ArticleAbdominal radiology (New York)2023
Differentiation between renal epithelioid angiomyolipoma and clear cell renal cell carcinoma using clear cell likelihood score.
Article in Abdominal radiology (New York), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 9 citations in OpenAlex.
- Combined radiological approach for characterization of solid renal masses: a proposed strategy for integrating the RENAL nephrometry score into the clear cell likelihood score.BMC medical imaging · 2026Article
- Article
- Modified clear cell likelihood score and a new CAT score in the assessment of indeterminate small renal masses.Journal of cancer research and clinical oncology · 2026Article
- Case Report: mTOR inhibitor treatment for epithelioid angiomyolipoma harboring biallelicFrontiers in oncology · 2026Article
- Article
- Resolution of hypokalemia following nephrectomy for a presumed renal cell carcinoma revealing a large angiomyolipoma: A case report.Urology case reports · 2025Article
- Imaging characteristics of renal epithelioid angiomyolipoma and its correlation with risk stratification.Scientific reports · 2025Article
- Clear cell likelihood score may improve diagnosis and management of renal masses.Abdominal radiology (New York) · 2024Review
- Diagnostic accuracy of the Clear Cell Likelihood Score and selected MRI parameters in the characterization of indeterminate renal masses - a single-institution study.Abdominal radiology (New York) · 2024Article
- Is there enough evidence supporting the clinical adoption of clear cell likelihood score (ccLS)? An updated systematic review and meta-analysis.Insights into imaging · 2024Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
purposeClear cell likelihood score (ccLS) may be a reliable diagnostic method for distinguishing renal epithelioid angiomyolipoma (EAML) and clear cell renal cell carcinoma (ccRCC). In this study, we aim to explore the value of ccLS in differentiating EAML from ccRCC.
methodsWe performed a retrospective analysis in which 27 EAML patients and 60 ccRCC patients underwent preoperative magnetic resonance imaging (MRI) at our institution. Two radiologists trained in the ccLS algorithm scored independently and the consistency of their interpretation was evaluated. The difference of the ccLS score was compared between EAML and ccRCC in the whole study cohort and two subgroups [small renal masses (SRM; ≤ 4 cm) and large renal masses (LRM; > 4 cm)].
resultsIn total, 87 patients (59 men, 28 women; mean age, 55±11 years) with 90 renal masses (EAML: ccRCC = 1: 2) were identified. The interobserver agreement of two radiologists for the ccLS system to differentiate EAML from ccRCC was good (k = 0.71). The ccLS score in the EAML group and the ccRCC group ranged from 1 to 5 (73.3% in scores 1-2) and 2 to 5 (76.7% in scores 4-5), respectively, with statistically significant differences (P < 0.001). With the threshold value of 2, ccLS can distinguish EAML from ccRCC with the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 87.8%, 95.0%, 73.3%, 87.7%, and 88.0%, respectively. The AUC (area under the curve) was 0.913. And the distribution of the ccLS score between the two diseases was not affected by tumor size (P = 0.780).
conclusionThe ccLS can distinguish EAML from ccRCC with high accuracy and efficiency.
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