Publications by authors named "F V Gleeson"
Background: Multiple management guidelines for intraductal papillary mucinous neoplasms (IPMNs) have been published to improve risk stratification and resource utilization. This study aims to evaluate trends in endoscopic ultrasound (EUS) use and agreement between cross-sectional imaging and EUS for specific pancreas cystic lesion (PCL) features.
Methods: This retrospective cohort study included consecutive adults undergoing EUS for suspected IPMN detected with cross-sectional imaging (CT/MRCP) between 2013 and 2015 (Cohort 1) and 2018-2020 (Cohort 2).
Purpose: The purpose of this work is to validate a simple and versatile integrated variable flip angle (VFA) method for mapping B in hyperpolarized MRI, which can be used to correct signal variations due to coil inhomogeneity.
Theory And Methods: Simulations were run to assess performance of the VFA B mapping method compared to the currently used constant flip angle (CFA) approach. Simulation results were used to inform the design of VFA sequences, validated in four volunteers for hyperpolarized xenon-129 imaging of the lungs and another four volunteers for hyperpolarized carbon-13 imaging of the human brain.
Article Synopsis
- A multicenter study aimed to evaluate the effectiveness of methylated DNA markers (MDMs) found in pancreatic juice (PJ) for detecting pancreatic ductal adenocarcinoma (PDAC) when used alone and in combination with a blood test, CA 19-9.
- The analysis included DNA samples from 88 confirmed PDAC cases and 134 control cases, utilizing logistic regression to summarize accuracy through the area under the receiver-operating characteristic curve (AUROC).
- Results showed that the combination model of PJ-MDMs and CA 19-9 achieved a higher accuracy (AUROC of 0.95) compared to using PJ-MDMs (0.87) or CA 19-9 alone (0
Evaluating the impact of artificial intelligence-assisted image analysis on the diagnostic accuracy of front-line clinicians in detecting fractures on plain X-rays (FRACT-AI): protocol for a prospective observational study.
BMJ Open
September 2024
Introduction: Missed fractures are the most frequent diagnostic error attributed to clinicians in UK emergency departments and a significant cause of patient morbidity. Recently, advances in computer vision have led to artificial intelligence (AI)-enhanced model developments, which can support clinicians in the detection of fractures. Previous research has shown these models to have promising effects on diagnostic performance, but their impact on the diagnostic accuracy of clinicians in the National Health Service (NHS) setting has not yet been fully evaluated.
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- Atrial fibrillation (AF) ablation can lead to serious complications like esophageal injuries, which can create life-threatening fistulas; EUS (Endoscopic Ultrasound) is being explored as a better diagnostic tool than EGD (Esophagogastroduodenoscopy) for detecting these injuries.
- A study of 234 patients showed that EUS effectively identified various conditions post-ablation, including pleural effusions and esophageal wall changes, with a strong association between certain EUS findings and the severity of esophageal injury.
- The findings suggest that EUS is a safe and potentially superior method for evaluating post-ablation injuries in patients, with recommendations for prioritizing EUS over EGD in these