29 Apr Contrast-ultrasound dispersion imaging for renal cell carcinoma diagnostics
Contrast-ultrasound dispersion imaging for renal cell carcinoma diagnostics
16 April, 2025
Peiran Chen, Simona Turco, Zhaohan Liu, Christiaan Widdershoven, Jorg Oddens, Hessel Wijkstra, Massimo Mischi & Patricia Zondervan
Abstract
Cost-effective screening methods for Renal Cell Carcinoma (RCC) are still lacking. Angiogenesis is a recognized hallmark of cancer growth, leading to distinguishable perfusion patterns in tumors from those in normal tissue.
This establishes the basis for diagnostic imaging solutions by dynamic contrast-enhanced ultrasound (DCE-US). In the past years, we have developed contrast-ultrasound dispersion imaging (CUDI) techniques to quantify prostate DCE-US acquisitions, obtaining promising results for prostate cancer localization.
In this pilot study, we investigated for the first time its feasibility for RCC localization. DCE-US acquisitions of the kidney in 5 patients were used to perform CUDI analysis. With the obtained CUDI parameters and the delineated tumor and parenchyma regions, we performed pixel-based classification, from which the highest area under the receiver-operating-characteristic curve (AUC) = 0.96 was obtained for an individual patient, and an average AUC = 0.68 was obtained for the full patient dataset, showing the potential of CUDI for solid RCC localization.
Further validation in a larger dataset and evaluation of the compatibility of point-of-care diagnosis are required.
Introduction
With over 430,000 new cases and around 180,000 new deaths in 2020, kidney cancer accounts for 2.2% and 1.8% of all oncological diagnoses and deaths worldwide, respectively [1].
About nine out of ten cancers in the kidney are renal cell carcinomas (RCCs) [2]. RCC comprises a broad spectrum of histopathological entities, of which the three main RCC subtypes are: clear-cell RCC (ccRCC), papillary RCC (pRCC-type I and II), and chromophobe RCC (chRCC) [3]. Typically, RCC appears symptom-free at its early stage until progression [4].
Patients with RCCs can be cured at an early stage, while patients with stage four disease have a 12% five-year survival rate only [5]. Nowadays, over 60% of RCCs are diagnosed incidentally with computed tomography (CT) imaging performed for other medical purposes [3, 4].
Therefore, an efficient diagnostic method compatible with point-of-care diagnosis is in demand for RCC detection and screening, especially at an early stage.
Conclusions
Our preliminary results show the potential of CUDI for solid RCC diagnostics, encouraging us to extend the dataset with a large number of reliable DCE-US acquisitions and corresponding histopathological results for further validation.
Moreover, the recently developed 3D ultrasound imaging together with multiparametric image analysis techniques are worth investigating in the scenario of point-of-care diagnosis of kidney cancer.
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