Diagnostic Imaging for Solid Renal Tumors: A Pictorial Review

Lesion-aware cross-phase attention network for renal tumor subtype classification on multi-phase CT scans

Multi-phase computed tomography (CT) has been widely used for the preoperative diagnosis of kidney cancer due to its non-invasive nature and ability to characterize renal lesions. However, since enhancement patterns of renal lesions across CT phases are different even for the same lesion type, the visual assessment by radiologists suffers from inter-observer variability in clinical practice. Although deep learning-based approaches have been recently explored for differential diagnosis of kidney cancer, they do not explicitly model the relationships between CT phases in the network design, limiting the diagnostic performance. In this paper, we propose a novel lesion-aware cross-phase attention network (LACPANet) that can effectively capture temporal dependencies of renal lesions across CT phases to accurately classify the lesions into five major pathological subtypes from time-series multi-phase CT images. We introduce a 3D inter-phase lesion-aware attention mechanism to learn effective 3D lesion features that are used to estimate attention weights describing the inter-phase relations of the enhancement patterns. We also present a multi-scale attention scheme to capture and aggregate temporal patterns of lesion features at different spatial scales for further improvement. Extensive experiments on multi-phase CT scans of kidney cancer patients from the collected dataset demonstrate that our LACPANet outperforms state-of-the-art approaches in diagnostic accuracy.

Contrast-enhanced ultrasound (CEUS): applications from the kidneys to the bladder

Contrast-enhanced ultrasound (CEUS) is an advanced ultrasound (US) technique utilizing ultrasound contrast agents (UCAs) to provide detailed visualization of anatomic and vascular architecture, including the depiction of microcirculation. CEUS has been well-established in echocardiography and imaging of focal hepatic lesions and recent studies have also shown the utility of CEUS in non-hepatic applications like the urinary system. The updated guidelines by the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) from 2018 describe the use of CEUS for non-hepatic applications. CEUS' excellent safety profile and spatial resolution make it a superior modality to conventional US and is often comparable and even superior to CECT in some instances. In comparison to other cross-sectional imaging modalities such as CECT or MRI, CEUS offers a safe (by virtue of non-nephrotoxic US contrast agents), accurate, cost-efficient, readily available, and a quick means of evaluation of multiple pathologies of the urinary system. CEUS also has the potential to reduce the overall economic burden on patients requiring long-term follow-up due to its low cost as compared to CT or MRI techniques. This comprehensive review focuses on the applications of CEUS in evaluating the urinary system from the kidneys to the urinary bladder. CEUS can be utilized in the kidney to evaluate complex cystic lesions, indeterminate lesions, pseudotumors (vs solid renal tumors), renal infections, and renal ischemic disorders. Additionally, CEUS has also been utilized in evaluating renal transplants. In the urinary bladder, CEUS is extremely useful in differentiating a bladder hematoma and bladder cancer when conventional US techniques show equivocal results. Quantitative parameters of time-intensity curves (TICs) of CEUS examinations have also been studied to stage and grade bladder cancers. Although promising, further research is needed to definitively stage bladder cancers and classify them as muscle-invasive or non-muscle invasive using quantitative CEUS to guide appropriate intervention. CEUS has been very effective in the classification of cystic renal lesions, however, further research is needed in differentiating benign from malignant renal masses.

An automated two-stage approach to kidney and tumor segmentation in CT imaging

BACKGROUND

The incidence of kidney tumors is progressively increasing each year. The precision of segmentation for kidney tumors is crucial for diagnosis and treatment.

OBJECTIVE

To enhance accuracy and reduce manual involvement, propose a deep learning-based method for the automatic segmentation of kidneys and kidney tumors in CT images.

METHODS

The proposed method comprises two parts: object detection and segmentation. We first use a model to detect the position of the kidney, then narrow the segmentation range, and finally use an attentional recurrent residual convolutional network for segmentation.

RESULTS

Our model achieved a kidney dice score of 0.951 and a tumor dice score of 0.895 on the KiTS19 dataset. Experimental results show that our model significantly improves the accuracy of kidney and kidney tumor segmentation and outperforms other advanced methods.

CONCLUSION

The proposed method provides an efficient and automatic solution for accurately segmenting kidneys and renal tumors on CT images. Additionally, this study can assist radiologists in assessing patients' conditions and making informed treatment decisions.

Multifaceted Imaging of Renal Lesions With an Emphasis on Cross-Sectional Imaging

Introduction Renal lesions are common findings encountered in cross-sectional imaging. Ultrasonography (USG), computed tomography (CT), and magnetic resonance imaging (MRI) are available modalities for evaluating renal lesions. The Bosniak classification system aids in classifying a renal lesion into a particular category based on various imaging characteristics on contrast-enhanced CT (CECT).  Materials and methods The CT report archives were searched for the keyword 'Bosniak' lesions, and six illustrative cases were selected to be included in the review. Results Six cases under Bosniak categories I to IV were included in the review. Operative follow-ups were added in cases where patients underwent surgery. Discussion We have reviewed the imaging features of various renal lesions with cross-sectional modalities, namely CT and MRI, with special emphasis on the Bosniak classification system, including its amendments. Conclusion The Bosniak system is widely used to classify and characterize renal lesions. The authors have presented a scoping review of the features of renal lesions and the Bosniak system.

Tumor-to-Tumor Metastasis of Lung Cancer to Kidney Cancer: A Review of the Literature and Our Experience

Tumor-to-tumor metastasis (TTM) is a rare phenomenon documented in patients with multiple primary cancers. This condition is defined as a metastasis between two true primary tumors. The most frequently reported recipient tumor is renal cell carcinoma (RCC), and the lung carcinomas are the most common metastatic tumor donors. Therefore, this paper attempts to address the current gap in knowledge about this rare phenomenon. The first part of this review outlines the recently proposed models and mechanisms involved in the TTM process. The second part then summarizes and analyzes previous case reports in the literature. We also present our experience with the case of lung cancer that metastasized into RCC. Given the sporadic incidence of TTM, no specific management guidelines exist. Therefore, considering TTM in patients with multiple primary tumors is important as it could potentially modify the oncological management offered.

An automatic texture feature analysis framework of renal tumor: surgical, pathological, and molecular evaluation based on multi-phase abdominal CT

OBJECTIVES

To determine whether the texture feature analysis of multi-phase abdominal CT can provide a robust prediction of benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in renal tumor.

METHODS

A total of 1051 participants with renal tumor were split into the internal cohort (850 patients from four different hospitals) and the external testing cohort (201 patients from another local hospital). The proposed framework comprised a 3D-kidney and tumor segmentation model by 3D-UNet, a feature extractor for the regions of interest based on radiomics and image dimension reduction, and the six classifiers by XGBoost. A quantitative model interpretation method called SHAP was used to explore the contribution of each feature.

RESULTS

The proposed multi-phase abdominal CT model provides robust prediction for benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in the internal validation set, with the AUROC values of 0.88 ± 0.1, 0.90 ± 0.1, 0.91 ± 0.1, 0.89 ± 0.1, 0.84 ± 0.1, and 0.88 ± 0.1, respectively. The external testing set also showed impressive results, with AUROC values of 0.83 ± 0.1, 0.83 ± 0.1, 0.85 ± 0.1, 0.81 ± 0.1, 0.79 ± 0.1, and 0.81 ± 0.1, respectively. The radiomics feature including the first-order statistics, the tumor size-related morphology, and the shape-related tumor features contributed most to the model predictions.

CONCLUSIONS

Automatic texture feature analysis of abdominal multi-phase CT provides reliable predictions for multi-tasks, suggesting the potential usage of clinical application.

CLINICAL RELEVANCE STATEMENT

The automatic texture feature analysis framework, based on multi-phase abdominal CT, provides robust and reliable predictions for multi-tasks. These valuable insights can serve as a guiding tool for clinical diagnosis and treatment, making medical imaging an essential component in the process.

KEY POINTS

• The automatic texture feature analysis framework based on multi-phase abdominal CT can provide more accurate prediction of benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in renal tumor. • The quantitative decomposition of the prediction model was conducted to explore the contribution of the extracted feature. • The study involving 1051 patients from 5 medical centers, along with a heterogeneous external data testing strategy, can be seamlessly transferred to various tasks involving new datasets.

