Inference and uncertainty in radiology

Area of Science:

• Philosophy of Science
• Medical Imaging
• Radiology

Background:

• Radiology reports communicate patient condition knowledge derived from image observations.
• Inference, primarily inductive and abductive, forms the basis for deriving explanations and predictions from empirical data.
• Conclusions from inductive reasoning are inherently contingent and provisional, necessitating methods to address uncertainty.

Purpose of the Study:

• To explore the philosophical foundations of radiology and their practical implications.
• To highlight the necessity of managing uncertainty in radiology interpretations.
• To examine the relevance of frequentist and Bayesian probability paradigms in routine radiological practice.

Main Methods:

• Philosophical analysis of inference and uncertainty in scientific reasoning.
• Description of frequentist and Bayesian probability theories.
• Discussion of the dialectic tension between these probability paradigms.

Main Results:

• Radiology reports rely on inferential reasoning, leading to inherent uncertainty in interpretations.
• Two primary paradigms for managing uncertainty in natural sciences, frequentist and Bayesian probability, are relevant to radiology.
• The tension between these paradigms is observable in daily radiologist-clinician interactions.

Conclusions:

• A deeper understanding of the philosophical underpinnings of radiology is essential for practical applications.
• Managing uncertainty is a critical aspect of radiology report generation and interpretation.
• The frequentist and Bayesian approaches to probability offer frameworks for understanding and addressing uncertainty in radiological practice.