Evaluation of contrast-enhanced ultrasound for predicting tumor grade in small (≤4 cm) clear cell renal cell carcinoma: Qualitative and quantitative analysis

Abstract

OBJECTIVE:

The study aimed to evaluate the utility of qualitative and quantitative analysis employing contrast-enhanced ultrasound (CEUS) in predicting the WHO/ISUP grade of small (≤4 cm) clear cell renal cell carcinoma (ccRCCs).

METHODS:

Patients with small ccRCCs, confirmed by histological examination, underwent preoperative CEUS and were classified into low- (grade I/II) and high-grade (grade III/IV) groups. Qualitative and quantitative assessments of CEUS were conducted and compared between the two groups. Diagnostic performance was assessed using receiver operating characteristic curves.

RESULTS:

A total of 72 patients were diagnosed with small ccRCCs, comprising 23 individuals in the high-grade group and 49 in the low-grade group. The low-grade group exhibited a significantly greater percentage of hyper-enhancement compared to the high-grade group (79.6% VS 39.1%, P < 0.05). The low-grade group showed significantly higher relative index values for peak enhancement, wash-in area under the curve, wash-in rate, wash-in perfusion index, and wash-out rate compared to the high-grade group (all P < 0.05). The AUC values for qualitative and quantitative parameters in predicting the WHO/ISUP grade of small ccRCCs ranged from 0.676 to 0.756.

CONCLUSIONS:

Both qualitative and quantitative CEUS analysis could help to distinguish the high- from low-grade small ccRCCs.

Keywords

Contrast-enhanced ultrasound WHO/ISUP grade clear cell renal cell carcinoma quantitative analysis small renal mass

1 Introduction

Advancements in medical diagnostic techniques have prompted greater detection of small (≤4 cm) renal cell carcinoma (RCC), most of which are clear cell RCC (ccRCC) [1, 2]. Most cases of small ccRCCs treated by surgery manifest as localized tumors with tumor grades I or II [3]. Moreover, the stable mortality rate associated with RCC concerns about potential over-diagnosis and overtreatment of small (≤4 cm) renal masses (SRM) [4]. The five-year cancer-specific survival (CSS) rate for incidentally detected small RCCs ranged from 95% to 100%, while patients who developed metastases (2% of small RCCs) had only a 5% to 10% CSS rate [5]. Therefore, it is imperative to have dependable risk prediction for SRM to ensure proper management. The World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade is considered one of the most reliable independent risk factors [6]. He et al. reported that a significantly higher incidence of distant metastasis among high-grade (WHO/ISUP grade III and IV) small ccRCCs compared to their low-grade (WHO/ISUP grade I and II) ones [3].

The diagnostic accuracy, safety, and impact on clinical outcomes of biopsy in SRMs continue to be a subject of debate, giving rise to questions about its effectiveness [7 –9]. The commonly employed imaging modalities for evaluating RCC are computed tomography (CT) and magnetic resonance imaging (MRI). However, the presence of ionizing radiation in CT and the nephrotoxic effect of intravenous contrast material in both CT and MRI limit their utilization in certain circumstances, such as pregnant women or patients with impaired renal function [10].

Contrast-enhanced ultrasound (CEUS) represents a reliable and cost-effective manner for the evaluation of both the size and enhancement characteristics of SRMs without subjecting patients to ionizing radiation or requiring the use of nephrotoxic contrast agents [11 –14]. CEUS offers several advantages, including a high signal-to-background ratio, pure intravascular distribution, and real-time dynamic observation during the examination [15, 16]. Comparatively to CT or MRI, these advantages of CEUS enable the improved the detection of microvessels [16]. Several studies have reported the efficacy of CEUS in classifying histological subtypes of SMRs and its usefulness in displaying microvascular perfusion patterns [17, 18]. However, there is limited literature available on the use of CEUS to discriminate between WHO/ISUP high-grade and low-grade small ccRCCs. Huang et al. reported that CEUS characteristics might assist in discriminating between WHO/ISUP grade I RCCs and grade II/III/IV RCCs [19]. Nonetheless, their study encompassed both ccRCC and papillary RCC (pRCC), which exhibit distinct biological behaviors and CEUS characteristics [17, 18]. Meng et al. concluded that CEUS features could differentiate grade III/IV from grade I/II ccRCCs [20]. However, their investigation included a diverse range of masses with varying sizes, while prior research indicated that the CEUS characteristics of ccRCCs were influenced by tumor size [21].

In this research, we aimed to evaluate the utility of qualitative and quantitative analysis employing CEUS in predicting WHO/ISUP grade of small (≤4 cm) ccRCCs.

2 Materials and methods

2.1 Patients

It was approved by our hospital’s ethics committee to conduct this retrospective study. Patients with small ccRCCs who underwent CUES between February 2021 and September 2022 were enrolled. Prior to CEUS examinations, informed consent was obtained. Inclusion criteria included: (1) 4 cm or smaller ccRCCs, (2) preoperative ultrasound (US) and CEUS performed, and (3) surgical pathology confirming ccRCC graded by WHO/IUSP. Exclusion criteria included (1) masses larger than 4 cm, (2) non-ccRCC or ccRCC with uncertain WHO/IUSP grade, and (3) inadequate contrast-enhanced video due to factors such as a fragile breath-hold. A total of 72 small ccRCCs were included.

