Expanding the Role of Ultrasound for the Characterization of Renal Masses

Characteristics of high frame frequency contrast-enhanced ultrasound in renal tumors

OBJECTIVE

This study aims to analyze the characteristics of high frame rate contrast-enhanced ultrasound (H-CEUS) in renal lesions and to improve the ability for differential diagnosis of renal tumors.

METHODS

A total of 140 patients with renal lesions underwent contrast-enhanced ultrasound (CEUS) examination in the First Affiliated Hospital of Nanchang University from July 2022 to July 2023. Based on the tumor pathology and the results of enhanced CT, tumor patients were divided into malignant and benign groups. All subjects were examined using gray-scale ultrasound, conventional contrast-enhanced ultrasound (C-CEUS), and H-CEUS, and their dynamic images were recorded. Two radiologists independently analyzed and recorded the results of ultrasound, C-CEUS, and H-CEUS images and statistically analyzed the features of C-CEUS and H-CEUS images. The independent sample t-test was used to compare the difference in age and maximum diameter of nodules between the benign and malignant groups. The χ2 test was used to compare the sex, mode of operation, gray-scale ultrasound characteristics, and enhancement characteristics of the two CEUS modes (enhancement mode, regression mode, enhancement degree, enhancement uniformity, enhancement or not, enhancement direction, post-enhancement boundary and range, and pseudocapsule) between the benign and malignant groups. The difference in vascular morphology of malignant nodules of varying sizes under two angiographic modes.

RESULTS

There were significant differences in gender (χ2 = 10.408, P = 0.001), mode of operation (χ2 = 47.089, P < 0.001), nodule composition (χ2 = 7.481, P = 0.003), nodule echo (χ2 = 20.926, P < 0.001), necrosis (χ2 = 31.343, P < 0.001) and nodule blood flow (χ2 = 9.006, P = 0.029) between the benign and malignant groups. There were significant differences in the regression model (χ2 = 6.782, P = 0.034) and enhancement direction (χ2 = 13.771, P = 0.001) between the two radiographic techniques in the malignant group. There was a significant difference in the enhancement uniformity between the two CEUS techniques in the benign group (χ2 = 8.264, P = 0.004). There was a significant difference between the two CEUS techniques in displaying the vascular morphology in the malignant group with the maximum diameter of nodules ≤ 4.0 cm (χ2 = 11.421, P < 0.022). However, there was no significant difference between the two techniques in the malignant group with the maximum diameter of nodules > 4.0 cm.

CONCLUSION

Increasing the frame rate of ultrasound images is helpful to accurately display the enhanced features and vascular morphology of renal tumors, especially for malignant tumors with a maximum diameter of ≤ 4.0 cm. Thus, H-CEUS can make up for the limitation of CEUS with regard to the display of vascular morphology.

Role of Contrast-Enhanced Ultrasound With the Enhancement Pattern and Qualitative Analysis for Differentiating Hypovascular Solid Renal Lesions

OBJECTIVE

The aim of the work described here was to explore the clinical value of contrast-enhanced ultrasound (CEUS) with the enhancement pattern and qualitative analysis in distinguishing different types of hypovascular solid renal lesions.

METHODS

A total of 140 patients with 140 renal tumors (all diagnosed by pathology), which manifested hypo-enhancement on CEUS, were included in this study. We compared conventional ultrasound (US) and CEUS features in five common hypovascular renal tumors, including renal angiomyolipoma (RAML), clear cell renal cell carcinoma (ccRCC), renal pelvic urothelial carcinoma (RPUC), papillary renal cell carcinoma (pRCC) and chromophobe renal cell carcinoma (chRCC). The diagnostic value of conventional US and qualitative parameters of CEUS for differentiating hypovascular solid renal lesions were evaluated.

RESULTS

The mean age of patients with a benign renal lesion was younger than that of patients with a malignant renal lesion (p < 0.05). Echogenicity and qualitative parameters such as wash-out, perfusion defects and perilesional rim-like enhancement (PRE) in the two groups differed significantly (all p values <0.05). Benign renal lesions exhibited mainly slow wash-out, whereas malignant renal lesions exhibited predominantly fast wash-out on CEUS (p < 0.05). There were significant differences in echogenicity, such as between RAML and ccRCC, between RAML and RPUC and between RAML and pRCC (all p values <0.05). The rates of appearance of perfusion defect in ccRCC (48%, 13/27) and pRCC (53%, 10/19) were significantly higher than the rate in RAML (14%, 6/43) (p < 0.05). The rates of appearance of PRE in ccRCC (15%, 4/27), pRCC (26%, 5/19) and chRCC (24%,4/17) were significantly higher than the rate in RAML (9%, 4/43) (p < 0.05).

CONCLUSION

CEUS with the enhancement pattern and qualitative analysis may be helpful in distinguishing malignant from benign hypovascular renal lesions.

Artificial Intelligence in Renal Cell Carcinoma Histopathology: Current Applications and Future Perspectives

Renal cell carcinoma (RCC) is characterized by its diverse histopathological features, which pose possible challenges to accurate diagnosis and prognosis. A comprehensive literature review was conducted to explore recent advancements in the field of artificial intelligence (AI) in RCC pathology. The aim of this paper is to assess whether these advancements hold promise in improving the precision, efficiency, and objectivity of histopathological analysis for RCC, while also reducing costs and interobserver variability and potentially alleviating the labor and time burden experienced by pathologists. The reviewed AI-powered approaches demonstrate effective identification and classification abilities regarding several histopathological features associated with RCC, facilitating accurate diagnosis, grading, and prognosis prediction and enabling precise and reliable assessments. Nevertheless, implementing AI in renal cell carcinoma generates challenges concerning standardization, generalizability, benchmarking performance, and integration of data into clinical workflows. Developing methodologies that enable pathologists to interpret AI decisions accurately is imperative. Moreover, establishing more robust and standardized validation workflows is crucial to instill confidence in AI-powered systems' outcomes. These efforts are vital for advancing current state-of-the-art practices and enhancing patient care in the future.

Renal cell carcinoma of different pathological types in bilateral native kidneys of a kidney transplant recipient: A case report and literature review

Patients after kidney transplantation have a much higher risk of developing malignant tumors than the general population. And the native kidney is an organ relatively susceptible to malignant tumors after renal transplantation. However, the simultaneous development of bilateral renal tumors is very rare; especially the bilateral native kidneys harbor different pathological types of renal cell carcinoma (RCC). We report a case of a patient who developed malignant tumors in both native kidneys nearly 19 years after renal transplantation. This patient underwent bilateral laparoscopic radical nephrectomy, and postoperative pathological examination showed clear cell RCC on the left native kidney and papillary RCC on the right one. And the early detection and surgical treatment resulted in a good prognosis. The literature related to the diagnosis and treatment of bilateral RCC after renal transplantation is also reviewed.