Therapeutic applications of carbon nanomaterials in renal cancer

Carbon nanomaterials (CNMs), including carbon nanotubes (CNTs), graphene, and nanodiamonds (NDs), have shown great promise in detecting and treating numerous cancers, including kidney cancer. CNMs can increase the sensitivity of diagnostic techniques for better kidney cancer identification and surveillance. They enable targeted medicine delivery specifically to tumour locations, with little effect on healthy tissue. Because of their unique chemical and physical characteristics, they can avoid the body's defence mechanisms, making it easier to accumulate where tumours exist. Consequently, CNMs provide more effective drug delivery to kidney cancer cells. It also helps in improving the efficacy of treatment. This review explores the potential of several CNMs in improving therapeutic strategies for kidney cancer. We briefly covered the physicochemical properties and therapeutic applications of CNMs. Additionally, we discussed how structural modifications in CNMs enhance their precision in treating renal cancer. A thorough overview of CNM-based gene, peptide, and drug delivery strategies for the treatment of renal cancer is presented in this review. It covers information on other CNM-based therapeutic approaches, such as hyperthermia, photodynamic therapy, and photoacoustic therapy. Also, the interactions of CNMs with the tumour microenvironment (TME) are explored, including modulation of the immune response, regulation of tumour hypoxia, interactions between CNMs and TME cells, effects of TME pH on CNMs, and more. Finally, potential side effects of CNMs, such as toxicity, bio corona formation, enzymatic degradation, and biocompatibility, are also discussed.

Partial nephrectomy of a horseshoe kidney associated with renal cell carcinoma and ureteral stone: A clinical case report

Key Clinical Message

Although anatomical and vascular abnormalities of the horseshoe kidney might be challenging, complete preoperative imaging evaluations and accurate organ-sparing surgical planning can lead to much lower complications.

Abstract

Horseshoe kidney (HK) is one of the most common renal fusion anomalies. Renal carcinoids are rarely reported in HK patients. Here, we described a rare case of advanced right renal cell carcinoma (RCC) along with proximal left ureter stone in a 41-year-old man who presented with a complaint of turbid urine. Early blood tests revealed a blood urea nitrogen of 44 mg/dL and serum creatinine of 1.35 mg/dL. The urine analysis showed microscopic hematuria (6-8 RBCs) and few calcium oxalate crystals. The imaging evaluations revealed an HK anomaly with a solid mass on the right side and a 4 mm stone in the proximal left ureter. The findings suggested RCC which was confirmed by histopathology examination. Consequently, the patient was scheduled for an organ-preserving open surgery of a right kidney tumor with concomitant left ureterolithotomy. The 16-month follow-up showed no urological complications, metastasis, or tumor proliferation. Although the anatomical and vascular abnormalities of HK might be challenging, organ-sparing surgical treatment should be considered in feasibly resectable tumors. Complete preoperative imaging evaluations to identify the characteristics of HK, as well as accurate surgical planning, can lead to much lower complications.

Clinical practice guidelines for the diagnosis and surveillance of BAP1 tumour predisposition syndrome

BRCA1-associated protein-1 (BAP1) is a recognised tumour suppressor gene. Germline BAP1 pathogenic/likely pathogenic variants are associated with predisposition to multiple tumours, including uveal melanoma, malignant pleural and peritoneal mesothelioma, renal cell carcinoma and specific non-malignant neoplasms of the skin, as part of the autosomal dominant BAP1-tumour predisposition syndrome. The overall lifetime risk for BAP1 carriers to develop at least one BAP1-associated tumour is up to 85%, although due to ascertainment bias, current estimates of risk are likely to be overestimated. As for many rare cancer predisposition syndromes, there is limited scientific evidence to support the utility of surveillance and, therefore, management recommendations for BAP1 carriers are based on expert opinion. To date, European recommendations for BAP1 carriers have not been published but are necessary due to the emerging phenotype of this recently described syndrome and increased identification of BAP1 carriers via large gene panels or tumour sequencing. To address this, the Clinical Guideline Working Group of the CanGene-CanVar project in the United Kingdom invited European collaborators to collaborate to develop guidelines to harmonize surveillance programmes within Europe. Recommendations with respect to BAP1 testing and surveillance were achieved following literature review and Delphi survey completed by a core group and an extended expert group of 34 European specialists including Geneticists, Ophthalmologists, Oncologists, Dermatologists and Pathologists. It is recognised that these largely evidence-based but pragmatic recommendations will evolve over time as further data from research collaborations informs the phenotypic spectrum and surveillance outcomes.

Biological sex disparity in survival outcomes following treatment for renal cell carcinoma: A systematic review and meta-analysis

INTRODUCTION

Renal cell carcinoma (RCC), a type of kidney cancer has biological sex-based differences that play a role in cancer incidence. Specifically, the incidence of urinary system cancers in men is two times greater than in women, while the incidence of genital cancers is three times greater. There is conflicting epidemiologic and limited evidence in the literature to suggest apparent biological sex discrepancy. The primary objective of this review and meta-analysis is to synthesize evidence to understand biological sex disparity in the survival outcomes of RCC following any treatment intervention.

METHODS

A three-step search strategy was utilized in this review. We searched MEDLINE, EMBASE and PsycINFO databases for manuscript on biological sex differences in treatment outcomes. Study screening, critical appraisal, and data extraction were executed independently by pairs of reviewers among co-authors. Studies that had any form of treatment modality in the management of RCC were included. Study designs included observational studies in the form of prospective and retrospective studies that utilized cox proportional hazard assumption to conduct survival analysis. The data synthesis was carried out using the R metafor software package (Software version of 1.2.8) and Microsoft Office Excel 2019 package (Microsoft Corporation, USA). The random effects model was estimated using restricted maximum likelihood estimation (REML). Data synthesis included narrative review and meta-analysis.

RESULTS

We had 23 eligible studies for this review. On review of the full text, 35 studies were excluded due to irrelevances to measure estimates utilized. Finally, 12 studies were selected for the meta-analysis with a total of n = 21,2453 individuals. Females had a better survival outcome following a treatment intervention for RCC than their male counterpart [Mean effect size = -0.1737 (95 % CI: -0.2524, -0.0949)].

CONCLUSION

Females were more likely to be cancer free than their male counterpart following treatment for RCC. This finding will inform appropriate decision making for stakeholders.

Exploratory Analysis of the Role of Radiomic Features in the Differentiation of Oncocytoma and Chromophobe RCC in the Nephrographic CT Phase

In diagnostic imaging, distinguishing chromophobe renal cell carcinomas (chRCCs) from renal oncocytomas (ROs) is challenging, since they both present similar radiological characteristics. Radiomics has the potential to help in the differentiation between chRCCs and ROs by extracting quantitative imaging. This is a preliminary study of the role of radiomic features in the differentiation of chRCCs and ROs using machine learning models. In this retrospective work, 38 subjects were involved: 19 diagnosed with chRCCs and 19 with ROs. The CT nephrographic contrast phase was selected in each case. Three-dimensional segmentations of the lesions were performed and the radiomic features were extracted. To assess the reliability of the features, the intraclass correlation coefficient was calculated from the segmentations performed by three radiologists with different degrees of expertise. The selection of features was based on the criteria of excellent intraclass correlation coefficient (ICC), high correlation, and statistical significance. Three machine learning models were elaborated: support vector machine (SVM), random forest (RF), and logistic regression (LR). From 105 extracted features, 41 presented an excellent ICC and 6 were not highly correlated with each other. Only two features showed significant differences according to histological type and machine learning models were developed with them. LR was the better model, in particular, with an 83% precision.

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.

MR Virtual Biopsy of Solid Renal Masses: An Algorithmic Approach

Between 1983 and 2002, the incidence of solid renal tumors increased from 7.1 to 10.8 cases per 100,000. This is in large part due to the increase in the volume of ultrasound and cross-sectional imaging, although a majority of solid renal tumors are still found incidentally. Ultrasound and computed tomography (CT) have been the mainstay of renal mass screening and diagnosis but recent advances in magnetic resonance (MR) technology have made this the optimal choice when diagnosing and staging renal tumors. Our purpose in writing this review is to survey the modern MR imaging approach to benign and malignant solid renal tumors, consolidate the various imaging findings into an easy-to-read reference, and provide an imaging-based, algorithmic approach to renal mass characterization for clinicians. MR is at the forefront of renal mass characterization, surpassing ultrasound and CT in its ability to describe multiple tissue parameters and predict tumor biology. Cutting-edge MR protocols and the integration of diagnostic algorithms can improve patient outcomes, allowing the imager to narrow the differential and better guide oncologic and surgical management.

