Diffusion-weighted imaging of focal renal lesions: a meta-analysis. Eur Radiol. 2014;24:241-249. [PMID: 24337912 DOI: 10.1007/s00330-013-3004-x]

PEComas: A review of imaging and clinical features

Perivascular epithelioid cell tumors (PEComas) are a group of rare mesenchymal tumors, which demonstrate varied imaging appearances and treatment options. These tumors may arise de novo or in the setting of systemic disorders, such as tuberous sclerosis. Some PEComas are benign and easily resected while others may represent systemic or metastatic disease with limited therapeutic options. The purpose of this review is to introduce the topic of perivascular epithelioid cell tumors and the most common tumors within the PEComa family as well as discuss the epidemiology, morphology, radiographic appearance, and treatment options of these rare tumors.

Treatment of fat-poor renal angiomyolipoma with ectopic blood supply by fluorescent laparoscopy: A case report and review of literature

BACKGROUND

Renal angiomyolipoma and renal cell carcinoma are the most common benign and malignant tumors of the kidney respectively, and the preoperative differential diagnosis is crucial due to the wide difference in treatment methods. Fat-poor renal angiomyolipoma is a relatively rare type of in renal angiomyolipoma. Its fat imaging features are not obvious, and it is easily misdiagnosed as renal cell carcinoma.

CASE SUMMARY

We report the case of a 41-year-old man who complained of osphyalgia. Subsequent abdominal computed tomography scans revealed that a heterogeneous mass was seen in the lower pole of the right kidney, with the size of about 53 mm × 47 mm. And showed two right renal arteries, with the mass supplied by an ectopic vessel from the abdominal aorta. Fluorescent laparoscopic blockade of the right renal heterotopic artery and partial nephrectomy was performed. Based on histological and immunohistochemical findings, the tumor was diagnosed as fat-poor renal angiomyolipoma.

CONCLUSION

The use of fluorescent laparoscopy can effectively help intraoperative management, and the fluorescence pattern provided by intravenous indocyanine green can help suggest the final diagnosis, effectively guide the surgical decision-making, and avoid preoperative imaging diagnosis leading to nephrectomy for benign renal tumors, through fluorescent navigation of tumor supply vessel precise block, minimize the loss of renal function.

Molecular Characterization of Metastatic Oncocytoma With Exceptional Response to Treatment: A Case Report

Comprehensive molecular characterization and effective therapy in a rare case of metastatic renal oncocytoma.

Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics

Background: Small renal masses (SRMs) are defined as contrast-enhanced renal lesions less than or equal to 4 cm in maximal diameter, which can be compatible with stage T1a renal cell carcinomas (RCCs). Currently, 50-61% of all renal tumors are found incidentally. Methods: The characteristics of the lesion influence the choice of the type of management, which include several methods SRM of management, including nephrectomy, partial nephrectomy, ablation, observation, and also stereotactic body radiotherapy. Typical imaging methods available for differentiating benign from malignant renal lesions include ultrasound (US), contrast-enhanced ultrasound (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI). Results: Although ultrasound is the first imaging technique used to detect small renal lesions, it has several limitations. CT is the main and most widely used imaging technique for SRM characterization. The main advantages of MRI compared to CT are the better contrast resolution and tissue characterization, the use of functional imaging sequences, the possibility of performing the examination in patients allergic to iodine-containing contrast medium, and the absence of exposure to ionizing radiation. For a correct evaluation during imaging follow-up, it is necessary to use a reliable method for the assessment of renal lesions, represented by the Bosniak classification system. This classification was initially developed based on contrast-enhanced CT imaging findings, and the 2019 revision proposed the inclusion of MRI features; however, the latest classification has not yet received widespread validation. Conclusions: The use of radiomics in the evaluation of renal masses is an emerging and increasingly central field with several applications such as characterizing renal masses, distinguishing RCC subtypes, monitoring response to targeted therapeutic agents, and prognosis in a metastatic context.

Renal Mass Imaging with MRI Clear Cell Likelihood Score: A User's Guide

Small solid renal masses (SRMs) are frequently detected at imaging. Nearly 20% are benign, making careful evaluation with MRI an important consideration before deciding on management. Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma subtype with potentially aggressive behavior. Thus, confident identification of ccRCC imaging features is a critical task for the radiologist. Imaging features distinguishing ccRCC from other benign and malignant renal masses are based on major features (T2 signal intensity, corticomedullary phase enhancement, and the presence of microscopic fat) and ancillary features (segmental enhancement inversion, arterial-to-delayed enhancement ratio, and diffusion restriction). The clear cell likelihood score (ccLS) system was recently devised to provide a standardized framework for categorizing SRMs, offering a Likert score of the likelihood of ccRCC ranging from 1 (very unlikely) to 5 (very likely). Alternative diagnoses based on imaging appearance are also suggested by the algorithm. Furthermore, the ccLS system aims to stratify which patients may or may not benefit from biopsy. The authors use case examples to guide the reader through the evaluation of major and ancillary MRI features of the ccLS algorithm for assigning a likelihood score to an SRM. The authors also discuss patient selection, imaging parameters, pitfalls, and areas for future development. The goal is for radiologists to be better equipped to guide management and improve shared decision making between the patient and treating physician. © RSNA, 2023 Quiz questions for this article are available in the supplemental material. See the invited commentary by Pedrosa in this issue.

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.

Role of multiparametric MRI in characterization of complicated cystic renal masses

Background

Bosniak classification improves sensitivity and specificity for malignancy among cystic renal masses characterized with MRI. The quantitative parameters derived from diffusion-weighted imaging, and contrast enhancement, can be used in distinguishing between benign and malignant cystic renal masses.

Methods

This prospective observational study included 58 patients (39 male and 19 female) with complicated cystic renal mass initially diagnosed by US or CT. All patients underwent multiparametric MRI study (Pre- and Post-Gd-enhanced T1WI, T2WI and DWI) by using 3 Tesla MRI scanner. Each cystic renal lesion was assigned a category based on Bosniak classification. Demographic data were recorded. ADC ratio, dynamic enhancement parameters in both corticomedullary and nephrographic phases as well as absolute washout were calculated and compared using ROC curve analysis.

Results

The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the multiparametric MRI in categorization of cystic renal masses according to Bosniak classification version 2019 were 90.32%, 100%, 100%, 90% and 94.83%, respectively, which was higher compared to biparametric MRI and conventional MRI.

Conclusions

Multiparametric MRI can be utilized to confidently evaluate cystic renal masses, overcoming the traditional limitations of overlapping morphological imaging features. Quantitative parameters derived from multiparametric MRI allow better evaluation of complex cystic renal tumors to distinguish between benign and malignant complex cystic renal lesions.