2.2 US and CEUS examination

Two ultrasound systems, namely the Philips EPIQ 7 with probe C5-1, and Siemens ACUSON Sequoia with probe 5C1 were utilized to perform US and CEUS examinations. Initially, the US was utilized to observe the lesions’ location, position, size, echogenicity, and blood flow signal. A lesion with rich blood was selected as the target plane for CEUS. An index of 0.08 was chosen for the mechanical index. Subsequently, an intravenous injection of contrast agents (SonoVue, Bracco) with 1.6–2.4 ml was followed by a 5 ml saline flush. Patients were instructed to breathe slowly and shallowly throughout the entire procedure. Continuous observation of real-time dynamic images was conducted for a minimum of 2–3 minutes subsequent to each injection. A repeat injection might be administered if necessary following the dissipation of the contrast. The images and video recordings obtained from each fully documented US and CEUS examination were systematically archived on a dedicated hard disk to facilitate subsequent analysis and evaluation.

2.3 The US and CEUS qualitative analysis

Two radiologists (L M and W JY, with 8 and 10 years’ experience respectively) conducted a qualitative analysis of the US and CEUS features. In cases of disagreement, a group discussion with a senior radiologist (L BM, with 30 years’ experience) was held to achieve a consensus. None of the radiologists had access to any pathological data. The US imaging analysis encompassed various imaging characteristics, such as the location, position, diameter, echogenicity (relative to the parenchyma, hyperechoic, or hypoechoic), and blood flow signal. Several qualitative characteristics of CEUS were evaluated: (1) The speed of wash-in during the cortical phase of CEUS was categorized as fast and slow based on the different arrival time of contrast agents within tumors relative to that in the adjacent renal cortex; (2) Similarly, the speed of wash-out during the parenchymal phase of CEUS was classified into fast and slow; (3) The degree of enhancement (non-hyper- or hyper-enhancement) compared to the adjacent renal parenchyma; (4) Homogeneous enhancement (with or without), whether there was no enhancement area within the mass during CEUS; and (5) A pseudocapsule was an enhanced rim of surrounding mass (Figs. 1 and 2).

Fig. 1

US and CEUS images of low-grade (grade II) tumor in a 56-year-old woman. (A) Conventional US showed a hyperechoic solid mass with blood flow signal, measuring about 3.96×3.70 cm in size; (B) It showed homogeneous hyper-enhancement; (C) The pseudocapsule was present in this mass (arrow); (D) The mass showed fast wash-out; (E) The green and yellow circles enclose the enhancement of the tumor and the adjacent normal renal parenchyma, respectively. The red rectangular box enclosed both of them; (F) The time-intensity curves of tumor (green) and normal renal parenchyma (yellow): the TIC of tumors showed a higher peak, larger AUC values and steeper ascending and descending branch relative to the normal renal parenchyma.

Fig. 2

US and CEUS images of high-grade (grade IV) tumor in a 67-year-old woman. (A) Conventional US showed a hypoechoic solid mass with blood flow signal, measuring about 3.60×3.50 cm in size; (B) The mass showed slow wash-in; (C) It showed homogeneous hypo-enhancement, without pseudocapsule; (D) The mass showed fast wash-out; (E) The green and yellow circles enclose the enhancement of the tumor and the adjacent normal renal parenchyma, respectively. The red rectangular box enclosed both of them; (F) The time-intensity curves of tumor (green) and normal renal parenchyma (yellow): the TIC of tumors showed a lower peak, smaller AUC values, and flat ascending and descending branch relative to the normal renal parenchyma.

2.4 Quantitative analysis of CEUS

Quantitative analysis was conducted by a third radiologist (Q HL, with 4 years of experience). The analysis utilized VueBox^® software to examine contrast video data. Three regions of interest (ROI) were drawn, including a delimitation ROI encompassing the mass and its surrounding tissue, a tumor ROI (ROI_tumor) containing the area with the highest level of enhancement within the mass while avoiding large blood vessels and necrotic areas, and a reference ROI (ROI_reference) containing the adjacent normal renal cortex at the same depth with tumor (Figs. 1E and 2E). The reduction of respiratory motion artifacts was achieved by using motion compensation. Time-intensity curves (TICs) were created from ROIs by the software, as well as various parameters of perfusion were calculated, including PE (peak enhancement), WiAUC (wash-in area under the curve), WiR (wash-in rate), WiPI (wash-in perfusion index), WoAUC (wash-out area under the curve), WiWoAUC (wash-in and wash-out area under the curve), WoR (wash-out rate), RT (rise time), mTTI (mean transit time local), TTP (time to peak), and FT (fall time). PE, WiAUC, WiR, WiPI, WoAUC, WiWoAUC, and WoR may be influenced by factors such as mass depth, contrast dose, and equipment variability. To mitigate these technical and individual variances, the relative percentage index was computed using the formula Δ= (ROI_tumor - ROI_reference) / ROI_reference. The parameters of RT, mTTI, TTP, and FT were calculated using the formula Δ= ROI_tumor - ROI_reference.

2.5 Statistics

We checked the normal distribution of the data using the Shapiro-Wilk test. Data with a normal distribution were presented as mean±standard deviation, while non-normally distributed data were reported as median (interquartile range). Qualitative data were presented in frequency (percentage). To compare quantitative and qualitative data, we used the Wilcoxon or t-Student and χ² or Fisher’s exact test as appropriate. To determine sensitivity, specificity, and area under the curve (AUC), the receiver operating characteristic curve (ROC) analysis was undertaken. Statistical significance was defined as a p-value<0.05. Analyses were conducted using R (version 4.2.1).