Qualitative Assessment of Contrast-Enhanced Ultrasound in Differentiating Clear Cell Renal Cell Carcinoma and Oncocytoma

BACKGROUND

We aimed to assess whether clear cell renal cell carcinoma (ccRCC) can be differentiated from renal oncocytoma (RO) on a contrast-enhanced ultrasound (CEUS).

METHODS

Between January 2021 and October 2022, we retrospectively queried and analyzed our prospectively maintained dataset. Renal mass features were scrutinized with conventional ultrasound imaging (CUS) and CEUS. All lesions were confirmed by histopathologic diagnoses after nephron-sparing surgery (NSS). A multivariable analysis was performed to identify the potential predictors of ccRCC. The area under the curve (AUC) was depicted in order to assess the diagnostic accuracy of the multivariable model.

RESULTS

A total of 126 renal masses, including 103 (81.7%) ccRCC and 23 (18.3%) RO, matched our inclusion criteria. Among these two groups, we found significant differences in terms of enhancement (homogeneous vs. heterogeneous) (p < 0.001), wash-in (fast vs. synchronous/slow) (p = 0.004), wash-out (fast vs. synchronous/slow) (p = 0.001), and rim-like enhancement (p < 0.001). On the multivariate logistic regression, heterogeneous enhancement (OR: 19.37; p = <0.001) and rim-like enhancement (OR: 3.73; p = 0.049) were independent predictors of ccRCC. Finally, these two variables had an AUC of 82.5% and 75.3%, respectively.

CONCLUSIONS

Diagnostic imaging for presurgical planning is crucial in the choice of either conservative or radical management. CEUS, with its unique features, revealed its usefulness in differentiating ccRCC from RO.

99mTc-Sestamibi SPECT/CT and histopathological features of oncocytic renal neoplasia

BACKGROUND

^99mTc-Sestamibi Single Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) contributes to the non-invasive differentiation of renal oncocytoma (RO) from renal cell carcinoma (RCC) by characterising renal tumours as Sestamibi positive or Sestamibi negative regarding their ^99mTc-Sestamibi uptake compared to the non-tumoral renal parenchyma.

PURPOSE

To determine whether ^99mTc- Sestamibi uptake in renal tumour and the non-tumoral renal parenchyma measured using Standard Uptake Value (SUV) SPECT, has a beneficial role in differentiating RO from RCC.

MATERIAL AND METHODS

Fifty-seven renal tumours from 52 patients were evaluated. In addition to visual evaluation of ^99mTc-Sestamibi uptake, SUV_max measurements were performed in the renal tumour and the ipsilateral non-tumoral renal parenchyma. Analysis of the area under the receiver operating characteristic curve identified an optimal cut-off value for detecting RO, based on the relative ratio of ^99mTc- Sestamibi uptake.

RESULTS

Semiquantitative evaluation of ^99mTc-Sestamibi uptake did not improve the performance of ^99mTc- Sestamibi SPECT/CT in detecting RO. ^99mTc- Sestamibi SPECT/CT identifies a group of mostly indolent Sestamibi-positive tumours with low malignant potential containing RO, Low-Grade Oncocytic Tumours, Hybrid Oncocytic Tumours, and a subset of chromophobe RCCs.

CONCLUSION

The imaging limitations for accurate differentiation of Sestamibi-positive renal tumours mirror the recognised diagnostic complexities of the histopathologic evaluation of oncocytic neoplasia. Patients with Sestamibi-positive renal tumours could be better suited for biopsy and follow-up, according to the current active surveillance protocols.

The multispeciality approach to the management of localised kidney cancer

Historically, kidney cancer was approached in a siloed single-speciality way, with urological surgeons managing the localised stages of the disease and medical oncologists caring for patients if metastases developed. However, improvements in the management of localised kidney cancer have occurred rapidly over the past two decades with greater understanding of the disease biology, diagnostic options, and innovations in curative treatments. These developments are favourable for patients but provide a substantially more complex landscape for patients and clinicians to navigate, with associated challenging decisions about who to treat, how, and when. As such, the skill sets needed to manage the various aspects of the disease and guide patients appropriately outstrips the capabilities of one particular specialist, and the evolution of a multispeciality approach to the management of kidney cancer is now essential. In this Review, we summarise the current best multispeciality practice for the management of localised kidney cancer and the areas in need of further research and development.

Comparative Analysis for the Distinction of Chromophobe Renal Cell Carcinoma from Renal Oncocytoma in Computed Tomography Imaging Using Machine Learning Radiomics Analysis

Background: ChRCC and RO are two types of rarely occurring renal tumors that are difficult to distinguish from one another based on morphological features alone. They differ in prognosis, with ChRCC capable of progressing and metastasizing, but RO is benign. This means discrimination of the two tumors is of crucial importance. Objectives: The purpose of this research was to develop and comprehensively evaluate predictive models that can discriminate between ChRCC and RO tumors using Computed Tomography (CT) scans and ML-Radiomics texture analysis methods. Methods: Data were obtained from 78 pathologically confirmed renal masses, scanned at two institutions. Data from the two institutions were combined to form a third set resulting in three data cohorts, i.e., cohort 1, 2 and combined. Contrast-enhanced scans were used and the axial cross-sectional slices of each tumor were extracted from the 3D data using a semi-automatic segmentation technique for both 2D and 3D scans. Radiomics features were extracted before and after applying filters and the dimensions of the radiomic features reduced using the least absolute shrinkage and selection operator (LASSO) method. Synthetic minority oversampling technique (SMOTE) was applied to avoid class imbalance. Five ML algorithms were used to train models for predictive classification and evaluated using 5-fold cross-validation. Results: The number of selected features with good model performance was 20, 40 and 6 for cohorts 1, 2 and combined, respectively. The best model performance in cohorts 1, 2 and combined had an excellent Area Under the Curve (AUC) of 1.00 ± 0.000, 1.00 ± 0.000 and 0.87 ± 0.073, respectively. Conclusions: ML-based radiomics signatures are potentially useful for distinguishing ChRCC and RO tumors, with a reliable level of performance for both 2D and 3D scanning.

Neuroendocrine Neoplasms of the Female Genitourinary Tract: A Comprehensive Overview

Simple Summary

Primary neuroendocrine neoplasms (NENs) are a rare, heterogeneous group of tumors that include well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinoma, and paraganglioma. NENs in the urinary tract are observed in <0.05% of individuals, in whom the bladder is the most common site. In this review, we described the epidemiology, pathogenesis, imaging, staging, and management of the genitourinary NENs.

Abstract

Primary neuroendocrine neoplasms are a rare heterogeneous group of tumors that include well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinoma, and paraganglioma. An extensive literature search was used to compile the data regarding epidemiology, pathogenesis, imaging features, and management of the urinary system NENs. We also included the updated staging of the NENs at various locations of the urinary system.

Defining the Magnetic Resonance Features of Renal Lesions and Their Response to Everolimus in a Transgenic Mouse Model of Tuberous Sclerosis Complex

Tuberous sclerosis complex (TSC) is an inherited genetic disorder characterized by mutations in TSC1 or TSC2 class of tumor suppressers which impact several organs including the kidney. The renal manifestations are usually in the form of angiomyolipoma (AML, in 80% of the cases) and cystadenomas. mTOR inhibitors such as rapamycin and everolimus have shown efficacy in reducing the renal tumor burden. Early treatment prevents the progression of AML; however, the tumors regrow upon cessation of therapy implying a lifelong need for monitoring and management of this morbid disease. There is a critical need for development of imaging strategies to monitor response to therapy and progression of disease which will also facilitate development of newer targeted therapy. In this study we evaluated the potential of multiparametric ¹H magnetic resonance imaging (mpMRI) to monitor tumor response to therapy in a preclinical model of TSC, the transgenic mouse A/J Tsc2^+/-. We found 2-dimensional T₂-weighted sequence with 0.5 mm slice thickness to be optimal for detecting renal lesions as small as 0.016 mm³. Baseline characterization of lesions with MRI to assess physiological parameters such as cellularity and perfusion is critical for distinguishing between cystic and solid lesions. Everolimus treatment for three weeks maintained tumor growth at 36% from baseline, while control tumors displayed steady growth and were 70% larger than baseline at the end of therapy. Apparent diffusion coefficient, T₁ values and normalized T₂ intensity changes were also indictive of response to treatment. Our results indicate that standardization and implementation of improved MR imaging protocols will significantly enhance the utility of mpMRI in determining the severity and composition of renal lesions for better treatment planning.