Diagnostic Performance and Interreader Agreement of the MRI Clear Cell Likelihood Score for Characterization of cT1a and cT1b Solid Renal Masses: An External Validation Study

BACKGROUND. The clear cell likelihood score (ccLS) has been proposed for the noninvasive differentiation of clear cell renal cell carcinoma (ccRCC) from other renal neoplasms on multiparametric MRI (mpMRI), though further external validation remains needed. OBJECTIVE. The purpose of our study was to evaluate the diagnostic performance and interreader agreement of the ccLS version 2.0 (v2.0) for characterizing solid renal masses as ccRCC. METHODS. This retrospective study included 102 patients (67 men, 35 women; mean age, 56.9 ± 12.8 [SD] years) who underwent mpMRI between January 2013 and February 2018, showing a total of 108 (≥ 25% enhancing tissue) solid renal masses measuring 7 cm or smaller (83 cT1a [≤ 4 cm] and 25 cT1b [> 4 cm and ≤ 7 cm]), all with a histologic diagnosis. Three abdominal radiologists independently reviewed the MRI examinations using ccLS v2.0. Median reader sensitivity, specificity, and accuracy were computed for predicting ccRCC by ccLS of 4 or greater, and individual reader AUCs were derived. The percentage of masses that were ccRCC was calculated, stratified by ccLS. Interobserver agreement was assessed by the Fleiss kappa statistic. RESULTS. The sample included 45 ccRCCs (34 cT1a, 11 cT1b), 30 papillary renal cell carcinomas (RCCs), 13 chromophobe RCCs, 14 oncocytomas, and six fat-poor angiomyolipomas. Median reader sensitivity, specificity, and accuracy for predicting ccRCC by ccLS of 4 or greater were 85%, 82%, and 83% among cT1a masses and 82%, 100%, and 92% among cT1b masses. The three readers' AUCs for predicting ccRCC by ccLS for cT1a masses were 0.90, 0.84, and 0.89 and for cT1b masses were 0.99, 0.97, and 0.92. Across readers, the percentage of masses that were ccRCC among cT1a masses was 0%, 0%, 20%, 68%, and 93% for ccLS of 1, 2, 3, 4, and 5, respectively; among cT1b masses, the percentage of masses that were ccRCC was 0%, 0%, 32%, 90%, and 100% for ccLS of 1, 2, 3, 4, and 5, respectively. Interobserver agreement among cT1a and cT1b masses for ccLS of 4 or greater was 0.82 and 0.83 and for ccLS of 1-5 overall was 0.65 and 0.62, respectively. CONCLUSION. This study provides external validation of the ccLS, finding overall high measures of diagnostic performance and interreader agreement. CLINICAL IMPACT. The ccLS provides a standardized approach to the noninvasive diagnosis of ccRCC by MRI.

Bosniak classification of cystic renal masses, version 2019: Is it helpful to incorporate the diffusion weighted imaging characteristic of lesions into the guideline?

Objective

To improve understanding of diffusion weighted imaging (DWI) characteristic of MRI and clinical variables, further optimize the Bosniak classification for diagnosis of cystic renal masses (CRMs).

Methods

This study retrospectively analyzed 130 CRMs in 125 patients with CT or MRI, including 87 patients with DWI (b = 600, 1000 s/mm2). Clinical variables and histopathological results were recorded. Two radiologists in consensus analyzed images of each lesion for the size, thickness of wall, number of septum, enhancement of wall/septum, wall nodule, signal intensity on DWI, calcification, and cyst content. Clinical variables, CT and MRI image characteristics were compared with pathology or follow-up results to evaluate the diagnostic performance for CRMs.

Results

Of the 130 lesions in 125 patients, histological analysis reported that 36 were malignant, 38 were benign, and no change was found in 56 followed-up lesions (mean follow-up of 24 months). The incidences of cystic wall thickened, more septa, measurable enhancement of wall/septum, nodule(s) on CT/MRI, and high signal intensity on DWI were significantly higher in malignant than in benign CRMs (CT: p = 0.005, p < 0.001, p < 0.001, p < 0.001, p < 0.001; MRI: p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001). Combination of MRI including DWI features with CT findings showed the highest area under ROC curve (0.973) in distinguishing benign and malignant CRMs.

Conclusions

Incorporating DWI characteristic of CRMs into Bosniak classification helps to improve diagnostic efficiency.

Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme

Purpose

To develop a system for multi-parametric MRI to differentiate benign from malignant solid renal masses and assess its accuracy compared to the gold standard of histopathological diagnosis.

Methods

This is a retrospective analysis of patients who underwent 3 Tesla mpMRI for further assessment of small renal tumours with specific scanning and reporting protocol incorporating T2 HASTE signal intensity, contrast enhancement ratios, apparent diffusion coefficient and presence of microscopic/macroscopic fat. All MRIs were reported prior to comparison with histopathologic diagnosis and a reporting scheme was developed. 2 × 2 contingency table analysis (sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)), Fisher Exact test were used to assess the association between suspicion of malignancy on mpMRI and histopathology, and descriptive statistics were performed.

Results

67 patients were included over a 5-year period with a total of 75 renal masses. 70 masses were confirmed on histopathology (five had pathognomonic findings for angiomyolipomas; biopsy was therefore considered unethical, so these were included without histopathology). Three patients were excluded due to a non-diagnostic result, non-standardised imaging and one found to be an organising haematoma rather than a mass. Therefore 72 cases were included in analysis (in 64 patients, with seven patients having multiple tumours). Unless otherwise specified, all further statistics refer to individual tumours rather than patients. 52 (72.2%) were deemed ‘suspicious or malignant’ and 20 (27.8%) were deemed ‘benign’ on mpMRI. 51 cases (70.8%) had renal cell carcinoma confirmed. The sensitivity, NPV, specificity and PPV for MRI for detecting malignancy were 96.1%, 90%, 85.7% and 94.2% respectively, Fisher’s exact test demonstrated p < 0.0001 for the association between suspicion of malignancy on MRI and histopathology.

Conclusion

The de Silva St George classification scheme performed well in differentiating benign from malignant solid renal masses, and may be useful in predicting the likelihood of malignancy to determine the need for biopsy/excision. Further validation is required before this reporting system can  be recommended for clinical use.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-022-01082-9.

Differentiation of benign from malignant solid renal lesions with MRI-based radiomics and machine learning

BACKGROUND

Solid renal masses are often indeterminate for benignity versus malignancy on magnetic resonance imaging. Such masses are typically evaluated with either percutaneous biopsy or surgical resection. Percutaneous biopsy can be non-diagnostic and some surgically resected lesions are inadvertently benign.

PURPOSE

To assess the performance of ten machine learning (ML) algorithms trained with MRI-based radiomics features in distinguishing benign from malignant solid renal masses.

METHODS

Patients with solid renal masses identified on pre-intervention MRI were curated from our institutional database. Masses with a definitive diagnosis via imaging (for angiomyolipomas) or via biopsy or surgical resection (for oncocytomas or renal cell carcinomas) were selected. Each mass was segmented for both T2- and post-contrast T1-weighted images. Radiomics features were derived from the segmented masses for each imaging sequence. Ten ML algorithms were trained with the radiomics features gleaned from each MR sequence, as well as the combination of MR sequences.

RESULTS

In total, 182 renal masses in 160 patients were included in the study. The support vector machine algorithm trained on radiomics features from T2-weighted images performed superiorly, with an accuracy of 0.80 and an area under the curve (AUC) of 0.79. Linear discriminant analysis (accuracy = 0.84 and AUC = 0.77) and logistic regression (accuracy = 0.78 and AUC = 0.78) algorithms trained on T2-based radiomics features performed similarly. ML algorithms trained on radiomics features from post-contrast T1-weighted images or the combination of radiomics features from T2- and post-contrast T1-weighted images yielded lower performance.

