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Updated: Aug 5, 2026

In Vivo, Percutaneous, Needle Based, Optical Coherence Tomography of Renal Masses
Published on: March 30, 2015
Toward a Structured Imaging Reporting System for Kidney Masses: The Molecular Imaging Perspective on KI-RADS
Wonkyu P Choi1, Md Zobaer Islam2, Louis J Mazzarelli3
1The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Molecular imaging offers deeper biological insight for characterizing indeterminate renal masses, potentially enhancing the Kidney Imaging Reporting and Data System (KI-RADS) for better risk stratification.
Area of Science:
- Oncology
- Radiology
- Molecular Imaging
Background:
- The Kidney Imaging Reporting and Data System (KI-RADS) requires imaging characteristics linked to tumor biology for optimal risk stratification of indeterminate renal masses.
- Multi-parametric magnetic resonance imaging is valuable for staging and characterization, but molecular imaging offers more fundamental biological insights.
Purpose of the Study:
- To review current renal mass characterization imaging approaches.
- To discuss the evidence and potential of molecular imaging in renal mass risk stratification.
- To propose a molecular imaging-focused companion KI-RADS framework.
Main Methods:
- Review of current imaging modalities for renal mass characterization.
- Discussion of radiotracers like 99mTc-sestamibi and 89Zr-girentuximab.
- Exploration of synergy between anatomic imaging, molecular imaging, and biopsy.
Main Results:
- Molecular imaging agents (99mTc-sestamibi, 89Zr-girentuximab) show promise for risk stratification.
- Studies demonstrate strong correlations between molecular imaging findings and tumor biology.
- A proposed molecular imaging-based KI-RADS framework uses a five-point Likert scale.
Conclusions:
- Molecular imaging provides crucial biological insights for indeterminate renal masses.
- Integration of molecular imaging into KI-RADS is warranted for improved risk stratification.
- Future directions include data integration and artificial intelligence applications.
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