Diagnostic accuracy of contrast-enhanced computed tomography and contrast-enhanced magnetic resonance imaging of small renal masses in real practice: sensitivity and specificity according to subjective radiologic interpretation

Avoiding "Needless" nephrectomy: What is the role of small renal mass biopsy in 2024?

Current guidelines do not mandate routine preoperative renal mass biopsy (RMB) for small renal masses (SRMs), which results in a considerable rate (18%-26%) of needless nephrectomy/partial nephrectomy for benign renal tumors. In light of this ongoing practice, a narrative review was conducted to examine the role of routine RMB for SRM. First, arguments justifying the current non-biopsy approach to SRM are critically reviewed and contested. Second, as a standalone procedure, RMB is critically assessed; RMB was found to have higher sensitivity, specificity, and an equal or lower complication rate when compared with other commonly preoperatively biopsied solid organ tumors (e.g., breast, prostate, lung, pancreas, thyroid, and liver). Based on the foregoing information, we propose a paradigm shift in SRM management, advocating for an updated policy in which partial nephrectomy or nephrectomy for SRM invariably occurs only after a preoperative biopsy confirms that a SRM is indeed malignant.

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.

A Review of the Paradigmatic Role of Adipose Tissue in Renal Cancer: Fat Measurement and Tumor Behavior Features

(1) Background: Renal-cell carcinoma (RCC) incidence has been steadily rising, with obesity identified as a potential risk factor. However, the relationship between obesity and RCC prognosis remains unclear. This systematic review aims to investigate the impact of different adipose tissue measurements on RCC behavior and prognosis. (2) Methods: A search of MEDLINE databases identified 20 eligible studies focusing on various fat measurements, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), perirenal adipose tissue (PRAT), and the Mayo adhesive probability (MAP) score. (3) Results: The review revealed conflicting findings regarding the association between adipose tissue measurements and RCC outcomes. While some studies suggested a protective role of certain fat deposits, particularly VAT, against disease progression and mortality, others reported contradictory results across different adipose metrics and RCC subtypes. (4) Conclusions: Methodological variations and limitations, such as retrospective designs and sample size constraints, pose challenges to standardization and generalizability. Further research is needed to understand these associations better and establish standardized approaches for adiposity assessment in RCC patients, which could inform clinical practice and therapeutic decision-making.

Deep learning algorithm (YOLOv7) for automated renal mass detection on contrast-enhanced MRI: a 2D and 2.5D evaluation of results

INTRODUCTION

Accurate diagnosis and treatment of kidney tumors greatly benefit from automated solutions for detection and classification on MRI. In this study, we explore the application of a deep learning algorithm, YOLOv7, for detecting kidney tumors on contrast-enhanced MRI.

MATERIAL AND METHODS

We assessed the performance of YOLOv7 tumor detection on excretory phase MRIs in a large institutional cohort of patients with RCC. Tumors were segmented on MRI using ITK-SNAP and converted to bounding boxes. The cohort was randomly divided into ten benchmarks for training and testing the YOLOv7 algorithm. The model was evaluated using both 2-dimensional and a novel in-house developed 2.5-dimensional approach. Performance measures included F1, Positive Predictive Value (PPV), Sensitivity, F1 curve, PPV-Sensitivity curve, Intersection over Union (IoU), and mean average PPV (mAP).

RESULTS

A total of 326 patients with 1034 tumors with 7 different pathologies were analyzed across ten benchmarks. The average 2D evaluation results were as follows: Positive Predictive Value (PPV) of 0.69 ± 0.05, sensitivity of 0.39 ± 0.02, and F1 score of 0.43 ± 0.03. For the 2.5D evaluation, the average results included a PPV of 0.72 ± 0.06, sensitivity of 0.61 ± 0.06, and F1 score of 0.66 ± 0.04. The best model performance demonstrated a 2.5D PPV of 0.75, sensitivity of 0.69, and F1 score of 0.72.

CONCLUSION

Using computer vision for tumor identification is a cutting-edge and rapidly expanding subject. In this work, we showed that YOLOv7 can be utilized in the detection of kidney cancers.