CONCLUSION

Machine learning models trained with radiomics features derived from T2-weighted images can provide high accuracy for distinguishing benign from malignant solid renal masses.

CLINICAL IMPACT

Machine learning models derived from MRI-based radiomics features may improve the clinical management of solid renal masses and have the potential to reduce the frequency with which benign solid renal masses are biopsied or surgically resected.

Real world outcomes of biopsy-proven oncocytic neoplasm of the kidney managed by surveillance

Objectives

To evaluate outcomes of patients diagnosed with oncocytic renal neoplasms on routine renal mass biopsy and to describe the natural history of these tumours when managed with surveillance as opposed to immediate intervention. To report disease-specific survival.

Patients and methods

Patients were identified from a retrospective review of pathology databases from three tertiary referral centres that utilise renal mass biopsy in routine clinical practice. All patients with biopsy-proven oncocytic tumours were included and a retrospective review of online patient records was undertaken.

Results

There were 184 biopsy-proven oncocytic renal neoplasms identified in 172 patients. There were two biopsy complications (both pneumothorax, Clavien-Dindo Grade I). Of these lesions, 135 were reported as oncocytomas or oncocytic renal neoplasms that were not further classified and 37 were reported as chromophobe carcinoma (ChRCC). The median age at diagnosis was 70 (33-88). The average tumour diameter at diagnosis was 33 mm. One hundred seven tumours were initially managed with surveillance (including 13 ChRCC) with a minimum follow-up of 6 months and a median of 39 months (6-144) whereas 49 patients underwent immediate treatment. The mean growth rate across all oncocytic renal neoplasms managed by surveillance was 3 mm/year. There was no statistically significant difference in growth rates between oncocytic renal neoplasms and ChRCC. Thirteen patients with oncocytic renal neoplasms initially managed by surveillance moved on to an active management strategy during follow-up. The clinical indication given for a change from surveillance was tumour growth in 12 cases and patient choice in 1 case. Where definitive pathology was available, there was 85% concordance with the biopsy. There were no cases of development of metastatic disease or disease-related morbidity or mortality during the study.

Conclusions

This multicentre retrospective cohort study supports the hypothesis that selected biopsy-proven oncocytic renal neoplasms can be safely managed with surveillance in the medium term. Routine renal mass biopsy may reduce surgery for benign or indolent renal tumours and the potential associated morbidity for these patients.

Ultrasound, CT, and MR Imaging for Evaluation of Cystic Renal Masses

Cystic renal masses are often encountered during abdominal imaging. Although most of them are benign simple cysts, some cystic masses have malignant characteristics. The Bosniak classification system provides a useful way to classify cystic masses. The Bosniak classification is based on the results of a well-established computed tomography protocol. Over the past 30 years, the classification system has been refined and improved. This paper reviews the literature on this topic and compares the advantages and disadvantages of different screening and classification methods. Patients will benefit from multimodal diagnosis for lesions that are difficult to classify after a single examination.

Apparent Diffusion Coefficient Map-Based Texture Analysis for the Differentiation of Chromophobe Renal Cell Carcinoma from Renal Oncocytoma

Preoperative imaging differentiation between ChRCC and RO is difficult with conventional subjective evaluation, and the development of quantitative analysis is a clinical challenge. Forty-nine patients underwent partial or radical nephrectomy preceded by MRI and followed by pathological diagnosis with ChRCC or RO (ChRCC: n = 41, RO: n = 8). The whole-lesion volume of interest was set on apparent diffusion coefficient (ADC) maps of 1.5T-MRI. The importance of selected texture features (TFs) was evaluated, and diagnostic models were created using random forest (RF) analysis. The Mean Decrease Gini as calculated through RF analysis was the highest for mean_ADC_value. ChRCC had a significantly lower mean_ADC_value than RO (1.26 vs. 1.79 × 10−3 mm2/s, p < 0.0001). Feature selection by the Boruta method identified the first-quartile ADC value and GLZLM_HGZE as important features. ROC curve analysis showed that there was no significant difference in the classification performances between the mean_ADC_value-only model and the Boruta model (AUC: 0.954 vs. 0.969, p = 0.236). The mean ADC value had good predictive ability for the distinction between ChRCC and RO, comparable to that of the combination of TFs optimized for the evaluated cohort. The mean ADC value may be useful in distinguishing between ChRCC and RO.

Common Subtype of Small Renal Mass MR Imaging Characterisation: A Medical Center Experience in Taiwan

Purpose

Many studies have shown that multiparametric magnetic resonance imaging (MRI) may be helpful for differentiating malignant renal cell carcinomas (RCCs) from benign lesions. However, the key imaging characteristics that differ between malignant and benign tumors still require further discussion.

Methods

We analyzed 60 adult patients diagnosed with 72 small renal masses (SRMs) who received preoperative MRI from 2014 to 2019 at a hospital in Taiwan. The MRI features included conventional MRI parameters, diffusion-weighted imaging (DWI) data, and dynamic contrast-enhanced (DCE) patterns, which were documented and compared among the four common subtypes: clear cell RCC (ccRCC), papillary RCC (pRCC), angiomyolipoma (AML) and other types of RCC. The apparent diffusion coefficient (ADC) values of high- and low-grade RCCs were also analyzed.

Results

The results show that ccRCC had higher T2-weighted signal intensity than the other three subgroups, a higher arterial wash-in index (AWI) and ADC value than AML and pRCC, and manifested a plateau (n = 9, 25%) or washout (n = 27, 75%) enhancement pattern. AMLs exhibited more intravoxel fat than the other three subtype groups, and half of the AMLs (6 in 12) contained bulk fat. pRCC demonstrated a more progressive (n = 3, 60%) enhancement pattern than the other three subgroups. The ADC value of high-grade RCCs was significantly lower than that of low-grade RCCs.

Conclusion

These findings may indicate that multiparametric MRI is useful in differentiating among four common pathological types of SRMs, and the ADC value may be helpful in evaluating the histological grade of malignancy.

Renal Cell Carcinoma or Oncocytoma? The Contribution of Diffusion-Weighted Magnetic Resonance Imaging to the Differential Diagnosis of Renal Masses

Background and Objectives: Renal Cell Carcinoma (RCC) accounts for 85% and oncocytomas constitute 3–7% of solid renal masses. Oncocytomas can be confused, especially with hypovascular RCC. The purpose of this research was to evaluate the contribution of diffusion-weighted imaging (DWI) and contrast-enhanced MRI sequences in the differential diagnosis of RCC and oncocytoma Materials and Methods: 465 patients with the diagnosis of RCC and 45 patients diagnosed with oncocytoma were retrospectively reviewed between 2009 to 2020. All MRI acquisitions were handled by a 1.5 T device (Achieva, Philips Healthcare, Best, The Netherlands) and all images were evaluated by the consensus of two radiologists with 10–15 years’ experience. The SPSS package program version 15.0 software was used for statistical analysis of the study. Chi-square test, Mann–Whitney U test or the Kruskal–Wallis tests were used in the statistical analysis. A receiver operating characteristic (ROC) curve was used to calculate the cut-off values Results: The results were evaluated with a 95% confidence interval and a significance threshold of p < 0.05. ADC values (p < 0.001) and enhancement index (p < 0.01) were significantly lower in the RCC group than the oncocytoma group. Conclusion: DWI might become an alternative technique to the contrast-enhanced MRI in patients with contrast agent nephropathy or with a high risk of nephrogenic systemic fibrosis, calculation of CI of the oncocytoma and RCCs in the contrast-enhanced acquisitions would contribute to the differential diagnosis.

