A5007901486- Pulmonary Hypertension Research and Treatments
- Cardiovascular Function and Risk Factors
- Cardiac Imaging and Diagnostics
- Radiomics and Machine Learning in Medical Imaging
- Advanced X-ray and CT Imaging
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Venous Thromboembolism Diagnosis and Management
- Artificial Intelligence in Healthcare and Education
- Radiation Dose and Imaging
- Lung Cancer Diagnosis and Treatment
- Cardiac Valve Diseases and Treatments
- Congenital Heart Disease Studies
- Systemic Sclerosis and Related Diseases
- Ultrasound in Clinical Applications
- Atomic and Subatomic Physics Research
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Cardiovascular Disease and Adiposity
- Vascular Procedures and Complications
- COVID-19 diagnosis using AI
- Advanced MRI Techniques and Applications
- Aortic aneurysm repair treatments
- Medical Imaging and Pathology Studies
- Liver Disease and Transplantation
- Pancreatic function and diabetes
- Radiology practices and education
University of Sheffield
2019-2024
Chesterfield Royal Hospital NHS Foundation Trust
2024
Sheffield Teaching Hospitals NHS Foundation Trust
2019-2024
Royal Hallamshire Hospital
2016-2024
Insigneo
2021-2024
Royal College of Radiologists
2024
Istituti di Ricovero e Cura a Carattere Scientifico
2024
Imperial College London
2024
Hospital Clínic de Barcelona
2024
MultiMedica
2024
BackgroundAmong patients meeting diagnostic criteria for idiopathic pulmonary arterial hypertension (IPAH), there is an emerging lung phenotype characterised by a low diffusion capacity carbon monoxide (DLCO) and smoking history. The present study aimed at detailed characterisation of these patients.MethodsWe analysed data from two European registries, COMPERA (launched in 2007) ASPIRE (from 2001 onwards), to identify diagnosed with IPAH defined DLCO less than 45% predicted We compared...
Background Diagnostic rates and risk factors for the subsequent development of chronic thromboembolic pulmonary hypertension (CTEPH) following embolism (PE) are not well defined. Methods Over a 10-year period (2010–2020), consecutive patients attending PE follow-up clinic in Sheffield, UK (population 554 600) all diagnosed with CTEPH at (PH) referral centre Sheffield (referral population estimated 15–20 million) were included. Results Of 1956 3 months diagnosis acute PE, 41 cumulative...
Background Segmentation of cardiac structures is an important step in evaluation the heart on imaging. There has been growing interest how artificial intelligence (AI) methods—particularly deep learning (DL)—can be used to automate this process. Existing AI approaches segmentation have mostly focused MRI. This systematic review aimed appraise performance and quality supervised DL tools for CT. Methods Embase Medline databases were searched identify related studies from January 1, 2013...
Background There is clinical need to better quantify lung disease severity in pulmonary hypertension (PH), particularly idiopathic arterial (IPAH) and PH associated with (PH-LD). Purpose To fibrosis on CT angiograms using an artificial intelligence (AI) model assess whether this approach can be used combination radiologic scoring predict survival. Materials Methods This retrospective multicenter study included adult patients IPAH or PH-LD who underwent incidental imaging between February...
Computed tomography (CT) pulmonary angiography is widely used in patients with suspected hypertension (PH). However, the diagnostic and prognostic significance remains unclear. The aim of this study was to (a) build a CT model (b) test its significance.Consecutive PH undergoing routine right heart catheterisation (RHC) were identified. Axial reconstructed images derive metrics. Multivariate regression analysis performed derivation cohort identify predict mPAP ≥ 25 mmHg (the existing ESC...
Background Cardiac MRI measurements have diagnostic and prognostic value in the evaluation of cardiopulmonary disease. Artificial intelligence approaches to automate cardiac segmentation are emerging but require clinical testing. Purpose To develop evaluate a deep learning tool for quantitative functional studies assess its use prognosis patients suspected having pulmonary hypertension. Materials Methods A retrospective multicenter multivendor data set was used learning–based contouring...