MRI for the detection of small malignant renal masses: a systematic review and meta-analysis

Objective

We aimed to review the available evidence on the diagnostic performance of magnetic resonance imaging in differentiating malignant from benign small renal masses.

Methods

An electronic literature search of Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar was performed to identify relevant articles up to 31 January 2023. We included studies that reported the diagnostic accuracy of using magnetic resonance imaging to differentiate small (≤4 cm) malignant from benign renal masses. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using the bivariate model and the hierarchical summary receiver operating characteristic model. The study quality evaluation was performed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

Results

A total of 10 studies with 860 small renal masses (815 patients) were included in the current meta-analysis. The pooled sensitivity and specificity of the studies for the detection of malignant masses were 0.85 (95% CI 0.79-0.90) and 0.83 (95% CI 0.67-0.92), respectively.

Conclusions

MRI had a moderate diagnostic performance in differentiating small malignant renal masses from benign ones. Substantial heterogeneity was observed between studies for both sensitivity and specificity.

Small Renal Masses: Developing a Robust Radiomic Signature

(1) Background and (2) Methods: In this retrospective, observational, monocentric study, we selected a cohort of eighty-five patients (age range 38-87 years old, 51 men), enrolled between January 2014 and December 2020, with a newly diagnosed renal mass smaller than 4 cm (SRM) that later underwent nephrectomy surgery (partial or total) or tumorectomy with an associated histopatological study of the lesion. The radiomic features (RFs) of eighty-five SRMs were extracted from abdominal CTs bought in the portal venous phase using three different CT scanners. Lesions were manually segmented by an abdominal radiologist. Image analysis was performed with the Pyradiomic library of 3D-Slicer. A total of 108 RFs were included for each volume. A machine learning model based on radiomic features was developed to distinguish between benign and malignant small renal masses. The pipeline included redundant RFs elimination, RFs standardization, dataset balancing, exclusion of non-reproducible RFs, feature selection (FS), model training, model tuning and validation of unseen data. (3) Results: The study population was composed of fifty-one RCCs and thirty-four benign lesions (twenty-five oncocytomas, seven lipid-poor angiomyolipomas and two renal leiomyomas). The final radiomic signature included 10 RFs. The average performance of the model on unseen data was 0.79 ± 0.12 for ROC-AUC, 0.73 ± 0.12 for accuracy, 0.78 ± 0.19 for sensitivity and 0.63 ± 0.15 for specificity. (4) Conclusions: Using a robust pipeline, we found that the developed RFs signature is capable of distinguishing RCCs from benign renal tumors.

Diagnostic performance of multiparametric magnetic resonance imaging in the differentiation of clear cell renal cell cancer

PURPOSE

This study aimed to evaluate the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI) in the differentiation of renal cell carcinoma (RCC) subtypes.

METHODS

This is a retrospective diagnostic performance study, in which the diagnostic performances of mpMRI features were evaluated to differentiate clear cell RCC (ccRCC) from non-clear cell RCC (non-ccRCC). Adult patients who were evaluated using a 3-Tesla dynamic contrast-enhanced mpMRI before undergoing partial or radical nephrectomy for possible malignant renal tumors were included in the study. Signal intensity change percentages (SICP) between contrast-enhanced phases and pre-administration period for both the tumor and normal renal cortex, and tumor-to-cortex enhancement index (TCEI); tumor apparent diffusion coefficient (ADC) values; tumor-to-cortex ADC ratio; and a scale which was developed according to the tumor signal intensities on the axial fat-suppressed T2-weighted Half-Fourier Acquisition Single-shot Turbo spin Echo (HASTE) images were used in ROC analysis to estimate the presence of ccRCC in the patients. The reference test positivity was the histopathologic examination of the surgical specimens.

RESULTS

Ninety-eight tumors from 91 patients were included in the study, and 59 of them were ccRCC, 29 were pRCC, and 10 were chRCC. The mpMRI features that had the three highest sensitivity rates were excretory phase SICP, T2-weighted HASTE scale score, and corticomedullary phase TCEI (93.2%, 91.5%, and 86.4%, respectively). However, those with the three highest specificity rates were nephrographic phase TCEI, excretory phase TCEI, and tumor ADC value (94.9%, 94.9%, and 89.7%, respectively).