3 Results

3.1 Characteristics of patients and US features

There were a total of 72 patients with small ccRCCs enrolled in this study. Out of these, 49 patients were grouped into a low-grade group (WHO/ISUP: 3 grade I and 46 grade II), while 23 patients were group into a high-grade group (WHO/ISUP: 21 grade III and 2 grade IV). Table 1 summarizes the characteristics of patients as well as US features. Gender, age, diameter, location, position, echogenicity, and blood flow signals did not exhibit significant differences between the two groups (all P > 0.05).

Table 1
Patient demographics and conventional ultrasound features

High-grade Low-grade P

N = 23 N = 49

Gender: 1.000

Female 7 (30.4%) 16 (32.7%)

Male 16 (69.6%) 33 (67.3%)

Age (y) 53.0 (12.1) 51.8 (13.4) 0.704

Size (cm) 3.50 (3.00, 3.80) 3.00 (2.50, 3.80) 0.200

1.000

0–2 cm 3 (13.0%) 8 (16.3%)

2–4 cm 20 (87.0%) 41 (83.7%)

Position: 0.129

Left 8 (34.8%) 28 (57.1%)

Right 15 (65.2%) 21 (42.9%)

Location: 0.335

Down 8 (34.8%) 21 (42.9%)

middle 6 (26.1%) 17 (34.7%)

Up 9 (39.1%) 11 (22.4%)

Echo:

Hyperecho 15 (65.2%) 26 (53.1%) 0.474

Hypoecho 8 (34.8%) 23 (46.9%)

Blood flow signals 0.704

Without 3 (13.0%) 5 (10.2%)

With 20 (87.0%) 44 (89.8%)

	High-grade	Low-grade	P
Gender:			1.000
Female	7 (30.4%)	16 (32.7%)
Male	16 (69.6%)	33 (67.3%)
Age (y)	53.0 (12.1)	51.8 (13.4)	0.704
Size (cm)	3.50 (3.00, 3.80)	3.00 (2.50, 3.80)	0.200
			1.000
0–2 cm	3 (13.0%)	8 (16.3%)
2–4 cm	20 (87.0%)	41 (83.7%)
Position:			0.129
Left	8 (34.8%)	28 (57.1%)
Right	15 (65.2%)	21 (42.9%)
Location:			0.335
Down	8 (34.8%)	21 (42.9%)
middle	6 (26.1%)	17 (34.7%)
Up	9 (39.1%)	11 (22.4%)
Echo:
Hyperecho	15 (65.2%)	26 (53.1%)	0.474
Hypoecho	8 (34.8%)	23 (46.9%)
Blood flow signals			0.704
Without	3 (13.0%)	5 (10.2%)
With	20 (87.0%)	44 (89.8%)

3.2 Qualitative analysis with CEUS

The percentage of hyper-enhancement in the low-grade small ccRCCs was significantly higher than that in high-grade ones (79.6% VS 39.1%, P < 0.05). Although the low-grade group exhibited a greater proportion of homogeneous enhancement, presence of pseudocapsule, fast wash-in, and slow wash-out patterns in comparison to the high-grade group, statistical analysis denoted that these differences did not reach significance (all P > 0.05, as shown in Table 2). The ROC analysis indicated that the degree of enhancement could differentiate high-grade small ccRCCs from low-grade ones, showing an AUC of 0.702, a sensitivity of 60.9%, and a specificity of 79.6%.

Table 2
The qualitative CEUS analysis for small ccRCCs

High-grade Low-grade P

N = 23 N = 49

Enhancement 0.002

Hyper 9 (39.1%) 39 (79.6%)

Non-hyper 14 (60.9%) 10 (20.4%)

Homogeneity: 0.321

No 13 (56.5%) 20 (40.8%)

Yes 10 (43.5%) 29 (59.2%)

Pseudocapsule: 0.249

Absent 12 (52.2%) 17 (34.7%)

Present 11 (47.8%) 32 (65.3%)

Wash-in: 0.078

Fast 19 (82.6%) 47 (95.9%)

Slow 4 (17.4%) 2 (4.1%)

Wash-out: 0.175

Fast 15 (65.2%) 22 (44.9%)

Slow 8 (34.8%) 27 (55.1%)

	High-grade	Low-grade	P
Enhancement			0.002
Hyper	9 (39.1%)	39 (79.6%)
Non-hyper	14 (60.9%)	10 (20.4%)
Homogeneity:			0.321
No	13 (56.5%)	20 (40.8%)
Yes	10 (43.5%)	29 (59.2%)
Pseudocapsule:			0.249
Absent	12 (52.2%)	17 (34.7%)
Present	11 (47.8%)	32 (65.3%)
Wash-in:			0.078
Fast	19 (82.6%)	47 (95.9%)
Slow	4 (17.4%)	2 (4.1%)
Wash-out:			0.175
Fast	15 (65.2%)	22 (44.9%)
Slow	8 (34.8%)	27 (55.1%)

3.3 Quantitative analysis with CEUS

Table 3 summarizes the results of quantitative analysis for small ccRCCs of different WHO/IUSP grades. Significant differences were found between the two groups in ΔPE, ΔWiPI, ΔWiAUC, ΔWoR, and ΔWiR (all P < 0.05), with higher values observed in the low-grade small ccRCCs. While the low-grade small ccRCCs showed higher in the ΔWoAUC and ΔWiWoAUC, these differences were not statistical difference (all P > 0.05). There was also no statistical difference in ΔRT, ΔTTP, ΔFT, and ΔmTTI (all P > 0.05). Regarding the ROC analysis, the ΔWiPI displayed a good classification performance, achieving an AUC of 0.756. Furthermore, it exhibited a sensitivity of 78.3% and specificity of 71.4% (as detailed in Table 4).

