Real-World Imaging Data: Opportunities and Challenges

Area of Science:

• Biomedical Research
• Health Informatics
• Medical Imaging

Background:

• Clinical data generation is rapidly increasing, enhancing the utility of real-world data (RWD) for evidence generation.
• Real-world evidence (RWE) initially focused on electronic health records and claims data.
• Real-world imaging data (RWiD) is an emerging valuable resource, supported by advancements in imaging infrastructure and data technologies.

Purpose of the Study:

• To provide an educational overview of real-world imaging data (RWiD).
• To discuss the background, challenges, and opportunities associated with RWiD.
• To highlight RWiD applications in life sciences and biopharmaceutical use cases.

Main Methods:

• Review of current literature and technological advancements in RWiD.
• Analysis of the value proposition of incorporating actual medical images into real-world datasets.
• Identification of challenges in RWiD utilization, including deidentification, harmonization, storage, transfer, and computation.

Main Results:

• RWiD, the retrospective collection of routinely gathered clinical imaging data, offers richer information than radiology reports alone.
• Medical imaging is crucial for clinical decision-making across specialties and surveillance.
• Successful RWiD implementation requires addressing complex data management and processing hurdles.

Conclusions:

• RWiD represents a significant advancement in leveraging comprehensive data for biomedical research.
• Overcoming technical and logistical challenges is key to unlocking the full potential of RWiD.
• RWiD applications hold promise for accelerating drug discovery and development in the life sciences and biopharmaceutical industries.