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Updated: Jun 28, 2026
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
A user's guide to calculate return on investment for artificial intelligence algorithms and imaging technologies.
Alan Finkelstein1, Lauren Fane2, Teya Plastich3
1Department of Imaging Sciences, University of Rochester, Rochester, USA. alan_finkelstein@urmc.rochester.edu.
Abdominal Radiology (New York)
|June 26, 2026
Summary
Radiology leaders can now use a practical ROI analysis toolkit to financially evaluate AI and imaging technologies. This framework helps avoid common pitfalls and ensures sound decision-making for technology adoption.
Area of Science:
- Radiology and Health Informatics
- Health Economics and Outcomes Research
Background:
- Radiology departments face increasing pressure to evaluate new technologies like AI and advanced imaging.
- Leadership often lacks formal financial analysis training for technology assessments.
- Return on Investment (ROI) analysis provides a structured method for evaluating technology's financial impact.
Purpose of the Study:
- To provide a practical toolkit for radiology leaders to conduct financial evaluations of AI and imaging technologies.
- To adapt the AHRQ framework for ROI analysis tailored to radiology.
- To guide decision-making for adopting new technologies.
Main Methods:
- The review adapts the AHRQ framework for ROI analysis in radiology.
- Key metrics discussed include ROI, cost-effectiveness analysis, incremental cost-effectiveness ratio, and net present value (NPV).
- Critical design considerations such as scope, time horizon, comparison groups, and cost/benefit identification are highlighted.
Main Results:
- An illustrative case study on AI for chest CT interpretation highlights common pitfalls.
- Pitfalls include exaggerated financial benefits and overlooked costs like IT integration and training.
- The framework promotes transparent and financially sound technology evaluations.
Conclusions:
- Radiology leaders can utilize this ROI analysis framework for more informed technology assessments.
- Systematic application of the framework leads to better financial decision-making regarding AI and imaging innovations.
- The toolkit aims to improve the financial justification and adoption of new technologies in radiology.