The independent indicators of contrast-enhanced ultrasound for predicting renal cell carcinoma

DOI: https://doi.org/10.21203/rs.2.18434/v1

Abstract

Background: The value of contrast-enhanced ultrasound (CEUS) in differentiating between renal cell carcinoma (RCC) and angiomyolipoma (AML) was analyzed. The purpose of this study was to identify the independent indicators of CEUS for predicting RCC.

Methods: A total of 172 renal tumors (150 RCCs, 22 AMLs) in 165 patients underwent conventional ultrasound (CUS) and CEUS examinations before radical or partial nephrectomy, and the features on CUS and CEUS were analyzed.

Results: There were significant differences in echogenicity, blood flow signals in color Doppler flow imaging (CDFI), peak intensity, homogeneity of enhancement, wash in, wash out, and perilesional rim-like enhancement between RCC and AML (P<0.05 for all). Multivariate analysis indicated that perilesional rim-like enhancement (P=0.035, odds ratio [OR]=9.907, 95% confidence interval [CI]: 1.169-83.971) and fast wash out (P=0.001, OR =9.755, 95%[CI]: 2.497-38.115) were independent indicators for predicting RCC. The area under the receiver operating characteristic (ROC) curve (AUC) for perilesional rim-like enhancement was 0.838 (95% CI:0.774-0.890) with 76.7% sensitivity and 90.9% specificity, while the AUC of fast wash out was 0.833 (95% CI:0.768-0.885) with 74.7% sensitivity and 81.8% specificity.

Conclusions: This study indicated that CEUS has value in differentiating RCC and AML. Present perilesional rim-like enhancement and fast wash out may be important indicators for predicting RCC.

Introduction

Renal cell carcinoma (RCC), one of the most lethal urological malignancies, originates in the renal tubular epithelium of the urinary system [1, 2]. Its incidence has been increasing year by year, and runs up to 3% of malignant tumors in human beings [3]. Renal angiomyolipoma (AML), comprising 2.0–6.4% of all renal tumors, is the most common benign mesenchymal neoplasm of the renal [4, 5]. Imaging is the most important differential diagnosis method for the both above. Up to now, the commonly used imaging diagnostic methods include ultrasound (US), computed-tomography (CT), magnetic resonance imaging (MRI), and so on. However, both CT and MRI have disadvantages of high cost, ionizing radiation, and adverse reactions induced by iodine contrast agents or gadolinium contrast agents [6]. Though CUS is a readily available, inexpensive, non-invasive, and non-ionizing imaging modality, it has limited use when attempting to differentiate between RCC and AML.

Therefore, a safe and accurate imaging modality is needed to differentiate between RCC and AML, and Contrast-enhanced ultrasound (CEUS) using microbubble-based contrast agents has garnered increasing attention in this regard. CEUS has unique advantages with its advantages of non-ionizing, real-time imaging modality, and rare and mild adverse reactions induced by contrast agents [7]. The previous studies [8, 9] have reported that CEUS might have a good ability to assess renal masses, but its diagnostic value is still controversial.

Thus, the present study aimed at analyzing the diagnostic performance of CEUS in differentiating between RCC and AML proved pathologically, and identifying the independent indicators of CEUS for predicting RCC.

Materials and methods

Patients

This single-institution retrospective study was approved by the ethical committee of Huadong hospital, and written informed consent was obtained from all patients. Between August 2012 and January 2019, 165 patients with172 renal masses were recruited for the study, included 145 patients (117 males and 33 females, age range 25–86 years, mean age 61.2±12.4 years) with 150 RCCs and 20 patients (5 males and 17 females, age range 22–75 years, mean age 55.7±16.0 years) with 22 AMLs. Inclusion criteria were as follows: 1) patients underwent CUS and CEUS before radical or partial nephrectomy; 2) renal tumor pathologically confirmed as RCC or AML; 3) sufficient normal renal tissue around mass; and 4) patient had not undergone any invasive treatments before CUS and CEUS. Exclusion criteria were 1) pure cystic mass; 2) the video clips of CEUS were incomplete; and 3) a history of cardiac failure or respiratory disorders.