Kidney tumor diffusion-weighted magnetic resonance imaging derived ADC histogram parameters combined with patient characteristics and tumor volume to discriminate oncocytoma from renal cell carcinoma

PURPOSE

To assess the ability to discriminate oncocytoma from RCC based on a model using whole tumor ADC histogram parameters with additional use of tumor volume and patient characteristics.

METHOD

In this prospective study, 39 patients (mean age 65 years, range 28-79; 9/39 (23%) female) with 39 renal tumors (32/39 (82%) RCC and 7/39 (18%) oncocytoma) underwent multiparametric MRI between November 2014 and June 2018. Two regions of interest (ROIs) were drawn to cover both the entire tumor volume and a part of healthy renal cortex. ROI ADC maps were calculated using a mono-exponential model and ADC histogram distribution parameters were calculated. A logistic regression model was created using ADC histogram parameters, radiographic and patient characteristics that were significantly different between oncocytoma and RCC. A ROC curve of the model was constructed and the AUC, sensitivity and specificity were calculated. Furthermore, differences in intra-patient ADC histogram parameters between renal tumor and healthy cortex were calculated. A separate ROC curve was constructed to differentiate oncocytoma from RCC using statistically significant intra-patient parameter differences.

RESULTS

ADC standard deviation (p = 0.008), entropy (p = 0.010), tumor volume (p = 0.012), and patient sex (p = 0.018) were significantly different between RCC and oncocytoma. The regression model of these parameters combined had an ROC-AUC of 0.91 with a sensitivity of 86% and specificity of 84%. Intra-patient difference in ADC 25th percentile (p < 0.01) and entropy (p = 0.030) combined had a ROC-AUC of 0.86 with a sensitivity and specificity of 86%, and 81%, respectively.

CONCLUSION

A model combining ADC standard deviation and entropy with tumor volume and patient sex has the highest diagnostic value for discrimination of oncocytoma. Although less accurate, intra-patient difference in ADC 25th percentile and entropy between renal tumor and healthy cortex can also be used. Although the results of this preliminary study do not yet justify clinical use of the model, it does stimulate further research using whole tumor ADC histogram parameters.

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.

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.

Apparent diffusion coefficient cannot discriminate metastatic and non-metastatic lymph nodes in rectal cancer: a meta-analysis

BACKGROUND

Our aim was to provide data regarding use of diffusion-weighted imaging (DWI) for distinguishing metastatic and non-metastatic lymph nodes (LN) in rectal cancer.

METHODS

MEDLINE library, EMBASE, and SCOPUS database were screened for associations between DWI and metastatic and non-metastatic LN in rectal cancer up to February 2021. Overall, 9 studies were included into the analysis. Number, mean value, and standard deviation of DWI parameters including apparent diffusion coefficient (ADC) values of metastatic and non-metastatic LN were extracted from the literature. The methodological quality of the studies was investigated according to the QUADAS-2 assessment. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian, and Laird random-effects models with inverse-variance weights were used to account the heterogeneity between the studies. Mean DWI values including 95% confidence intervals were calculated for metastatic and non-metastatic LN.

RESULTS

ADC values were reported for 1376 LN, 623 (45.3%) metastatic LN, and 754 (54.7%) non-metastatic LN. The calculated mean ADC value (× 10-3 mm2/s) of metastatic LN was 1.05, 95%CI (0.94, 1.15). The calculated mean ADC value of the non-metastatic LN was 1.17, 95%CI (1.01, 1.33). The calculated sensitivity and specificity were 0.81, 95%CI (0.74, 0.89) and 0.67, 95%CI (0.54, 0.79).

CONCLUSION

No reliable ADC threshold can be recommended for distinguishing of metastatic and non-metastatic LN in rectal cancer.

18Fluorodeoxyglucose-positron emission tomography/computed tomography for differentiation of renal tumors in hereditary kidney cancer syndromes

PURPOSE

To assess differences in FDG-PET/CT uptake among four subtypes of renal tumors: clear cell RCC (ccRCC), papillary type I and II RCC (pRCC), and oncocytoma.

METHODS

This retrospective study investigated 33 patients with 98 hereditary renal tumors. Lesions greater than 1 cm and patients with a timeframe of less than 18 months between preoperative imaging and surgery were considered. FDG-PET/CT images were independently reviewed by two nuclear medicine physicians, blinded to clinical information. Volumetric lesion SUV_mean was measured and used to calculate a target-to-background ratio respective to liver (TBR). The Shrout-Fleiss intra-class correlation coefficient was used to assess reliability between readers. A linear mixed effects model, accounting for within-patient correlations, was used to compare TBR values of primary renal lesions with and without distant metastasis.

RESULTS

The time interval between imaging and surgery for all tumors had a median of 77 (Mean: 139; Range: 1-512) days. Intra-class reliability of mean TBR resulted in a mean κ score of 0.93, indicating strong agreement between the readers. The mixed model showed a significant difference in mean TBR among the subtypes (p < 0.0001). Pairwise comparison showed significant differences between pRCC type II and ccRCC (p < 0.0001), pRCC type II and pRCC type I (p = 0.0001), and pRCC type II and oncocytoma (p = 0.0016). Furthermore, a significant difference in FDG uptake was present between primary pRCC type II renal lesions with and without distant metastasis (p = 0.023).

CONCLUSION

pRCC type II lesions demonstrated significantly higher FDG activity than ccRCC, pRCC type I, or oncocytoma. These findings indicate that FDG may prove useful in studying the metabolic activity of renal neoplasms, identifying lesions of highest clinical concern, and ultimately optimizing active surveillance, and personalizing management plans.

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.

The diagnostic utility of diffusion weighted MRI imaging and ADC ratio to distinguish benign from malignant renal masses: sorting the kittens from the tigers

Background

MRI is playing an increasing role in risk stratification and non-invasive diagnosis of the undifferentiated small renal mass. This study was designed to assess the reliability of MRI in diagnostic evaluation of renal masses, specifically characterising lesions with diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) values.

Methods

This is a retrospective analysis of patients undergoing MRI as part of their clinical workup for a renal mass suspicious for renal cell carcinoma (RCC) on CT or ultrasound followed by biopsy and/or surgical excision. All cases were conducted on 3 Tesla MRI, with conventional breath-held sequences, DWI and dynamic contrast enhanced phases. Tumour regions of interest were evaluated on ADC maps and compared with T2 weighted and post-contrast images.

