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Applications of Artificial Intelligence in Lung Pathology
1University of Pittsburgh Medical Center, 200 Lothrop Street C-620, Pittsburgh, PA 15213, USA.
Surgical Pathology Clinics
|May 1, 2024
Summary
Artificial intelligence (AI) and machine learning (ML) tools are advancing lung pathology diagnostics. Integration into clinical practice requires establishing regulatory, workflow, and payment frameworks.
Area of Science:
- Pathology
- Computational pathology
- Artificial intelligence in medicine
Background:
- Artificial intelligence (AI) and machine learning (ML) are increasingly utilized in pathology.
- Numerous applications are emerging for lung pathology diagnostics and prognostics.
Purpose of the Study:
- To review current and emerging AI/ML tools in lung pathology.
- To identify key applications and challenges for clinical integration.
Main Methods:
- Literature review of AI/ML applications in lung pathology.
- Analysis of specific use cases including stain evaluation, tumor interpretation, and predictive modeling.
Main Results:
- AI/ML tools show promise in evaluating acid-fast stains, PD-L1 expression, non-small-cell lung carcinoma histology, mesothelioma features, and interstitial lung disease patterns.
- Applications include predicting therapy response and assessing the tumor microenvironment using H&E slides.
- Nondestructive tissue evaluation methods are also being developed.
Conclusions:
- AI/ML tools offer significant potential to enhance lung pathology.
- Development of regulatory, workflow, and payment frameworks is crucial for successful clinical integration.
