Use of Radiomics to Predict Adverse Outcomes in Patients with Pulmonary Embolism: A Scoping Review of an Unresolved...

Background: Inherent to the challenge of acute pulmonary embolism (APE), the breadth of presentation ranges from asymptomatic pulmonary emboli to sudden death. Risk stratification of patients with APE is mandatory for determining the appropriate therapeutic management approach. However, the optimal clinically most relevant combination of predictors of death remains to be determined. Radiomics is an emerging discipline in medicine that extracts and analyzes quantitative data from medical images using mathematical algorithms. In APE, these data can reveal thrombus characteristics that are not visible to the naked eye, which may help to more accurately identify patients at higher risk of early clinical deterioration or mortality. We conducted a scoping review to explore the current evidence on the prognostic performance of radiomic models in patients with APE. Methods: PubMed, Web of Science, EMBASE, and Scopus were searched for studies published between January 2010 and April 2025. Eligible studies evaluated the use of radiomics to predict adverse outcomes in patients with APE. The PROSPERO registration number is CRD420251083318. Results: Nine studies were included in this review. There was significant heterogeneity in the methodology for feature selection and model development. Radiomic models demonstrated variable performance across studies. Models that combined radiomic features with clinical data tended to show better predictive accuracy. Conclusions: This scoping review underscores the potential of radiomic models, particularly when combined with clinical data, to improve risk stratification in patients with APE.