Table 3
The quantitative CEUS Analysis for small ccRCCs

High-grade Low-grade P

N = 23 N = 49

ΔPE 0.28 (–0.16, 0.62) 0.98 (0.41, 2.21) 0.001

ΔWiAUC 0.00 (–0.22, 0.82) 0.64 (0.22, 1.64) 0.017

ΔWiR 0.23 (–0.22, 1.04) 1.76 (0.45, 3.17) 0.001

ΔWiPI 0.34 (–0.15, 0.57) 1.05 (0.43, 2.18) <0.001

ΔWoAUC 0.07 (–0.42, 1.00) 0.54 (–0.06, 1.42) 0.170

ΔWoR 0.33 (–0.24, 2.11) 1.85 (0.31, 3.56) 0.006

ΔWiWoAUC 0.04 (–0.34, 1.02) 0.53 (0.03, 1.44) 0.099

ΔRT 0.34 (–3.35, 1.44) –0.81 (–4.84, 0.30) 0.274

ΔmTTl –4.69 (49.5) –17.38 (42.8) 0.297

ΔTTP –0.56 (–1.88, 1.56) –0.13 (–2.66, 0.72) 0.928

ΔFT 0.36 (–9.53, 5.59) –1.89 (–10.89, 0.66) 0.296

	High-grade	Low-grade	P
ΔPE	0.28 (–0.16, 0.62)	0.98 (0.41, 2.21)	0.001
ΔWiAUC	0.00 (–0.22, 0.82)	0.64 (0.22, 1.64)	0.017
ΔWiR	0.23 (–0.22, 1.04)	1.76 (0.45, 3.17)	0.001
ΔWiPI	0.34 (–0.15, 0.57)	1.05 (0.43, 2.18)	<0.001
ΔWoAUC	0.07 (–0.42, 1.00)	0.54 (–0.06, 1.42)	0.170
ΔWoR	0.33 (–0.24, 2.11)	1.85 (0.31, 3.56)	0.006
ΔWiWoAUC	0.04 (–0.34, 1.02)	0.53 (0.03, 1.44)	0.099
ΔRT	0.34 (–3.35, 1.44)	–0.81 (–4.84, 0.30)	0.274
ΔmTTl	–4.69 (49.5)	–17.38 (42.8)	0.297
ΔTTP	–0.56 (–1.88, 1.56)	–0.13 (–2.66, 0.72)	0.928
ΔFT	0.36 (–9.53, 5.59)	–1.89 (–10.89, 0.66)	0.296

PE: peak enhancement; WiAUC: wash-in area under the curve; WiR: wash-in rate; WiPI: wash-in perfusion index; WoAUC: wash-out area under the curve; WiWoAUC: wash-in and wash-out area under the curve; WoR: wash-out rate; RT: rise time; mTTl: mean transit time local; TTP: time to peak; FT: fall time.

Table 4

Performance of CEUS for distinguishing high- and low-grade small ccRCCs

Parameters	AUC (95% CI)	Sensitivity (%)	Specificity (%)
Enhancement	0.702 (0.586, 0.819)	60.9	79.6
ΔwiPI	0.756 (0.635, 0.877)	78.3	71.4
ΔPE	0.752 (0.633, 0.872)	78.3	69.4
ΔWoR	0.702 (0.576, 0.828)	87.0	46.9
ΔWiR	0.734 (0.615, 0.852)	91.3	51.0
ΔWiAUC	0.676 (0.533, 0.820)	52.2	87.8

PE: peak enhancement; WiAUC: wash-in area under the curve; WiR: wash-in rate; WiPI: wash-in perfusion index; WoR: wash-out rate; CI: confidence interval; AUC: area under the curve.

4 Discussion

Accurate preoperative diagnosis of SRM represents both a critical focus and a significant challenge in clinical research. Dual Source CT, with a sensitivity of 80–99% and specificity of 79–92%, is preferred for SRM as it provides additional information and enhances precision through advanced post-processing techniques, but it involves ionizing radiation and contrast agent side effects [22]. Diffusion MRI offers excellent soft tissue contrast and characterize microstructural changes in tissues with no ionizing radiation (sensitivity 74–90%, specificity 78–88%) but has longer scan times and motion artifacts [23 –26]. The utility of [18F]fluorodeoxyglucose-positron emission tomography CT (PET-CT) in identifying SRM remains to be determined, as it is typically employed for characterizing local recurrent and metastases [1, 27]. CEUS, with a sensitivity of 95–100% and specificity of 37–81%, stands out for its safety, avoiding ionizing radiation and contrast agents sides, and providing real-time imaging [11–17 , 29]. Despite being operator-dependent and having limited penetration depth, CEUS offers significant advantages in safety and immediate imaging, making it valuable for patient-specific scenarios and complementing other modalities to enhance diagnostic accuracy (Table 5).

