Key result
Deep learning-derived clot ratio on CTPA predicts higher risk stratification in acute PE.
Why the study?
Risk stratification for patients with acute pulmonary embolism is important for treatment and prognosis evaluation, prompting the development of a novel CTPA clot burden score using deep learning.
Does a deep learning-derived clot ratio improve risk stratification in patients with acute pulmonary embolism compared to traditional clot burden scores?
Observational (n=70)
No
Does a deep learning-derived clot ratio improve risk stratification in patients with acute pulmonary embolism compared to traditional clot burden scores?
A deep learning-derived clot ratio on CT pulmonary angiography correlates with risk stratification in acute pulmonary embolism and may outperform traditional clot burden scores.
May aid PE risk stratification in stable patients; leaves open superiority to traditional scores in prospective studies.
Background: Risk stratification for patients with acute pulmonary embolism (APE) is significantly important for treatment and prognosis evaluation. We aimed to develop a novel clot burden score on computed tomography pulmonary angiography (CTPA) based on deep learning (DL) algorithm for risk stratification of APE. Methods: The study retrospectively enrolled patients newly diagnosed with APE in China-Japan Friendship Hospital consecutively. We collected baseline data and CTPA parameters, and calculated four different clot burden scores, including Qanadli score, Mastora score, clot volume and clot ratio. The former two were calculated by two radiologists separately, while clot volume and clot ratio were based on the DL algorithm. The area under the curve (AUC) of four clot burden scores were analyzed. Results: Seventy patients were enrolled, including 17 in high-/intermediate-high risk and 53 in low-/intermediate-low risk. Clot burden was related to the risk stratification of APE. Among four clot burden scores, clot ratio had the highest AUC (0.719, 95% CI: 0.569-0.868) to predict patients with higher risk. In the patients with hemodynamically stable APE, only clot ratio presented statistical difference (P=0.046). Conclusions: Clot ratio is a new imaging marker of clot burden which correlates with the risk stratification of patients with APE. Higher clot ratio may indicate higher risk and acute right ventricular dysfunction in patients with hemodynamically stable status.
No takes yet. Share an insight, caveat, or question.
Xi et al. (2023) conducted an observational in Acute pulmonary embolism (APE) (n=70). Clot ratio based on deep learning algorithm vs. Qanadli score, Mastora score, and clot volume was evaluated on Prediction of higher risk stratification (AUC 0.719, 95% CI 0.569-0.868). A deep learning-derived clot ratio on CT pulmonary angiography predicted higher risk stratification in patients with acute pulmonary embolism (AUC 0.719; 95% CI 0.569-0.868).
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: