Multiparametric MRI of solid renal masses: pearls and pitfalls

Update on Renal Cell Carcinoma Diagnosis with Novel Imaging Approaches

This review highlights recent advances in renal cell carcinoma (RCC) imaging. It begins with dual-energy computed tomography (DECT), which has demonstrated a high diagnostic accuracy in the evaluation of renal masses. Several studies have suggested the potential benefits of iodine quantification, particularly for distinguishing low-attenuation, true enhancing solid masses from hyperdense cysts. By determining whether or not a renal mass is present, DECT could avoid the need for additional imaging studies, thereby reducing healthcare costs. DECT can also provide virtual unenhanced images, helping to reduce radiation exposure. The review then provides an update focusing on the advantages of multiparametric magnetic resonance (MR) imaging performance in the histological subtyping of RCC and in the differentiation of benign from malignant renal masses. A proposed standardized stepwise reading of images helps to identify clear cell RCC and papillary RCC with a high accuracy. Contrast-enhanced ultrasound may represent a promising diagnostic tool for the characterization of solid and cystic renal masses. Several combined pharmaceutical imaging strategies using both sestamibi and PSMA offer new opportunities in the diagnosis and staging of RCC, but their role in risk stratification needs to be evaluated. Although radiomics and tumor texture analysis are hampered by poor reproducibility and need standardization, they show promise in identifying new biomarkers for predicting tumor histology, clinical outcomes, overall survival, and the response to therapy. They have a wide range of potential applications but are still in the research phase. Artificial intelligence (AI) has shown encouraging results in tumor classification, grade, and prognosis. It is expected to play an important role in assessing the treatment response and advancing personalized medicine. The review then focuses on recently updated algorithms and guidelines. The Bosniak classification version 2019 incorporates MRI, precisely defines previously vague imaging terms, and allows a greater proportion of masses to be placed in lower-risk classes. Recent studies have reported an improved specificity of the higher-risk categories and better inter-reader agreement. The clear cell likelihood score, which adds standardization to the characterization of solid renal masses on MRI, has been validated in recent studies with high interobserver agreement. Finally, the review discusses the key imaging implications of the 2017 AUA guidelines for renal masses and localized renal cancer.

Differentiation between adrenocortical carcinoma and lipid-poor adrenal adenoma using a multiparametric MRI-based diagnostic algorithm

PURPOSE

The purpose of this study was to evaluate the capabilities of multiparametric magnetic resonance imaging (MRI) in differentiating between lipid-poor adrenal adenoma (LPAA) and adrenocortical carcinoma (ACC).

MATERIALS AND METHODS

Patients of two centers who underwent surgical resection of LPAA or ACC after multiparametric MRI were retrospectively included. A training cohort was used to build a diagnostic algorithm obtained through recursive partitioning based on multiparametric MRI variables, including apparent diffusion coefficient and chemical shift signal ratio (i.e., tumor signal intensity index). The diagnostic performances of the multiparametric MRI-based algorithm were evaluated using a validation cohort, alone first and then in association with adrenal tumor size using a cut-off of 4 cm. Performances of the diagnostic algorithm for the diagnosis of ACC vs. LPAA were calculated using pathology as the reference standard.

RESULTS

Fifty-four patients (27 with LPAA and 27 with ACC; 37 women; mean age, 48.5 ± 13.3 [standard deviation (SD)] years) were used as the training cohort and 61 patients (24 with LPAA and 37 with ACC; 47 women; mean age, 49 ± 11.7 [SD] years) were used as the validation cohort. In the validation cohort, the diagnostic algorithm yielded best accuracy for the diagnosis of ACC vs. LPAA (75%; 46/61; 95% CI: 55-88) when used without lesion size. Best sensitivity was obtained with the association of the diagnostic algorithm with tumor size (96%; 23/24; 95% CI: 80-99). Best specificity was obtained with the diagnostic algorithm used alone (76%; 28/37; 95% CI: 60-87).

CONCLUSION

A multiparametric MRI-based diagnostic algorithm that includes apparent diffusion coefficient and tumor signal intensity index helps discriminate between ACC and LPAA with high degrees of specificity and accuracy. The association of the multiparametric MRI-based diagnostic algorithm with adrenal lesion size helps maximize the sensitivity of multiparametric MRI for the diagnosis of ACC.

Prevalence of 'Fat-Poor' Adrenal Adenomas at Chemical-Shift MRI

OBJECTIVE

: To determine the prevalence of 'fat-poor' adrenal adenomas at chemical-shift-MRI.

MATERIALS AND METHODS

: This prospective IRB approved study identified 104 consecutive patients with 127 indeterminate adrenal masses that underwent 1.5-T chemical-shift-MRI between 2021-2023. Two blinded radiologists independently measured: 1) 2-Dimensionsal (2D) chemical-shift signal intensity (SI)-index on 2D Chemical-shift-MRI (SI-index >16.5% diagnosed presence of microscopic fat), 2) unenhanced CT attenuation (in cases where unenhanced CT was available).

RESULTS

: From 127 adrenal masses, there were 94% (119/127) adenomas and 6% (8/127) other masses (2 pheochromocytoma, 5 metastases, 1 lymphoma). 98% (117/119) adenomas had SI-Index >16.5%, only 2% (2/119) adenomas were 'fat-poor' by MRI. SI-Index >16.5% was 100% specific for adenoma, all other masses had SI-Index <16.5%. Unenhanced CT was available in 43% (55/127) lesions (50 adenomas, 5 other masses). 34% (17/50) adenomas were lipid-poor (>10 HU). Percentage of adenomas with SI-Index >16.5% were: 1) ≤10 HU, 100% (33/33), 2) 11-29 HU, 100% (12/12), 3) ≥30 HU, 60% (3/5). No other masses had attenuation ≤10 HU (0/5).

CONCLUSION

: Fat-poor adrenal adenomas are uncommon using 2D chemical-shift signal intensity index >16.5% at 1.5-T, occurring in approximately 2% of adenomas in this large prospective series.

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.

Assessment of Imaging Findings of Renal Carcinoma Subtypes with 3.0T MRI

BACKGROUND

The prevalence of renal masses has escalated as a result of the augmented utilization of cross-sectional imaging techniques. The approach to managing renal masses may exhibit variability contingent upon the subtype of renal cell carcinoma (RCC).

AIM

This research aimed to distinguish between clear cell and papillary RCCs, utilizing dynamic contrast magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

The study assessed the MR images of 112 patients with RCC. Two radiologists independently analyzed tumor size, vascular involvement, signal characteristics in T1- and T2-weighted sequences, the presence of hemosiderin, both microscopic and macroscopic fat content, enhancement patterns, and apparent diffusion coefficient (ADC) values derived from b-values of 1000 s/mm².

RESULTS

Seventy patients had clear cell RCC, and 42 had papillary. In the clear cell RCC, microscopic fat content was significantly higher than the papillary RCC (P < 0.001). However, in papillary RCC, hemosiderin content was substantially greater (P = 0.001). On T2-weighted MR images, clear cell RCCs were usually hyperintense, while papillary RCCs were hypointense (P < 0.001). Even though the rapid enhancement pattern was observed in clear cell RCCs, the progressive enhancement pattern was more prevalent in papillary RCCs (P < 0.001).

CONCLUSION

Hyperintensity on T2-weighted images, microscopic fat content, and rapid enhancement pattern may be indicative of clear cell RCC, whereas hypointensity on T2-weighted images, hemosiderin content, and a progressive contrast pattern may be diagnostic for papillary RCC.

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.

Functional Magnetic Resonance Urography in Children-Tips and Pitfalls

MR urography can be an alternative to other imaging methods of the urinary tract in children. However, this examination may present technical problems influencing further results. Special attention must be paid to the parameters of dynamic sequences to obtain valuable data for further functional analysis. The analysis of methodology for renal function assessment using 3T magnetic resonance in children. A retrospective analysis of MR urography studies was performed in a group of 91 patients. Particular attention was paid to the acquisition parameters of the 3D-Thrive dynamic with contrast medium administration as a basic urography sequence. The authors have evaluated images qualitatively and compared contrast-to-noise ratio (CNR), curves smoothness, and quality of baseline (evaluation signal noise ratio) in every dynamic in each patient in every protocol used in our institution. Quality analysis of the image (ICC = 0.877, p < 0.001) was improved so that we have a statistically significant difference in image quality between protocols (χ²(3) = 20.134, p < 0.001). The results obtained for SNR in the medulla and cortex show that there was a statistically significant difference in SNR in the cortex (χ²(3) = 9.060, p = 0.029). Therefore, the obtained results show that with the newer protocol, we obtain lower values of standard deviation for TTP in the aorta (in ChopfMRU: first protocol SD = 14.560 vs. fourth protocol SD = 5.599; in IntelliSpace Portal: first protocol SD = 15.241 vs. fourth protocol SD = 5.506). Magnetic resonance urography is a promising technique with a few challenges that arise and need to be overcome. New technical opportunities should be introduced for everyday practice to improve MRU results.

