Contrast-Enhanced Ultrasound Characteristics of Renal Pelvis Urothelial Carcinoma and Its Relationship with Microvessel Density

Ultrasound findings and clinical characteristics in differentiating renal urothelial carcinoma from endophytic clear cell renal cell carcinoma

OBJECTIVE

This study aimed to evaluate the clinical characteristics and features of conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) in differentiating between renal urothelial carcinomas (RUC) and endophytic clear cell renal cell carcinomas (EccRCC).

METHODS

A total of 72 RUCs and 120 EccRCCs confirmed by pathology were assessed retrospectively. Both CUS and CEUS were performed within 4 weeks before the surgery. Logistic regression analyses were used to select statistically significant variables of clinical, CUS, and CEUS features for the differentiation of RUC and EccRCC. Sensitivity (SEN), specificity (SPE), and the area under the receiver-operating characteristic curve (AUC) were assessed for diagnostic performance. Inter- and intra-observer agreements of CUS and CEUS features were evaluated using the intra-class correlation coefficient(ICC).

RESULTS

Multiple logistic regression analysis demonstrated that clinical (age >50 years old and hematuria), CUS (size <4.0 cm, hypo-echogenicity, irregular shape, hydronephrosis) and CEUS (absence of non-enhancement area, iso- /hypo-enhancement in cortical phase and absence of rim-like enhancement) features were independent factors for RUC diagnosis. When combining clinical characters with CUS and CEUS features into an integrated diagnostic criterion, the AUC reached 0.917 (95% CI 0.873-0.961), with a sensitivity of 95.8% and specificity of 87.5%. ICC ranged from 0.756 to 0.907 for inter-observer agreement and 0.791 to 0.934 for intra-observer agreement for CUS and CEUSfeatures.

CONCLUSIONS

The combination of clinical features of age and hematuria with imaging features of CUS and CEUS can be useful for the differentiation between RUC and EccRCC.

Development and validation of a clinical and ultrasound features-based nomogram for preoperative differentiation of renal urothelial carcinoma and central renal cell carcinoma

PURPOSE

This study aimed to develop and validate an ultrasound (US)-based nomogram for the preoperative differentiation of renal urothelial carcinoma (rUC) from central renal cell carcinoma (c-RCC).

METHODS

Clinical data and US images of 655 patients with 655 histologically confirmed malignant renal tumors (521 c-RCCs and 134 rUCs) were collected and divided into training (n = 455) and validation (n = 200) cohorts according to examination dates. Conventional US and contrast-enhanced US (CEUS) tumor features were analyzed to determine those that could discriminate rUC from c-RCC. Least absolute shrinkage and selection operator regression was applied to screen clinical and US features for the differentiation of rUC from c-RCC. Using multivariate logistic regression analysis, a diagnostic model of rUC was constructed and visualized as a nomogram. The diagnostic model's performance was assessed in the training and validation cohorts by calculating the area under the receiver operating characteristic curve (AUC) and calibration plot. Decision curve analysis (DCA) was used to assess the clinical usefulness of the US-based nomogram.

RESULTS

Seven features of both clinical features and ultrasound imaging were selected to build the diagnostic model. The nomogram achieved favorable discrimination in the training (AUC = 0.996, 95% CI: 0.993-0.999) and validation (AUC = 0.995, 95% CI: 0.974, 1.000) cohorts, and good calibration (Brier scores: 0.019 and 0.016, respectively). DCA demonstrated the clinical usefulness of the US-based nomogram.

CONCLUSION

A noninvasive clinical and US-based nomogram combining conventional US and CEUS features possesses good predictive value for differentiating rUC from c-RCC.

Predictive Model of CK7 Expression in Patients With Clear Cell Renal Cell Carcinoma by Combined Multimodal Ultrasound Diagnostic Techniques: A Retrospective Study

OBJECTIVE

The aim of the work described here was to develop and validate a predictive model for cytokeratin 7 (CK7) expression in clear cell renal cell carcinoma (ccRCC) patients by combining multimodal ultrasound diagnostic techniques.

METHODS

This retrospective study enrolled 157 surgically confirmed ccRCC patients. All patients underwent pre-operative multimodal ultrasound diagnostic examinations, including B-mode ultrasound (US), color Doppler flow imaging (CDFI) and contrast-enhanced ultrasound (CEUS). The patients were randomly divided into a training group (103 cases) and a testing group (54 cases). Univariate and multivariate logistic regression analyses were performed in the training group to identify independent indicators associated with CK7 positivity. These indicators were included in the predictive model. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the model's discriminative ability and accuracy. Decision curve analysis (DCA) and nomogram visualization were used to assess the clinical utility of the predictive model.