Results

Of the 66 renal tumours included, 33 (50.0%) were Clear Cell RCC, 11 (16.7%) were Oncocytoma, nine (13.6%) were Angiomyolipoma (AML), nine (13.6%) were Papillary RCC and four (6.1%) were Chromophobe RCC. Oncocytoma had the largest ADC values, significantly larger than AMLs and all RCC subtypes (p < 0.001). The average ADC value was also significantly larger in Clear Cell RCCs compared to AMLs, and other RCC subtypes (p < 0.001).

Conclusions

MRI with DWI/ADC imaging may aid the differentiation of oncocytomas from RCCs and stratify RCC subtypes, Further studies are required to validate these findings.

Trial registration: Not applicable/retrospective study.

Imaging Characterization of Renal Masses

The detection of a renal mass is a relatively frequent occurrence in the daily practice of any Radiology Department. The diagnostic approaches depend on whether the lesion is cystic or solid. Cystic lesions can be managed using the Bosniak classification, while management of solid lesions depends on whether the lesion is well-defined or infiltrative. The approach to well-defined lesions focuses mainly on the differentiation between renal cancer and benign tumors such as angiomyolipoma (AML) and oncocytoma. Differential diagnosis of infiltrative lesions is wider, including primary and secondary malignancies and inflammatory disease, and knowledge of the patient history is essential. Radiologists may establish a possible differential diagnosis based on the imaging features of the renal masses and the clinical history. The aim of this review is to present the contribution of the different imaging techniques and image guided biopsies in the diagnostic management of cystic and solid renal lesions.

Contrast-enhanced ultrasound (CEUS) of cystic renal lesions in comparison to CT and MRI in a multicenter setting

PURPOSE

Contrast-enhanced-ultrasound (CEUS) has been frequently used in assessment of cystic renal lesions.

OBJECTIVE

The aim of this study was to investigate the Bosniak classification in CEUS compared to CT and MRI in a multi-center setting.

METHODS

Bosniak classification in CEUS examinations of cystic renal lesions were compared to imaging findings in computed-tomography (ceCT) and magnetic-resonance-imaging (ceMRI). Imaging results were correlated to histopathological reports. All examinations were performed by experts (EFSUMB level 3) using up-to-date CEUS examination-protocols.

RESULTS

Overall, 173 cystic renal lesions were compared to subgroups CT (n = 87) and MRI (n = 86). Using Bosniak-classification 64/87 renal cysts (73.6%) were rated equal compared to CT with upgrade of four lesions (4.6%) and downgrade of 19 lesions (21.8%) by CT (Intra-class-correlation [ICC] coefficient of 0.824 [p < 0.001]). CEUS compared to MRI, presenting different scoring especially in classes Bosniak IIF (n = 16/31) and Bosniak III (n = 16/28) with an ICC coefficient of 0.651 (p < 0.001).

CONCLUSION

CEUS can visualize even finest septal and small nodular wall enhancement, which may result in an upgrade of cystic lesions into a higher Bosniak class compared to CT or MRI. Thus, a modification of the Bosniak classification on CEUS may reduce unnecessary biopsies and surgery.

Characterizing T2 iso- and hypo-intense renal masses on MRI: Can templated algorithms improve accuracy?

PURPOSE

To assess if a templated algorithm can improve the diagnostic performance of MRI for characterization of T2 isointense and hypointense renal masses.

METHODS

In this retrospective study, 60 renal masses with histopathologic diagnoses that were also confirmed as T2 iso- or hypointense on MRI were identified (mean ± standard deviation, range: 3.9 ± 2.5, 1.0-13.7 cm). Two semi-quantitative diagnostic algorithms were created based on MRI features of renal masses reported in the literature. Three body-MRI trained radiologists provided clinical diagnoses based on their experience and separately provided semiquantitative data for each components of the two algorithms. The algorithms were applied separately by a radiology trainee without additional interpretive input. Logistic regression was used to compare the accuracy of the three methods in distinguishing malignant versus benign lesions and in diagnosing the exact histopathology. Inter-reader agreement for each method was calculated using Fleiss' kappa statistics.

RESULTS

The accuracy of the two algorithms and clinical experience were similar (70%, 69%, and 64%, respectively, p = 0.22-0.32), with fair to moderate inter-reader agreement (Fleiss's kappa: r = 0.375, r = 0.308, r = 0.375, respectively, all p < 0.0001). The accuracy of the two algorithms and clinical experience in diagnosing specific histopathology were also no different from each other (34%, 29%, and 32%, respectively, p = 0.49-0.74), with fair to moderate inter-reader agreement (Fleiss's kappa: r = 0.20, r = 0.28, r = 0.375, respectively, all p < 0.0001).

CONCLUSION

Semi-quantitative templated algorithms based on MRI features of renal masses did not improve the ability to diagnose T2 iso- and hypointense renal masses when compared to unassisted interpretation by body MR trained subspecialists.

Multiparametric MR for Solid Renal Mass Characterization

Multiparametric MR provides a noninvasive means for improved differentiation between benign and malignant solid renal masses. Although most large, heterogeneous renal masses are due to renal cell carcinoma, smaller "indeterminate" renal masses are being identified on cross-sectional imaging. Although definitive diagnosis of a solid renal mass may not always be possible by MR imaging, integrated evaluation of multiple MR imaging parameters can result in concise differential diagnosis. Multiparametric MR should be considered a critical step in the triage of patients with a solid renal mass for whom treatment options are being considered in the context of morbidity, prognosis, and mortality.

Diagnostic test accuracy of ADC values for identification of clear cell renal cell carcinoma: systematic review and meta-analysis

OBJECTIVES

To perform a systematic review on apparent diffusion coefficient (ADC) values of renal tumor subtypes and meta-analysis on the diagnostic performance of ADC for differentiation of localized clear cell renal cell carcinoma (ccRCC) from other renal tumor types.

METHODS

Medline, Embase, and the Cochrane Library databases were searched for studies published until May 1, 2019, that reported ADC values of renal tumors. Methodological quality was evaluated. For the meta-analysis on diagnostic test accuracy of ADC for differentiation of ccRCC from other renal lesions, we applied a bivariate random-effects model and compared two subgroups of ADC measurement with vs. without cystic and necrotic areas.

RESULTS

We included 48 studies (2588 lesions) in the systematic review and 13 studies (1126 lesions) in the meta-analysis. There was no significant difference in ADC of renal parenchyma using b values of 0-800 vs. 0-1000 (p = 0.08). ADC measured on selected portions (sADC) excluding cystic and necrotic areas differed significantly from whole-lesion ADC (wADC) (p = 0.002). Compared to ccRCC, minimal-fat angiomyolipoma, papillary RCC, and chromophobe RCC showed significantly lower sADC while oncocytoma exhibited higher sADC. Summary estimates of sensitivity and specificity to differentiate ccRCC from other tumors were 80% (95% CI, 0.76-0.88) and 78% (95% CI, 0.64-0.89), respectively, for sADC and 77% (95% CI, 0.59-0.90) and 77% (95% CI, 0.69-0.86) for wADC. sADC offered a higher area under the receiver operating characteristic curve than wADC (0.852 vs. 0.785, p = 0.02).

CONCLUSIONS

ADC values of kidney tumors that exclude cystic or necrotic areas more accurately differentiate ccRCC from other renal tumor types than whole-lesion ADC values.

