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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...

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Opportunistic Screening with Imaging: Actionable Insights from Unused Data.

Matthew H Lee¹, John W Garrett¹, Joshua D Warner¹

¹Department of Radiology, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA.

Radiologic Clinics of North America

|April 22, 2026

Summary

Artificial intelligence enhances clinical imaging by enabling opportunistic screening for diseases. This adds value to existing data, improving patient health outcomes and expanding radiology

Keywords:

AI Biomarkers Cardiovascular disease Metabolic disease Opportunistic screening Osteoporosis Sarcopenia Value-based care

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Area of Science:

Radiology and Medical Imaging
Artificial Intelligence in Healthcare
Public Health

Background:

Increasing volumes of clinical imaging data are generated.
Artificial intelligence (AI) technologies are emerging rapidly.
Existing imaging data often remains underutilized.

Purpose of the Study:

To explore the potential of AI in extracting additional value from existing imaging data.
To investigate the concept of value-added opportunistic screening.
To enhance patient health benefits beyond the primary imaging purpose.

Main Methods:

Leveraging AI technologies to analyze existing clinical imaging data.
Identifying opportunities for opportunistic screening.
Targeting clinically significant diseases and public health concerns.

Main Results:

AI enables the extraction of additional value from unused imaging data.
Opportunistic screening provides health benefits beyond the original imaging purpose.
Enhanced risk assessment, prevention, and treatment paradigms are possible.

Conclusions:

AI-driven opportunistic screening expands the reach and impact of radiology.
This approach benefits both individual patients and the population.
Maximizing the value of clinical imaging data is crucial for public health.