CONCLUSION

Several parameters on mpMRI showed an acceptable performance to differentiate ccRCC from non-ccRCC.

Utility of Fluorine18 Fluoro-2-deoxy-D-glucose Positron Emission Tomography/Computed Tomography in Metabolic Characterization of Solid Renal Mass Lesion and Localization of Extra Renal Lesions in the Body - A Prospective Study from the Tertiary Care Center in South India

Purpose of the Study

Renal mass lesions in majority of the cases are due to malignant etiology and about one-third of them are reported with metastatic lesions at the time of presentation. Thus proper investigational workup is needed for staging and thereby treatment planning. The current fluorine18 fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (F18-FDG PET/CT) study was designed to characterize renal mass lesions metabolically and identifying other metabolically active lesions in the body suggesting metastatic disease.

Materials and Methods

A total of 24 patients (males - 18 and females - 6) with a mean age of 53.8 ± 12.3 years were recruited in this study for dual time-point PET/CT scan. All patients with renal mass lesions underwent contrast-enhanced CT prior to PET/CT. Metabolic parameters such as maximum standardized uptake value (max.SUV) with a cut off ≥2.5 and retention index (RI) of ≥10% were used to label the lesion as malignant and remaining less than cutoff as benign. The final diagnosis of lesion on imaging was confirmed with a histopathological examination (HPE).

Results

Using max.SUV cut off value, 17/24 renal mass lesions were characterized as malignant and remaining 7/24 renal lesions of benign etiology. PET/CT showed sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 80%, 75%, 94.1%, 42.8%, and 79.1%, respectively, by considering HPE as a gold standard. Nine patients were diagnosed with distant site involvement suggestive of metastases.

Conclusion

F18-FDG PET/CT can efficiently characterize solid renal mass lesion as benign and malignant using metabolic parameters such as max.SUV and RI. In addition, whole-body survey identified distant site involvement in 25% of the patients, thus contributing change in management.

Development and Evaluation of a Novel Deep-Learning-Based Framework for the Classification of Renal Histopathology Images

Kidney cancer has several types, with renal cell carcinoma (RCC) being the most prevalent and severe type, accounting for more than 85% of adult patients. The manual analysis of whole slide images (WSI) of renal tissues is the primary tool for RCC diagnosis and prognosis. However, the manual identification of RCC is time-consuming and prone to inter-subject variability. In this paper, we aim to distinguish between benign tissue and malignant RCC tumors and identify the tumor subtypes to support medical therapy management. We propose a novel multiscale weakly-supervised deep learning approach for RCC subtyping. Our system starts by applying the RGB-histogram specification stain normalization on the whole slide images to eliminate the effect of the color variations on the system performance. Then, we follow the multiple instance learning approach by dividing the input data into multiple overlapping patches to maintain the tissue connectivity. Finally, we train three multiscale convolutional neural networks (CNNs) and apply decision fusion to their predicted results to obtain the final classification decision. Our dataset comprises four classes of renal tissues: non-RCC renal parenchyma, non-RCC fat tissues, clear cell RCC (ccRCC), and clear cell papillary RCC (ccpRCC). The developed system demonstrates a high classification accuracy and sensitivity on the RCC biopsy samples at the slide level. Following a leave-one-subject-out cross-validation approach, the developed RCC subtype classification system achieves an overall classification accuracy of 93.0% ± 4.9%, a sensitivity of 91.3% ± 10.7%, and a high classification specificity of 95.6% ± 5.2%, in distinguishing ccRCC from ccpRCC or non-RCC tissues. Furthermore, our method outperformed the state-of-the-art Resnet-50 model.