 

CUS and CEUS examination

Both CUS and CEUS were performed by a single radiologist (C.L.) at our institution with 17 years of experience in abdominal US and 13 years in CEUS. The examinations were performed using an ultrasound scanner (4C1 probe, 3–5 MHz, mechanical index <0.10, Aplio500, Toshiba Medical Systems, Otawara, Japan). Initially CUS was conducted to obtain the position, shape, echogenicity, size, margins, homogeneity, and orientation of the tumor, then color Doppler flow imaging (CDFI) was used to assess the blood flow of the tumor. The depth of the renal lesions was all less than 10 cm in this study. Optimal scanning containing both mass and normal adjacent renal parenchyma was selected, and the system was then switched to contrast imaging mode using CPS technology. The US contrast agent used in this study was SonoVue (Bracco, Milan, Italy), a sulfur hexafluoride (SF6)-filled microbubble which was stabilized by phospholipids. The SonoVue freeze-dried powder was shaken with 5ml of normal saline, and a dose of 1.6–2.4ml contrast agent, which was chosen individually depending on the weight, height, and age of the patient, was administered into the antecubital vein in a bolus fashion, followed by 5-ml saline flush. The timer and video recorder were started and the contrast agent was injected simultaneously. All patients were required to maintain slow shallow breathing, and checked in real time for at least 3 minutes. If a tumor was incompletely assessed, a second injection was repeated 15 minutes after the first injection. The single images and video clips of CUS and CEUS were stored in the local hard drive for subsequent analysis.

 

Imaging interpretation and data evaluation

The images and video clips saved on the local hard drive were reviewed in random by two independent radiologists (D.X.H. and Z.J.), both blinded to the pathological results. Both radiologists had more than 10 years of experience in abdominal US and 8 years in reading CEUS images. The CUS characteristics included the mass position, shape, echogenicity, size, margins, homogeneity, orientation, and color flow signals. The CEUS characteristics included the degree of peak enhancement, the homogeneity of enhancement, the perilesional rim-like enhancement and the ‘‘wash in’’ and ‘‘wash out’’ pattern. The normal renal cortex adjacent to the tumor was used as the control for comparison of the enhancement. The degree of tumor peak enhancement was classified as hyper-, iso-, and hypo-enhancement. The homogeneity at peak enhancement was classified as homogeneous, which was defined as a lesion completely enhancing without any defects, and heterogeneous, which was defined as a lesion with unenhanced areas, regardless of various enhancement degrees. The perilesional rim-like enhancement becoming more distinct in the late phase was considered to represent the presence of a pseudocapsule, which was classified as with or without. Both the wash in and wash out of contrast in renal masses were described as fast, synchronous, or slow. The value of these features was calculated and analyzed to differentiate the diagnosis between RCC and AML. If conclusions of the two radiologists were different, they consulted with a third reviewer to reach a final conclusion by discussions.

 

Statistical analysis

Continuous variables were expressed as mean ± standard deviation (SD), and discrete variables as numbers and percentages. The Shapiro-Wilk W test was used to determine whether data was normally distributed, and the F test determine whether the variables had homogeneity of variance. Differences between RCC and AML were analyzed using Independent-Sample t test and Mann-Whitney U test for continuous variables, and Pearson’s chi-square test and Fisher’s exact tests for discrete variables. The variables that showed strong performance in basic statistics were subjected to the multivariate logistic regression analysis for predicting RCC. We calculated odds ratio (OR), 95% confidence intervals (CIs), and P value. Those variables with significant and independent influence were isolated and used to fit the receiver operating characteristic (ROC) curve determining the area under the ROC curve (AUC). We determined the optimal cut-off values for the represented indices that showed the highest AUC. The corresponding sensitivity, specificity, and AUC were calculated with 95% CIs. Statistical analysis was performed by using IBM SPSS Statistics version 22.0 for Windows (IBM Corp., Armonk, NY, USA) and MedCalc Statistics version 15.2. A P value <0.05 was considered statistically significant.