KEY POINTS

• Selective ADC of renal tumors, excluding cystic and necrotic areas, provides better discriminatory ability than whole-lesion ADC to differentiate clear cell RCC from other renal lesions, with area under the receiver operating characteristic curve (AUC) of 0.852 vs. 0.785, respectively (p = 0.02). • Selective ADC of renal masses provides moderate sensitivity and specificity of 80% and 78%, respectively, for differentiation of clear cell renal cell carcinoma (RCC) from papillary RCC, chromophobe RCC, oncocytoma, and minimal-fat angiomyolipoma. • Selective ADC excluding cystic and necrotic areas are preferable to whole-lesion ADC as an additional tool to multiphasic MRI to differentiate clear cell RCC from other renal lesions whether the highest b value is 800 or 1000.

Deep Learning to Distinguish Benign from Malignant Renal Lesions Based on Routine MR Imaging

PURPOSE

With increasing incidence of renal mass, it is important to make a pretreatment differentiation between benign renal mass and malignant tumor. We aimed to develop a deep learning model that distinguishes benign renal tumors from renal cell carcinoma (RCC) by applying a residual convolutional neural network (ResNet) on routine MR imaging.

EXPERIMENTAL DESIGN

Preoperative MR images (T2-weighted and T1-postcontrast sequences) of 1,162 renal lesions definitely diagnosed on pathology or imaging in a multicenter cohort were divided into training, validation, and test sets (70:20:10 split). An ensemble model based on ResNet was built combining clinical variables and T1C and T2WI MR images using a bagging classifier to predict renal tumor pathology. Final model performance was compared with expert interpretation and the most optimized radiomics model.

RESULTS

Among the 1,162 renal lesions, 655 were malignant and 507 were benign. Compared with a baseline zero rule algorithm, the ensemble deep learning model had a statistically significant higher test accuracy (0.70 vs. 0.56, P = 0.004). Compared with all experts averaged, the ensemble deep learning model had higher test accuracy (0.70 vs. 0.60, P = 0.053), sensitivity (0.92 vs. 0.80, P = 0.017), and specificity (0.41 vs. 0.35, P = 0.450). Compared with the radiomics model, the ensemble deep learning model had higher test accuracy (0.70 vs. 0.62, P = 0.081), sensitivity (0.92 vs. 0.79, P = 0.012), and specificity (0.41 vs. 0.39, P = 0.770).

CONCLUSIONS

Deep learning can noninvasively distinguish benign renal tumors from RCC using conventional MR imaging in a multi-institutional dataset with good accuracy, sensitivity, and specificity comparable with experts and radiomics.

Imaging protocols for renal multiparametric MRI and MR urography: results of a consensus conference from the French Society of Genitourinary Imaging

OBJECTIVES

To develop technical guidelines for magnetic resonance imaging aimed at characterising renal masses (multiparametric magnetic resonance imaging, mpMRI) and at imaging the bladder and upper urinary tract (magnetic resonance urography, MRU).

METHODS

The French Society of Genitourinary Imaging organised a Delphi consensus conference with a two-round Delphi survey followed by a face-to-face meeting. Two separate questionnaires were issued for renal mpMRI and for MRU. Consensus was strictly defined using a priori criteria.

RESULTS

Forty-two expert uroradiologists completed both survey rounds with no attrition between the rounds. Fifty-six of 84 (67%) statements of the mpMRI questionnaire and 44/71 (62%) statements of the MRU questionnaire reached final consensus. For mpMRI, there was consensus that no injection of furosemide was needed and that the imaging protocol should include T2-weighted imaging, dual chemical shift imaging, diffusion-weighted imaging (use of multiple b-values; maximal b-value, 1000 s/mm²) and fat-saturated single-bolus multiphase (unenhanced, corticomedullary, nephrographic) contrast-enhanced imaging; late imaging (more than 10 min after injection) was judged optional. For MRU, the patients should void their bladder before the examination. The protocol must include T2-weighted imaging, anatomical fast T1/T2-weighted imaging, diffusion-weighted imaging (use of multiple b-values; maximal b-value, 1000 s/mm²) and fat-saturated single-bolus multiphase (unenhanced, corticomedullary, nephrographic, excretory) contrast-enhanced imaging. An intravenous injection of furosemide is mandatory before the injection of contrast medium. Heavily T2-weighted cholangiopancreatography-like imaging was judged optional.

CONCLUSION

This expert-based consensus conference provides recommendations to standardise magnetic resonance imaging of kidneys, ureter and bladder.

KEY POINTS

• Multiparametric magnetic resonance imaging (mpMRI) aims at characterising renal masses; magnetic resonance urography (MRU) aims at imaging the urinary bladder and the collecting systems. • For mpMRI, no injection of furosemide is needed. • For MRU, an intravenous injection of furosemide is mandatory before the injection of contrast medium; heavily T2-weighted cholangiopancreatography-like imaging is optional.

Update on MR urography (MRU): technique and clinical applications

Magnetic resonance imaging of the upper tract (pyelocalyces and ureters) or MR Urography (MRU) is technically possible and when performed correctly offers similar visualization of the upper tracts and for detection of non-calculous diseases of the collecting system similar specificity but with lower sensitivity compared to CTU. MRU provides the ability to simultaneously image the kidneys and urinary bladder with improved soft tissue resolution, better tissue characterization and when combined with assessment of the upper tract, a comprehensive examination of the urinary system. MRU requires meticulous attention to technical details and is a longer more demanding examination compared to CTU. Advances in MR imaging techniques including: parallel imaging, free-breathing motion compensation techniques and compressed sensing can dramatically shorten examination times and improve image quality and patient tolerance for the exam. This review article discusses updates in the MRU technique, summarizes clinical indications and opportunities for MRU in clinical practice and reviews advantages and disadvantages of MRU compared to CTU.

Apparent Diffusion Coefficient Distinguishes Malignancy in T1-Hyperintense Small Renal Masses

OBJECTIVE. Small renal masses (< 4 cm) can be difficult to accurately classify as benign or malignant, particularly when they appear T1 hyperintense on MRI. This intrinsic signal, potentially related to intralesional hemorrhage, may limit evaluation of signal intensity on DWI. The purpose of this study was to test whether apparent diffusion coefficient (ADC) measurements may distinguish malignancy. MATERIALS AND METHODS. This single-center retrospective study identified patients with a T1-hyperintense renal mass less than 4 cm on MRI. Malignant lesions were pathologically proven; a benign mass was established by a predefined hierarchy of pathologic proof, follow-up ultrasound, or follow-up imaging showing more than 5 years of stability. T1 hyperintensity, defined as a signal intensity equivalent to or greater than the adjacent renal cortex, was confirmed by a senior abdominal radiologist. Two additional abdominal radiologists independently measured ADC of the lesion, which was normalized to the ADC of the background ipsilateral kidney and represented as ADC_ratio. RESULTS. The final cohort included 58 benign and 37 malignant renal lesions in 95 patients. Interrater agreement for ADC measurements was almost perfect (κ = 0.836-0.934). ADC_ratio was significantly lower in malignant compared with benign lesions (0.65 ± 0.29 vs 1.03 ± 0.32; p < 0.001). Malignant lesions were significantly larger than benign lesions (2.66 ± 0.86 cm vs 1.50 ± 0.65 cm; p < 0.001); however, after controlling for lesion size, ADC_ratio remained a significant predictor of malignancy (p < 0.001). CONCLUSION. ADC_ratio was highly reproducible for T1-hyperintense small renal masses and was significantly lower in malignant compared with benign renal masses.