Diagnostic value of 18F-FDG PET/CT versus contrast-enhanced MRI for venous tumour thrombus and venous bland thrombus in renal cell carcinoma

The purpose of this study was to compare the ability of ¹⁸F-FDG PET/CT and contrast-enhanced MRI (CEMRI) to detect and grade venous tumour thrombus (VTT) and venous bland thrombus (VBT) in RCC and assess invasion of the venous wall by VTT. The PET/CT and CEMRI data of 41 patients with RCC were retrieved. The difference in maximum standardized uptake value (SUVmax) between VTT and VBT was analysed. According to their pathological diagnosis, the patients were divided into those with and without venous wall invasion. The PET/CT and CEMRI features, including the SUVmax of the primary lesion and VTT, maximum venous diameter, complete occlusion of the vein by VTT, and VTT morphology, were compared between the two groups. All 41 patients had VTT, and eleven of the 41 patients had VBT. The mean SUVmax of the VTT (6.33 ± 4. 68, n = 41) was significantly higher than that of the VBT (1.37 ± 0.26, n = 11; P < 0.001). Ten of the 11 cases of VBT were correctly diagnosed by ¹⁸F-FDG PET/CT, and all 11 were diagnosed by CEMRI. Both ¹⁸F-FDG PET/CT and CEMRI can effectively detect VTT and distinguish VTT from VBT. ¹⁸F-FDG PET/CT is less effective in grading VTT than CEMRI. Complete venous occlusion by VTT indicates venous wall invasion.

Differentiating Benign from Malignant Renal Tumors Using T2- and Diffusion-Weighted Images: A Comparison of Deep Learning and Radiomics Models Versus Assessment from Radiologists

BACKGROUND

Differentiating benign from malignant renal tumors is important for selection of the most effective treatment.

PURPOSE

To develop magnetic resonance imaging (MRI)-based deep learning (DL) models for differentiation of benign and malignant renal tumors and to compare their discrimination performance with the performance of radiomics models and assessment by radiologists.

STUDY TYPE

Retrospective.

POPULATION

A total of 217 patients were randomly assigned to a training cohort (N = 173) or a testing cohort (N = 44).

FIELD STRENGTH/SEQUENCE

Diffusion-weighted imaging (DWI) and fast spin-echo sequence T2-weighted imaging (T2WI) at 3.0T.

ASSESSMENT

A radiologist manually labeled the region of interest (ROI) on each image. Three DL models using ResNet-18 architecture and three radiomics models using random forest were developed using T2WI alone, DWI alone, and a combination of the two image sets to discriminate between benign and malignant renal tumors. The diagnostic performance of two radiologists was assessed based on professional experience. We also compared the performance of each model and the radiologists.

STATISTICAL TESTS

The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the performance of each model and the radiologists. P < 0.05 indicated statistical significance.

RESULTS

The AUC of the DL models based on T2WI, DWI, and the combination was 0.906, 0.846, and 0.925 in the testing cohorts, respectively. The AUC of the combination DL model was significantly better than that of the models based on individual sequences (0.925 > 0.906, 0.925 > 0.846). The AUC of the radiomics models based on T2WI, DWI, and the combination was 0.824, 0.742, and 0.826 in the testing cohorts, respectively. The AUC of two radiologists was 0.724 and 0.667 in the testing cohorts.

CONCLUSION

Thus, the MRI-based DL model is useful for differentiating benign from malignant renal tumors in clinic, and the DL model based on T2WI + DWI had the best performance.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

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.

Phase I study to assess safety, biodistribution and radiation dosimetry for 89Zr-girentuximab in patients with renal cell carcinoma

PURPOSE

In this phase I study, we evaluated the safety, biodistribution and dosimetry of [⁸⁹Zr]Zr-DFO-girentuximab (⁸⁹Zr-girentuximab) PET/CT imaging in patients with suspicion of clear cell renal cell carcinoma (ccRCC).

METHODS

Ten eligible patients received an intravenous administration of 37 MBq (± 10%) of ⁸⁹Zr-girentuximab at mass doses of 5 mg or 10 mg. Safety was evaluated according to the NCI CTCAE (version 4.03). Biodistribution and normal organ dosimetry was performed based on PET/CT images acquired at 0.5, 4, 24, 72 and 168 h post-administration. Additionally, tumour dosimetry was performed in patients with confirmed ccRCC and visible tumour uptake on PET/CT imaging.

