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Updated: May 30, 2025
A Porcine Model of Acute Autologous Pulmonary Embolism
Published on: September 6, 2024
Imaging of Acute Pulmonary Embolism: An Update.
Kiran Batra1, Fernando U Kay2, Robert C Sibley2
1Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Advanced imaging techniques like multi-energy CT improve acute pulmonary embolism diagnosis with lower radiation doses. Artificial intelligence shows promise in assisting with image analysis and patient triage.
Area of Science:
- Radiology
- Medical Imaging
- Cardiopulmonary Imaging
Background:
- Acute pulmonary embolism (PE) diagnosis relies heavily on medical imaging.
- Current imaging modalities face challenges in balancing scan speed, radiation dose, and image quality.
Purpose of the Study:
- To review the advancements in multi-energy CT (MECT) for acute PE evaluation.
- To explore the emerging role of artificial intelligence (AI) in PE imaging.
Main Methods:
- Discussion of dual-energy CT (DECT) and photon-counting CT (PCCT) technologies.
- Review of AI applications in image acquisition, processing, and interpretation for PE.
Main Results:
- MECT techniques enable faster scanning, reduced radiation exposure, and enhanced image quality for PE detection.
- AI demonstrates potential in streamlining workflow, aiding in the triage of positive PE studies, and acting as a secondary reader.
Conclusions:
- Multi-energy CT represents a significant advancement in the imaging of acute pulmonary embolism.
- Artificial intelligence offers promising adjunctive tools to improve the efficiency and accuracy of PE diagnosis.
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