Relationship of renal apparent diffusion coefficient and functional MR urography in children with pelvicalyceal dilation

OBJECTIVE

The aim is to evaluate the age-related changes and relationship of renal apparent diffusion coefficient (ADC) against the morphological and functional changes detected by functional magnetic resonance urography (fMRU) in children with pelvicalyceal dilation, with suspected or known ureteropelvic junction obstruction.

MATERIALS AND METHODS

We retrospectively analyzed fMRUs with diffusion-weighted imaging (DWI) of the kidney in 35 subjects (25 males; median age: 7.1 years, range: 0.3-22.7 years) with 70 kidneys (40 with pelvicalyceal dilation and 30 with no pelvicalyceal dilation). Inclusion criteria were pelvicalyceal dilation, the absence of duplex kidneys and no ureteric dilation. DWI was performed with 3 diffusion gradient directions (b values = 0, 200, 500, 800 and 1,000 s/mm2). Metrics for fMRU included calyceal and renal transit times (CTT, RTT), time-to-peak (TTP), differential renal function based on volume (vDRF), Patlak number (pDRF) and combined volume and Patlak number (vpDRF). The grades of pelvicalyceal dilation, cortical thinning and corticomedullary differentiation were evaluated. The relationship between ADC values and the fMRU parameters was analyzed.

RESULTS

ADC increases with age in kidneys without pelvicalyceal dilation (R²=0.37, P<0.001). Renal ADC does not correlate with any of the morphological or fMRU parameters (P>0.07). The median ADC of kidneys without pelvicalyceal dilation was 3.73×10^-3 mm²/s (range: 2.78-5.37×0^-3 mm²/s) and the median ADC of kidneys with pelvicalyceal dilation was 3.82×10^-3 mm²/s (range: 2.70-5.70×10^-3 mm²/s). There was no correlation between ADC and the absolute differences of vDRF or pDRF (P>0.33).

CONCLUSION

Renal ADC does not correlate with morphological and functional results of fMRU changes in children with pelvicalyceal dilation due to suspected or known ureteropelvic junction obstruction.

Role of Virtual Biopsy in the Management of Renal Masses

OBJECTIVE. Renal masses comprise a heterogeneous group of pathologic conditions, including benign and indolent diseases and aggressive malignancies, complicating management. In this article, we explore the emerging role of imaging to provide a comprehensive noninvasive characterization of a renal mass-so-called "virtual biopsy"-and its potential use in the management of patients with renal tumors. CONCLUSION. Percutaneous renal mass biopsy (RMB) remains a valuable method to provide a presurgical histopathologic diagnosis of renal masses, but it is an invasive procedure and is not always feasible. Accumulating data support the use of imaging features to predict histopathology of renal masses. Imaging may help address some of the inherent limitations of RMB, and in certain settings, a multimodal clinical approach may allow decreasing the need for RMB.

Radiomics in Kidney Cancer: MR Imaging

Renal tumors encompass a heterogeneous disease spectrum, which confounds patient management and treatment. Percutaneous biopsy is limited by an inability to sample every part of the tumor. Radiomics may provide detail beyond what can be achieved from human interpretation. Understanding what new technologies offer will allow radiologists to play a greater role in caring for patients with renal cell carcinoma. In this article, we review the use of radiomics in renal cell carcinoma, in both the pretreatment assessment of renal masses and posttreatment evaluation of renal cell carcinoma, with special emphasis on the use of multiparametric MR imaging datasets.

Assessment of the extracellular volume fraction for the grading of clear cell renal cell carcinoma: first results and histopathological findings

OBJECTIVES

To assess the potential of T1 mapping-based extracellular volume fraction (ECV) for the identification of higher grade clear cell renal cell carcinoma (cRCC), based on histopathology as the reference standard.

METHODS

For this single-center, institutional review board-approved prospective study, 27 patients (17 men, median age 62 ± 12.4 years) with pathologic diagnosis of cRCC (nucleolar International Society of Urological Pathology (ISUP) grading) received abdominal MRI scans at 1.5 T using a modified Look-Locker inversion recovery (MOLLI) sequence between January 2017 and June 2018. Quantitative T1 values were measured at different time points (pre- and postcontrast agent administration) and quantification of the ECV was performed on MRI and histological sections (H&E staining).

RESULTS

Reduction in T1 value after contrast agent administration and MR-derived ECV were reliable predictors for differentiating higher from lower grade cRCC. Postcontrast T1_diff values (T1_diff = T1 difference between the native and nephrogenic phase) and MR-derived ECV were significantly higher for higher grade cRCC (ISUP grades 3-4) compared with lower grade cRCC (ISUP grades 1-2) (p < 0.001). A cutoff value of 700 ms could distinguish higher grade from lower grade tumors with 100% (95% CI 0.69-1.00) sensitivity and 82% (95% CI 0.57-0.96) specificity. There was a positive and strong correlation between MR-derived ECV and histological ECV (p < 0.01, r = 0.88). Interobserver agreement for quantitative longitudinal relaxation times in the T1 maps was excellent.

CONCLUSIONS

T1 mapping with ECV measurement could represent a novel in vivo biomarker for the classification of cRCC regarding their nucleolar grade, providing incremental diagnostic value as a quantitative MR marker.

KEY POINTS

• Reduction in MRI T1 relaxation times after contrast agent administration and MR-derived extracellular volume fraction are useful parameters for grading of clear cell renal cell carcinoma (cRCC). • T1 differences between the native and the nephrogenic phase are higher for higher grade cRCC compared with lower grade cRCC and MRI-derived extracellular volume fraction (ECV) and histological ECV show a strong correlation. • T1 mapping with ECV measurement may be helpful for the noninvasive assessment of cRCC pathology, being a safe and feasible method, and it has potential to optimize individualized treatment options, e.g., in the decision of active surveillance.

High signal renal tumors on DWI: the diagnostic value of morphological characteristics

PURPOSE

To assess the usefulness of morphological characteristics of diffusion-weighted imaging (DWI) for differentiating malignant renal tumors from benign renal tumors, and clear cell renal cell carcinoma (RCC) from non-clear cell RCC at 3.0 T.

METHODS

The study included 249 patients with 251 histopathologically confirmed renal tumors that showed high signal on DWI. For each tumor, two radiologists independently evaluated apparent diffusion coefficient (ADC) values and morphological characteristics of DWI. The differences in the quantitative and qualitative magnetic resonance imaging (MRI) features determined by the readers were assessed. The ADC values between malignant and benign renal tumors and between clear cell and non-clear cell RCC were compared using Mann-Whitney tests. The proportional differences of morphological characteristics of DWI between malignant and benign renal tumors and between clear cell and non-clear cell RCC were compared using Chi-square tests.

