Artificial Intelligence to Improve Detection and Risk Stratification of Acute Pulmonary Embolism (AID-PE)

The goal of this exploratory observational study is to assess the feasibility and real-world clinical impact of implementing Artificial Intelligence (AI) software for the detection of acute Pulmonary Embolism (PE) in patients who undergo Computed Tomography Pulmonary Angiogram (CTPA). The main questions that this study aims to answer are: \[Question 1\] What is the real-world impact of AI on the clinical outcomes and decision making by radiologists and clinicians in the management of acute PE? \[Question 2\] Is AI software for the detection of acute PE acceptable to use in clinical practice and do they have a favourable impact on clinical workload? \[Question 3\] Is it cost-effective to implement AI software for the detection of acute PE in clinical practice? Patients having a CTPA for the detection of acute PE will have their imaging analysed by AI software in combination with a human radiologist. Researchers will aim to compare the clinical and radiology specific outcomes with a retrospective cohort of patients who have had standard routine radiology reporting.