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.

Cystic Renal Masses: Old and New Paradigms

Cystic renal masses describe a spectrum of lesions with benign and/or malignant features. Cystic renal masses are most often identified incidentally with the Bosniak classification system stratifying their malignant potential. Solid enhancing components most often represent clear cell renal cell carcinoma yet display an indolent natural history relative to pure solid renal masses. This has led to an increased adoption of active surveillance as a management strategy in those who are poor surgical candidates. This article provides a contemporary overview of historical and emerging clinical paradigms in the diagnosis and management of this distinct clinical entity.

Diagnostic Accuracy of MRI for Solid Renal Masses: A Systematic Review and Meta-analysis

BACKGROUND

Biparametric (bp)-MRI and multiparametric (mp)-MRI may improve the diagnostic accuracy of renal mass histology.

PURPOSE

To evaluate the available evidence on the diagnostic accuracy of bp-MRI and mp-MRI for solid renal masses in differentiating malignant from benign, aggressive from indolent, and clear cell renal cell carcinoma (ccRCC) from other histology.

STUDY TYPE

Systematic review.

POPULATION

MEDLINE, EMBASE, and CENTRAL up to January 11, 2022 were searched.

FIELD STRENGTH/SEQUENCE

1.5 or 3 Tesla.

ASSESSMENT

Eligible studies evaluated the accuracy of MRI (with at least two sequences: T2, T1, dynamic contrast and diffusion-weighted imaging) for diagnosis of solid renal masses in adult patients, using histology as reference standard. Risk of bias and applicability were assessed using QUADAS-2.

STATISTICAL TESTS

Meta-analysis using a bivariate logitnormal random effects model.

RESULTS

We included 10 studies (1239 masses from approximately 1200 patients). The risk of bias was high in three studies, unclear in five studies and low in two studies. The diagnostic accuracy of malignant (vs. benign) masses was assessed in five studies (64% [179/281] malignant). The summary estimate of sensitivity was 95% (95% confidence interval [CI]: 77%-99%), and specificity was 63% (95% CI: 46%-77%). No study assessed aggressive (vs. indolent) masses. The diagnostic accuracy of ccRCC (vs. other subtypes) was evaluated in six studies (47% [455/971] ccRCC): the summary estimate of sensitivity was 85% (95% CI: 77%-90%) and specificity was 77% (95% CI: 73%-81%).

DATA CONCLUSION

Our study reveals deficits in the available evidence on MRI for diagnosis of renal mass histology. The number of studies was limited, at unclear/high risk of bias, with heterogeneous definitions of solid masses, imaging techniques, diagnostic criteria, and outcome measures.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

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.

Deep-learning-based ensemble method for fully automated detection of renal masses on magnetic resonance images

Purpose

Accurate detection of small renal masses (SRM) is a fundamental step for automated classification of benign and malignant or indolent and aggressive renal tumors. Magnetic resonance image (MRI) may outperform computed tomography (CT) for SRM subtype differentiation due to improved tissue characterization, but is less explored compared to CT. The objective of this study is to autonomously detect SRM on contrast-enhanced magnetic resonance images (CE-MRI).

Approach

In this paper, we described a novel, fully automated methodology for accurate detection and localization of SRM on CE-MRI. We first determine the kidney boundaries using a U-Net convolutional neural network. We then search for SRM within the localized kidney regions using a mixture-of-experts ensemble model based on the U-Net architecture. Our dataset contained CE-MRI scans of 118 patients with different solid kidney tumor subtypes including renal cell carcinomas, oncocytomas, and fat-poor renal angiomyolipoma. We evaluated the proposed model on the entire CE-MRI dataset using 5-fold cross validation.

Results

The developed algorithm reported a Dice similarity coefficient of 91.20 ± 5.41 % (mean ± standard deviation) for kidney segmentation from 118 volumes consisting of 25,025 slices. Our proposed ensemble model for SRM detection yielded a recall and precision of 86.2% and 83.3% on the entire CE-MRI dataset, respectively.

Conclusions

We described a deep-learning-based method for fully automated SRM detection using CE-MR images, which has not been studied previously. The results are clinically important as SRM localization is a pre-step for fully automated diagnosis of SRM subtypes.

Magnetic Resonance Imaging Virtual Biopsy of Common Solid Renal Masses-A Pictorial Review

ABSTRACT

The expanded application of radiologic imaging resulted in an increased incidence of renal masses in the recent decade. Clinically, it is difficult to determine the malignant potential of the renal masses, thus resulting in complex management. Image-guided biopsies are the ongoing standard of care to identify molecular variance but are limited by tumor accessibility and heterogeneity. With the evolving importance of individualized cancer therapies, radiomics has displayed promising results in the identification of tumoral mutation status on routine imaging. This article discusses how magnetic resonance imaging features can guide a radiologist toward identifying renal mass characteristics.

Evaluation of renal space occupying lesions with multiparametric MRI and its correlation with histopathology findings- an observational study

The term multiparametric MRI, is a useful tool in reference to an approach that takes advantage of the added value of different MR imaging acquisitions to yield anatomic and pathophysiologic information about renal space occupying lesions and to evaluate patients with different tumors, including genitourinary malignancies. The role of multiparametric MRI is continuously growing because of its ability to detect and characterize renal space occupying lesions as well as to assess response to treatment. An observational study was carried out in 50 patients who presented with renal mass, based on clinical suspicion and prior imaging diagnosis of neoplastic renal space occupying lesion. Total renal space occupying lesions were 50, of which, 38 were males & 12 were females. The age range of the study population was 30-80 years. In our study, Agreement analysis between mpMRI diagnosis and HPE diagnosis of different RCC subtypes was statistically significant. So, multiparametric MRI had a role in differentiating the subtypes of RCC which had fair agreement with HPE. The present study results state that the renal mass lesions has different ADC values for different lesions because of the change in tissue contents and there was a statistically significant difference in ADC values between low and high-stage RCCs. Histologic and radiologic profiles of renal space occupying lesions and diverse subtypes of RCC can be used as biologic indicators of clinical behavior, response to treatment, and prognosis.

Role of diffusion-weighted MRI for prediction of regional lymph node positivity in radiologically organ-confined renal tumour: a prospective study

Background

Lymph node metastasis is one of the major factors that decide the prognosis of renal cell carcinoma. Presently, lymphadenectomy is only accepted as the most precise and dependable staging method to detect lymph node invasion; still, its therapeutic value for renal cell carcinoma is controversial. Diffusion-weighted magnetic resonance imaging along with its apparent diffusion coefficient value has already shown great value as a non-invasive modality to detect early microstructural changes in various human tumours. The present study is done to know the role of DWMRI in determining regional lymph node positivity in radiologically organ-confined renal cell carcinoma.

Methods

In this prospective study, we measured the ADC value of renal mass and regional lymph node in patient of RCC. ADC value < 1.25 is taken as cut-off to determine lymph node involvement. A malignant lymph node was confirmed by histopathology postoperatively. After that, we analysed the data retrospectively and studied the association between cut-off ADC value and lymph node positivity.

Results

Total 44 patients of RCC were evaluated in the study. Out of 44 patients, lymph node was found to be malignant on histopathology in 25 (56.8%) patients, and of these, 23 patients had ADC value < 1.25. This association was statistically significant (p < 0.05). The findings of DW MRI were accurate in 72.7% of patients with sensitivity of 63.1%, specificity of 80% and positive predictive value of 70.5%.

Conclusions

Lymph node with ADC value < 1.25 × 10–3 mm2/s has higher probabilities of harbouring malignant cell, so ADC value of DWMRI can be used as a sensitive and specific parameter to differentiate malignant lymph node from benign lymph node. However, our futuristic observation needs to be validated by multi-institutional large sample cohort.

Comparison of image quality and depiction of microscopic fat at 2-D and 3-D T1-Weighted (T1W) chemical shift (dual-echo) MRI for evaluation of adrenal adenomas

OBJECTIVE

To compare image quality and detection of microscopic fat in adrenal adenomas imaged with 2-D and 3-D chemical shift imaging (CSI) and, to derive parameters which best match 2-D and 3-D-CSI.

