
Opinion|Videos|June 2, 2025
Early Detection of ccRCC
Panelists discuss how deep learning applied to imaging data sets may advance kidney cancer assessment, though they believe the next major leap will require true molecular imaging that reveals what tumors are expressing.
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Episodes in this series

Future Directions for Imaging in Kidney Cancer
Main Discussion Topics:
- Potential for deep learning and artificial intelligence (AI) to extract additional information from imaging data sets
- Recognition that computational approaches have limitations
- The future likely requires molecular imaging that assesses tumor expression patterns.
Key Points for Physicians:
- AI and deep learning may identify imaging features not apparent to human readers.
- Computational approaches alone may have limitations.
- Molecular imaging represents the next frontier in renal mass characterization.
Notable Insights:
Although AI approaches show promise, the experts believe the most significant advances will come from molecular imaging techniques that directly assess tumor biology.
Clinical Significance:
Combination of computational approaches and molecular imaging will likely provide the next major advance in renal mass characterization.
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