Results

Characteristics of the enrolled patients

A pathologic diagnosis was obtained for all masses via a laparoscopic or open radical or partial nephrectomy. One single mass was detected in 142 patients with RCCs and 16 patients with AMLs, and two masses were detected in the remaining 7 patients. Of the patients with two nodules, 2 had AML in each kidney, 2 had RCC in each kidney, 1had RCC in the left kidney, 1had RCC and AML in the left kidney, and 1had AML in the left kidney and RCC in the right kidney. Thus, a total of 165 patients with172 renal masses were recruited, 150 (87.2%) were RCCs and 22 (12.8%) were AMLs. The RCCs were clear cell carcinoma (129, 86.0%), papillary carcinoma (11, 7.3%), chromophobe carcinoma (10, 6.7%), respectively. Though age distribution, tumor location, and surgical method were not significantly different between RCCs and AMLs, more percentage of patients with RCC were male than that with AML (P=0.000). (Table 1)

 

CUS characteristics of renal masses

The diameter of RCCs (mean, 40.4±22.1mm; range, 7-130mm) and AMLs (mean, 34.7±22.2cm; range, 9-80mm) made no significant difference (P=0.258). (Table 2). There were also no significant differences in terms of shape, margin, orientation, and homogeneity between RCCs and AMLs. Significant differences existed in echogenicity and CDFI pattern.

 

CEUS characteristics of renal masses

CEUS characteristics of renal masses are listed in Table 3. All the indices (peak intensity, homogeneity, wash in, wash out, and perilesional rim-like enhancement) are significantly different between RCCs and AMLs (P<0.05 for all).

 

The independent indicators correlated with RCCs

Multivariate analysis was used to identify the potential indicators of RCCs. The results showed that perilesional rim-like enhancement and fast wash out were independent indicators correlated with RCCs (Table 4). Fig.1 shows the ROC curves of perilesional rim-like enhancement and fast wash out correlated with RCCs. The AUC of perilesional rim-like enhancement was 0.838 (95% CI:0.774-0.890) with 76.7% sensitivity and 90.9% specificity, while the AUC of fast wash out was 0.833 (95% CI: 0.768-0.885) with 74.7% sensitivity and 81.8% specificity (Table 5).

Discussions

RCC, the most common renal malignancy, is characterized by numerous thin-walled blood vessels with rich blood flow, and common findings include intra-tumoral necrosis, hemorrhage, and calcification [10]. AML, the most common renal benign neoplasm, contains varying proportion of thick-walled blood vessels, smooth muscle, and fat tissue [4]. Most AMLs need only active surveillance rather than invasive treatment, but for RCC, especially for clear cell RCC, surgical resection is the preferred therapy [11, 12]. Therefore, it is important to differentiate them for the prognostic evaluation and clinical treatment decision.

Compared to CT and MRI, CUS is usually the preferred choice for detecting renal lesions because it is readily available, inexpensive, noninvasive, non-ionizing, and provides images in real time [13]. However, it has limited use when attempting to differentiate between RCC and AML because of its lower accuracy in the characterization of some renal masses [14]. The current study showed that, among all the characteristics on CUS, only echogenicity allowed the differentiation of RCC and AML. To the extent known, hypoechoic renal masses are mostly considered to be malignant while hyperechoic and iso-echoic renal masses are often referred to as benign. However, hyperechoic RCCs were noted in 23 masses (15.3%) and iso-echoic RCCs were noted in 28 masses (18.7%). Four AMLs (18.2%) were hypoechoic and one (4.5%) was iso-echoic on CUS in this study. Therefore, CUS had limited ability to distinguish between RCC and AML. As for CDFI, RCC differed from AML with respect to blood flow signals (p = 0.000). However, there were 16(72.7%) AMLs and 49(32.7%) RCCs without blood flow signals in the study. Therefore, further imaging studies are needed for patients with uncharacterized renal tumors.

The previous studies have reported that CEUS imaging technology, without severe risk or discomfort, has a good ability to assess renal lesions [1517], but its diagnostic value is still controversial. Thus, the present study aimed at analyzing the diagnostic performance of CEUS in differentiating between RCC and AML proved pathologically. And our study showed that perilesional rim-like enhancement and fast wash out were independent indicators correlated with RCC.

The perilesional rim-like enhancement around the tumor was considered to represent the presence of a pseudocapsule (Fig. 2). It results from tumor growth producing compression, ischemia, and necrosis of adjacent normal parenchyma, with subsequent deposition of fibrous tissue [12, 18]. In our study, a pseudocapsule was observed on the histologic examination. And in this study, CEUS showed that more percentage of perilesional rim-like enhancement was observed in RCC than in AML (p = 0.000). The perilesional rim-like enhancement was observed in 76.7% (115/150) of RCCs, which was similar to the figures reported by Xu et al. [19] and van et al. [20]. The presence of perilesional rim-like enhancement was regard as an important predictor of RCC. Additionlly, the current study found that 2(9.1%) AMLs presented with incomplete rim-like enhancement. This might be related to the distribution of blood vessels in AML.