RESULTS

⁸⁹Zr-girentuximab was administered in ten patients as per protocol. No treatment-related adverse events ≥ grade 3 were reported. ⁸⁹Zr-girentuximab imaging allowed successful differentiation between ccRCC and non-ccRCC lesions in all patients, as confirmed with histological data. Dosimetry analysis using OLINDA/EXM 2.1 showed that the organs receiving the highest doses (mean ± SD) were the liver (1.86 ± 0.40 mGy/MBq), the kidneys (1.50 ± 0.22 mGy/MBq) and the heart wall (1.45 ± 0.19 mGy/MBq), with a mean whole body effective dose of 0.57 ± 0.08 mSv/MBq. Tumour dosimetry was performed in the 6 patients with histologically confirmed ccRCC resulting in a median tumour-absorbed dose of 4.03 mGy/MBq (range 1.90-11.6 mGy/MBq).

CONCLUSIONS

This study demonstrates that ⁸⁹Zr-girentuximab is safe and well tolerated for the administered activities and mass doses and allows quantitative assessment of ⁸⁹Zr-girentuximab PET/CT imaging in patients with suspicion of ccRCC.

TRIAL REGISTRATION

NCT03556046-14th of June, 2018.

Infiltrative Renal Malignancies: Imaging Features, Prognostic Implications, and Mimics

Infiltrative renal malignancies are a subset of renal masses that are morphologically characterized by a poorly defined interface with the renal parenchyma. Infiltrative renal malignancies are less common but more aggressive than more typical renal malignancies and carry an overall worse prognosis. Although an infiltrative renal process often represents a malignant neoplasm, infiltrative masses include a wide spectrum of diseases including primary renal cortical, medullary, and pelvic tumors; lymphoproliferative processes; metastases; and various infectious, inflammatory, immune-mediated, and vascular mimics. The imaging features of these masses are often nonspecific, but with the appropriate history, laboratory results, and clinical context, the radiologist can help narrow the diagnosis and guide further treatment. An invited commentary by Lee is available online.Online supplemental material is available for this article. ^©RSNA, 2021.

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.

Prevalence of benign pathology after partial nephrectomy for suspected renal tumor: A systematic review and meta-analysis

OBJECTIVE

To investigate the overall prevalence of benign pathology after partial nephrectomy (PN) and identify predictive factors for benign pathology after PN.

METHODS

A systematic review was performed following the PRISMA guidelines. PubMed/Medline, Embase, and the Cochrane Library were searched up to January 2019PRISMA guidelines. The data for the meta-analysis and network meta-analysis were pooled using a random-effects model.

RESULTS

There were 144 studies included in the final analysis, which was comprised of 79 observational studies (n = 37,300) and 65 comparative studies (n = 18,552). The overall prevalence rate of benign pathology after PN was 0.19 (95% CI: 0.18-0.21). According to the procedure types, the prevalence rate of benign pathology was 0.17 (95% CI: 0.15-0.19), 0.24 (95% CI: 0.22-0.27), and 0.16 (95% CI: 0.15-0.18) in open partial nephrectomy, laparoscopic partial nephrectomy, and robot-assisted laparoscopic partial nephrectomy, respectively. The significant moderating factors were gender, publication year, the origin of the study, and procedure types. The three most common benign pathology types were oncocytomas, angiomyolipomas, and renal cysts (44.50%, 30.20%, and 10.99%, respectively).

CONCLUSIONS

The overall prevalence of benign pathology after PN was not low and it was affected by female gender, studies published before 2010, studies originating from Western areas, and laparoscopic procedure types.

