New Diagnostic Tools for Pulmonary Embolism Detection.
Jacob ShapiroAdam ReichardPatrick E MuckPublished in: Methodist DeBakey cardiovascular journal (2024)
The presentation of pulmonary embolism (PE) varies from asymptomatic to life-threatening, and management involves multiple specialists. Timely diagnosis of PE is based on clinical presentation, D-dimer testing, and computed tomography pulmonary angiogram (CTPA), and assessment by a Pulmonary Embolism Response Team (PERT) is critical to management. Artificial intelligence (AI) technology plays a key role in the PE workflow with automated detection and flagging of suspected PE in CTPA imaging. HIPAA-compliant communication features of mobile and web-based applications may facilitate PERT workflow with immediate access to imaging, team activation, and real-time information sharing and collaboration. In this review, we describe contemporary diagnostic tools, specifically AI, that are important in the triage and diagnosis of PE.
Keyphrases
- pulmonary embolism
- artificial intelligence
- machine learning
- deep learning
- inferior vena cava
- big data
- computed tomography
- high resolution
- palliative care
- emergency department
- loop mediated isothermal amplification
- health information
- magnetic resonance imaging
- healthcare
- label free
- electronic health record
- quality improvement
- high throughput
- case report
- positron emission tomography
- fluorescence imaging
- photodynamic therapy
- pet ct
- single cell