The wash out would be possible in arteriovenous fistulas or in normal physiological reflux through the renal vein [21]. Compared with the normal renal parenchyma, RCCs often exhibit fast wash out, while AMLs more often show slow wash out [22]. Xue et al. [23] assessed the difference of enhancement patterns among the three RCC subtypes with CEUS, their results demonstrated that most RCCs were fast wash out with the percentage of 47.5(95/200), 89.7(52/58), 76.5(39/51) for clear cell RCCs, papillary RCCs, chromophobe RCCs, respectively. Our results showed that 56.0(84/150) RCCs were fast wash out. This may be related to the higher percentage of clear cell RCCs included in this study. Sun et al. [24] reported that 26%(5/19) of AMLs were fast wash out, while, 74% lesions were confirmed by two enhanced imaging examinations including CEUS and CT/MRI. In our study, all the lesions were diagnosed via surgical pathology and only 4.5% (1/22) of AMLs were fast wash out.

Heterogeneous enhancement on CEUS correlated with the existence of hemorrhage, necrosis and cystic change [25]. Though, RCCs were manifested mostly as heterogeneous enhancement as a result of the rapid growth of the tumor and proneness to ischemic necrosis, heterogeneous enhancement was not the independent indicators for predicting RCCs in our study. This may be related to the size of the tumors included in this study. Moreover, Jiang et al. [26] Xue et al. [23] and Xu et al. [27] analyzed the CEUS characteristics of RCC in relation to tumor size. Their studies showed that heterogeneous enhancement was mainly seen in tumors > 3 cm (72.9–91%), compared to 28.2–55% in tumors ≤ 3 cm. This might because that the small tumors grow slowly and rarely have necrosis change. Though most AMLs are discovered incidentally, some AMLs can present with spontaneous hemorrhage, particularly in masses larger than 4 cm [28]. Moreover, Lu et al [29] reported that 17.6% (6/34) AMLs was heterogeneous enhancement. In this study, 22.7% (5/22) AMLs was heterogeneous enhancement (Fig. 3), and all the masses were larger than 4 cm.

The main limitation of our study is the relatively small number of AMLs (n = 22) cases, so the possibility of selection bias should be considered. Prospective studies with larger numbers of AMLs patients are required to validate our results. An additional limitation is that we restricted our analysis to RCCs and AMLs, without considering its subtypes, other benign tumors, or other malignant tumors. Further studies should be performed for the differentiation of all the above. A further limitation is that pathologic findings proven by surgical resection as an inclusive criterion exclude already characterized nonsurgical masses, such as small typical AMLs.

Conclusion

Our findings suggest that CEUS imaging features including wash out and perilesional rim-like enhancement may be important indicators for predicting RCCs. These imaging features may help to differentiate RCCs for the prognostic evaluation and clinical treatment decision.

Abbreviations

AML:Angiomyolipoma; AUC:Area under the curve; B:Regression coefficient; CDFI:Color Doppler flow imaging; CEUS:Contrast-enhanced ultrasound; CI:Confidence interval; CUS:Conventional ultrasound; OR:Odds ratio; PN:Partial nephrectomy; RCC:Renal cell carcinoma; RN:Radical nephrectomy; ROC:Receiver operating characteristic; SE:Standard error

Declarations

Acknowledgements

Not applicable.

Authors’ contributions

HC, LC and YC conceived and designed the study. LC performed the examination. JZ and XD performed analysis of images. ZZ was the main surgeon. CL performed analysis of pathology. HC and YL collected patient data. HC and LF analyzed the data and wrote the paper. LC was in charge of the final version. All authors reviewed and approved the final manuscript for publication.

Authors’ information

1Department of Ultrasound, Huadong Hospital, Fudan University, Shanghai, China.2Shanghai Key Laboratory of Clinical Geriatric Medicine, Shanghai, China.3Department of Pathology, Huadong Hospital, Fudan University, Shanghai, China.4Department of Urology, Huadong Hospital, Fudan University, Shanghai, China.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, or publication of this article.