ACR Appropriateness Criteria® Indeterminate Renal Mass

Renal masses are increasingly detected in asymptomatic individuals as incidental findings. CT and MRI with intravenous contrast and a dedicated multiphase protocol are the mainstays of evaluation for indeterminate renal masses. A single-phase postcontrast dual-energy CT can be useful when a dedicated multiphase renal protocol CT is not available. Contrast-enhanced ultrasound with microbubble agents is a useful alternative for characterizing renal masses, especially for patients in whom iodinated CT contrast or gadolinium-based MRI contrast is contraindicated. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Von Hippel-Lindau syndrome and renal tumours: radiological diagnostic and treatment options. A case report and literature review

Background

Von Hippel-Lindau disease (VHL) is a rare autosomal dominant syndrome diagnosed for 1 out of 36000-45000 newborns and 90% of the patients have a clinical manifestation before 65 years of age. Affected individuals have an increased risk of developing tumours in several organs or their systems. The most common tumours are retinal or central nervous system hemangioblastomas (60-80%) and VHL-associated renal lesions. Contrast-enhanced computer tomography (CECT) is the gold standard for the diagnosis and characterization of renal tumours. The best treatment option for VHL syndrome-caused renal tumours are nephron-sparing treatment techniques (cryotherapy, radiofrequency, or microwave ablation), which require imaging control. All these innovative treatment techniques are extremely important for VHL patients, because they increase the quality of life by staving off renal dialysis and preventing distant metastases.

Case report

Our case report presents a 16-year-old female with multiple renal cysts observed on ultrasound examination and clinically and molecularly diagnosed with Von Hippel-Lindau syndrome (deletion of the entire VHL gene). After that, for past 11 years multiple renal tumours were removed by cryoablation and patient monitoring on contrast-enhanced magnetic resonance (MRI) and CECT control scans was conducted.

Conclusions

Active multidisciplinary patient follow-up, routine radiological examinations, and correct treatment tactics allow controlling the  progression of renal cell carcinoma and other tumours associated with VHL syndrome, maintaining a normal organ function for a long time, and preventing distant metastases and fatal disease outcomes.

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Is percutaneous image-guided renal tumour ablation ready for prime time?

In the last few decades, thermal ablation (TA) techniques have been increasingly applied to treat small localised renal cell carcinomas. Despite this trend, there is still an underuse of TA compared to surgery and a substantial lack of high-quality evidence derived from large, prospective, randomised controlled trials comparing the long-term oncologic outcomes of TA and surgery. Therefore, in this narrative review, we assess published guidelines and recent literature concerning the diagnosis and management of kidney-confined renal cell carcinoma to understand whether percutaneous image-guided TA is ready to be proposed as a first-line treatment.

Deep learning based classification of solid lipid-poor contrast enhancing renal masses using contrast enhanced CT

OBJECTIVE

Establish a workflow that utilizes convolutional neural nets (CNN) to classify solid, lipid-poor, contrast enhancing renal masses using multiphase contrast enhanced CT (CECT) images and to assess the performance of the resulting network.

METHODS

In this institutional review board approved study of 143 patients with predominantly solid, lipid-poor, contrast enhancing renal lesions (46 benign and 97 malignant), patients with a pre-operative multiphase CECT of the abdomen and pelvis obtained between June 2009 and June 2015 were retrospectively queried. Benign renal masses included oncocytoma and lipid-poor angiomyolipoma and the malignant group included clear cell, papillary, and chromophobe carcinomas.Region of interests of whole tumor volumes were manually segmented, and CT phase images with the largest cross-section of the segmented tumor in the axial plane were used for assessment. Post-surgical pathological evaluation was used to establish diagnosis.The segmented images of renal masses were used as input to a CNN. The data were augmented and split into training (83.9%) and validation sets (16.1%) to determine the hyperparameters of the CNN. Thereafter. the performance of the resulting CNN was quantified using eightfold cross-validation.

RESULTS

The CNN-based classifier demonstrated an overall accuracy of 78% (95% confidence interval: 76-80%), sensitivity of 70% (95% confidence interval: 66-74%), specificity of 81% (79-83%) and an area under the curve of 0.82.

CONCLUSION

A CNN-based classifier to diagnose solid enhancing malignant renal masses based on multiphase CECT images was developed.

ADVANCES IN KNOWLEDGE

It was established that a CNN-based classifier could be trained to accurately distinguish malignant renal lesions.

