Exophytic Renal Urothelial Carcinoma Versus Renal Clear-cell Carcinoma: Clinical Data and Computed Tomography Findings

被引:0
作者
Chen Xin [1 ]
Chen Yidi [2 ]
Lei Yiwu [1 ]
Huang Fuling [1 ]
Tang Cheng [1 ]
Long Liling [1 ]
机构
[1] Guangxi Med Univ, Dept Radiol, Affiliated Hosp 1, Nanning, Guangxi, Peoples R China
[2] Sichuan Univ, West China Hosp, Dept Radiol, Chengdu, Sichuan, Peoples R China
关键词
Exophytic; urothelial carcinoma; renal clear-cell carcinoma; collecting system invasion; computed tomography; differential diagnosis; independent predictor; predictive model; URINARY COLLECTING SYSTEM; TRANSITIONAL-CELL; CT; NEPHROURETERECTOMY; INVASION; OUTCOMES; MDCT;
D O I
10.2174/1573405618666220513125457
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background: Distinguishing exophytic renal urothelial carcinoma (ERUC) from exophytic renal clear-cell carcinoma (ERCCC) with collecting system invasion may be difficult as they involve similar locations and collecting system invasion. Objective: The study aimed to characterize the clinical data and computed tomography (CT) features that can aid in differentiating ERUC from ERCCC. Methods: Data from 17 patients with ERUC and 222 patients with ERCCC were retrospectively assessed. CT and clinical features exhibiting significant differences in t-tests/Mann-Whitney U-test and chi-square tests/Fisher's exact tests were analyzed using receiver operating characteristic (ROC) curves. Variables with an area under the curve (AUC) <0.7 were excluded. Univariate logistic regression analysis was used to analyze the associations of CT and clinical features with ERUC or ERCCC. Variables with odds ratio (OR) values being close to 1 in univariate logistic regression were excluded from multivariate logistic regression. A predictive model was then constructed based on the predictors (p<0 in multivariate logistic regression). Differential diagnostic performance was assessed with AUC values. Results: Multivariate logistic regression analysis identified preserving reniform contour (OR: 45.27, 95% confidence interval [CI]: 4.982-411.39) and infiltrative growth pattern (OR: 21.741, 95% CI: 1.898-249.049) as independent predictors that can be used to distinguish ERUC from ERCCC. AUC values for preserving reniform contour, infiltrative growth pattern, and Model-1 were 0.907 (95% CI: 0.817-0.998), 0.837 (95% CI: 0.729-0.946), and 0.947 (95% CI: 0.874-1), respectively. Conclusion: The independent predictors and predictive model may play an important role in preoperative differentiation between ERUC and ERCCC.
引用
收藏
页码:1325 / 1334
页数:10
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