Funding

This work was supported by grants for a 2016 Science and Technology Project of the Shanghai Municipal Health and Family Planning Commission (project no. 201640285, Chen L).

Availability of data and materials

Data is available upon request from the corresponding author.

Ethics approval and consent to participate

This single-institution retrospective study was approved by the ethical committee of Huadong hospital, and written informed consent was obtained from all patients.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References

[1] Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394-424.

[2] Capitanio U, Bensalah K, Bex A, Boorjian SA, Bray F, Coleman J, et al. Epidemiology of Renal Cell Carcinoma. Eur Urol. 2019;75(1):74-84.

[3] Chen XY, Lan M, Zhou Y, Chen WZ, Hu D, Liu JM, et al. Risk factors for bone metastasis from renal cell cancer. J Bone Oncol. 2017; 9:29-33.

[4] Hartman DS, Goldman SM, Friedman AC, Davis CJ Jr, Madewell JE, Sherman JL. Angiomyolipoma: ultrasonic-pathologic correlation. Radiology. 1981; 139(2):451-8.

[5] Esheba GS, Esheba NS. Angiomyolipoma of the kidney: Clinicopathological and immunohistochemical study. J Egypt Natl Canc Inst. 2013;25(3):125-34

[6] Chen L, Wang L, Diao X, Qian W, Fang L, Pang Y, et al. The diagnostic value of contrast-enhanced ultrasound in differentiating small renal carcinoma and angiomyolipoma. Biosci Trends. 2015; 9(4):252-58.

[7] Huang DY, Yusuf GT, Daneshi M, Husainy MA, Ramnarine R, Sellars ME, et al. Contrast-enhanced US – guided Interventions: Improving Success Rate and Avoiding Complications Using US Contrast Agents. Radiographics. 2017;37(2):652-64.

[8] Kasoji SK, Chang EH, Mullin LB, Chong WK, Rathmell WK, Dayton PA. A pilot clinical study in characterization of malignant renal-cell carcinoma subtype with contrast-enhanced ultrasound. Ultrason Imaging. 2017;39(2):126-36.

[9] Rübenthaler J, Paprottka K, Marcon J, Hameister E, Hoffmann K, Joiko N, et al. Comparison of magnetic resonance imaging (MRI) and contrast-enhanced ultrasound (CEUS) in the evaluation of unclear solid renal lesions. Clin Hemorheol Microcirc. 2016;64(4):757-63.

 [10] Jh R. Renal cell carcinoma. Curr Opin Oncol. 1992;4(3):427-34.

[11] Markić D, Krpina K, Ahel J, Španjol J, Gršković A, Štifter S, et al. Different presentations of renal cell cancer on ultrasound and computerized tomography. Urologia. 2014;81(4):228-232.

[12] Yamashita Y, Honda S, Nishiharu T, Urata J, Takahashi M. Detection of pseudocapsule of renal cell carcinoma with MR imaging and CT. AJR Am J Roentgenol. 1996;166(5):1151-5

[13] Siracusano S, Bertolotto M, Ciciliato S, Valentino M, Liguori G, Visalli F. The current role of contrast-enhanced ultrasound (CEUS) imaging in the evaluation of renal pathology. World J Urol. 2011;29(5):633-8.

[14] Oh TH, Lee YH, Seo IY. Diagnostic efficacy of contrast-enhanced ultrasound for small renal masses. Korean J Urol. 2014;55(9):587-92.

[15] Klezl P, Kaspar M, Klecka J, Richterova R, Stanc O, Burgetova A, et al. The role of contrast-enhanced pulse inversion harmonic imaging (CEUS) and contrast-enhanced computed tomography (CECT) in the preoperative diagnosis of renal lesions. Urologe A. 2018;57(2):181-90.

[16] Ziegelmüller BK, Spek A, Szabados B, Casuscelli J, Clevert DA, Staehler M. Epidemiology and diagnostic assessment of small renal masses. Urologe A. 2018;57(3):274-9.

[17] Gummadi S, Eisenbrey J R, Lyshchik A. Contrast-enhanced ultrasonography in interventional oncology. Abdom Radiol (NY). 2018;43:3166-75.