METHODS

This two-phase, retrospective, and phantom + prospective study was IRB approved. First, a retrospective assessment of 50 consecutive adrenal adenomas imaged at 1.5 T with 2-D (TR minimum, Flip Angle [FA] 70°, TE 2.2/4.4 ms.) and 3-D (TR minimum, FA 10°, TE 2.2/4.4 ms.] CSI was performed. Second, phantom (varied fat: water concentration) experiments guided a prospective assessment of 12 consecutive adrenal adenomas imaged at 1.5 T with 3-D CSI (FA 10°, 18°). Two blinded radiologists independently evaluated: image quality, signal intensity (SI) cancellation (5-point Likert scale), and CSI-index ([SI.In.Phase-SI.Opposed.Phase/SI.In.Phase]*100).

RESULTS

2-D-CSI yielded higher image quality (p < 0.001) and, subjectively (p < 0.001) and quantitatively (p < 0.001) had more SI cancellation from microscopic fat. Proportion of adenomas with no detectable microscopic fat (3-D; 26-36% subjectively, 18-24% quantitatively [CSI-index < 16.5%] versus 2-D; 20-22% subjectively, 6-8% quantitatively) differed (p = 0.008-0.08 subjectively, 0.008-0.03 quantitatively) by CSI technique. Phantom experiments indicated 18°FA 3-D-CSI compared favorably to 70° 2-D-CSI for fat detection between 5% and 50%. In vivo, there was no differences in subjective or quantitative SI cancellation comparing 18°3D-CSI and 2D-CSI (p = 0.16-0.56 and 0.73-0.60). Greater SI cancellation occurred with 18°3D compared to 10°3D-CSI evaluated subjectively (p = 0.003-0.01).

CONCLUSION

2-D CSI has subjectively higher image quality and shows more signal intensity loss from microscopic fat in adrenal adenomas compared to 10° flip angle 3-D-CSI. Increasing the 3-D flip angle to 18° more closely matches depiction of microscopic fat to 2-D-CSI at 1.5 T.

Multicenter Evaluation of Multiparametric MRI Clear Cell Likelihood Scores in Solid Indeterminate Small Renal Masses

Background Solid small renal masses (SRMs) (≤4 cm) represent benign and malignant tumors. Among SRMs, clear cell renal cell carcinoma (ccRCC) is frequently aggressive. When compared with invasive percutaneous biopsies, the objective of the proposed clear cell likelihood score (ccLS) is to classify ccRCC noninvasively by using multiparametric MRI, but it lacks external validation. Purpose To evaluate the performance of and interobserver agreement for ccLS to diagnose ccRCC among solid SRMs. Materials and Methods This retrospective multicenter cross-sectional study included patients with consecutive solid (≥25% approximate volume enhancement) SRMs undergoing multiparametric MRI between December 2012 and December 2019 at five academic medical centers with histologic confirmation of diagnosis. Masses with macroscopic fat were excluded. After a 1.5-hour training session, two abdominal radiologists per center independently rendered a ccLS for 50 masses. The diagnostic performance for ccRCC was calculated using random-effects logistic regression modeling. The distribution of ccRCC by ccLS was tabulated. Interobserver agreement for ccLS was evaluated with the Fleiss κ statistic. Results A total of 241 patients (mean age, 60 years ± 13 [SD]; 174 men) with 250 solid SRMs were evaluated. The mean size was 25 mm ± 8 (range, 10-39 mm). Of the 250 SRMs, 119 (48%) were ccRCC. The sensitivity, specificity, and positive predictive value for the diagnosis of ccRCC when ccLS was 4 or higher were 75% (95% CI: 68, 81), 78% (72, 84), and 76% (69, 81), respectively. The negative predictive value of a ccLS of 2 or lower was 88% (95% CI: 81, 93). The percentages of ccRCC according to the ccLS were 6% (range, 0%-18%), 38% (range, 0%-100%), 32% (range, 60%-83%), 72% (range, 40%-88%), and 81% (range, 73%-100%) for ccLSs of 1-5, respectively. The mean interobserver agreement was moderate (κ = 0.58; 95% CI: 0.42, 0.75). Conclusion The clear cell likelihood score applied to multiparametric MRI had moderate interobserver agreement and differentiated clear cell renal cell carcinoma from other solid renal masses, with a negative predictive value of 88%. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Mileto and Potretzke in this issue.

Nephrometry scoring systems: their importance for the planning of nephron-sparing surgery and the relationships among them

In recent years, the development of new imaging techniques and scoring systems have improved the diagnosis and management of small renal masses. Imaging-based nephrometry scoring systems play an interesting role in the planning of nephron-sparing surgery, providing surgeons with the information necessary to determine the complexity of the renal mass, to deliver the appropriate postoperative care, and to predict adverse outcomes. The aim of this study was to review nephrometry scoring systems, evaluating their characteristics and the relationships among them. The urology and radiology communities should decide which nephrometry scoring system will prevail and be used in daily practice.

Inter-individual comparison of diagnostic accuracy of adrenal washout CT compared to chemical shift MRI plus the T2-weighted (T2W) adrenal MRI calculator in indeterminate adrenal masses: a retrospective non-inferiority study

OBJECTIVE

To compare diagnostic accuracy of washout (WO)-CT to chemical shift (CS)-MRI + T2W adrenal MRI Calculator (T2W-Calculator) to diagnose adrenal adenoma in indeterminate adrenal masses.

METHODS

This retrospective, cross-sectional, non-inferiority study evaluated 40 consecutive indeterminate adrenal masses; each with WO-CT and MRI. Two blinded radiologists independently evaluated in mixed order: pre-contrast attenuation (Hounsfield Units, HU) and absolute WO ([Peak.HU-Delay.HU]/[Peak.HU-Pre.HU] × 100%), Chemical Shift Signal Intensity (CS-SI) Index, T2W SI ratio, and Entropy (which were imputed into the T2W-Calculator). Diagnostic accuracy for adrenal adenoma was tabulated using 2 × 2 tables. True -positive diagnoses of adenoma were CT = Pre-HU < 10 or absolute WO ≥ 60%, MRI = SI index ≥ 16.5% or T2W-Calculator < 0.631.

RESULTS

There were 73% (29/40) adenomas and 27% (11/40) other masses (5 pheochromocytoma, 3 solitary fibrous tumor, 1 metastasis, 1 cavernous hemangioma, and 1 adrenocortical carcinoma). Sensitivity, specificity, and accuracy for diagnosis of adenoma using CT-WO were 78% (95% confidence intervals [CI] 56-93%), 35% (14-62%), and 57% (42-71%) Reader 1 and 72% (53-87%), 46% (17-77%), and 59% (41-76%) Reader 2. Sensitivity, specificity, and accuracy for diagnosis of adenoma using MRI were 100% (88-100%), 64% (34-90%), and 82% (67-97%) Reader 1 and 86% (68-96%), 73% (39-94%), and 80% (64-95%) Reader 2. MRI had higher overall accuracy (p = 0.02 Reader 1, 0.05 Reader 2) compared to CT-WO.

CONCLUSION

Chemical shift MRI combined with the T2W adrenal MRI calculator is not inferior to CT Washout for diagnosis of adrenal adenoma among indeterminate adrenal masses.

Transfer learning-based approach for automated kidney segmentation on multiparametric MRI sequences

Purpose: Multiparametric magnetic resonance imaging (mp-MRI) is being investigated for kidney cancer because of better soft tissue contrast ability. The necessity of manual labels makes the development of supervised kidney segmentation algorithms challenging for each mp-MRI protocol. Here, we developed a transfer learning-based approach to improve kidney segmentation on a small dataset of five other mp-MRI sequences. Approach: We proposed a fully automated two-dimensional (2D) attention U-Net model for kidney segmentation on T1 weighted-nephrographic phase contrast enhanced (CE)-MRI (T1W-NG) dataset ( N = 108 ). The pretrained weights of T1W-NG kidney segmentation model transferred to five other distinct mp-MRI sequences model (T2W, T1W-in-phase (T1W-IP), T1W-out-of-phase (T1W-OP), T1W precontrast (T1W-PRE), and T1W-corticomedullary-CE (T1W-CM), N = 50 ) and fine-tuned by unfreezing the layers. The individual model performances were evaluated with and without transfer-learning fivefold cross-validation on average Dice similarity coefficient (DSC), absolute volume difference, Hausdorff distance (HD), and center-of-mass distance (CD) between algorithm generated and manually segmented kidneys. Results: The developed 2D attention U-Net model for T1W-NG produced kidney segmentation DSC of 89.34 ± 5.31 % . Compared with randomly initialized weight models, the transfer learning-based models of five mp-MRI sequences showed average increase of 2.96% in DSC of kidney segmentation ( p = 0.001 to 0.006). Specifically, the transfer-learning approach increased average DSC on T2W from 87.19% to 89.90%, T1W-IP from 83.64% to 85.42%, T1W-OP from 79.35% to 83.66%, T1W-PRE from 82.05% to 85.94%, and T1W-CM from 85.65% to 87.64%. Conclusions: We demonstrate that a pretrained model for automated kidney segmentation of one mp-MRI sequence improved automated kidney segmentation on five other additional sequences.