Table 5
Comparative efficacy of imaging modalities for differentiating small malignant renal tumors

Modality Sensitivity (%) Specificity (%) Advantages Limitations

Dual source CT 80–99 79–92 Provides additional information through advanced post-processing techniques Ionizing radiation, iodinated contrast agent side effects

Diffusion MRI 74–90 78–88 Good soft tissue contrast, characterize microstructural changes in tissues Longer scan times, motion artifacts

PET CT Undetermined Undetermined Functional imaging, good for detecting local recurrent and metastases Expensive, involves ionizing radiation

CEUS 95–100 37–81 High signal-to-background ratio, pure intravascular distribution and real-time imaging Operator dependent, limited penetration depth

Modality	Sensitivity (%)	Specificity (%)	Advantages	Limitations
Dual source CT	80–99	79–92	Provides additional information through advanced post-processing techniques	Ionizing radiation, iodinated contrast agent side effects
Diffusion MRI	74–90	78–88	Good soft tissue contrast, characterize microstructural changes in tissues	Longer scan times, motion artifacts
PET CT	Undetermined	Undetermined	Functional imaging, good for detecting local recurrent and metastases	Expensive, involves ionizing radiation
CEUS	95–100	37–81	High signal-to-background ratio, pure intravascular distribution and real-time imaging	Operator dependent, limited penetration depth

The outcomes worsened as the WHO/ISUP grade of ccRCCs increased from I to IV [30]. Preoperative prediction of nuclear grade can be clinically valuable, especially in cases involving small ccRCC. In the current study, both qualitative and quantitative CEUS characteristics of 72 small ccRCCs were evaluated to determine whether CEUS could aid in distinguishing between high- and low-grade tumors. In qualitative analysis, it was observed that low-grade small ccRCCs exhibited a significantly higher proportion of hyperenhancement compared to high-grade ones. And in quantitative analysis, the values of ΔPE, ΔWiAUC, ΔWiPI, ΔWiR, and ΔWoR were also significantly higher in the low-grade tumors. The AUC values for these parameters in predicting the WHO/ISUP grade of small ccRCCs ranged from 0.676 to 0.756.

Identifying the CEUS patterns of different renal masses aids in the accurate diagnosis and management of conditions such as abscesses, tuberculosis, infarction, and other related disorders (Table 6). Abscesses typically exhibit non-enhanced central part with hyperenhancement capsule. Renal tuberculosis presents with heterogeneous enhancement, necrosis, and lobar pattern of calcification [31 –33]. Post-infarction inflammation is marked by wedge-shaped, non-enhancement areas within an otherwise normal-appearing kidney [31]. CcRCC usually shows hyper/iso-enhancement with fast wash-in, while non-ccRCC presents hypo-enhancement with slow wash-in [34, 35]. Metastatic kidney lesions generally demonstrate hypo-enhancement throughout the imaging process [36, 37]. Angiomyolipoma show hyperenhancement without a pseudocapsule sign [17]. Oncocytomas present homogeneous hyperenhancement without a pseudocapsule sign [38].

Table 6

Characteristic CEUS for differentiating renal lesions

Renal lesions	Characteristic CEUS
Abscess	Non-enhanced central part with hyperenhanced capsule
Renal tuberculosis	Heterogeneous enhancement, necrosis, and lobar pattern of calcification
Post-infarction inflammation	Wedge-shaped, non-enhanced areas within an otherwise normal-appearing kidney
CcRCC	Hyper/iso-enhancement with fast wash-in
Non-ccRCC	Hypo-enhancement with slow wash-in
Metastatic lesions	Hypo-enhancement throughout the imaging process
Angiomyolipoma	Hyper-enhancement without a pseudocapsule sign
Oncocytoma	Homogeneous hyperenhancement without a pseudocapsule sign

A hallmark of ccRCC is the presence of a dense neovascular network surrounding the cancer cells, as well as abundant neovascularization. Based on a meta-analysis of 289 small ccRCCs from 10 studies, 69.2% of small ccRCCs exhibited hyper-enhancement, which was consistent with the findings of our study [30]. The degree of enhancement serves as an indicator of the tumor’s blood supply status. Our study had a higher percentage of hyper-enhancement in the low-grade group, which conflicted with a previous study conducted by Huang et al. [19]. The study found that 72% of low-grade tumors were non-hyper-enhanced, while 59.6% of high-grade tumors were hyper-enhanced [19]. The possible explanation for this disparity lies in the fact their study included both ccRCC and pRCC, and categorized grade I into the low- and grade II/III/IV into the high-grade group. Despite the application of WHO/ISUP grading to both tumor types, they exhibit distinct tumor micro-vessel structures and enhancement patterns [17 , 37]. Specifically, the CEUS characteristics of pRCCs often demonstrate hypo-enhancement due to the presence of small micro-vessels and the absence of large vascular or artier-venous fistulas. Conversely, ccRCCs typically exhibits hyper-enhancement due to their characteristics of abundant, aberrant shape, malformed, discontinuous vessels, along with arteriovenous fistulas.

Meng et al. previously reported that low-grade ccRCCs demonstrated a higher percentage of pseudocapsule compared to high-grade ones (58.9% VS 36.7%, P < 0.05). Our study observed a similar trend, but the differences did not reach statistical significance (65.3% VS 47.8%, P = 0.249) [20]. These variations may be partially attributed to differences in tumor sizes. The occurrence of the pseudocapsule was directly associated with the mass size, being significantly more prevalent in ccRCC measuring between 2–5 cm, in comparison to those smaller or larger than 5 cm [17, 21]. According to the results of our study, no significant difference was discovered between the low- and high-grade small ccRCCs concerning lesion size (3.0 cm VS 3.5 cm, P = 0.2). Furthermore, there was also no significant significance observed regarding the proportion of tumors measuring between 0–2 cm and 2–4 cm in diameter (83.7% VS 87.0%, P = 1.00).