[18] Ascenti G, Gaeta M, Magno C, Mazziotti S, Blandino A, Melloni D, et al. Contrast-enhanced second-harmonic sonography in the detection of pseudocapsule in renal cell carcinoma. AJR Am J Roentgenol. 2004;182(6):1525-30.

[19] Xu ZF, Xu HX, Xie XY, Liu GJ, Zheng YL, Lu MD. Renal cell carcinoma and renal angiomyolipoma: differential diagnosis with real-time contrast-enhanced ultrasonography. J Ultrasound Med. 2010;29(5):709-17.

[20] van Oostenbrugge TJ, Runneboom W, Bekers E, Heidkamp J, Langenhuijsen JF, Veltien A, et al. MRI as a tool to assess surgical margins and pseudocapsule features directly following partial nephrectomy for small renal masses. Eur Radiol. 2019;29(2):509-16.

[21] Rübenthaler J, Reimann R, Hristova P, Staehler M, Reiser M, Clevert DA. Parametric imaging of clear cell and papillary renal cell carcinoma using contrast-enhanced ultrasound (CEUS). Clin Hemorheol and Microcirc. 2015;63(2):89-97.

[22] Kazmierski B, Deurdulian C, Tchelepi H, Grant EG. Applications of contrast-enhanced ultrasound in the kidney. Abdom Radiol. 2018;43(4):880-98.

[23] Xue LY, Lu Q, Huang BJ, Li CX, Yan LX, Wang WP. Differentiation of subtypes of renal cell carcinoma with contrast-enhanced ultrasonography. Clin Hemorheol Microcirc. 2016;63(4):361-71.

[24] Sun D, Wei C, Li Y, Lu Q, Zhang W, Hu B. Contrast-Enhanced Ultrasonography with Quantitative Analysis allows Differentiation of Renal Tumor Histotypes. Sci Rep. 2016;6:35081.

[25] Li CX, Lu Q, Huang BJ, Xue LY, Yan LX, Zheng FY, et al. Quantitative evaluation of contrast-enhanced ultrasound for differentiation of renal cell carcinoma subtypes and angiomyolipoma. Eur J Radiol. 2016;85(4):795-802.

[26] Jiang J, Chen Y, Zhou Y, Zhang H. Clear cell renal cell carcinoma: contrast-enhanced ultrasound features relation to tumor size. Eur J Radiol. 2010;73(1):162-7.

[27] Xu ZF, Xu HX, Xie XY, Liu GJ, Zheng YL, Liang JY, et al. Renal cell carcinoma: real-time contrast-enhanced ultrasound findings. Abdoml Imaging. 2010;35(6):750-6.

[28] King KG, Gulati M, Malhi H, Hwang D, Gill IS, Cheng PM, et al. Quantitative assessment of solid renal masses by contrast-enhanced ultrasound with time-intensity curves: how we do it. Abdom Imaging. 2015;40(7):2461-71.

[29] Lu Q, Xue LY, Huang BJ, Wang WP, Li CX. Histotype differentiation of hypo-echoic renal tumors on CEUS: usefulness of enhancement homogeneity and intensity. Abdom Imaging. 2015;40(6):1675-83.

Tables

Table 1. Patient clinical characteristics

Characteristics

Description

AML(n=22)

RCC(n=150)

x2 / t

P-value

Gender

Male

5(22.7)

117(78.0)

28.427

0.000b

 

Female

17(77.3)

33(22.0)

 

 

Age

mean±SD(years)

55.7±16.0

61.2±12.4

1.846

0.067a

Laterality

Left kidney

12(54.5)

79(52.7)

0.027

0.869b

 

Right kidney

10(45.5)

71(47.3)

 

 

Tumor location

Upper pole

9(40.9)

45(30.0)

1.403

0.496b

 

Middle part

5(22.7)

50(33.3)

 

 

 

Lower pole

8(36.4)

55(36.7)

 

 

Surgical methods

RN

12(54.5)

111(74.0)

3.564

0.059b

 

Nephron-sparing PN

10(45.5)

39(26.0)

 

 

AML, angiomyolipoma; RCC, renal cell carcinoma; RN, Radical nephrectomy; PN, partial nephrectomy; Values are presented as the number (%), a, Independent-Sample t-test and Mann-Whitney U test; b, Pearson’s Chi square test.