Renal Cell Carcinoma Ablation: Preprocedural, Intraprocedural, and Postprocedural Imaging

The rising incidence of renal cell carcinoma (RCC) in recent decades necessitates careful consideration of additional treatment options, especially for patients who may be poor surgical candidates. An emerging body of evidence suggests that ablation may be performed effectively and safely even in patients with multiple comorbidities. Accordingly, clinical guidelines now include thermal ablation as an alternative for such patients with localized tumors that are 4.0 cm or smaller. Recent experience with these minimally invasive techniques has led to a greater understanding of the imaging findings that merit close attention when ablation is anticipated, or after it is performed. These imaging findings may guide the interventionalist's perception of the risks, technical challenges, and likelihood of treatment success associated with RCC ablation. The present review provides an overview of clinically relevant radiologic findings during the preprocedural, intraprocedural, and postprocedural period in the context of image-guided renal ablation. Keywords: Interventional-Body, Kidney, Percutaneous, Urinary © RSNA, 2019.

Association of Prevalence of Benign Pathologic Findings After Partial Nephrectomy With Preoperative Imaging Patterns in the United States From 2007 to 2014

Importance

Although the intent of nephron-sparing surgery is to eradicate malignant tumors found on preoperative imaging, benign masses often cannot be differentiated from malignant tumors. However, in the past there have been discrepancies in the reported percentages of benign masses removed by partial nephrectomy (PNx).

Objective

To investigate the annual trend of prevalence of benign pathologic findings after PNx and to investigate what potential factors are associated with this prevalence.

Design, Setting, and Participants

A total of 18 060 patients who underwent PNx between 2007 and 2014 were selected from Truven Health MarketScan Research Databases. We selected those patients who underwent PNx as an inpatient from 2007 and set the surgery date as the index date. Overall, a total of 21 445 patients with International Classification of Diseases, Ninth Revision, Clinical Modification code of 55.4 were identified from 2007 to 2015.

Main Outcomes and Measures

The annual trend of benign pathologic findings was described as an actual number and as a proportion. Univariate and multiple analyses were performed to investigate factors predictive of a benign final pathologic diagnosis, including type of preoperative imaging modality or performance of a renal mass biopsy.

Results

Among the 18 060 patients, mean (SD) age was 57 (12) years, and there were 10637 (58.9%) men and 7423 (41.1%) women. The overall prevalence of benign pathologic findings was 30.9% and the annual trends demonstrated a prevalence of over 30% for nearly every year of the study period. On univariate analysis, the performance of magnetic resonance imaging (MRI) and renal mass biopsy was associated with benign pathologic findings (P = .02 and P < .001, respectively). On multivariable analysis, female sex (odds ratio [OR], 0.62; 95% CI, 0.58-0.66; P < .001), older age (>65 years) (OR, 0.99; 95% CI, 0.99-0.99; P < .001), and computed tomography (CT) only preoperative imaging (OR, 1.16; 95% CI, 1.05-1.28; P = .004) were associated with benign pathologic findings after PNx.

Conclusions and Relevance

We found that the overall prevalence of benign pathologic findings after PNx was higher than the literature suggests, with consistent year-over-year rates exceeding 30%. Female sex, older age (>65 years), and CT only preoperative imaging were predictive of a benign tumor. Further elucidation concerning covariates associated with a benign diagnosis should be the focus of future investigations to identify a cohort of patients who could potentially avoid unnecessary surgical intervention.

National trends of preoperative imaging modalities before partial nephrectomy for renal masses in the U.S. from 2007-2015

INTRODUCTION

Although the performance of partial nephrectomies (PN) for renal masses has increased rapidly over the years, only a few studies have investigated the frequency and patterns of preoperative imaging modalities. The aim of this study was to investigate the frequency and patterns in preoperative imaging modalities before PN.

METHODS

A total of 21 445 patients who underwent PN between 2007 and 2015 were selected from a national representative population in the MarketScan database and included in this study. The annual incidence and proportion of PN, as well as the use of each preoperative imaging modality were analyzed.