The present study identified significant differences in several parameters between low-grade and high-grade tumors. Specifically, ΔPE, ΔWiAUC, ΔWiPI, ΔWiR, and ΔWoR were notably higher in low-grade tumors, while other parameters, including ΔWoAUC, ΔWiWoAUC, ΔRT, ΔTTP, ΔFT, and ΔmTTI, did not exhibit significant differences. In comparison to the high-grade small ccRCCs, the TIC of the low-grade ones showed a higher peak, larger AUC values, and steeper ascending and descending branches relative to the adjacent renal parenchyma (Figs. 1F and 2F). These findings suggest increased concentration and velocity of contrast agents in low-grade small ccRCCs, indicative of higher blood volumes and faster perfusion and washout rates. This was concordant with previous study by Meng et al. [20]. Similar observations were also found on contrast-enhanced CT. Zhang et al. noted increased normalized iodine concentrations in grade I/II ccRCCs compared to those of grade III/IV [39]. The nuclear grade of ccRCC has been linked to the density and structure of the microvasculature. It reported that high-grade ccRCC exhibited higher microvessels density and microvessels area than low-grade ccRCC [40]. Furthermore, low-grade ccRCCs tended to have fewer undifferentiated vessels compared to high-grade ones [20, 41]. Tumor perfusion, on the other hand, was mainly provided by mature vessels and luminal vessels [42]. The observed relationship between tumor grade and peak enhancement, as well as the differences in wash-in/out rates, could possibly be due to variations in tumor vascularization.

While both qualitative and quantitative perfusion features consistently indicated faster rates in low-grade tumors, statistical significance was observed only in quantitative analysis, with no significant difference found in qualitative analysis. Quantitative analysis offered some advantages, including the provision of precise numerical data, reduction of operator dependency, and enhancement of result reproducibility and reliability [43 –45]. This approach enabled accurate measurement and analysis of tissue microvascularization, unveiling differences that might not be apparent through qualitative analysis.

This study had some limitations. Firstly, being a retrospective study, it may have some selection bias. Therefore, further prospective studies are warranted to validate our findings. Secondly, there were few WHO/ISUP grade I and IV small ccRCCs. Finally, the lack of prognostic follow-up in our study is attributed to the fact that our cases were collected within a relatively short period of time following treatment.

5 Conclusion

Both qualitative and quantitative features of CEUS demonstrated potential in differentiating high- and low-grade small ccRCCs.

Footnotes

Acknowledgments

This work was financially supported by Department of Science and Technology of Guangdong Province (Grant number 2020B1515120098) and National natural Science Foundation of China (Grant number 2020YFC0122104).

References

Sanchez

, Feldman

, Hakimi

. Current management of small renal masses, including patient selection, renal tumor biopsy, active surveillance, and thermal ablation. J Clin Oncol. 2018;36(36):3591–600.

Nguyen

, Gill

, Ellison

. The evolving presentation of renal carcinoma in the United States: trends from the Surveillance, Epidemiology, and End Results program. J Urol. 2006;176(6 Pt 1):2397–400, 2400.

, Liu

, Tian

, Li

, Xu

, Xiao

, et al. Predictive Factors Affecting Metastasis of Small Renal Mass and Its Prognostic Analysis. Clin Med Insights Oncol. 2022;16:1363196285.

Znaor

, Lortet-Tieulent

, Laversanne

, Jemal

, Bray

. International variations and trends in renal cell carcinoma incidence and mortality. Eur Urol. 2015;67(3):519–30.

Umbreit

, Shimko

, Childs

, Lohse

, Cheville

, Leibovich

, et al. Metastatic potential of a renal mass according to original tumour size at presentation. Bju Int. 2012;109(2):190–4, 194.

Delahunt

, Eble

, Egevad

, Samaratunga

. Grading of renal cell carcinoma. Histopathology. 2019;74(1):4–17.

Lebret

, Poulain

, Molinie

, Herve

, Denoux

, Guth

, et al. Percutaneous core biopsy for renal masses: indications, accuracy and results. J Urol. 2007;178(4 Pt 1):1184–8, 1188.

Leveridge

, Finelli

, Kachura

, Evans

, Chung

, Shiff

, et al. Outcomes of small renal mass needle core biopsy, nondiagnostic percutaneous biopsy, and the role of repeat biopsy. Eur Urol. 2011;60(3):578–84.

Halverson

, Kunju

, Bhalla

, Gadzinski

, Alderman

, Miller

, et al. Accuracy of determining small renal mass management with risk stratified biopsies: confirmation by final pathology. J Urol. 2013;189(2):441–6.

10.

Roussel

, Capitanio

, Kutikov

, Oosterwijk

, Pedrosa

, Rowe

, et al. Novel Imaging Methods for Renal Mass Characterization: A Collaborative Review. Eur Urol. 2022;81(5):476–88.

11.

Liu

, Gong

, Chen

, Yuan

, Hu

. Clinical Application Value of Contrast-Enhanced Ultrasound in the Diagnosis of Renal Space-Occupying Lesions. Int J Nephrol Renovasc Dis. 2023;16:253–9.