RESULTS

Univariate logistic regression analysis revealed that US and CDFI observations were not correlated with CK7 expression and could not predict it. Multivariate logistic regression analysis identified age (odds ratio [OR] = 0.953, 95% confidence interval [CI]: 0.909-0.999), wash-in pattern (OR = 0.180, 95% CI: 0.063-0.513) and enhancement homogeneity (OR = 11.610, 95% CI: 1.394-96.675) as independent factors related to CK7 positivity in ccRCC. Incorporating these variables into the predictive model resulted in areas under the receiver operating characteristic curve of 0.812 (95% CI: 0.711-0.913) for the training group and 0.792 (95% CI: 0.667-0.924) for the testing group. The calibration curve and DCA revealed that the model had good accuracy and clinical utility of the model.

CONCLUSION

The combination of multimodal ultrasound diagnostic techniques in constructing a predictive model for CK7 expression in ccRCC patients has significant predictive value.

Application of contrast-enhanced ultrasound in diagnosis and grading of bladder urothelial carcinoma

PURPOSE

To explore the application of contrast-enhanced ultrasound (CEUS) for the diagnosis and grading of bladder urothelial carcinoma (BUC).

METHODS

The results of a two-dimensional ultrasound, color Doppler ultrasound and CEUS, were analyzed in 173 bladder lesion cases. The ultrasound and surgical pathology results were compared, and their diagnostic efficacy was analyzed.

RESULTS

There were statistically significant differences between BUC and benign lesions in terms of color blood flow distribution intensity and CEUS enhancement intensity (both P < 0.05). The area under the time-intensity curve (AUC), rising slope, and peak intensity of BUC were significantly higher than those of benign lesions (all P < 0.05). The H/T (height H / basal width T)value of 0.63 was the critical value for distinguishing high- and low-grade BUC, had a diagnostic sensitivity of 80.0% and a specificity of 60.0%.

CONCLUSION

The combination of CEUS and TIC can help improve the diagnostic accuracy of BUC. There is a statistically significant difference between high- and low-grade BUC in contrast enhancement intensity (P < 0.05); The decrease of H/T value indicates the possible increase of the BUC grade.

Correlations between contrast-enhanced ultrasound and microvessel density in non-small cell lung cancer: A prospective study

Background

Immunohistochemical microvessel density (MVD) is an early indicator of angiogenesis and it could be used to evaluate the therapeutic efficacy of non-small cell lung cancer (NSCLC). We sought to identify the ability of contrast-enhanced ultrasound (CEUS) in evaluating MVD of subpleural NSCLC.

Methods

We prospectively collected CEUS data of NSCLC confirmed by ultrasound-guided transthoracic needle biopsy from October 2019 to February 2021, The MVD of NSCLC counted by CD34-positive vessels of immunohistochemical staining. Microflow enhancement (MFE) of CEUS was divided into "dead wood", "cotton", and "vascular" patterns. Pathology subgroup and MVD between different MFE patterns were analyzed, respectively. The arrival time, time to peak, peak intensity (PI), and area under curve (AUC) derivefrom time-intensity curve of CEUS with MVD in NSCLC and its pathological subgroups (adenocarcinoma and squamous cell carcinoma) were subjected to correlation analysis.

Results

A total of 87 patients were included in this study, consisting of 53 cases of adenocarcinoma and 34 cases of squamous cell carcinoma with a mean MVD of 27.8 ± 12.2 mm^-1. There was a significant statistical difference in MFE patterns between two pathological subgroups (p < 0.05). Besides, the MVD of "cotton" and "vascular" patterns were significantly higher than that of "dead wood" pattern (both of p < 0.05), whereas there was no significant difference in MVD between "cotton" pattern and "vascular" pattern. PI and AUC of CEUS were positively correlated with the MVD of NSCLC (r = 0.497, p < 0.001, and r = 0.367, p < 0.001, respectively). Besides, PI and AUC of CEUS were positively correlated with the MVD of squamous cell carcinoma (r = 0.802, and r = 0.663, respectively; both of p < 0.001). Only the PI was positively correlated with the MVD of lung adenocarcinoma (r = 0.288, p = 0.037).

Conclusions

MFE patterns and quantitative parameters of CEUS had good correlation with MVD of NSCLC, especially in squamous cell carcinoma.