An overview of non-invasive imaging modalities for diagnosis of solid and cystic renal lesions

Contrast-Enhanced Ultrasound in the Diagnosis of Solid Renal Lesions

The availability of imaging methods has enabled increased detection of kidney lesions, which are a common clinical problem. It is estimated that more than half of patients over the age of 50 have at least one undetermined mass in the kidney. The appropriate characterization and diagnosis of lesions imaged in the kidney allows for proper therapeutic management. Previously, contrast-enhanced computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI) have been used in their extended diagnosis. However, the limitations of these techniques, such as radiation exposure, renal toxicity, and allergies to contrast agents, must be considered. Contrast-enhanced ultrasound (CEUS) is increasingly being used as an examination to resolve interpretive doubts that arise with other diagnostic methods. Indeed, it can be considered both as a problem-solving technique for diagnosing and distinguishing lesions and as a technique used for observation in preservative treatment. Evaluation of the enhancement curve over time on CEUS examination can help to differentiate malignant renal cell carcinoma (RCC) subtypes that should be resected from benign lesions, such as oncocytoma or angiomyolipoma (AML), in which surgery can be avoided. It allows for distinguishing between benign and malignant tumors, renal and pseudotumors, and solid and cystic tumors. Therefore, with recent advances in ultrasound technology, CEUS has emerged as a fast, reliable, and cost-effective imaging tool in the preoperative evaluation and diagnosis of solid renal masses.

Localized cystic kidney disease: a case report unveiling clinical and histopathological challenges

Localized cystic kidney disease (LCKD) is a distinct renal disorder characterized by the presence of cysts within specific regions of the kidneys. We present a rare case of a 41-year-old African American man, who presented to our medical center with lower urinary tract symptoms and gross hematuria. The initial assessment culminated in the identification of an uncomplicated urinary tract infection, prompting the prescription of appropriate oral antibiotic therapy. On follow-up after 5 months, the patient presented with gross hematuria. Imaging studies revealed a mixed-density cystic lesion of 2.6 cm situated within the interpolar region of the right kidney. This cystic lesion exhibited intricate septations at the superior pole of the kidney. Robotic-assisted right partial nephrectomy was performed, and pathologic examination was diagnostic for LCKD. This report not only underscores the uniqueness of LCKD but also presents a comprehensive review of the existing literature that pertains to this condition. Particular emphasis is placed upon its inherent benign behavior and its marked divergence from the progressive trajectory commonly associated with other renal diseases. We also explored the incidental findings of the disease, its diverse clinical symptomatology, conceivable etiological underpinnings, and the array of diagnostic modalities used. Finally, similarities in histopathologic findings with polycystic kidney disease and other entities are discussed, underscoring the importance of accurate diagnosis and management.

Artificial intelligence for renal cancer: From imaging to histology and beyond

Artificial intelligence (AI) has made considerable progress within the last decade and is the subject of contemporary literature. This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation. Renal cell carcinoma (RCC) has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging. This creates considerable challenges as approximately 10%–17% of kidney tumors are designated as benign in histopathological evaluation; however, certain co-morbid populations (the obese and elderly) have an increased peri-interventional risk. AI offers an alternative solution by helping to optimize precision and guidance for diagnostic and therapeutic decisions. The narrative review introduced basic principles and provide a comprehensive overview of current AI techniques for RCC. Currently, AI applications can be found in any aspect of RCC management including diagnostics, perioperative care, pathology, and follow-up. Most commonly applied models include neural networks, random forest, support vector machines, and regression. However, for implementation in daily practice, health care providers need to develop a basic understanding and establish interdisciplinary collaborations in order to standardize datasets, define meaningful endpoints, and unify interpretation.

Cross-sectional imaging assessment of renal masses with emphasis on MRI

Magnetic resonance imaging (MRI) is a useful complementary imaging tool for the diagnosis and characterization of renal masses, as it provides both morphologic and functional information. A core MRI protocol for renal imaging should include a T1-weighted sequence with in- and opposed-phase images (or, alternatively with DIXON technique), T2-weighted and diffusion-weighted images as well as a dynamic contrast-enhanced sequence with subtraction images, followed by a delayed post-contrast T1-weighted sequence. The main advantages of MRI over computed tomography include increased sensitivity for contrast enhancement, less sensitivity for detection of calcifications, absence of pseudoenhancement, and lack of radiation exposure. MRI may be applied for renal cystic lesion characterization, differentiation of renal cell carcinoma (RCC) from benign solid renal tumors, RCC histologic grading, staging, post-treatment follow-up, and active surveillance of patients with treated or untreated RCC.

The role of imaging in the management of renal masses

The wide availability of cross-sectional imaging is responsible for the increased detection of small, usually asymptomatic renal masses. More than 50 % of renal cell carcinomas (RCCs) represent incidental findings on noninvasive imaging. Multimodality imaging, including conventional US, contrast-enhanced US (CEUS), CT and multiparametric MRI (mpMRI) is pivotal in diagnosing and characterizing a renal mass, but also provides information regarding its prognosis, therapeutic management, and follow-up. In this review, imaging data for renal masses that urologists need for accurate treatment planning will be discussed. The role of US, CEUS, CT and mpMRI in the detection and characterization of renal masses, RCC staging and follow-up of surgically treated or untreated localized RCC will be presented. The role of percutaneous image-guided ablation in the management of RCC will be also reviewed.