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

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

Analysis of a Deep Learning-Based Superresolution Algorithm Tailored to Partial Fourier Gradient Echo Sequences of the Abdomen at 1.5 T: Reduction of Breath-Hold Time and Improvement of Image Quality

OBJECTIVES

The aim of this study was to investigate the feasibility and impact of a novel deep learning superresolution algorithm tailored to partial Fourier allowing retrospectively theoretical acquisition time reduction in 1.5 T T1-weighted gradient echo imaging of the abdomen.

MATERIALS AND METHODS

Fifty consecutive patients who underwent a 1.5 T contrast-enhanced magnetic resonance imaging examination of the abdomen between April and May 2021 were included in this retrospective study. After acquisition of a conventional T1-weighted volumetric interpolated breath-hold examination using Dixon for water-fat separation (VIBEStd), the acquired data were reprocessed including a superresolution algorithm that was optimized for partial Fourier acquisitions (VIBESR). To accelerate theoretically the acquisition process, a more aggressive partial Fourier setting was applied in VIBESR reconstructions practically corresponding to a shorter acquisition for the data included in the retrospective reconstruction. Precontrast, dynamic contrast-enhanced, and postcontrast data sets were processed. Image analysis was performed by 2 radiologists independently in a blinded random order without access to clinical data regarding the following criteria using a Likert scale ranging from 1 to 4 with 4 being the best: noise levels, sharpness and contrast of vessels, sharpness and contrast of organs and lymph nodes, overall image quality, diagnostic confidence, and lesion conspicuity.Wilcoxon signed rank test for paired data was applied to test for significance.

RESULTS

Mean patient age was 61 ± 14 years. Mean acquisition time for the conventional VIBEStd sequence was 15 ± 1 seconds versus theoretical 13 ± 1 seconds of acquired data used for the VIBESR reconstruction. Noise levels were evaluated to be better in VIBESR with a median of 4 (4-4) versus a median of 3 (3-3) in VIBEStd by both readers (P < 0.001). Sharpness and contrast of vessels as well as organs and lymph nodes were also evaluated to be superior in VIBESR compared with VIBEStd with a median of 4 (4-4) versus a median of 3 (3-3) (P < 0.001). Diagnostic confidence was also rated superior in VIBESR with a median of 4 (4-4) versus a median of 3.5 (3-4) in VIBEStd by reader 1 and with a median of 4 (4-4) for VIBESR and a median of 4 (4-4) for VIBEStd by reader 2 (both P < 0.001).

CONCLUSIONS

Image enhancement using deep learning-based superresolution tailored to partial Fourier acquisitions of T1-weighted gradient echo imaging of the abdomen provides improved image quality and diagnostic confidence in combination with more aggressive partial Fourier settings leading to shorter scan time.

Role of non-contrast magnetic resonance imaging in pre-surgical evaluation of renal masses in renal impairment patients

Background

The aim of this work is to study the role of non-contrast MRI in pre-surgical evaluation of renal masses in renal impairment patients as confirmed by both intraoperative and histopathological findings. Intraoperative and histopathological findings were correlated with radiological data.

Methods

This prospective study included 20 patients comprising 25 renal masses. The data were collected in a period from April 2018 to September 2019. All patients underwent partial or radical nephrectomy by the same surgeon.

Results

Based on MRI findings, 9 masses (36%) and 8 masses (32%) were found to be associated with collecting system invasion and perinephric fat invasion, respectively. Histopathological assessment confirmed only 6 cases (24%) with collecting system invasion and 7 cases (28%) demonstrated perinephric fat. Seven masses (28%) had intralesional hemorrhage detected by MRI and confirmed by pathological findings. The MRI detected 6 cases (24%) with lymph nodes invasion, while the histopathological assessment confirmed lymphatic invasion in 7 cases (28%). Only 2 cases (8%) had vascular invasion detected by preoperative MRI and confirmed by histopathology and surgery. The final histopathological examination confirmed 20 malignant neoplasms (80%: RCC = 18, leiomyosarcoma = 2), 3 benign neoplasms (12%: angiomyolipoma = 1, oncocytoma = 2) and 2 non-neoplastic benign masses (8%: renal abscess = 1, xanthogranulomatous pyelonephritis = 1).

Conclusion

Non-contrast MRI is a crucial imaging tool in renal impairment patients who cannot be examined with contrast-enhanced CT or MRI. It assesses the extent of the renal sinus fat and the perinephric fat invasion.

Quantitative 3-tesla multiparametric MRI in differentiation between renal cell carcinoma subtypes

Background

MRI provides several distinct quantitative parameters that may better differentiate renal cell carcinoma (RCC) subtypes. The purpose of the study is to evaluate the diagnostic accuracy of apparent diffusion coefficient (ADC), chemical shift signal intensity index (SII), and contrast enhancement in differentiation between different subtypes of renal cell carcinoma.

Results

There were 63 RCC as regard surgical histopathological analysis: 43 clear cell (ccRCC), 12 papillary (pRCC), and 8 chromophobe (cbRCC). The mean ADC ratio for ccRCC (0.75 ± 0.13) was significantly higher than that of pRCC (0.46 ± 0.12, P < 0.001) and cbRCC (0.41 ± 0.15, P < 0.001). The mean ADC value for ccRCC (1.56 ± 0.27 × 10−3 mm2/s) was significantly higher than that of pRCC (0.96 ± 0.25 × 10−3 mm2/s, P < 0.001) and cbRCC (0.89 ± 0.29 × 10−3 mm2/s, P < 0.001). The mean SII of pRCC (1.49 ± 0.04) was significantly higher than that of ccRCC (0.93 ± 0.01, P < 0.001) and cbRCC (1.01 ± 0.16, P < 0.001). The ccRCC absolute corticomedullary enhancement (196.7 ± 81.6) was significantly greater than that of cbRCC (177.8 ± 77.7, P < 0.001) and pRCC (164.3 ± 84.6, P < 0.001).

Conclusion

Our study demonstrated that multiparametric MRI is able to afford some quantitative features such as ADC ratio, SII, and absolute corticomedullary enhancement which can be used to accurately distinguish different subtypes of renal cell carcinoma.

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

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

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.

Application of a Novel Iterative Denoising and Image Enhancement Technique in T1-Weighted Precontrast and Postcontrast Gradient Echo Imaging of the Abdomen: Improvement of Image Quality and Diagnostic Confidence

OBJECTIVES

The aim of this study was to investigate the impact of a novel iterative denoising and image enhancement technique in T1-weighted precontrast and postcontrast volume-interpolated breath-hold examination (VIBE) of the abdomen on image quality, noise levels, and diagnostic confidence without change of acquisition parameters.

MATERIALS AND METHODS

Fifty patients were included in this retrospective, monocentric, institutional review board-approved study after clinically indicated magnetic resonance imaging of the abdomen including T1-weighted precontrast and postcontrast imaging. After acquisition of the standard VIBE (VIBES), images were processed with a novel reconstruction algorithm using the same raw data as for VIBES, resulting in a denoised and enhanced dataset (VIBEDE). Two different radiologists evaluated both datasets in a randomized order regarding sharpness of organs as well as vessels, noise levels, artifacts, overall image quality, and diagnostic confidence using a Likert scale ranging from 1 to 4 with 4 being the best. Furthermore, in the presence of focal liver lesions, the largest lesion was measured in the postcontrast dataset, and lesion detectability was analyzed using a Likert scale (1-4).

