related complications is challenging, for which purpose value brain magnetic resonance imaging (MRI) has not been well investigated. We used a convolutional neural network (CNN) explore contribution MRI conventional prognostic determinants. Method data from two randomised control trials HIV-positive and HIV-negative adults clinical TBM in...
Abstract Background Determining Aβ‐PET status is crucial for Alzheimer’s disease trials. Standard uptake value ratio (SUVR) using a reference region common semi‐quantitative technique. Sex differences in regional blood flow and white matter (WM) could impact SUVR differentially depending on the region. It important to understand how methodological factors can influence derived Aβ status. Method Individuals from Insight 46 (1946 British birth cohort) underwent PET/MR scanning with...