12.

Das

, Agarwal

, Sharma

, Seth

. Role of Contrast-Enhanced Ultrasound in Evaluation of Cystic Renal Mass. J Ultrasound Med. 2023;42(12):2873–81.

13.

Jung

, Stroszczynski

, Jung

. Advanced multimodal imaging of solid thyroid lesions with artificial intelligence-optimized B-mode, elastography, and contrast-enhanced ultrasonography parametric and with perfusion imaging: Initial results. Clin Hemorheol Microcirc. 2023;84(2):227–36.

14.

Sidhu

, Cantisani

, Dietrich

, Gilja

, Saftoiu

, Bartels

, et al. The EFSUMB Guidelines and Recommendations for the Clinical Practice of Contrast-Enhanced Ultrasound (CEUS) in Non-Hepatic Applications: Update 2017 (Long Version). Ultraschall Med. 2018;39(2):e2–44.

15.

Ren

, Zhao

, Xiao

, Li

, Zhang

, Zhu

, et al. Contrast-enhanced ultrasound in evaluating the severity of acute kidney injury: An animal experimental study. Clin Hemorheol Microcirc. 2023;85(4):447–58.

16.

Putz

, Erlmeier

, Wiesinger

, Verloh

, Stroszczynski

, Banas

, et al. Contrast-enhanced ultrasound (CEUS) in renal imaging at an interdisciplinary ultrasound centre: Possibilities of dynamic microvascularisation and perfusion. Clin Hemorheol Microcirc. 2017;66(4):293–302.

17.

, Gao

, Xiang

, Mao

, Jiang

. Diagnostic Value of Qualitative and Quantitative Contrast-Enhanced Ultrasound for Pathological Subtypes of Small Solid Renal Masses. J Ultrasound Med. 2023.

18.

Liu

, Cao

, Chen

, Fang

, Liu

, Zhan

, et al. The quantitative evaluation of contrast-enhanced ultrasound in the differentiation of small renal cell carcinoma subtypes and angiomyolipoma. Quant Imaging Med Surg. 2022;12(1):106–18.

19.

Huang

, Nie

, Zhu

, Liu

, Wang

. Diagnostic Value of Contrast-Enhanced Ultrasound Features for WHO/ISUP Grading in Renal Cell Carcinoma. J Ultrasound Med. 2023.

20.

Meng

, Yang

, Zhao

, Sun

, Wang

. Associations between tumor grade, contrast-enhanced ultrasound features, and microvascular density in patients with clear cell renal cell carcinoma: a retrospective study. Quant Imaging Med Surg. 2022;12(3):1882–92.

21.

Jiang

, Chen

, Zhou

, Zhang

. Clear cell renal cell carcinoma: contrast-enhanced ultrasound features relation to tumor size. Eur J Radiol. 2010;73(1):162–7.

22.

Patel

, Bibbey

, Choudhury

, Leder

, Nelson

, Marin

. Characterization of Small (<4cm) Focal Renal Lesions: Diagnostic Accuracy of Spectral Analysis Using Single-Phase Contrast-Enhanced Dual-Energy CT. AJR Am J Roentgenol. 2017;209(4):815–25.

23.

Ludwig

, Ballard

, Shetty

, Siegel

, Yano

. Apparent Diffusion Coefficient Distinguishes Malignancy in T1-Hyperintense Small Renal Masses. AJR Am J Roentgenol. 2020;214(1):114–21.

24.

, Li

, Zhu

, Hu

, Li

, Xia

, et al. Whole-Tumor Quantitative Apparent Diffusion Coefficient Histogram and Texture Analysis to Differentiation of Minimal Fat Angiomyolipoma from Clear Cell Renal Cell Carcinoma. Acad Radiol. 2019;26(5):632–9.

25.

Park

, Kim

. Small (<4cm) Renal Tumors With Predominantly Low Signal Intensity on T2-Weighted Images: Differentiation of Minimal-Fat Angiomyolipoma From Renal Cell Carcinoma. AJR Am J Roentgenol. 2017;208(1):124–30.

26.

Mytsyk

, Dutka

, Yuriy

, Maksymovych

, Caprnda

, Gazdikova

, et al. Differential diagnosis of the small renal masses: role of the apparent diffusion coefficient of the diffusion-weighted MRI. Int Urol Nephrol. 2018;50(2):197–204.

27.

Singhal

, Singh

, Parida

, Agrawal

. Role of PSMA-targeted PET-CT in renal cell carcinoma: a systematic review and meta-analysis. Ann Nucl Med. 2024;38(3):176–87.

28.

Cao

, Fang

, Chen

, Zhan

, Diao

, Liu

, et al. The Value of Contrast-Enhanced Ultrasound in Diagnosing Small Renal Cell Carcinoma Subtypes and Angiomyolipoma. J Ultrasound Med. 2022;41(6):1415–23.

29.

Liu

, Cao

, Chen

, Fang

, Liu

, Zhan

, et al. The quantitative evaluation of contrast-enhanced ultrasound in the differentiation of small renal cell carcinoma subtypes and angiomyolipoma. Quant Imaging Med Surg. 2022;12(1):106–18.

30.

Dagher

, Delahunt

, Rioux-Leclercq

, Egevad

, Srigley

, Coughlin

, et al. Clear cell renal cell carcinoma: validation of World Health Organization/International Society of Urological Pathology grading. Histopathology. 2017;71(6):918–25.

31.