RESULTS

Precontrast and postcontrast sharpness of organs and sharpness of vessels were rated significantly superior by both readers in VIBEDE with a median of 4 (interquartile range, 0) compared with VIBES with a median of 3 (1) (all P's < 0.0001). Precontrast and postcontrast noise levels were also rated superior by both readers in VIBEDE with a median of 4 (0) compared with VIBES with a median of 3 (1) for precontrast and a median of 3 (0) (median of 3 [1] for reader 2) for postcontrast imaging (all P's < 0.0001).Overall image quality was also rated higher with a median of 4 (0) in VIBEDE versus 3 (1) in VIBES (P < 0.0001). Twenty-seven imaging studies contained liver lesions. There was no difference regarding the number and localization between the readers and between VIBES and VIBEDE. Lesion detectability was rated by both readers significantly better in VIBEDE with a median of 4 (0) compared with a median of 4 (1) for reader 1 and a median of 3 (1) for reader 2 (P = 0.001 for reader 1; P < 0.001 for reader 2). Consequently, diagnostic confidence was also significantly superior in VIBEDE versus VIBES with a median of 4 (0) for both (P = 0.001). Interreader agreement resulted in a Cohen κ of 0.76 for precontrast analysis as well as of 0.76 for postcontrast analysis.

CONCLUSIONS

Application of a novel iterative denoising and image enhancement technique in T1-weighted VIBE precontrast and postcontrast imaging of the abdomen is feasible, providing superior image quality, noise levels, and diagnostic confidence.

Bosniak Classification of Cystic Renal Masses, Version 2019: A Pictorial Guide to Clinical Use

Cystic renal masses are commonly encountered in clinical practice. In 2019, the Bosniak classification of cystic renal masses, originally developed for CT, underwent a major revision to incorporate MRI and is referred to as the Bosniak Classification, version 2019. The proposed changes attempt to (a) define renal masses (ie, cystic tumors with less than 25% enhancing tissue) to which the classification should be applied; (b) emphasize specificity for diagnosis of cystic renal cancers, thereby decreasing the number of benign and indolent cystic masses that are unnecessarily treated or imaged further; (c) improve interobserver agreement by defining imaging features, terms, and classes of cystic renal masses; (d) reduce variation in reported malignancy rates for each of the Bosniak classes; (e) incorporate MRI and to some extent US; and (f) be applicable to all cystic renal masses encountered in clinical practice, including those that had been considered indeterminate with the original classification. The authors instruct how, using CT, MRI, and to some extent US, the revised classification can be applied, with representative clinical examples and images. Practical tips, pitfalls to avoid, and decision tree rules are included to help radiologists and other physicians apply the Bosniak Classification, version 2019 and better manage cystic renal masses. An online resource and mobile application are also available for clinical assistance. An invited commentary by Siegel and Cohan is available online. ^©RSNA, 2021.

Imaging of ureter: a primer for the emergency radiologist

In this review article, we will discuss the gamut of abnormalities involving the ureters. In the emergency department, ureterolithiasis is the most common indication for imaging abdomen and pelvis. However, spectrum of ureteral abnormalities including congenital, infectious and inflammatory, primary and secondary ureteral malignancies, retroperitoneal fibrosis rare described in this article may be encountered. Thus, we will describe acute subacute as well as chronic conditions that may affect ureter. Knowledge of common, as well as rare entities and their imaging features, is of utmost importance to enable appropriate management.

Adequacy of Unenhanced MRI for Surveillance of Small (Clinical T1a) Solid Renal Masses

OBJECTIVE. The purpose of this study was to determine if contrast enhancement is necessary for MRI surveillance of clinical T1a (cT1a) solid renal masses. MATERIALS AND METHODS. With institutional review board approval, 36 patients who underwent two or more contrast-enhanced (CE) MRI examinations (median, four examinations; range, two to 10 examinations) for surveillance of 39 cT1a solid renal masses between 2009 and 2019 (median time between scans, 2 years; range, 1-7 years) were evaluated. Two radiologists independently measured renal mass size and assessed tumor stage in two sessions for baseline and follow-up examinations using T1-weighted nephrographic phase CE-MRI and unenhanced single-shot T2-weighted MRI in mixed order with a 4-week washout period. Comparisons were performed using the Wilcoxon sign-rank test and Pearson correlation. Bland-Altman and intraclass correlation determined interobserver agreement. RESULTS. Mean size ± SD of renal masses on CE-MRI and T2-weighted MRI were 18 ± 5 mm (range, 9-37 mm) and 18 ± 5 mm (range, 9-37 mm) for radiologist 1 and 19 ± 7 mm (range, 10-39 mm) and 19 ± 6 mm (range, 10-39 mm) for radiologist 2 with near perfect correlation (for radiologist 1, β = 0.9897; for radiologist 2, β = 0.9317; p < .001). Interob-server agreement for measurements comparing radiologist 1 and radiologist 2 on CEMRI and T2-weighted MRI and intraobserver agreement for measurements on CE-MRI and T2-weighted MRI were excellent. Mean growth rate of renal masses measured on CE-MRI and T2-weighted MRI were 2 ± 2 mm (range, -5 to 8 mm) and 2 ± 3 mm (range, -3 to 8 mm) for radiologist 1 and 3 ± 5 mm (range, -1 to 18 mm) and 3 ± 6 mm (range, -1 to 24 mm) for radiologist 2 with high correlation (for radiologist 1, β = 0.8313 [p < .001]; for radiologist 2, β = 0.848 [p = .002]). At baseline, all tumors were subjectively cT1a on CE-MRI and T2-weighted MRI (p > .99, intraclass correlation coefficient [ICC] = 1). During follow-up, one mass progressed to T3 on CE-MRI and T2-weighted MRI for radiologist 1 and radiologist 2 (p > .99, ICC = 1). CONCLUSION. In this study, size measurements on unenhanced T2-weighted MRI had near perfect correlation to measurements using CE-MRI in cT1a solid renal masses undergoing surveillance, with high agreement between and within observers. Clinical staging did not differ comparing T2-weighted MRI and CE-MRI, with near perfect agreement. Contrast enhancement is not necessary for follow-up size measurements in cT1a solid renal masses with MRI.

Magnetic Resonance Imaging Radiomics Analyses for Prediction of High-Grade Histology and Necrosis in Clear Cell Renal Cell Carcinoma: Preliminary Experience

INTRODUCTION

Percutaneous renal mass biopsy results can accurately diagnose clear cell renal cell carcinoma (ccRCC); however, their reliability to determine nuclear grade in larger, heterogeneous tumors is limited. We assessed the ability of radiomics analyses of magnetic resonance imaging (MRI) to predict high-grade (HG) histology in ccRCC.

PATIENTS AND METHODS

Seventy patients with a renal mass underwent 3 T MRI before surgery between August 2012 and August 2017. Tumor length, first-order statistics, and Haralick texture features were calculated on T2-weighted and dynamic contrast-enhanced (DCE) MRI after manual tumor segmentation. After a variable clustering algorithm was applied, tumor length, washout, and all cluster features were evaluated univariably by receiver operating characteristic curves. Three logistic regression models were constructed to assess the predictability of HG ccRCC and then cross-validated.

RESULTS

At univariate analysis, area under the curve values of length, and DCE texture cluster 1 and cluster 3 for diagnosis of HG ccRCC were 0.7 (95% confidence interval [CI], 0.58-0.82, false discovery rate P = .008), 0.72 (95% CI, 0.59-0.84, false discovery rate P = .004), and 0.75 (95% CI, 0.63-0.87, false discovery rate P = .0009), respectively. At multivariable analysis, area under the curve for model 1 (tumor length only), model 2 (length + DCE clusters 3 and 4), and model 3 (DCE cluster 1 and 3) for diagnosis of HG ccRCC were 0.67 (95% CI, 0.54-0.79), 0.82 (95% CI, 0.71-0.92), and 0.81 (95% CI, 0.70-0.91), respectively.

CONCLUSION

Radiomics analysis of MRI images was superior to tumor size for the prediction of HG histology in ccRCC in our cohort.

Utility of T2-weighted MRI to Differentiate Adrenal Metastases from Lipid-Poor Adrenal Adenomas

Purpose

To evaluate T2-weighted MRI features to differentiate adrenal metastases from lipid-poor adenomas.

Materials and Methods

With institutional review board approval, this study retrospectively compared 40 consecutive patients (mean age, 66 years ± 10 [standard deviation]) with metastases to 23 patients (mean age, 60 years ± 15) with lipid-poor adenomas at 1.5- and 3-T MRI between June 2016 and March 2019. A blinded radiologist measured T2-weighted signal intensity (SI) ratio (SI_nodule/SI_{psoas muscle}), T2-weighted histogram features, and chemical shift SI index. Two blinded radiologists (radiologist 1 and radiologist 2) assessed T2-weighted SI and T2-weighted heterogeneity using five-point Likert scales.