Contrast-Enhanced Ultrasound (CEUS) in the Evaluation of Renal Masses with Histopathological Validation—Results from a Prospective Single-Center Study

Background: To evaluate the diagnostic accuracy of contrast-enhanced ultrasound (CEUS) in characterizing between malignant and benign renal lesions confirmed by histological examination. Methods: Overall, 110 patients, for a total of 118 renal masses previously identified at CT and MRI underwent CEUS. An expert radiologist evaluated morphological, qualitative and quantitative parameters. Acquired data were analyzed to assess the value of each parameter to differentiate between malignant and benign lesions. Results: Histological results of 118 renal masses showed 88 (75%) malignant lesions and 30 (25%) benign lesions. Among morphological features, inhomogeneous echogenicity was the best predictor of malignancy depicting a sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 76%, 76%, 88% and 57%, respectively. Among qualitative parameters, the most reliable parameter was the presence of pseudo-capsule. Here, sensitivity, specificity, positive PPV and NPV were 85%, 86%, 94% and 71%, respectively. Among quantitative parameters, the most reliable parameters were peak intensity (PI) and the area under the (AUC) with sensitivity, specificity, PPV and NPV values of 94%, 92%, 96% and 87% and 99%, 92%, 97% and 97%, respectively. Finally, the most reliable parameters were combined to distinguish between benign and malignant lesions. The best combination obtained was restricted to CEUS parameters (PI and AUC). Here, sensitivity, specificity, PPV, NPV and accuracy rate were 93%, 100%, 100%, 83% and 93%, respectively. Conclusions: CEUS increases the US accuracy to discriminate between benign and malignant renal lesions.

Diagnostic Workup for Patients with Solid Renal Masses: A Cost-Effectiveness Analysis

Background: For patients with solid renal masses, a precise differentiation between malignant and benign tumors is crucial for forward treatment management. Even though MRI and CT are often deemed as the gold standard in the diagnosis of solid renal masses, CEUS may also offer very high sensitivity in detection. The aim of this study therefore was to evaluate the effectiveness of CEUS from an economical point of view. Methods: A decision-making model based on a Markov model assessed expenses and utilities (in QALYs) associated with CEUS, MRI and CT. The utilized parameters were acquired from published research. Further, a Monte Carlo simulation-based deterministic sensitivity analysis of utilized variables with 30,000 repetitions was executed. The willingness-to-pay (WTP) is at USD 100,000/QALY. Results: In the baseline, CT caused overall expenses of USD 10,285.58 and an efficacy of 11.95 QALYs, whereas MRI caused overall expenses of USD 7407.70 and an efficacy of 12.25. Further, CEUS caused overall expenses of USD 5539.78, with an efficacy of 12.44. Consequently, CT and MRI were dominated by CEUS, and CEUS remained cost-effective in the sensitivity analyses. Conclusions: CEUS should be considered as a cost-effective imaging strategy for the initial diagnostic workup and assessment of solid renal masses compared to CT and MRI.

Advancements in nanomedicines for the detection and treatment of diabetic kidney disease

In the diabetic kidneys, morbidities such as accelerated ageing, hypertension and hyperglycaemia create a pro-inflammatory microenvironment characterised by extensive fibrogenesis. Radiological techniques are not yet optimised generating inconsistent and non-reproducible data. The gold standard procedure to assess renal fibrosis is kidney biopsy, followed by histopathological assessment. However, this method is risky, invasive, subjective and examines less than 0.01% of kidney tissue resulting in diagnostic errors. As such, less than 10% of patients undergo kidney biopsy, limiting the accuracy of the current diabetic kidney disease (DKD) staging method. Standard treatments suppress the renin-angiotensin system to control hypertension and use of pharmaceuticals aimed at controlling diabetes have shown promise but can cause hypoglycaemia, diuresis and malnutrition as a result of low caloric intake. New approaches to both diagnosis and treatment are required. Nanoparticles (NPs) are an attractive candidate for managing DKD due to their ability to act as theranostic tools that can carry drugs and enhance image contrast. NP-based point-of-care systems can provide physiological information previously considered unattainable and provide control over the rate and location of drug release. Here we discuss the use of nanotechnology in renal disease, its application to both the treatment and diagnosis of DKD. Finally, we propose a new method of NP-based DKD classification that overcomes the current systems limitations.

Socio-economic burden of disease: Survivorship costs for renal cell carcinoma

OBJECTIVE

The objective of this study is to assess the risk-stratified 10-year socio-economic burden of renal cell carcinoma (RCC) follow-up costs after initial treatment in Germany from 2000 to 2020.

METHODS

A micro-costing method considering direct and indirect medical expenditure associated with follow-up procedures was employed to calculate survivorship costs per patient. The frequencies of physician-patient visits, examinations and diagnostic tests were extracted from guidelines, whilst expenses were sourced from literature and official scales of tariffs. Societal costs were calculated based on three perspectives: patients, providers and insurers.

RESULTS

Mean societal 10-year follow-up costs per patient amounted to EUR 3,377 (95%CI: 2,969-3,791) for low-risk, EUR 3,367 (95%CI: 3,003-3,692) for medium-risk and EUR 4,299 (95%CI: 3,807-4,755) for high-risk RCC in 2020. Spending increased by +32% from 2000 to 2020 for low-risk RCC, whilst medium-and high-risk RCC expenditure was cut by -39% and -22%, respectively. Patients shouldered 27%, providers 43% and insurers 35% of costs in 2020. Resources were consumed by medical imaging (52%), physician-patient consultations (31%), travel expenses (17%) and blood tests (1%).

CONCLUSION

Results highlight the economic burden cancer survivorship poses for society. Cancer survivors require individualised, evidence-based and insurance-covered follow-up schedules to permit the early detection of side-effects, metastasis and secondary malignancies.

Radiology Imaging Scans for Early Diagnosis of Kidney Tumors: A Review of Data Analytics-Based Machine Learning and Deep Learning Approaches

Plenty of disease types exist in world communities that can be explained by humans’ lifestyles or the economic, social, genetic, and other factors of the country of residence. Recently, most research has focused on studying common diseases in the population to reduce death risks, take the best procedure for treatment, and enhance the healthcare level of the communities. Kidney Disease is one of the common diseases that have affected our societies. Sectionicularly Kidney Tumors (KT) are the 10th most prevalent tumor for men and women worldwide. Overall, the lifetime likelihood of developing a kidney tumor for males is about 1 in 466 (2.02 percent) and it is around 1 in 80 (1.03 percent) for females. Still, more research is needed on new diagnostic, early, and innovative methods regarding finding an appropriate treatment method for KT. Compared to the tedious and time-consuming traditional diagnosis, automatic detection algorithms of machine learning can save diagnosis time, improve test accuracy, and reduce costs. Previous studies have shown that deep learning can play a role in dealing with complex tasks, diagnosis and segmentation, and classification of Kidney Tumors, one of the most malignant tumors. The goals of this review article on deep learning in radiology imaging are to summarize what has already been accomplished, determine the techniques used by the researchers in previous years in diagnosing Kidney Tumors through medical imaging, and identify some promising future avenues, whether in terms of applications or technological developments, as well as identifying common problems, describing ways to expand the data set, summarizing the knowledge and best practices, and determining remaining challenges and future directions.

Clampless Laparoscopic Tumor Enucleation for Exophytic Masses Greater Than 4 cm: Is Renorrhaphy Necessary?

Objective: To demonstrate the safety of clampless 3D laparoscopic tumor enucleation (cLTE) for exophytic T1b kidney masses, avoiding suture to achieve hemostasis. Methods: Between January 2010 and January 2021, 241 consecutive patients with an exophytic renal tumor underwent sutureless cLTE. Patients with predominantly endophytic growth or tumors 4 mm closer to the collecting system less were excluded. In all cases, an attempt was made to accomplish surgery without suturing kidney parenchyma. Data were obtained from a retrospective review of history and physical examinations, operative and pathology reports, anesthesia records during the hospital stay, and follow-up visits. Results: Among 241 patients who underwent cLTE, 148 had cT1a and 93 had cT1b renal tumor. The median tumor size was 32 mm, and the median R.E.N.A.L. (radius exophytic/endophytic nearness anterior/posterior location) score was 6. Renorrhaphy was necessary in 5 cases. The median operative time (OT) was 100 minutes, and the estimated blood loss (EBL) was 150 mL. The median 24-hour decrease in hemoglobin was 1.8 g/dL. The median length of stay was 4 days. Nineteen patients had postoperative complications: 3 cases had Clavien-Dindo (CD) 3a or more, 6 had CD2, and 10 had CD1. Comparing the T1a and T1b groups, except for the median OT and the EBL, no significant differences were observed in all the other variables analyzed. In both groups, renal function was preserved after 1 year from surgery. Conclusion: Our experience showed that sutureless cLTE is safe and feasible for T1b tumors leading to radical oncological outcomes and preserving renal function.