Fernandez

, Sebastia

, Pano

, Corominas

, Vas

, Garcia-Roch

, et al. Contrast-enhanced US in Renal Transplant Complications: Overview and Imaging Features. Radiographics. 2024;44(6):e230182.

32.

Psenicny

, Glusic

, Pokorn

, Kljucevsek

. Contrast-enhanced ultrasound in detection and follow-up of focal renal infections in children. Br J Radiol. 2022;95(1140):20220290.

33.

Moller

, Lowe

, Jenssen

, Chaubal

, Gottschall

, Misselwitz

, et al. Comments and Illustrations of Ultrasound Findings in Extrapulmonary Tuberculosis Manifestations. Diagnostics (Basel). 2024;14(7).

34.

Furrer

, Spycher

, Buttiker

, Gross

, Bosshard

, Thalmann

, et al. Comparison of the Diagnostic Performance of Contrast-enhanced Ultrasound with That of Contrast-enhanced Computed Tomography and Contrast-enhanced Magnetic Resonance Imaging in the Evaluation of Renal Masses: A Systematic Review and Meta-analysis. Eur Urol Oncol. 2020;3(4):464–73.

35.

Wei

, Tian

, Xia

, Huang

, Zhang

, Xia

, et al. Contrast-enhanced ultrasound findings of adult renal cell carcinoma associated with Xp11.2 translocation/TFE3 gene fusion: comparison with clear cell renal cell carcinoma and papillary renal cell carcinoma. Cancer Imaging. 2019;20(1):1.

36.

Marschner

, Ruebenthaler

, Schwarze

, Negrao

DFG

, Zhang

, Clevert

. Comparison of computed tomography (CT), magnetic resonance imaging (MRI) and contrast-enhanced ultrasound (CEUS) in the evaluation of unclear renal lesions. Rofo. 2020;192(11):1053–9.

37.

Rubenthaler

, Negrao

DFG

, Mueller-Peltzer

, Clevert

. Evaluation of renal lesions using contrast-enhanced ultrasound (CEUS); a 10-year retrospective European single-centre analysis. Eur Radiol. 2018;28(11):4542–9.

38.

Tufano

, Leonardo

, Di Bella

, Lucarelli

, Dolcetti

, Dipinto

, et al. Qualitative Assessment of Contrast-Enhanced Ultrasound in Differentiating Clear Cell Renal Cell Carcinoma and Oncocytoma. J Clin Med. 2023;12(9).

39.

Zhang

, Zhang

, Xu

, Bai

, Zhang

, Chen

, et al. Prediction of World Health Organization /International Society of Urological Pathology (WHO/ISUP) Pathological Grading of Clear Cell Renal Cell Carcinoma by Dual-Layer Spectral CT. Acad Radiol. 2022.

40.

, Yang

, Liu

, Pu

, Qu

, Xu

, et al.

Are tumor-associated micro-angiogenesis and lymphangiogenesis considered as the novel prognostic factors for patients with Xp11.2 translocation renal cell carcinoma?

Bmc Cancer. 2020;20(1):1182.

41.

Coy

, Young

, Douek

, Pantuck

, Brown

, Sayre

, et al. Association of qualitative and quantitative imaging features on multiphasic multidetector CT with tumor grade in clear cell renal cell carcinoma. Abdom Radiol (NY). 2019;44(1):180–9.

42.

Kan

, Phongkitkarun

, Kobayashi

, Tang

, Ellis

, Lee

, et al. Functional CT for quantifying tumor perfusion in antiangiogenic therapy in a rat model. Radiology. 2005;237(1):151–8.

43.

Lin

, Wang

, Yan

, Li

, Tian

, Li

, et al. Interobserver reproducibility of contrast-enhanced ultrasound in diabetic nephropathy. Br J Radiol 2022;95(1129):20210189.

44.

Ridolfi

, Abbattista

, Busilacchi

, Brunelli

. Contrast-enhanced ultrasound evaluation of hepatic microvascular changes in liver diseases. World J Gastroenterol. 2012;18(37):5225–30.

45.

Dietrich

, Correas

, Cui

, Dong

, Havre

, Jenssen

, et al. EFSUMB Technical Review - Update Dynamic Contrast-Enhanced Ultrasound (DCE-CEUS) for the Quantification of Tumor Perfusion. Ultraschall Med. 2024;45(1):36–46.

	High-grade	Low-grade	P
	N = 23	N = 49
Gender:			1.000
Female	7 (30.4%)	16 (32.7%)
Male	16 (69.6%)	33 (67.3%)
Age (y)	53.0 (12.1)	51.8 (13.4)	0.704
Size (cm)	3.50 (3.00, 3.80)	3.00 (2.50, 3.80)	0.200
			1.000
0–2 cm	3 (13.0%)	8 (16.3%)
2–4 cm	20 (87.0%)	41 (83.7%)
Position:			0.129
Left	8 (34.8%)	28 (57.1%)
Right	15 (65.2%)	21 (42.9%)
Location:			0.335
Down	8 (34.8%)	21 (42.9%)
middle	6 (26.1%)	17 (34.7%)
Up	9 (39.1%)	11 (22.4%)
Echo:
Hyperecho	15 (65.2%)	26 (53.1%)	0.474
Hypoecho	8 (34.8%)	23 (46.9%)
Blood flow signals			0.704
Without	3 (13.0%)	5 (10.2%)
With	20 (87.0%)	44 (89.8%)