Results

Subjectively, T2-weighted SI (P < .001 for radiologist 1 and radiologist 2) and T2-weighted heterogeneity (P < .001, for radiologist 1 and radiologist 2) were higher in metastases compared with adenomas when assessed by both radiologists. Agreement between the radiologists was substantial for T2-weighted SI (Cohen κ = 0.67) and T2-weighted heterogeneity (κ = 0.62). Metastases had higher T2-weighted SI ratio than adenomas (3.6 ± 1.7 [95% confidence interval {CI}: 0.2, 8.2] vs 2.2 ± 1.0 [95% CI: 0.6, 4.3], P < .001) and higher T2-weighted entropy (6.6 ± 0.6 [95% CI: 4.9, 7.5] vs 5.0 ± 0.8 [95% CI: 3.5, 6.6], P < .001). At multivariate analysis, T2-weighted entropy was the best differentiating feature (P < .001). Chemical shift SI index did not differ between metastases and adenomas (P = .748). Area under the receiver operating characteristic curve (AUC) for T2-weighted SI ratio and T2-weighted entropy were 0.76 (95% CI: 0.64, 0.88) and 0.94 (95% CI: 0.88, 0.99). The logistic regression model combining T2-weighted SI ratio with T2-weighted entropy yielded AUC of 0.95 (95% CI: 0.91, 0.99) and did not differ compared with T2-weighted entropy alone (P = .268). There was no difference in logistic regression model accuracy comparing the data by either field strength, 1.5- or 3-T MRI (P > .05).

Conclusion

Logistic regression models combining T2-weighted SI and T2-weighted heterogeneity can differentiate metastases from lipid-poor adenomas. Validation of these preliminary results is required.Keywords: Adrenal, MR-Imaging, UrinarySupplemental material is available for this article.© RSNA, 2020.

Update on MRI of Cystic Renal Masses Including Bosniak Version 2019

Incidental cystic renal masses are common, usually benign, and almost always indolent. Since 1986, the Bosniak classification has been used to express the risk of malignancy in a cystic renal mass detected at imaging. Historically, magnetic resonance imaging (MRI) was not included in that classification. The proposed Bosniak v.2019 update has formally incorporated MRI, included definitions of imaging terms designed to improve interobserver agreement and specificity for malignancy, and incorporated a variety of masses that were incompletely defined or not included in the original classification. For example, at unenhanced MRI, homogeneous masses markedly hyperintense at T₂ -weighted imaging (similar to cerebrospinal fluid) and homogeneous masses markedly hyperintense at fat suppressed T₁ -weighted imaging (approximately ≥2.5 times more intense than adjacent renal parenchyma) are classified as Bosniak II and may be safely ignored, even when they have not been imaged with a complete renal mass MRI protocol. MRI has specific advantages and is recommended to evaluate masses that at computed tomography (CT) 1) have abundant thick or nodular calcifications; 2) are homogeneous, hyperattenuating, ≥3 cm, and nonenhancing; or 3) are heterogeneous and nonenhancing. Although MRI is generally excellent for characterizing cystic renal masses, there are unique weaknesses of MRI that bear consideration. These details and others related to MRI of cystic renal masses are described in this review, with an emphasis on Bosniak v.2019. A website (https://bosniak-calculator.herokuapp.com/) and mobile phone apps named "Bosniak Calculator" have been developed for ease of assignment of Bosniak classes. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

Predicting common solid renal tumors using machine learning models of classification of radiologist-assessed magnetic resonance characteristics

PURPOSE

Solid renal masses (SRM) are difficult to differentiate based on standard MR features. The purpose of this study was to assess MR imaging features of SRM to evaluate performance of ensemble methods of classifying SRM subtypes.

MATERIALS AND METHODS

MR images of SRM (n = 330) were retrospectively evaluated for standard and multiparametric (mp) features. Models of MR features for predicting malignant and benign lesions as well as subtyping SRM were developed using a training dataset and performance was evaluated in a test data-set using recursive partitioning (RP), gradient booting machine (GBM), and random forest (RF) methods.

RESULTS

In the test dataset, GBM and RF models demonstrated an accuracy of 86% (95% CI 75% to 93%) for predicting benign versus malignant SRM compared to 83% (95% CI 71% to 91%) for the RP model. RF had the greatest accuracy in predicting SRM subtypes, 81.2% (95% CI 69.5% to 89.9%) compared with GBM 73.4% (95% CI 60.9% to 83.7%) or RP 70.3% (95% CI 57.6% to 81.1%). Marginal homogeneity was reduced by the RF model compared with the RP model (P < 0.001), but not the GBM model (P = 0.135). All models had high sensitivity and specificity for clear cell and papillary renal cell carcinomas (RCC), but performed less well in differentiating chromophobe RCC, oncocytomas, and fat-poor angiomyolipomas.

CONCLUSION

Ensemble methods for prediction of SRM from radiologist-assessed image characteristics have high accuracy for distinguishing benign and malignant lesions. SRM subtype classification is limited by the ability to categorize chromophobe RCCs, oncocytomas, and fat-poor angiomyolipomas.

Chemical shift imaging in the identification of those renal tumours that contain microscopic fat and the utility of multiparametric MRI in their differentiation

INTRODUCTION

The aim of this study was to assess the qualitative and MRI findings of renal tumours, to determine which lesions contain microscopic fat, one of the potential differentiating factors between tumour types.

METHODS

73 patients who underwent 3 Tesla MRI including chemical shift imaging, with subsequent biopsy or excision for histopathological diagnosis, were included in the study. The images were reviewed for a decrease in signal intensity (SI) on the opposed phase compared with the in-phase gradient echo T1 images, indicating the presence of microscopic fat. The chemical shift index was then calculated as a percentage of SI change and compared with the pathological diagnosis.

RESULTS

In total, 38 (52%) of lesions demonstrated a decrease in SI, consistent with microscopic fat. Microscopic fat was found in 28 (80%) clear cell renal cell carcinomas (RCCs), 6 (66.7%) angiomyolipomas, 2 (20%) papillary RCCs, 1 (20%) chromophobe RCC and 1 (9.1%) oncocytoma. Pairwise comparison of means indicated that the amount of microscopic fat was significantly larger only for angiomyolipomas compared with clear cell RCCs (P < 0.001) and other renal lesions (P < 0.001).

CONCLUSIONS

A decrease in SI on opposed phase compared with in-phase chemical shift imaging favours the diagnosis of either clear cell RCC or an angiomyolipoma. When combined with other parameters in mpMRI, this may aid differentiation of benign from malignant tumours and differentiation of aggressive from indolent RCC subtypes. This may be of value where biopsy is non-diagnostic, not feasible due to location or in high-risk patients.

Can acoustic radiation force impulse imaging (ARFI) accurately diagnose renal masses?: A protocol of systematic review and meta-analysis

BACKGROUND

Renal masses are increasingly being discovered because of the wide accessibility of modern high resolution imaging procedures. Previous clinical studies have reported that acoustic radiation force impulse imaging (ARFI) is used for diagnosis of renal masses. However, no study has investigated this topic systematically. Therefore, this study will evaluate the diagnostic value of ARFI for the diagnosis of renal masses.

METHODS

A systematic search using the databases of Cochrane Library, EMBASE, Pubmed, WANGFANG, and China National Knowledge Infrastructure will be performed to identify studies in which patients with renal masses are assessed by ARFI. Two investigators will independently screen the literature and extract the data. Any discrepancies will be resolved via discussion with the senior author. Study quality will be assessed by the Quality Assessment of Diagnostic Accuracy Studies 2 tool, and pooled sensitivity and specificity of various ARFI findings for the diagnosis of renal masses will be determined. Summary receiver operating characteristic curve will be used to assess the overall performance of ARFI.

RESULTS

This study will evaluate the diagnostic value of ARFI for the diagnosis of renal masses through sensitivity, specificity, positive and negative likelihood ratio, and diagnostic odds ratio.

CONCLUSION

This study will summarize the most recent evidence that focusing on the diagnosis of ARFI for renal masses.

STUDY REGISTRATION

INPLASY202060105.