The changing trends of image-guided biopsy of small renal masses before intervention-an analysis of European multinational prospective EuRECA registry

Objectives

To evaluate the use of pre-cryoablation biopsy for small renal masses (SRMs) and the effects of increasing uptake on histological results of treated SRMs.

Methods

From 2015 to 2019, patients with sporadic T1N0M0 SRMs undergoing percutaneous, laparoscopic, or open cryoablation from 14 European institutions within the European Registry for Renal Cryoablation (EuRECA) were included for the retrospective analysis. Univariate and multivariate logistic models were used to evaluate the trends, histological results, and the factors influencing use of pre-cryoablation biopsy.

Results

In total, 871 patients (median (IQR) age, 69 (14), 298 women) undergoing cryoablation were evaluated. The use of pre-cryoablation biopsy has significantly increased from 42% (65/156) in 2015 to 72% (88/122) in 2019 (p < 0.001). Patients treated for a benign histology are significantly more likely to have presented later in the trend, where pre-cryoablation biopsy is more prevalent (OR: 0.64, 95% CI 0.51–0.81, p < 0.001). Patients treated for undiagnosed histology are also significantly less likely to have presented in 2018 compared to 2016 (OR 0.31, 95% CI 0.10–0.97, p = 0.044). Patients aged 70+ are less likely to be biopsies pre-cryoablation (p < 0.05). R.E.N.A.L. nephrometry score of 10+ and a Charlson Comorbidity Index > 1 are factors associated with lower likelihood to not have received a pre-cryoablation biopsy (p < 0.05).

Conclusion

An increased use of pre-cryoablation biopsy was observed and cryoablation patients treated with a benign histology are more likely to have presented in periods where pre-cryoablation biopsy is not as prevalent. Comparative studies are needed to draw definitive conclusions on the effect of pre-cryoablation biopsy on SRM treatments.

Key Points

• The use of biopsy pre-ablation session has increased significantly from 42% of all patients in 2015 to 74% in 2019.

• Patients are less likely to be treated for a benign tumour if they presented later in the trend, where pre-cryoablation biopsy is more prevalent, compared to later in the trend (OR 0.64, 95% CI 0.51–0.81, p < 0.001).

• Patients with comorbidities or a complex tumour (R.E.N.A.L. nephrometry score > 10) are less likely to not undergo biopsy as a separate session to cryoablation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-08556-2.

Cancer Screening in Solid Organ Transplant Recipients: A Focus on Screening Liver, Lung, and Kidney Recipients for Cancers Related to the Transplanted Organ

Over the last few decades, the life expectancy of solid organ transplant recipients (SOTRs) has improved significantly. With SOTRs living longer, more recipients are dying from cancer. There is a reported 2- to 3-fold increased risk of cancer-specific mortality in SOTRs compared with the general population. Cancer in an SOTR can be de novo, recurrent, or donor-derived. Cancer screening in this population is crucial, as early detection and treatment may improve outcomes. In the absence of randomized controlled trials dedicated to SOTRs, clinicians rely on clinical practice guidelines from regional and national transplant societies; however, these may vary considerably across jurisdictions and transplanted organ. At present, no widely accepted consensus exists for cancer screening protocols in SOTRs, particularly with regard to screening for malignancy related to transplanted organ. Some SOTRs may be at higher risk of malignancies within the allograft. This is particularly the case in lung and liver recipients, though less common in kidney recipients who are at increased risk of developing renal cell cancer in their native kidneys. This increased risk has not been uniformly incorporated into screening recommendations for SOTRs. In this review, we summarize the cancer screening recommendations for SOTRs from various transplant organizations based on transplanted organ. This review also discusses the complexity and controversies surrounding screening of cancer in the allograft and future avenues to improve cancer detection in this context. More studies specific to SOTRs are required to form generalizable and evidence-based cancer screening guidelines, particularly with respect to cancer screening in the allograft.

Ectopic adrenal tissue in the kidney: A systematic review

Introduction: Ectopic adrenal tissue in the kidney, including “Ectopic adrenal tissue” and “Adrenal-renal fusion”, is a rare event with a specific behavior which may be difficult to distinguish clinically from renal neoplasms. We performed a systematic review on ectopic adrenal tissue variants reported in the literature underlining its clinical aspects. Methods: Manuscripts which presented a case report or case series of ectopic adrenal tissue in the kidney were included even if published in original articles, reviews, or letters to the editor. A specific search on SCOPUS®, PubMed®, and Web of Science® database was performed. Only English language papers published in a period ranging between August 1991 and April 2020 were considered. Additionally, a case we had at our institution is described, and its characteristics are included. Data on clinical presentation, type of adrenal anomaly, location, anatomopathological and immune-histotype characteristics were collected. Results: We identified 888 manuscripts. Among these 29 were included in this systematic review. Overall, 39 patients with renal adrenal fusion or adrenal ectopia were considered. In most cases, the diagnosis was made incidentally, or following investigation for flank pain, abdominal pain, or endocrinological disorders. CT scan frequently identified a solid vascularized lesion that was difficult to distinguish from renal neoplasm. Adrenal fusion was mostly located at the level of the upper pole. Adrenal rest was found in the renal parenchyma, renal hilum, or retroperitoneum in close proximity to the renal peduncle. Often these ectopic adrenal tissue lesions follow a benign behavior and can be classified as functioning or non-functioning adenomas. Rarely, they may experience neoplastic degeneration. The most frequently positive markers were inhibin, vimentin, melan-A, synaptophysin and anti-p450 scc. Conclusions: Ectopic adrenal tissue in the kidney is a rare event with specific clinical characteristics that need to be identified in order to arrive at a correct diagnosis and carry out appropriate treatment management.

DWI and ADC value versus ADC ratio in the characterization of solid renal masses: radiologic-pathologic correlation

Background

Renal masses are becoming an increasingly common finding on cross-sectional images. Characterization of the nature of the lesion either neoplastic or not, benign or malignant as well as further subtype characterization is becoming an important factor in determining management plan. The purpose of our study with to assess the sensitivity and specificity of both ADC mean value and ADC ratio in such characterization along with the calculation of different cutoff values to differentiate between different varieties, using pathological data as the main gold standard for diagnosis.

Results

Our study included 50 patients with a total of 72 masses. A final diagnosis was reached in 69 masses by pathological examination and three masses had clinical and laboratory signs of infection. We had a total of 49 malignant lesions (68%) and 23 benign lesions (32%). The ADC value of ccRCC (1.4 × 10−3 mm2/s) was significantly higher than all other renal masses. A cutoff ADC value of > 1.1 and a cutoff ADC ratio of > 0.56 can be used to differentiate between clear cell renal cell carcinoma and other lesions and an ADC value of < 0.8 and an ADC ratio of ≤ 0.56 to differentiate papillary renal cell carcinoma from other masses. There was no statistically significant ADC value to differentiate between benign and malignant lesions but a statistically significant ADC ratio (> 0.52) was reached.

Conclusion

ADC value and ADC ratio can be used as an adjunct tool in the characterization of different renal masses, with ADC ratio having a higher sensitivity, which can affect the prognosis and management of the patient.

Biological sex disparity in survival outcomes following treatment for renal cell carcinoma: a systematic review protocol

OBJECTIVE

This systematic review will assess the biological sex disparity in survival outcomes following treatment for renal cell carcinoma and analyze the estimates of biological sex disparity outcomes following supposed or proposed curative treatment.

INTRODUCTION

Renal cell carcinoma is a type of kidney cancer. There is a lack of conformity in the literature on the biological sex disparity in survival outcomes after treatment. This review will help inform the decision-making of clinicians, health care administrators, policy makers, public health workers, and pharmaceutical/biotechnology researchers in predicting positive outcomes following treatment.

INCLUSION CRITERIA

The review will consider prospective and retrospective studies on any form of treatment for renal cell carcinoma. The Cox proportional hazard assumption will be used to conduct survival analysis. Hazard rates of participants' survivability across biological sex will also be reported.