RESULTS

There were no significant differences in the quantitative and qualitative MRI features determined by the readers. The ADC values for malignant renal tumors were statistically significantly higher than those for benign renal tumors (p < 0.05), and the ADC values for clear cell RCC were statistically significantly higher than those for non-clear cell RCC (p < 0.05). The proportion of morphological characteristics of DWI between malignant and benign renal tumors was statistically significantly different at ring, nodular, flaky high signal. The proportion of morphological characteristics of DWI between clear cell and non-clear cell RCC was statistically significantly different at uniform high signal.

CONCLUSIONS

The morphological characteristics of DWI are useful in differentiating renal tumors.

Magnetic resonance imaging findings of renal cell carcinoma associated with Xp11.2 translocation/TFE3 gene fusion in adults: a pilot study

PURPOSE

The purpose of the study was to retrospectively analyze MRI findings of renal cell carcinoma associated with Xp11.2 translocation/TFE3 gene fusion (Xp11.2/TFE RCC) in adults.

METHODS

Sixteen patients with Xp11.2/TFE RCC were reviewed retrospectively. The clinical characteristics and imaging features were assessed and then compared between metastatic and non-metastatic subgroups.

RESULTS

The mean age at diagnosis was 47.4 (20-76) years. Seven (44 %) patients were men, and nine (56 %) patients were women. The lesions predominantly exhibited an endophytic distribution (n = 14, 88 %) with a capsule (n = 16, 100 %), accompanied by solid and cystic patterns (n = 12, 75%) and hemorrhage (n = 11, 69 %). The tumors prevalently appeared hyper- to isointense on T1WI (n = 14, 88 %), hypointense on T2WI (n = 13, 81 %), and hyperintense on DWI (n = 16, 100 %) with a lower ADC (P < 0.001) than that of the surrounding tissue. The tumors were less enhanced than the normal renal cortex in all phases with a prolonged enhancement pattern (P ≤ 0.001). In addition, six patients (38 %) developed recurrence or metastases. The RCCs with metastases showed an irregular shape (P = 0.013), an incomplete capsule (P = 0.018), heterogeneous solid-cystic patterns (P = 0.034), and hemorrhage (P = 0.037) than non-metastatic subgroups.

CONCLUSIONS

MRI provides valuable information for the diagnosis of adult Xp11.2/TFE RCCs. Features including irregular shape, incomplete capsule, mixed solid-cystic pattern, and hemorrhage may indicate the occurrence of recurrence or metastases.

Metanephric adenoma with low apparent diffusion coefficient value mimicking renal cell carcinoma: A case report

RATIONALE

Metanephric adenoma (MA) is a rare and often benign tumor. Most MAs were misdiagnosed as renal cell carcinomas (RCCs) preoperatively. Diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping can help to differentiate benign and malignant tumors. However, there are still pitfalls in using DWI and ADC to discriminate benign and malignant lesions.

PATIENT CONCERNS

A 56-year-old woman had a right renal metanephric adenoma. The tumor showed very low ADC value preoperatively and was misdiagnosed as a renal cell carcinoma.

DIAGNOSIS

Intraoperative ultrasound-guided percutaneous biopsy of tumor was performed. Based on the histopathological findings and immunohistochemical stains, a diagnosis of metanephric adenoma was suggested.

INTERVENTIONS

The patient received percutaneous cryoablation of this tumor. Five years later, she underwent right partial nephrectomy because local recurrence was revealed on a follow-up computed tomography (CT).

OUTCOMES

MA was confirmed again by histological examination. The patient was uneventful after surgery.

LESSONS

ADC mapping can be used for differentiating RCCs from other benign tumors by their lower ADC values. However, some benign and malignant lesions have overlapped low ADC values. This case illustrated that a benign lesion such as MA could mimic RCC on ADC, by its highly cellular component. Cryoablation is an optional treatment, which has an increased risk of local recurrence. Follow-up CT or MRI is useful and necessary for detection of local recurrence by depicting enhancing solid parts in a tumor over time.

Mono, bi- and tri-exponential diffusion MRI modelling for renal solid masses and comparison with histopathological findings

PURPOSE

To compare diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and tri-exponential models of the diffusion magnetic resonance imaging (MRI) signal for the characterization of renal lesions in relationship to histopathological findings.

METHODS

Sixteen patients planned to undergo nephrectomy for kidney tumour were scanned before surgery at 3 T magnetic resonance imaging (MRI), with T2-weighted imaging, DTI and diffusion weighted imaging (DWI) using ten b-values. DTI parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squared fitting of the DTI data and bi-, and tri-exponential fit parameters (Dbi, fstar,and Dtri, ffast,finterm) using a nonlinear fit of the multiple b-value DWI data. Average parameters were calculated for regions of interest, selecting the lesions and healthy kidney tissue. Tumour type and specificities were determined after surgery by histological examination. Mean parameter values of healthy tissue and solid lesions were compared using a Wilcoxon-signed ranked test and MANOVA.

RESULTS

Thirteen solid lesions (nine clear cell carcinomas, two papillary renal cell carcinoma, one haemangioma and one oncocytoma) and four cysts were included. The mean MD of solid lesions are significantly (p < 0.05) lower than healthy cortex and medulla, (1.94 ± 0.32*10- 3 mm2/s versus 2.16 ± 0.12*10- 3 mm2/s and 2.21 ± 0.14*10- 3 mm2/s, respectively) whereas ffast is significantly higher (7.30 ± 3.29% versus 4.14 ± 1.92% and 4.57 ± 1.74%) and finterm is significantly lower (18.7 ± 5.02% versus 28.8 ± 5.09% and 26.4 ± 6.65%). Diffusion coefficients were high (≥2.0*10- 3 mm2/s for MD, 1.90*10- 3 mm2/s for Dbi and 1.6*10- 3 mm2/s for Dtri) in cc-RCCs with cystic structures and/or haemorrhaging and low (≤1.80*10- 3 mm2/s for MD, 1.40*10- 3 mm2/s for Dbi and 1.05*10- 3 mm2/s for Dtri) in tumours with necrosis or sarcomatoid differentiation.

CONCLUSION

Parameters derived from a two- or three-component fit of the diffusion signal are sensitive to histopathological features of kidney lesions.

Imaging Advances in the Management of Kidney Cancer

New developments in cross-sectional imaging, including contrast-enhanced ultrasound, dual-energy computed tomography, multiparametric magnetic resonance imaging, single-photon emission computed tomography, and positron emission tomography, together with novel application of existing and novel radiotracers, have changed the landscape of renal mass characterization (ie, virtual biopsy) as well as the detection of metastatic disease, prognostication, and response assessment in patients with advanced kidney cancer. A host of imaging response criteria have been developed to characterize the response to targeted and immune therapies and correlate with patient outcomes, each with strengths and limitations. Recent efforts to advance the field are aimed at increasing objectivity with quantitative techniques and the use of banks of imaging data to match the vast genomic data that are becoming available. The emerging field of radiogenomics has the potential to transform further the role of imaging in kidney cancer management through eventual noninvasive characterization of the tumor histology and genetic microenvironment in single renal masses and/or metastatic disease. We review of the effect of currently available imaging techniques in the management of patients with kidney cancer, including localized, locally advanced, and metastatic disease.