Primary and secondary diseases of the perinephric space: an approach to imaging diagnosis with emphasis on MRI

The perinephric space is the middle compartment of the retroperitoneum, containing the kidneys and adrenal glands. Differential considerations for diseases involving primarily the perinephric space differ from those arising from the kidney itself, show variant imaging features, and require identification and characterisation by interpreting radiologists-an imaging diagnosis can be suggested in many cases. Lymphangiomas are congenital cystic lesions that may contain lipid-laden chyle, which may be detectable on magnetic resonance imaging (MRI). Retroperitoneal fibrosis, Erdheim-Chester disease, and lymphoma may present as a perinephric soft tissue rind. Osseous findings favour Erdheim-Chester, ureteric obstruction favours retroperitoneal fibrosis, and associated lymphadenopathy with mass-effect, but without invasion of adjacent structures favours lymphoma. Extramedullary haematopoiesis and brown fat stimulation are both characterised by signal drop on opposed-phase T1-weighted (W) images, the former resulting from severe anaemia and the latter in the context of elevated serum catecholamines, especially in the setting of phaeochromocytoma. Liposarcoma is the most common primary sarcoma of the retroperitoneum. Metastases are uncommon; however, they can be seen in melanoma, among other primary malignancies. Increased T1W signal hyperintensity is typical of melanoma metastases and haematomas. Abscesses show non-enhancing fluid centrally with marked diffusion restriction. This article presents a review of the perinephric space, pathological conditions of the perinephric space, and an approach towards imaging and diagnosis using cross-sectional imaging, with emphasis on MRI. MRI provides better tissue characterisation, assessment of enhancement kinetics, and detection of intralesional fat in comparison to CT. Clinical and laboratory correlation or tissue sampling may be required for definitive diagnosis in some cases.

Diagnostic accuracy of signal loss in in-phase gradient-echo images for differentiation between small renal cell carcinoma and lipid-poor angiomyolipomas

OBJECTIVES

To assess the diagnostic accuracy of signal loss on in-phase (IP) gradient-echo (GRE) images for differentiation between renal cell carcinomas (RCCs) and lipid-poor angiomyolipomas (lpAMLs).

METHODS

We retrospectively searched our institutional database for histologically proven small RCCs (<5.0 cm) and AMLs without visible macroscopic fat (lpAMLs). Two experienced radiologists assessed MRIs qualitatively, to depict signal loss foci on IP GRE images. A third radiologist drew regions of interest (ROIs) on the same lesions, on IP and out-of-phase (OP) images to calculate the ratio of signal loss. Diagnostic accuracy parameters were calculated for both techniques and the inter-reader agreement for the qualitative analysis was evaluated using the κ test.

RESULTS

15 (38.4%) RCCs lost their signal on IP images, with a sensitivity of 38.5% (95% CI = 23.4-55.4), a specificity of 100% (71.1-100), a positive predictive value (PPV) of 100% (73.4-100), a negative predictive value (NPV) of 31.4% (26.3-37.0), and an overall accuracy of 52% (37.4-66.3%). In terms of the quantitative analysis, the signal intensity index (SII= [(SI_IP - SI_OP) / SI_OP] x 100) for RCCs was -0.132 ± 0.05, while for AMLs it was -0.031 ± 0.02, p = 0.26. The AUC was 0.414 ± -0.09 (0.237-0.592). Using 19% of signal loss as the threshold, sensitivity was 16% and specificity was 100%. The κappa value for subjective analysis was 0.63.

CONCLUSION

Signal loss in "IP" images, assessed subjectively, was highly specific for distinction between RCCs and lpAMLs, although with low sensitivity. The findings can be used to improve the preoperative diagnostic accuracy of MRI for renal masses.

ADVANCES IN KNOWLEDGE

Signal loss on "IP" GRE images is a reliable sign for differentiation between RCC and lpAMLs.

Role of MRI in Staging of Penile Cancer

Penile cancer is one of the male-specific cancers. Accurate pretreatment staging is crucial due to a plethora of treatment options currently available. The 8^th edition American Joint Committee on Cancer-Tumor Node and Metastasis (AJCC-TNM) revised the staging for penile cancers, with invasion of corpora cavernosa upstaged from T2 to T3 and invasion of urethra downstaged from T3 to being not separately relevant. With this revision, MRI is more relevant in local staging because MRI is accurate in identifying invasion of corpora cavernosa, while the accuracy is lower for detection of urethral involvement. The recent European Urology Association (EAU) guidelines recommend MRI to exclude invasion of the corpora cavernosa, especially if penis preservation is planned. Identification of satellite lesions and measurement of residual-penile-length help in surgical planning. When nonsurgical treatment modalities of the primary tumor are being considered, accurate local staging helps in decision-making regarding upfront inguinal lymph node dissection as against surveillance. MRI helps in detection and extent of inguinal and pelvic lymphadenopathy and is superior to clinical palpation, which continues to be the current approach recommended by National Comprehensive Cancer Network (NCCN) treatment guidelines. MRI helps the detection of "bulky" lymph nodes that warrant neoadjuvant chemotherapy and potentially identify extranodal extension. However, tumor involvement in small lymph nodes and differentiation of reactive vs. malignant lymphadenopathy in large lymph nodes continue to be challenging and the utilization of alternative contrast agents (superparamagnetic iron oxide), positron emission tomography (PET)-MRI along with texture analysis is promising. In locally recurrent tumors, MRI is invaluable in identification of deep invasion, which forms the basis of treatment. Multiparametric MRI, especially diffusion-weighted-imaging, may allow for quantitative noninvasive assessment of tumor grade and histologic subtyping to avoid biopsy undersampling. Further research is required for incorporation of MRI with deep learning and artificial intelligence algorithms for effective staging in penile cancer. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:1612-1629.

Characterization of clear cell renal cell carcinoma and other renal tumors: evaluation of dual-energy CT using material-specific iodine and fat imaging

OBJECTIVE

This study aimed to assess material-specific iodine and fat images for diagnosis of clear cell renal cell carcinoma (cc-RCC) compared to papillary RCC (p-RCC) and other renal masses.

MATERIALS AND METHODS

With IRB approval, we identified histologically confirmed solid renal masses that underwent rapid-kVp-switch DECT between 2016 and 2018: 25 cc-RCC (7 low grade versus 18 high grade), 11 p-RCC, and 6 other tumors (2 clear cell papillary RCC, 2 chromophobe RCC, 1 oncocytoma, 1 renal angiomyomatous tumor). A blinded radiologist measured iodine and fat concentration on material-specific iodine-water and fat-water basis pair images. Comparisons were performed between groups using univariate analysis and diagnostic accuracy calculated by ROC.

RESULTS

Iodine concentration was higher in cc-RCC (6.14 ± 1.79 mg/mL) compared to p-RCC (1.40 ± 0.54 mg/mL, p < 0.001), but not compared to other tumors (5.0 ± 2.2 mg/mL, p = 0.370). Intratumoral fat was seen in 36.0% (9/25) cc-RCC (309.6 ± 234.3 mg/mL [71.1-762.3 ng/mL]), 9.1% (1/11) papillary RCC (97.11 mg/mL), and no other tumors (p = 0.036). Iodine concentration ≥ 3.99 mg/mL achieved AUC and sensitivity/specificity of 0.88 (CI 0.76-1.00) and 92.31%/82.40% to diagnose cc-RCC. To diagnose p-RCC, iodine concentration ≤ 2.5 mg/mL achieved AUC and sensitivity/specificity of 0.99 (0.98-1.00) and 100%/100%. The presence of intratumoral fat had AUC 0.64 (CI 0.53-0.75) and sensitivity/specificity of 34.6%/93.8% to diagnose cc-RCC. A logistic regression model combining iodine concentration and presence of fat increased AUC to 0.91 (CI 0.81-1.0) with sensitivity/specificity of 80.8%/93.8% to diagnose cc-RCC.

CONCLUSION

Iodine concentration values are highly accurate to differentiate clear cell RCC from papillary RCC; however, they overlap with other tumors. Fat-specific images may improve differentiation of clear cell RCC from other avidly enhancing tumors.

KEY POINTS

• Clear cell renal cell carcinoma (RCC) has significantly higher iodine concentration than papillary RCC, but there is an overlap in values comparing clear cell RCC to other renal tumors. • Iodine concentration ≤ 2.5 mg/mL is highly accurate to differentiate papillary RCC from clear cell RCC and other renal tumors. • The presence of microscopic fat on material-specific fat images was specific for clear cell RCC, helping to differentiate clear cell RCC from other avidly enhancing renal tumors.

Renal Cell Carcinoma: the Oncologist Asks, Can PSMA PET/CT Answer?