METHODS

A three-step search strategy will be used. First, a limited search of MEDLINE, Embase, and PsycINFO was conducted and text words in the title, abstract, and index terms were analyzed. Second, a search using identified keywords and index terms will be tailored for all included databases. Third, the reference lists of all included reports and articles will be screened to search for additional studies. There will be no language or date restrictions. Papers not written in English but with a professional translated copy will be included. Study screening, critical appraisal, and data extraction will be conducted independently by pairs of reviewers. Data synthesis will include narrative review and meta-analysis, if appropriate.

SYSTEMATIC REVIEW REGISTRATION NUMBER

PROSPERO CRD42020195721.

Risk of Cancer Among Sarcoidosis Patients With Biopsy-verified Nonnecrotizing Granulomatous Inflammation: Population-based Cohort Study

OBJECTIVE

To assess the long-term risk of hematologic cancers, invasive solid tumors, and nonmelanoma skin cancer (NMSC) among sarcoidosis patients with biopsy-verified nonnecrotizing granulomatous inflammation.

METHODS

We used Danish administrative registers with nationwide coverage to construct a cohort of 3892 patients with sarcoidosis and an age- and sex-matched comparison cohort of 38,920 population controls. For all patients, a biopsy demonstrating nonnecrotizing granulomatous inflammation had been obtained from the lower respiratory tract at the time of diagnosis. Study outcome was time to diagnosis of cancer. Follow-up began at time of sarcoidosis diagnosis and continued for up to 10 years. We calculated hazard ratios (HRs) as estimates of the cancer risk among the patients with sarcoidosis relative to that among the population controls and used cumulative incidence functions to calculate absolute 10-year risk estimates.

RESULTS

We observed an increased long-term risk of hematologic cancers (HR during the first 2 years of follow-up: 2.71 [95% CI 1.18-6.25]; HR after > 2 years of follow-up: 2.12 [95% CI 1.29-3.47]) and NMSC (HR after > 2 years of follow-up: 1.82 [95% CI 1.43-2.32]) among the patients with sarcoidosis. An increased risk of invasive solid tumors was only observed during the first 2 years (HR 1.55, 95% CI 1.18-2.04). Compared with the population controls, the patients with sarcoidosis had an increased absolute 10-year risk of hematologic cancers (risk difference 0.56%, 95% CI 0.11-1.01%) and NMSC (risk difference 1.58%, 95% CI 0.70-2.47%).

CONCLUSION

Sarcoidosis patients with biopsy-verified nonnecrotizing granulomatous inflammation have an increased long-term risk of hematologic cancers and NMSC compared with the general population.

Role of contrast-enhanced ultrasound in assessing indeterminate renal lesions and Bosniak ≥2F complex renal cysts found incidentally on CT or MRI

OBJECTIVE

To investigate the impact of contrast-enhanced ultrasound (CEUS) in reclassifying incidental renal findings categorized as indeterminate lesions (IL) or Bosniak ≥ 2F complex renal cysts (CRC) on CT or MRI.

METHODS

We retrospectively included 44 subjects who underwent CEUS between 2016 and 2019 to assess 48 IL (n = 12) and CRC (n = 36) incidentally found on CT or MRI. CEUS was performed by one radiologist with 10 year of experience with a sulfur hexafluoride-filled microbubble contrast agent. The same radiologist, blinded to clinical information and previous CT/MRIs, retrospectively reviewed CEUS images/videos, categorizing renal findings with Bosniak-derived imaging categories ranging from 0 (indeterminate) to 5 (solid lesion). CEUS-related reclassification rate was calculated (proportion of IL reclassified with an imaging category >0, or CRC reclassified below or above imaging category >2F). Using histological examination or a ≥ 24 months follow-up as the standard of reference, we also estimated per-lesion sensitivity/specificity for malignancy.

RESULTS

CEUS reclassified 24/48 findings (50.0%; 95% C.I. 35.2-64.7), including 12/12 IL (100%; 95% CI 73.5-100) and 12/36 CRC (33.3%; 95% C.I. 18.5-50.9), mostly above category >2F (66.7%). CEUS and CT/MRI showed 96.0% (95%CI 79.7-99.9) vs 44.0% (95%CI 24.4-65.1) sensitivity, and 82.6% (95%CI 61.2-95.1) vs 60.9% (95%CI 38.5-80.3%) specificity.

CONCLUSION

CEUS provided substantial and accurate reclassification of CT/MRI incidental findings.

ADVANCES IN KNOWLEDGE

Previous studies included Bosniak 2 incidental findings, thus possibly underestimating CEUS-induced reclassification rates. Using a more meaningful cut-off (Bosniak ≥2F), problem-solving CEUS was effective as well, with higher reclassification rates for CRC than in literature.

A CT-based radiomics nomogram for differentiation of small masses (< 4 cm) of renal oncocytoma from clear cell renal cell carcinoma

PURPOSE

Renal oncocytoma (RO) is the most commonly resected benign renal tumor because of misdiagnosis as renal cell carcinoma. This misdiagnosis is generally owing to overlapping imaging features. This study describes the building of a radiomics nomogram based on clinical data and radiomics signature for the preoperative differentiation of RO from clear cell renal cell carcinoma (ccRCC) on tri-phasic contrast-enhanced CT.

METHODS

A total of 122 patients (85 in training set and 37 in external validation set) with ROs (n = 46) or ccRCCs (n = 76) were enrolled. Patient characteristics and tri-phasic contrast-enhanced CT imaging features were evaluated to build a clinical factors model. A radiomics signature was constructed by extracting radiomics features from tri-phasic contrast-enhanced CT images and a radiomics score (Rad-score) was calculated. A radiomics nomogram was then built by incorporating the Rad-score and significant clinical factors according to a multivariate logistic regression analysis. The diagnostic performance of the above three models was evaluated in training and validation sets.

RESULTS

Central stellate area and perirenal fascia thickening were selected to build the clinical factors model. Eleven radiomics features were combined to construct the radiomics signature. The AUCs of the radiomics nomogram, which was based on the selected clinical factors and Rad-score, were 0.960 and 0.898 in the training and validation sets, respectively. The decision curves of the radiomics nomogram and radiomics signature in the validation set indicated an overall net benefit over the clinical factors model.

CONCLUSION

Our radiomics nomogram can effectively predict the preoperative diagnosis of ROs and may therefore be of assistance in sparing unnecessary surgery and tailoring precise therapy. The ROC curves of the clinical model, the radiomics signature and the radiomics nomogram for the validation set. RO = Renal oncocytoma; ccRCC = Clear cell renal cell carcinoma.

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.

Which criteria can be used to predict benignity in solid renal lesions lower-equal to 2 cm?

PURPOSE

To evaluate magnetic resonance imaging (MRI) criteria of solid renal lesions lower-equal to 2 cm to differentiate benign and malignant tumors, using histopathology as gold standard.

METHODS

Three radiologists independently evaluated objective and subjective MRI criteria of focal renal lesions. A total of 105 nodules of patients who had MRI and histopathological results in our institution were included. Subjective criteria evaluated were signal on T2-weighted imaging, presence of microscopic and macroscopic fat, hemosiderin, hemorrhage, central scar, segmented inversion enhancement and enhancement type; objective criteria were gender, ADC value, heterogeneity on T2-weighted imaging and proportion of enhancement in late post-contrast phases. Finally, the readers classified the lesions in probably benign or malignant. Interobserver agreement was evaluated by the Gwet method, and the quantitative variables by intraclass correlation coefficients. To adjust the predictive model, the logistic regression model was used considering the benignity variable as outcome.

RESULTS

A total of 26 nodules (24.5%) were benign and 79 (75.2%) were malignant, with size ranging from 7 to 20 mm (median: 14 mm). The most frequent subtype was papillary renal cell carcinoma (RCC) (35.2%), followed by clear-cell RCC (24.8%) and oncocytoma (12.4%). The univariate and multivariate analysis showed, among all categories evaluated, that microscopic fat (p: 0.072), intermediate (p: 0.004) and hyper-enhancement (p: 0.031) and female sex (p: 0.0047) had the best outcome for benignity, within odds ratios of 4.29, 5.75, 4.07 and 2.86, respectively.

CONCLUSION

In small solid renal lesions lower-equal to 2 cm, microscopic fat, moderate and hyper-enhancement and female sex were associated with benignity.

Renal cell carcinoma, part 1

ABSTRACT

Renal cell carcinoma (RCC) encompasses a group of malignancies that originate in the epithelium of the renal cortex, most often in the upper pole of the kidney. This article, the first of a three-part series on RCC, addresses the incidence and epidemiology of RCC along with its genetic alterations, risk factors, histologic characteristics, and imaging characteristics.

