Artificial intelligence risk stratification from dynamic digital subtraction angiography radiomics predicts pulmonary embolism and associates with clinical outcomes in deep vein thrombosis: A retrospective cohort study

Key Points

AI-guided risk stratification accurately predicts thrombus instability and hemodynamic impairment, enhancing decision-making.
Incidence of pulmonary embolism significantly decreased with AI-based system, improving patient safety and outcomes.
Retrospective cohort analysis analyzed clinical data and outcomes, using dynamic angiography radiomics for risk assessment.
AI's implementation may revolutionize treatment strategies, potentially lowering the need for invasive procedures like inferior vena cava filters.

Abstract

An AI-guided risk stratification system based on dynamic DSA radiomics accurately identifies thrombus instability and hemodynamic impairment in real time and suggests its potential to help enable more personalized therapeutic decisions during intervention. In this retrospective analysis, AI-based risk stratification was associated with a significantly lower incidence of PE and severe post-thrombotic syndrome while safely curbing the overuse of inferior vena cava filters, representing a transformative advancement in the precision management of acute deep vein thrombosis.

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Cite This Study

Kang et al. (Tue,) studied this question.

synapsesocial.com/papers/69a765d4badf0bb9e87daa03 https://doi.org/https://doi.org/10.1016/j.jvsv.2026.102450

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