 

 

Table 2. CUS characteristics of renal masses

Characteristics

Description

AML(n=22)

RCC(n=150)

x2 / t

P-value

Size

mean±SD(mm)

34.7±22.2

40.4±22.1

1.136

0.258a

Shape

Round/Oval

20(90.9)

121(80.7)

0.757

0.384c

 

Irregular

2(9.1)

29(19.3)

 

 

Margins

Well defined

21(95.5)

114(76.0)

3.226

0.072c

 

Poorly defined

1(4.5)

36(24.0)

 

 

Orientation

Outward from the renal capsule

18(81.8)

101(67.3)

1.888

0.169b

 

Inward at the renal parenchyma

4(18.2)

49(32.7)

 

 

Echogenicity

Hyper-echoic

17(77.3)

23(15.3)

33.153

0.000b

 

Iso-echoic

1(4.5)

28(18.7)

 

 

 

Hypo-echoic

4(18.2)

99(66.0)

 

 

Homogeneity

Homogeneous

17(77.3)

97(64.7)

1.364

0.243b

 

Heterogeneous

5(22.7)

53(35.3)

 

 

Blood flow signals in CDFI

Abundant inside

1(4.5)

25(16.7)

25.451

0.000d

 

Inside and perilesional

0(0)

37(24.7)

 

 

 

Perilesional

0(0)

29(19.3)

 

 

 

Slight inside

5(22.7)

10(6.7)

 

 

 

Without

16(72.7)

49(32.7)

 

 

AML, angiomyolipoma; RCC, renal cell carcinoma; CDFI, color Doppler flow imaging; Values are presented as the number (%); a, Independent-Sample t-test and Mann-Whitney U test; b, Pearson’s Chi square test; c, Continuous Correction Chi square; d, Fisher’s exact test.

 

 

Table 3. CEUS characteristics of renal masses

Characteristics

Description

AML(n-22)

RCC(n=150)

x2

P-value

Enhancement intensity

Hyper-enhancement

4(18.2)

112(74.7)

27.175

0.000b

 

Iso-enhancement

10(45.5)

17(11.3)

 

 

 

Hypo-enhancement

8(36.4)

21(14.0)

 

 

Homogeneity

Homogeneous

17(77.3)

72(48.0)

6.584

0.010a

 

Heterogeneous

5(22.7)

78(52.0)

 

 

Wash in

Fast

2(9.1)

73(48.7)

17.642

0.000a

 

Synchronous

11(50.0)

59(39.3)

 

 

 

Slow

9(40.9)

18(12.0)

 

 

Wash out

Fast

1(4.5)

84(56.0)

34.841

0.000a

 

Synchronous

2(9.1)

30(20.0)

 

 

 

Slow

19(86.4)

36(24.0)

 

 

perilesional rim-like enhancement

Present

2(9.1)

115(76.7)

40.279

0.000a

 

Absent

20(90.9)

35(23.3)

 

 

AML, angiomyolipoma; RCC, renal cell carcinoma; Values are presented as the number (%); a, Pearson’s Chi square test; b, Fisher’s exact test.

 

 

Table 4. Multivariate analysis with variable selection for predicting RCCs

Characteristics

B

SE

OR(95%CIs)

P-value

Echogenicity

0.949

0.535

2.583(0.905-7.369)

0.076

Blood flow signals in CDFI

0.498

0.463

1.645(0.663-4.078)

0.283

Enhancement intensity

0.194

0.798

1.214(0.254-5.802)

0.808

Homogeneity

0.475

1.035

1.608(0.211-12.233)

0.646

Wash in

1.433

0.883

4.191(0.742-23.669)

0.105

Wash out

2.278

0.695

9.755(2.497-38.115)

0.001

perilesional rim-like enhancement

2.293

1.090

9.907(1.169-83.971)

0.035

RCC, renal cell carcinoma; B, regression coefficient; SE, standard error; OR (95 %CIs), odds ratio (95% confidence intervals).

 

 

Table 5. ROC analyses of the independent variables for predicting RCCs

Variables

Cut-off value

Sensitivity (%)

Specificity (%)

AUC (95%CIs)

perilesional rim-like enhancement

Present

76.7

90.9

0.838(0.774-0.890)

Wash out

Fast

74.7

81.8

0.833(0.768-0.885)

RCC, renal cell carcinoma; AUC, area under the curve; 95 % CIs, 95% confidence intervals