Deep learning with a convolutional neural network model to differentiate renal parenchymal tumors: a preliminary study

PURPOSE

With advancements in medical imaging, more renal tumors are detected early, but it remains a challenge for radiologists to accurately distinguish subtypes of renal parenchymal tumors. We aimed to establish a novel deep convolutional neural network (CNN) model and investigate its effect on identifying subtypes of renal parenchymal tumors in T2-weighted fat saturation sequence magnetic resonance (MR) images.

METHODS

This retrospective study included 199 patients with pathologically confirmed renal parenchymal tumors, including 77, 46, 34, and 42 patients with clear cell renal cell carcinoma (ccRCC), chromophobe renal cell carcinoma (chRCC), angiomyolipoma (AML), and papillary renal cell carcinoma (pRCC), respectively. All enrolled patients underwent kidney MR scans with the field strength of 1.5 Tesla (T) or 3.0 T before surgery. We selected T2-weighted fat saturation sequence images of all patients and built a deep learning model to determine the type of renal tumors. Receiver operating characteristic (ROC) curve was depicted to estimate the performance of the CNN model; the accuracy, precision, sensitivity, specificity, F₁-score, and area under the curve (AUC) were calculated. One-way analysis of variance and χ² tests of independent samples were used to analyze the variables.

RESULTS

The experimental results demonstrated that the model had a 60.4% overall accuracy, a 61.7% average accuracy, and a macro-average AUC of 0.82. The AUCs for ccRCC, chRCC, AML, and pRCC were 0.94, 0.78, 0.80, and 0.76, respectively.

CONCLUSION

Deep CNN model based on T2-weighted fat saturation sequence MR images was useful to classify the subtypes of renal parenchymal tumors with a relatively high diagnostic accuracy.

Imaging and its Impact on Defining the Oligometastatic State

Successful treatment of oligometastatic disease (OMD) is facilitated through timely detection and localization of disease, both at the time of initial diagnosis (synchronous OMD) and following the initial therapy (metachronous OMD). Hence, imaging plays an indispensable role in management of patients with OMD. However, the challenges and complexities of OMD management are also reflected in the imaging of this entity. While innovations and advances in imaging technology have made a tremendous impact in disease detection and management, there remain substantial and unaddressed challenges for earlier and more accurate establishment of OMD state. This review will provide an overview of the available imaging modalities and their inherent strengths and weaknesses, with a focus on their role and potential in detection and evaluation of OMD in different organ systems. Furthermore, we will review the role of imaging in evaluation of OMD for malignancies of various primary organs, such as the lung, prostate, colon/rectum, breast, kidney, as well as neuroendocrine tumors and gynecologic malignancies. We aim to provide a practical overview about the utilization of imaging for clinicians who play a role in the care of those with, or at risk for OMD.

Deep learning for end-to-end kidney cancer diagnosis on multi-phase abdominal computed tomography

In 2020, it is estimated that 73,750 kidney cancer cases were diagnosed, and 14,830 people died from cancer in the United States. Preoperative multi-phase abdominal computed tomography (CT) is often used for detecting lesions and classifying histologic subtypes of renal tumor to avoid unnecessary biopsy or surgery. However, there exists inter-observer variability due to subtle differences in the imaging features of tumor subtypes, which makes decisions on treatment challenging. While deep learning has been recently applied to the automated diagnosis of renal tumor, classification of a wide range of subtype classes has not been sufficiently studied yet. In this paper, we propose an end-to-end deep learning model for the differential diagnosis of five major histologic subtypes of renal tumors including both benign and malignant tumors on multi-phase CT. Our model is a unified framework to simultaneously identify lesions and classify subtypes for the diagnosis without manual intervention. We trained and tested the model using CT data from 308 patients who underwent nephrectomy for renal tumors. The model achieved an area under the curve (AUC) of 0.889, and outperformed radiologists for most subtypes. We further validated the model on an independent dataset of 184 patients from The Cancer Imaging Archive (TCIA). The AUC for this dataset was 0.855, and the model performed comparably to the radiologists. These results indicate that our model can achieve similar or better diagnostic performance than radiologists in differentiating a wide range of renal tumors on multi-phase CT.

Targeted PET/CT imaging for clear cell renal cell carcinoma with radiolabeled antibodies: recent developments using girentuximab

PURPOSE OF REVIEW

Conventional imaging is unable to differentiate clear cell renal cell carcinoma (ccRCC) from other more indolent and benign renal tumors. Positron emission tomography/computed tomography (PET/CT) using radiolabeled antibodies may aid in detecting both localized and metastatic ccRCC. The purpose of this review is to summarize recent literature regarding the use of radiolabeled antibodies for imaging of ccRCC.

RECENT FINDINGS

Two recent studies evaluated the use of radiolabeled anticarbonic anhydrase IX antibody girentuximab for the imaging of ccRCC. PET/CT with 89zirconium-labeled girentuximab (89Zr-girentuximab PET/CT) was used to guide clinical decision making in 16 patients with localized disease. It had a high specificity for detecting ccRCC with 6/6 resected lesions with uptake proven to be ccRCC, all lesion without uptake showed to be indolent during follow-up. Clinical management was changed in 36% (5/14) of patients with the metastatic disease based on outcomes of the scan. Furthermore, in 42 patients 89Zr-girentuximab PET/CT combined with CT outperformed CT alone or combined with 18F fludeoxyglucose PET for detection of metastasis.

SUMMARY

89Zr-girentuximab PET/CT has the ability to diagnose ccRCC in localized disease. In metastatic disease, it enables the differentiation of ccRCC from non-ccRCC cancers and the evaluation of disease extent. 89Zr-girentuximab PET/CT diagnostic accuracy is currently evaluated in a multicenter phase III trial.

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.

Sporadic multiple renal angiomyolipoma with lymph node involvement: a case report and literature review

Angiomyolipoma (AML) is a benign tumor that mainly occurs in the kidneys. Simultaneous involvement of the kidney and local regional lymph nodes is very rare and might be misdiagnosed as a metastasizing malignant cancer. In the present study, a 50-year-old woman was referred to our hospital after a routine health screening ultrasound. Sporadic multiple renal AML with lymph node involvement was suspected based on the clinical manifestations and radiologic features. Partial nephrectomy was performed and a para-inferior vena cava lymph node was removed. The pathologic results confirmed multiple AML with lymph node invasion. We also reviewed the English-language literature regarding renal AML with lymph node involvement. We found that middle-aged women were likely to develop this disease and that loin pain was the main presenting feature. Most patients had no history of tuberous sclerosis complex. Radical nephrectomy was the predominant treatment. No local recurrence or distant metastasis occurred in any patients after radical nephrectomy or partial nephrectomy. In conclusion, renal AML with lymph node involvement is rare but can occur in both patients with tuberous sclerosis complex and those with multiple sporadic AML. Partial nephrectomy should be the first-line treatment, after which further treatment is not necessary.

Review of Prognostic Expression Markers for Clear Cell Renal Cell Carcinoma

Context: The number of prognostic markers for clear cell renal cell carcinoma (ccRCC) has been increasing regularly over the last 15 years, without being integrated and compared. Objective: Our goal was to perform a review of prognostic markers for ccRCC to lay the ground for their use in the clinics. Evidence Acquisition: PubMed database was searched to identify RNA and protein markers whose expression level was reported as associated with survival of ccRCC patients. Relevant studies were selected through cross-reading by two readers. Evidence Synthesis: We selected 249 studies reporting an association with prognostic of either single markers or multiple-marker models. Altogether, these studies were based on a total of 341 distinct markers and 13 multiple-marker models. Twenty percent of these markers were involved in four biological pathways altered in ccRCC: cell cycle, angiogenesis, hypoxia, and immune response. The main genes (VHL, PBRM1, BAP1, and SETD2) involved in ccRCC carcinogenesis are not the most relevant for assessing survival. Conclusion: Among single markers, the most validated markers were KI67, BIRC5, TP53, CXCR4, and CA9. Of the multiple-marker models, the most famous model, ClearCode34, has been highly validated on several independent datasets, but its clinical utility has not yet been investigated. Patient Summary: Over the years, the prognosis studies have evolved from single markers to multiple-marker models. Our review highlights the highly validated prognostic markers and multiple-marker models and discusses their clinical utility for better therapeutic care.

