ArticleJournal of clinical imaging science2024
Iodine quantification of renal lesions: Preliminary results using spectral-based material extraction on photon-counting CT.
Article in Journal of clinical imaging science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Understanding Photon-Counting CT: Physics, Detector Technology, and Image Reconstructions.Sensors (Basel, Switzerland) · 2026Review
- Photon-counting detector CT in oncology: a new era of cancer imaging.Insights into imaging · 2026Review
- Applications of photon-counting CT in oncologic imaging: A systematic review.World journal of radiology · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: To assess the range of quantitative iodine values in renal cysts (RC) (with a few renal neoplasms [RNs] as a comparison) to develop an expected range of values for RC that can be used in future studies for their differentiation. Material and Methods: Consecutive patients ( Results: A total of 259 renal lesions (243 RC and 16 RN) were analyzed. There were significant differences between RC and RN for all IC measures with the best-performing metrics being mean and maximum IC of the entire lesion ROI (AUC 0.912 and 0.917, respectively) but also mean and minimum IC of the most suspicious area in heterogeneous lesions (AUC 0.983 and 0.992, respectively). Most RC fell within a range of low measured iodine values although a few had higher values. Conclusion: Automated iodine quantification maps reconstructed from clinical PCCT have a high diagnostic ability to differentiate RCs and neoplasms. The data from this pilot study can be used to help establish quantitative values for clinical differentiation of renal lesions.
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