ArticleEuropean radiology2019
Development and prospective validation of a novel weighted quantitative scoring system aimed at predicting the pathological features of cystic renal masses.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 13 citations in OpenAlex.
- Bosniak IIF renal cysts: natural history and the impact of lesion size on progression.International urology and nephrology · 2026Observational
- Development and validation of a CT prediction model for precise stratification of renal cystic tumors: a multicenter retrospective study based on the BOSNIAK classification.European radiology · 2025Article
- Article
- Clinicopathological characteristics and typing of multilocular cystic renal neoplasm of low malignant potential.World journal of clinical cases · 2024Article
- Deep learning and radiomic feature-based blending ensemble classifier for malignancy risk prediction in cystic renal lesions.Insights into imaging · 2023Article
- Stratification of malignant renal neoplasms from cystic renal lesions using deep learning and radiomics features based on a stacking ensemble CT machine learning algorithm.Frontiers in oncology · 2022Article
- Bosniak classification of cystic renal masses, version 2019: Is it helpful to incorporate the diffusion weighted imaging characteristic of lesions into the guideline?Frontiers in oncology · 2022Article
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12 authors at 2 institutions in 1 country.
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Abstract
objectivesTo develop and prospectively validate a novel weighted quantitative scoring system based on CT findings, namely, the renal cyst index (RCI), aimed at preoperatively predicting the pathological features of cystic renal masses (CRMs).
methodsThe RCI was based on four critical features of CRMs: the cyst wall, septal, nodule, and cyst contents. These parameters were scored with 1, 2, or 3 points. Weight coefficients for these parameters were determined by the multivariable logistic regression. The odds ratio (OR) and 95% confidence interval (95% CI) were used to summarise the results. The RCI was defined as the sum of these four weight coefficients. Malignancy risk prediction models were built based on the retrospective evaluation of 441 patients. We also compared the prediction ability of the RCI with the Bosniak classification in the 441 patients and applied these novel models to 152 masses resected in our institution to prospectively validate the efficiency of the RCI.
resultsThe wall point (OR = 5.71 [95% CI = 1.734-18.808, p = 0.004, point = 2], OR = 12.665 [95% CI = 3.750-42.770, p < 0.001, point = 3]), septal point (OR = 3.325 [95% CI = 1.272-8.692, p = 0.014, point = 3]), nodule point (OR = 4.588 [95% CI = 1.429-14.729, p < 0.001, point = 2], OR = 17.032 [95% CI = 5.017-57.820, p = 0.010, point = 3]), content point (OR = 22.822 [95% CI = 1.041-495.995, p = 0.047, point = 2], OR = 2.723 [95% CI = 1.296-10.696, p = 0.015, point = 3]), and RCI (OR = 1.247 [95% CI = 1.197-1.299, p < 0.001]) were significantly associated with malignancy. Masses with an RCI < 6 were regarded as benign masses; masses with an RCI ≥ 10 were regarded as malignant masses. The malignancy risk of masses with an RCI > 6 but < 10 were determined by a nomogram. The prediction ability of the RCI was significantly superior to the Bosniak classification for Bosniak IIF and III masses (AUC: 0.912 vs. 0.753, p = 0.001). The RCI also accurately predicted the pathological features of 152 masses.
conclusionThe RCI is a reliable quantitative scoring system in predicting the malignancy risk of CRMs, and it outperformed the Bosniak classification system in some ways. KEY POINTS: • The renal cyst index (RCI) is a useful weighted quantitative classification system based on CT findings for diagnosing cystic renal masses. • The RCI outperforms the Bosniak classification system in some ways, especially for Bosniak IIF and III masses. • Masses with an RCI < 6 can be regarded as a simple cyst, while those with an RCI > 10 can be regarded as malignant masses.
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