ArticleAbdominal radiology (New York)2025
Spectral CT for non-invasive evaluation of bladder cancer grade.
Article in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Clinical indicators combined with spectral CT in differentiating non-muscle-invasive bladder urothelial carcinoma from cystitis glandularis.Abdominal radiology (New York) · 2026Article
- Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives.Insights into imaging · 2026Review
- Spectral CT-derived quantitative imaging parameters combined with inflammatory markers for exploratory preoperative grading of bladder cancer.Frontiers in oncology · 2026Article
- The value of spectral CT quantitative parameters in predicting Ki-67 level in ovarian cancer.Frontiers in oncology · 2025Article
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Authors and funding
13 authors.
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Abstract
objectiveTo investigate the potential role of dual-energy spectral computer tomography (CT) quantitative parameters in the definition of bladder cancer (BCa) pathological grading.
methodsThis retrospective study evaluated the use of spectral CT imaging features for BCa. From 2021 to 2023, 63 patients with histologically-confirmed BCa diagnosis were examined at our Institution. The patients were pathologically divided, following international guidelines, into two groups: low-grade (n = 24) and high-grade urothelial carcinoma group (n = 39). The iodine concentrations (IC), the normalized iodine concentrations (NIC), and the slope of the spectrum curve (SLOPE) were calculated along with the measure of each lesion CT value on the monochromatic image from 40 to 120 keV. The diagnostic performance was assessed by Receiver operator characteristic curve (ROC) analysis.
resultsThe high-grade group showed significantly higher mean values of IC, SLOPE, and HU in 40 KeV monoenergetic images (VMI
conclusionPreliminary data shows that quantitative parameters of dual-energy spectral CT can be helpful to characterize low-grade and high-grade urothelial bladder tumors. The prediction of high-grade BCa with non-invasive methods (e.g. dlCT) can aid in early detection of muscle-invasive and worse prognostic tumors that need more aggressive and timely treatments, personalizing the management on the risk of recurrence.
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