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Diagnostic Value of Clear Cell Likelihood Score v1.0 and v2.0 for Clear Cell Renal Cell Carcinoma: A Comparative Study1Department of Radiology, the first Medical Centre of Chinese PLA General Hospital, Beijing, China
Synopsis
Keywords: Kidney, Tumor, Small renal masses; Clear cell likelihood score; Clear cell renal cell carcinoma
ccLS provides a new tool for the diagnosis and differential diagnosis of solid renal tumors and can be used to assist radiologists in their daily diagnosis. In this study, Six radiologists were trained in the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0, respectively. The results show that although the interobserver agreement between ccLS v1.0 and ccLS v2.0 is comparable, the diagnostic performance of ccLS v2.0 in ccRCC is better than that of ccLS v1.0 and ccLS v2.0 reduces the percentage of ccRCC in 1-3 scores. This finding is helpful to improve the clinical universality of ccLS.Abstract
Introduction Small renal masses (SRMs) refer to lesions with a diameter of less than 4cm after contrast enhancement.1,2 Clear cell renal cell carcinoma (ccRCC) is the most common malignant subtype in solid SRMs (>25% approximate volume enhancement), with strong invasiveness, high metastasis risk, and poor prognosis,3-5 active intervention measures are necessary, so it is imperative to identify renal tumor pathological subtypes before operations.6-8 Clear Cell Likelihood Score (ccLS) is a 5-point scoring system based on multi-parameter magnetic resonance imaging (mp-MRI), which is extremely useful in the diagnosis and prognosis of ccRCC.9-13 In February 2022, Ivan Pedrosa et al updated Clear Cell Likelihood Score Version 2.0 (ccLS v2.0) to improve its diagnostic performance and clinical universality.14-18 The performance of ccLS v1.0 and ccLS v2.0 for the same batch of SRM patients has not been compared to date. Our study aims to compare the diagnostic performance and interobserver agreement of ccLS v1.0 and ccLS v2.0 for diagnosing ccRCC in solid SRMs.Methods In this study, clinical data and MR images of patients with pathologically confirmed solid SRMs were collected retrospectively from three academic medical centers from January 1, 2018 to December 31, 2021. Six abdominal radiologists were trained in the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0, respectively. Random-effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0, and the area under the curve (AUC) of the two scoring systems were compared using DeLong’s test. Cohen Kappa test was used to evaluate the interobserver agreement of the ccLS score, and the difference in the Cohen's Kappa was compared using the Gwet consistency coefficient.
Results In total, 691 patients (491 males, 200 females; mean age, 54±12 years) with 700 renal masses were identified. The results of the ccLS v1.0 and v2.0 suggested that the pooled accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 77.1%, 76.8%, 77.7%, 90.2%, 55.7% and 80.9%, 79.3%, 85.1%, 93.4%, 60.6%. AUC of ccLS v2.0 was superior to those of ccLS v1.0 for the diagnosis of ccRCC [0.897 (95%CI:0.223，0.768) vs 0.859 (95%CI:0.149, 0.793)], with significant differences (P＜0.01). Comparing ccLS v2.0 with ccLS v1.0, the percentage of ccRCC by the score of 1-3 has decreased from 27.1% to 17.6%, with significant differences (P＜0.001). In addition, the interobserver agreement of ccLS v1.0 and ccLS v2.0 were 0.56 and 0.60, and the differences were not statistically significant (P>0.05).
Discussion In this study, six radiologists scored 700 SRMs independently using ccLS v1.0 and ccLS v2.0. The results showed that the diagnostic performance of ccLS v2.0 was better than that of ccLS v1.0 in the diagnosis of ccRCC. The main reasons are as follows: firstly, ccLS v2.0 redefines renal tumor enhancement degree,14 as opposed to ccLS v1.0. Intense enhancement is a tumor enhancement greater than or equal to 100% renal cortex. More than 75% is considered an intense enhancement, which increases the percentage of renal tumors with intense enhancement and the score of the ccLS. Secondly, ccLS v2.0 redistributes the diagnostic weight of some parameters, highlighting the weight of microscopic fat. Some studies have shown that about 60% of ccRCC contain microscopic fat,19,20 which helps to increase the ccLS scores of SRM with microscopic fat and reduce the percentage of ccRCC in 1-3 scores (27.1% vs 17.6%, P <0.001). Finally, ccLS v2.0 weakens the segmental enhancement inversion (SEI) weight. At present, the practicability of SEI is still controversial.11,21,22 Kay et al.11 have shown that the existence of SEI on mpMRI is an independent predictor for the diagnosis of oncocytoma (OR: 16.21; 95%CI: 1.0-275.4), but the confidence interval is large (≈1), and the interobserver agreement among radiologists is moderate (κ = 0.49). In addition, SEI is present in 15% of ccRCC, so weakening the SEI imaging sign can further reduce the misdiagnosis rate and improve the diagnostic performance of ccLS in the diagnosis of ccRCC. And the diagnostic procedures of ccLS v1.0 and ccLS v2.0 are basically the same, as are the MRI sequences required for diagnosis and the imaging signs observed by radiologists, thus resulting in similar levels of interobserver agreement among radiologists.
Conclusion ccLS v2.0 provided better diagnostic performance than ccLS v1.0. ccLS v2.0 can reduce misdiagnosis and unnecessary puncture biopsies, and may be considered to support the daily diagnostic work of radiologists.
Acknowledgements
NoneReferences
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Figures
Table 1 Patient and Renal Mass Characteristics