Development and evaluation of a deep neural network for histologic classification of renal cell carcinoma on biopsy and surgical resection slides

Renal cell carcinoma (RCC) is the most common renal cancer in adults. The histopathologic classification of RCC is essential for diagnosis, prognosis, and management of patients. Reorganization and classification of complex histologic patterns of RCC on biopsy and surgical resection slides under a microscope remains a heavily specialized, error-prone, and time-consuming task for pathologists. In this study, we developed a deep neural network model that can accurately classify digitized surgical resection slides and biopsy slides into five related classes: clear cell RCC, papillary RCC, chromophobe RCC, renal oncocytoma, and normal. In addition to the whole-slide classification pipeline, we visualized the identified indicative regions and features on slides for classification by reprocessing patch-level classification results to ensure the explainability of our diagnostic model. We evaluated our model on independent test sets of 78 surgical resection whole slides and 79 biopsy slides from our tertiary medical institution, and 917 surgical resection slides from The Cancer Genome Atlas (TCGA) database. The average area under the curve (AUC) of our classifier on the internal resection slides, internal biopsy slides, and external TCGA slides is 0.98 (95% confidence interval (CI): 0.97-1.00), 0.98 (95% CI: 0.96-1.00) and 0.97 (95% CI: 0.96-0.98), respectively. Our results suggest that the high generalizability of our approach across different data sources and specimen types. More importantly, our model has the potential to assist pathologists by (1) automatically pre-screening slides to reduce false-negative cases, (2) highlighting regions of importance on digitized slides to accelerate diagnosis, and (3) providing objective and accurate diagnosis as the second opinion.

Changes in UK renal oncological surgical practice from 2008 to 2017: implications for cancer service provision and surgical training

OBJECTIVE

To determine and analyse the temporal changes in oncological nephrectomy practice and training opportunities using data obtained from the UK British Association of Urological Surgeons nephrectomy register from 2008 to 2017.

PATIENT AND METHODS

All nephrectomies within the dataset for this time period were analysed (n = 54 251). Cases were divided into radical nephrectomy (RN), partial nephrectomy (PN) and nephroureterectomy (NU). Simple nephrectomy, donor nephrectomy and benign PN were excluded. The annual frequencies for each oncological nephrectomy method, surgical approach, grade of surgeon, hospital caseload numbers and short-term surgical outcomes were determined.

RESULTS

Reported annual nephrectomy numbers increased by 2.5-fold in the 9-year time period. The number of hospitals performing nephrectomies decreased by 22%, however, more than 40% of centres performed more than 70 cases a year. There was a trend towards a decrease in overall length of hospital stay (9 vs 5 days; P < 0.01) and decreased transfusion rates. The proportion of minimally invasive procedures increased from 57% to 75%, with nephron-sparing rates increasing from 8.9% overall to 24.8%. With regard to surgical technique, robot-assisted surgery saw a mean annual increase of 222%. Overall, there was a 10% decrease in the proportion of PNs performed by trainee surgeons.

CONCLUSIONS

Renal surgery has changed considerably with regard to volume and also surgical approach, with rates of nephron-sparing surgery and minimally invasive surgery significantly increasing. Increasing hospital centralization and institutional experience, and a shift to robot-assisted surgery appear to have contributed to the observed improved patient outcomes. The increasing utilization of robot-assisted surgery has potential implications and challenges for the training of future urology surgeons.

Small renal masses (≤ 4 cm): differentiation of oncocytoma from renal clear cell carcinoma using ratio of lesion to cortex attenuation and aorta-lesion attenuation difference (ALAD) on contrast-enhanced CT

PURPOSE

We investigate the use of ratio of lesion to cortex (L/C) attenuation and aorta-lesion attenuation difference (ALAD) on multiphase contrast-enhanced CT to help distinguish oncocytoma from clear cell RCC in small renal masses (diameter < 4 cm).

METHODS

We retrospectively identified 76 patients that undergo CT before surgery for a suspicious small renal mass between January 2014 and December 2018 with pathological diagnosis of 21 oncocytomas (ROs), 25 clear cell RCCs, 7 chromophobe RCCs, 7 papillary RCCs, 7 multilocular cystic RCCs, 7 angiomyolipomas and 2 leiomyomas. CT attenuation values were obtained for the tumor, the normal renal cortex and the aorta, placing a circular region of interest (ROI) in the same slice by two radiologists, independently.

RESULTS

In the corticomedullary phase, ROs showed isodense enhancement to the renal cortex (ratio L/C 0.92 ± 0.12), while clear cell RCCs appeared hypodense to the renal cortex (ratio L/C 0.69 ± 0.20; p < 0.01) with an accuracy of 80% for diagnosing RO. In nephrographic phase, the ratio L/C attenuation was lower than the corticomedullary phase in ROs (0.78 ± 0.11) showing an early washout pattern, while the ratio L/C was similar to the corticomedullary phase in clear cell RCCs (0.69 ± 0.13; p = 0.025, with an accuracy of 65% for diagnosing RO). The ratio L/C attenuation showed considerable overlap between ROs and clear cell RCCs in the excretory phase (p = 0.27). Mean ALAD values in the nephrographic phase were 21.95 ± 16.24 for ROs and 36.96 ± 30.53 for clear cell RCCs (p = 0.049).

CONCLUSION

The ratio L/C attenuation in corticomedullary phase may be useful to differentiate RO from clear cell RCC.

Tissue-specific and interpretable sub-segmentation of whole tumour burden on CT images by unsupervised fuzzy clustering

BACKGROUND

Cancer typically exhibits genotypic and phenotypic heterogeneity, which can have prognostic significance and influence therapy response. Computed Tomography (CT)-based radiomic approaches calculate quantitative features of tumour heterogeneity at a mesoscopic level, regardless of macroscopic areas of hypo-dense (i.e., cystic/necrotic), hyper-dense (i.e., calcified), or intermediately dense (i.e., soft tissue) portions.

METHOD

With the goal of achieving the automated sub-segmentation of these three tissue types, we present here a two-stage computational framework based on unsupervised Fuzzy C-Means Clustering (FCM) techniques. No existing approach has specifically addressed this task so far. Our tissue-specific image sub-segmentation was tested on ovarian cancer (pelvic/ovarian and omental disease) and renal cell carcinoma CT datasets using both overlap-based and distance-based metrics for evaluation.

RESULTS

On all tested sub-segmentation tasks, our two-stage segmentation approach outperformed conventional segmentation techniques: fixed multi-thresholding, the Otsu method, and automatic cluster number selection heuristics for the K-means clustering algorithm. In addition, experiments showed that the integration of the spatial information into the FCM algorithm generally achieves more accurate segmentation results, whilst the kernelised FCM versions are not beneficial. The best spatial FCM configuration achieved average Dice similarity coefficient values starting from 81.94±4.76 and 83.43±3.81 for hyper-dense and hypo-dense components, respectively, for the investigated sub-segmentation tasks.

CONCLUSIONS

The proposed intelligent framework could be readily integrated into clinical research environments and provides robust tools for future radiomic biomarker validation.

Outcomes and predictors of benign histology in patients undergoing robotic partial or radical nephrectomy for renal masses: a multicenter study

Introduction

Theaim of this study was to assess preoperative factors associated with benign histology in patients undergoing surgical removal of a renal mass and to analyze outcomes of robotic partial nephrectomy (PN) and radical nephrectomy (RN) for these masses.

Material and methods

Overall, 2,944 cases (543 benign and 2,401 malignant) who underwent robotic PN and RN between 2003–2018 at 10 institutions worldwide were included. The assessment of the predictors of benign histology was made at the final surgical pathology report. Descriptive statistics, Mann-Whitney U, Pearson’s χ², and logistic regression analysis were used.

Results

Patients in the benign group were mostly female (61 vs. 33%; p <0.001), with lower body mass index (BMI) (26.0 vs. 27.1 kg/m²; p <0.001). The benign group presented smaller tumor size (2.8 vs. 3.5 cm; p <0.001), R.E.N.A.L. score (6.0 vs. 7.0; p <0.001). There was a lower rate of hilar (11 vs.18%; p = 0.001), cT≥3 (1 vs. 4.5%; p <0.001) tumors in the benign group. There was a statistically significant higher rate of PN in the benign group (97 vs. 86%; p <0.001) as well as a statistically significant lower 30-day re-admission rate (2 vs. 5%; p = 0.081). Multivariable analysis showed male gender (OR: 0.52; p <0.001), BMI (OR: 0.95; p <0.001), and cT3a (OR: 0.22; p = 0.005) to be inversely associated to benign histology.

Conclusions

In 18% of cases, a benign histologic type was found. Only 3% of these tumors were treated with RN. Female gender, lower BMI, and higher T staging showed to be independent predictors of benign histology.