RESULTS

Both annual crude number and frequency rate of PN decreased or became static since 2012. Computed tomography (CT) shows the greatest proportion of the crude number and percentage; despite a slight decrease in percentage, it is still >80%. Among the combinations, CT alone and CT combined with ultrasonography showed the highest performance rate during the complete observational period. The proportion of all other combinations, which include other complex combinations except CT alone, CT plus ultrasonography, CT plus magnetic resonance imaging (MRI), and CT plus MRI plus ultrasonography, was 13.95% in 2007, but increased to 19.04% in 2014.

CONCLUSIONS

CT still plays a major role in preoperative imaging for renal masses, whereby CT alone and CT combined with ultrasonography account for a major proportion of the preoperative imaging patterns. The use of other imaging combinations, as well as renal biopsies, shows an increasing trend. Additional studies are needed to investigate whether this trend in preoperative imaging is related to the frequency rate of PN.

Hyperpolarized 13C magnetic resonance imaging, using metabolic imaging to improve the detection and management of prostate, bladder, and kidney urologic malignancies

Approximately 25% of the 2 million new cancer diagnoses in the United States in 2018 were comprised of malignancies of the urogenital system. Of these cancers, 75% occurred in the kidney/renal pelvis, prostate, and urinary bladder. Early diagnosis is beneficial to long-term survival. Currently, urologists rely heavily on computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US), and positron emission tomography (PET) to both diagnose and offer prognoses, but these techniques are limited in their resolution and are more effective when cancers have reached macroscopic size in later stages. Recent developments in cancer metabolomics have revealed that cancerous cells preferentially upregulate specific metabolic pathways as a means of conserving their resources and maximizing their growth potential. This has opened a new avenue for early diagnosis with much higher resolution, reliability, and accuracy through ¹³C hyperpolarized MRI. Preferential cancer pathways can be elucidated through this technique using ¹³C-labeled molecules utilized for energy generation and tumor growth. As these pathways are identified, targeted therapies are being designed to inhibit these pathways to allow for treatment that is cytotoxic to malignant cells but preserves native cells. In this paper, we review the current understanding of urologic cancer metabolomics, specifically in the kidney, prostate, and bladder. We will review the basic physics of MRI and demonstrate how hyperpolarized ¹³C MRI offers an innovative solution to early diagnosis as well as creates novel avenues for more targeted therapy.

Diagnostic Imaging for Solid Renal Tumors: A Pictorial Review

The prognosis of renal tumors depends on histologic subtype. The increased use of abdominal imaging has resulted in an increase in the number of small renal incidentaloma in recent decades. Of these incidentally discovered tumors, 20% are benign lesions warranting conservative management, but most are renal cell carcinomas that warrant a more aggressive therapeutic approach due to their malignant potential. Dedicated diagnostic renal imaging is important for characterization of renal tumors to facilitate treatment planning. This review discusses the ability to detect and differentiate renal cell carcinoma subtypes, angiomyolipoma and oncocytoma based on ultrasound imaging, computed tomography, multiparametric magnetic resonance, and nuclear imaging.

Impact of tumor size on the outcome of patients with small renal cell carcinoma

BACKGROUND

​This study aims to establish potential correlation between tumor size and outcomes in patients with T1a kidney cancer registered within the surveillance, epidemiology and end results (SEER) database.

METHODS

SEER database (2004-2013) has been accessed through SEER*Stat program to determine the correlation between tumor size and cancer-specific survival in patients with T1a kidney cancer.  Survival analysis was conducted through Kaplan-Meier analysis and log-rank testing.

RESULTS

Five year kidney cancer-specific survival rates show progressive decline with increasing tumor size.  Moreover, kidney cancer-specific survival has been compared according to the initial local treatment modality (observation, ablation, partial or radical nephrectomy) across different size categories (<1 cm, 1-2 cm, 2-3 cm and 3-4 cm).  Survival curves of different treatment modalities were almost overlapping for patients with renal mass < 1cm. For patients with tumor size 1-2 cm, treatment modalities were overlapping at the first 60 months then the curve of observation diverged (P <0.0001). For patients with tumor size 2-3 cm and 3-4 cm, the curve of observation diverged early in the time course (P <0.0001).

CONCLUSION

Primary tumor size is an important factor that should be taken into consideration when evaluating the different treatment options for patients with small kidney cancers.​.