PURPOSE OF REVIEW

To critically review the potential clinical applications of prostate-specific membrane antigen (PSMA) radioactive ligands in renal cell carcinoma (RCC).

RECENT FINDINGS

Radioactive probes targeting PSMA hold promise in several malignancies in addition to prostate cancer, owing to the expression of PSMA by tumor neovasculature. The majority of clear cell RCCs (ccRCC), the most malignant RCC subtype, express PSMA on tumor-associated neovasculature. The endothelium of less aggressive RCC subtypes is PSMA positive in a lower, but still significant percentage of cases. PSMA might therefore represent an interesting theragnostic target in RCC. The preliminary data available suggest a potential role for PSMA-targeting radiopharmaceuticals in complementing conventional imaging for staging ccRCC patients at risk of nodal involvement and oligometastatic disease. Additional applications of PSMA imaging may be the selection and the response assessment of patients receiving anti-angiogenic treatments. The effectiveness of PSMA-targeting radionuclide therapy should also be investigated.

Diagnostic performance of prospectively assigned clear cell Likelihood scores (ccLS) in small renal masses at multiparametric magnetic resonance imaging

INTRODUCTION

Detection of small renal masses (SRM) is increasing with the use of cross-sectional imaging, although many incidental lesions have negligible metastatic potential. A method to identify this subtype would aid in risk stratification. A previously reported clear cell likelihood score (ccLS; 1-very unlikely, 2-unlikely, 3-equivocal, 4-likely, and 5-very likely), based on retrospective review of multiparametric magnetic resonance imaging (mpMRI), predicted the likelihood of encountering clear cell renal cell carcinoma (ccRCC) at surgery. Here, we assess the performance of ccLS prospectively assigned for prediction of ccRCC.

METHODS

Patients with a known renal mass who underwent mpMRI at a single institution between June 2016 and April 2018 were prospectively assigned a ccLS as part of the clinical MRI report. These patients were retrospectively reviewed, and those with a cT1a lesion and available pathological tissue diagnosis (diagnostic biopsy or extirpative surgery) were selected for analysis.

RESULTS

In total, 57 patients (mean age 61.7 ± 14.9 years) with 63 cT1a renal masses were identified. Mean tumor size was 2.7 ± 0.7 cm. Defining ccLS 4-5 lesions as positive demonstrated an overall accuracy of 84%, sensitivity of 89%, specificity of 79%, positive predictive value of 84%, and negative predictive value of 86%. A ccLS of 1-2 demonstrates an 86% accuracy and 100% sensitivity/positive predictive value of identifying non-ccRCC histology.

CONCLUSIONS

Utilizing prospectively assigned ccLS, we confirm that mpMRI can reasonably identify ccRCC histology in cT1a renal masses. Standardization of imaging protocols and reporting criteria such as the ccLS can be used to aid in the diagnosis and management of small renal masses.

Roles for active surveillance in renal cancer

PURPOSE OF REVIEW

With this review, we describe the most recent advances in active surveillance as well as diagnosis and management of small renal masses (SRMs).

RECENT FINDINGS

We discuss diagnosis, differentiation of solid from cystic lesions, risk prediction and treatment of the SRM. A better understanding of the disease facilitates the use of more conservatory treatments, such as active surveillance. Active surveillance has been increasingly accepted not only for SRM, but also for larger tumors and even metastatic patients. Exiting advances in risk prediction will help us define which patients can be safely managed with active surveillance and which require immediate treatment. Meanwhile, the use of renal tumor biopsies is still an important tool for these cases.

SUMMARY

Active surveillance is an option for many patients with renal masses. Noninvasive methods for diagnosis and risk prediction are being developed, but meanwhile, renal tumor biopsy is a useful tool. A better understanding of the disease increases the number of patients who can undergo active surveillance fully certain of the safety of their management.

Validation of Region of Interest Measurements for the Objective Assessment of Post-Contrast Enhancement of Renal Lesions on MRI

OBJECTIVE

The aim of this study was to validate the use of region of interest (ROI) measurements in MRI to objectively assess for enhancement in suspected solid renal masses and to determine a minimum threshold value for true enhancement.

METHODS

Contrast-enhanced renal MRI studies performed between January 2015 and December 2017 for patients with a known renal mass who had subsequent biopsy, or partial/radical nephrectomy were included. Two body imaging fellows independently measured the mean ROI values of renal masses, normal renal parenchyma, the ipsilateral psoas muscle and external air on the pre- and post-contrast sequences. The absolute and percentage changes in the mean ROI values were calculated. The readers were blinded to the pathology results.

RESULTS

104 patients were included in this study (mean age of 65 years; 58 males and 46 females). 74 patients (71%) had a diagnosis of renal cell carcinoma (RCC). Pathology showed clear-cell RCC in 55%, papillary RCC in 22%, and other RCC subtypes in 23%. There were 30 non-RCC renal lesions (29%), including oncocytoma, renal papillary adenoma, and renal metastasis.The minimum percentage change in ROI values in the pre- versus post-contrast images for all pathology-proven RCCs was 23% (range: 23-437%, mean: 143%); this represents relative enhancement and was referred to as the Signal Intensity Index (SII). The percentage change for normal renal parenchyma ranged from 32-317%. The maximum percentage change in ROI values for pathology proven renal cysts was 13% (range: -5-13%, mean: 3.5%). There was excellent inter observer agreement between the two readers [Intra-class correlation coefficient (r) 0.81].

CONCLUSION

The percentage change in ROI values (SII) can be a helpful tool in the objective assessment of true enhancement of renal masses and can supplement subtraction images. The minimum threshold for enhancement in our study was 23%.

ADVANCES IN KNOWLEDGE

Enhancement of a renal lesion can be determined using the objective tool of ROI measurements in the pre- and post-contrast MR images with a percentage change of 20% or above indicating enhancement. This is an additional objective tool, which in conjunction with the subtraction images may improve detection and appropriate diagnosis of renal lesions. It could also be helpful in cases where the subtraction images are degraded by motion artefact.

Can MRI be used to diagnose histologic grade in T1a (< 4 cm) clear cell renal cell carcinomas?

OBJECTIVE

To assess whether MRI can differentiate low-grade from high-grade T1a cc-RCC.

MATERIALS AND METHODS

With IRB approval, 49 consecutive solid < 4 cm cc-RCC (low grade [Grade 1 or 2] N = 38, high grade [Grade 3] N = 11) with pre-operative MRI before nephrectomy were identified between 2013 and 2018. Tumor size, apparent diffusion coefficient (ADC) histogram analysis, enhancement wash-in and wash-out rates, and chemical shift signal intensity index (SI index) were assessed by a blinded radiologist. Subjectively, two blinded Radiologists also assessed for (1) microscopic fat, (2) homogeneity (5-point Likert scale), and (3) ADC signal (relative to renal cortex); discrepancies were resolved by consensus. Outcomes were studied using Chi square, multivariate analysis, logistic regression modeling, and ROC. Inter-observer agreement was assessed using Cohen's kappa.

RESULTS

Tumor size was 24 ± 7 (13-39) mm with no association to grade (p = 0.45). Among quantitative features studied, corticomedullary phase wash-in index (p = 0.015), SI index (p = 0.137), and tenth-centile ADC (p = 0.049) were higher in low-grade tumors. 36.8% (14/38) low-grade tumors versus zero high-grade tumors demonstrated microscopic fat (p = 0.015; Kappa = 0.67). Microscopic fat was specific for low-grade disease (100.0% [71.5-100.0]) with low sensitivity (36.8% [21.8-54.6]). Other subjective features did not differ between groups (p > 0.05). A logistic regression model combining microscopic fat + wash-in index + tenth-centile-ADC yielded area under ROC curve 0.98 (Confidence Intervals 0.94-1.0) with sensitivity/specificity 87.5%/100%.

CONCLUSION

The combination of microscopic fat, higher corticomedullary phase wash-in and higher tenth-centile ADC is highly accurate for diagnosis of low-grade disease among T1a clear cell RCC.

Common pitfalls in renal mass evaluation: a practical guide

More than half of patients over 50 years of age have had at least one focal renal lesion detected as an incidental finding during an ultrasound, computed tomography, or magnetic resonance imaging examination. Although the majority of such lesions can be easily detected and correctly characterized, misdiagnoses may occur and are often related to methodological limitations, inappropriate imaging protocols, or misinterpretation. This pictorial essay provides recommendations on how to recognize benign and malignant renal processes that can be potentially missed or mischaracterized in imaging studies.

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.