Abstract Aims Pulmonary arterial hypertension (PAH) is a rare but serious disease associated with high mortality if left untreated. This study aims to assess the prognostic cardiac magnetic resonance (CMR) features in PAH using machine learning. Methods and results Seven hundred twenty-three consecutive treatment-naive patients were identified from ASPIRE registry; 516 included training, 207 validation cohort. A multilinear principal component analysis (MPCA)-based learning approach was used...
Objectives To determine the prognostic value of patterns right ventricular adaptation in patients with pulmonary arterial hypertension (PAH), assessed using cardiac magnetic resonance (CMR) imaging at baseline and follow-up. Methods Patients attending Sheffield Pulmonary Vascular Disease Unit suspected were recruited into ASPIRE (Assessing Spectrum Identified a REferral Centre) Registry. With exclusion congenital heart disease, consecutive PAH followed up until date census or death. Right...
Pulmonary hypertension (PH) in patients with chronic lung disease (CLD) predicts reduced functional status, clinical worsening and increased mortality, severe PH-CLD (≥35 mmHg) having a significantly worse prognosis than mild to moderate (21-34 mmHg). The aim of this cross-sectional study was assess the association between computed tomography (CT)-derived quantitative pulmonary vessel volume, PH severity aetiology CLD.Treatment-naïve CLD who underwent CT angiography, function testing right...
Systemic scleroderma (SSc), also known as systemic sclerosis, is a rare autoimmune disorder characterized by fibrosis of the skin and internal organs, well vascular abnormalities. Atherosclerosis, accumulation lipids fibrous tissue in arterial walls, significant cause cardiovascular morbidity mortality. Patients with are at an elevated risk for developing atherosclerosis, damage playing central role its pathogenesis. This article reviews multifactorial factors contributing to development...
Objectives Early identification of lung cancer on chest radiographs improves patient outcomes. Artificial intelligence (AI) tools may increase diagnostic accuracy and streamline this pathway. This study evaluated the performance commercially available AI-based software trained to identify cancerous nodules radiographs. Design retrospective included primary care acquired in a UK centre. The each radiograph independently outputs were compared with two reference standards: (1) radiologist...
Percutaneous endovascular aneurysm repair (PEVAR) has been shown to have high success rates, shorter operating times and length of stay compared open access. However, there exists a lack long-term follow-up data on these patients, questions remain regarding longer-term outcomes. This study aims assess the complications evolution accessed vessels post-PEVAR.Sixty-one cases bilateral PEVAR (122 groins) with > 36 months were analysed. Vessel diameter, calcification, dissection, lymphocele,...
Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and is recommended by the European Society of Cardiology/European Respiratory hypertension guidelines. The advent deep learning may allow more reliable measurement RA areas to improve clinical assessments. aim this study was automate cardiovascular magnetic resonance (CMR) measurements evaluate utility assessing repeatability, correlation invasive haemodynamics prognostic value. A CMR contouring model trained...
Abstract Recent studies have recognized the importance of characterizing extent lung disease in pulmonary hypertension patients by using Computed Tomography. The trustworthiness an artificial intelligence system is linked with depth evaluation functional, operational, usability, safety and validation dimensions. tool to uncertainty estimation model’s prediction. On other hand, functionality, operation usability can be achieved explainable deep learning approaches which verify patterns use...
Introduction Computed tomography pulmonary angiography (CTPA) is an essential test in the work-up of suspected vascular disease including hypertension and embolism. Cardiac great vessel assessments on CTPA are based visual assessment manual measurements which known to have poor reproducibility. The primary aim this study was develop automated whole heart segmentation (four chamber vessels) model for CTPA. Methods A nine structure semantic vessels developed using 200 patients (80/20/100...
Background Cardiac magnetic resonance (CMR) is the gold standard technique to assess biventricular volumes and function, increasingly being considered as an end-point in clinical studies. Currently, with exception of right ventricular (RV) stroke volume RV end-diastolic volume, there only limited data on minimally important differences (MIDs) reported for CMR metrics. Our study aimed identify MIDs metrics based US Food Drug Administration recommendations a outcome measure that should reflect...