MRI evaluation of small (<4cm) solid renal masses: multivariate modeling improves diagnostic accuracy for angiomyolipoma without visible fat compared to univariate analysis

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.

Diagnostic Value of Clear Cell Likelihood Score v1.0 and v2.0 for Common Subtypes of Small Renal Masses: A Multicenter Comparative Study

BACKGROUND

Clear cell likelihood score (ccLS) is reliable for diagnosing small renal masses (SRMs). However, the diagnostic value of Clear cell likelihood score version 1.0 (ccLS v1.0) and v2.0 for common subtypes of SRMs might be a potential score extension.

PURPOSE

To compare the diagnostic performance and interobserver agreement of ccLS v1.0 and v2.0 for characterizing five common subtypes of SRMs.

STUDY TYPE

Retrospective.

POPULATION

797 patients (563 males, 234 females; mean age, 53 ± 12 years) with 867 histologically proven renal masses.

FIELD STRENGTH/SEQUENCES

3.0 and 1.5 T/T2 weighted imaging, T1 weighted imaging, diffusion-weighted imaging, a dual-echo chemical shift (in- and opposed-phase) T1 weighted imaging, multiphase dynamic contrast-enhanced imaging.

ASSESSMENT

Six abdominal radiologists were trained in the ccLS algorithm and independently scored each SRM using ccLS v1.0 and v2.0, respectively. All SRMs had definite pathological results. The pooled area under curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the diagnostic performance of ccLS v1.0 and v2.0 for characterizing common subtypes of SRMs. The average κ values were calculated to evaluate the interobserver agreement of the two scoring versions.

STATISTICAL TESTS

Random-effects logistic regression; Receiver operating characteristic analysis; DeLong test; Weighted Kappa test; Z test. The statistical significance level was P < 0.05.

RESULTS

The pooled AUCs of clear cell likelihood score version 2.0 (ccLS v2.0) were statistically superior to those of ccLS v1.0 for diagnosing clear cell renal cell carcinoma (ccRCC) (0.907 vs. 0.851), papillary renal cell carcinoma (pRCC) (0.926 vs. 0.888), renal oncocytoma (RO) (0.745 vs. 0.679), and angiomyolipoma without visible fat (AMLwvf) (0.826 vs. 0.766). Interobserver agreement for SRMs between ccLS v1.0 and v2.0 is comparable and was not statistically significant (P = 0.993).

CONCLUSION

The diagnostic performance of ccLS v2.0 surpasses that of ccLS v1.0 for characterizing ccRCC, pRCC, RO, and AMLwvf. Especially, the standardized algorithm has optimal performance for ccRCC and pRCC. ccLS has potential as a supportive clinical tool.

EVIDENCE LEVEL

4.

TECHNICAL EFFICACY

Stage 2.

Metabolomics analysis of amino acid and fatty acids in colorectal cancer patients based on tandem mass spectrometry

Metabolic differences between colorectal cancer (CRC) and NI (NI) play an important role in early diagnoses and in-time treatments. We investigated the metabolic alterations between CRC patients and NI, and identified some potential biomarkers, and these biomarkers might be used as indicators for diagnosis of CRC. In this study, there were 79 NI, 50 CRC I patients, 52 CRC II patients, 56 CRC III patients, and 52 CRC IV patients. MS-MS was used to measure the metabolic alterations. Univariate and multivariate data analysis and metabolic pathway analysis were applied to analyze metabolic data and determine differential metabolites. These indicators revealed that amino acid and fatty acids could separate these groups. Several metabolites indicated an excellent variables capability in the separation of CRC patients and NI. Ornithine, arginine, octadecanoyl carnitine, palmitoyl carnitine, adipoyl carnitine, and butyryl carnitine/propanoyl carnitine were selected to distinguish the CRC patients and NI. And methionine and propanoyl carnitine, were directly linked to different stages of CRC. Receiver operating characteristics curves and variables importance in projection both represented an excellent performance of these metabolites. In conclusion, we assessed the difference between CRC patients and NI, which supports guidelines for an early diagnosis and effective treatment.

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.

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.

Comparison of MRI features in lipid-rich and lipid-poor adrenal adenomas using subjective and quantitative analysis

OBJECTIVE

To compare MR-imaging features in benign lipid-rich and lipid-poor adrenal adenomas.

MATERIALS AND METHODS

With institutional review board approval, we compared 23 consecutive lipid-poor adenomas (chemical shift [CS] signal intensity [SI] index < 16.5%) imaged with MRI to 29 consecutive lipid-rich adenomas (CS-SI index ≥ 16.5%) imaged during the same time period. A blinded radiologist measured T2-weighted (T2W) SI ratio (adrenal adenoma/psoas muscle), dynamic enhancement wash-in (WI) and wash-out (WO) indices, and T2W texture features. Two blinded Radiologists (R1/R2) assessed T2W-SI (relative to renal cortex) and T2W heterogeneity (using 5-Point Likert scales). Comparisons were performed between groups using independent t tests and Chi-square with Holm-Bonferroni correction.

RESULTS

There was no difference in age or gender between groups (p = 0.594, 0.051 respectively). Subjectively, all lipid-rich and lipid-poor adenomas were rated hypointense or isointense compared to renal cortex and T2W-SI did not differ between groups (p = 0.129, 0.124 for R1, R2). Agreement was substantial (Kappa = 0.67). There was no difference in T2W SI ratio (1.8 ± 0.9 [0.5-4.3] lipid rich versus 2.2 ± 1.0 [0.6-4.3] lipid poor, p = 0.139). Enhancement WI and WO did not differ comparing lipid-rich and lipid-poor adenomas (p = 0.759, 0.422 respectively). There was no difference comparing lipid-rich and lipid-poor adenomas T2W heterogeneity judged subjectively (p = 0.695, 0.139 for R1, R2; Kappa = 0.19) or by texture analysis (entropy, kurtosis, skewness; p = 0.134-0.191) with all adenomas except for one rated as mostly or completely homogeneous.

CONCLUSIONS

There is no difference in T2W signal intensity, enhancement pattern or T2W heterogeneity judged subjectively or by quantitative texture analysis comparing lipid-poor and lipid-rich adrenal adenomas.

Differentiation of renal angiomyolipoma without visible fat from small clear cell renal cell carcinoma by using specific region of interest on contrast-enhanced CT: a new combination of quantitative tools

Background

To investigate the value of using specific region of interest (ROI) on contrast-enhanced CT for differentiating renal angiomyolipoma without visible fat (AML.wovf) from small clear cell renal cell carcinoma (ccRCC).

Methods

Four-phase (pre-contrast phase [PCP], corticomedullary phase [CMP], nephrographic phase [NP], and excretory phase [EP]) contrast-enhanced CT images of AML.wovf (n = 31) and ccRCC (n = 74) confirmed by histopathology were retrospectively analyzed. The CT attenuation value of tumor (AVT), net enhancement value (NEV), relative enhancement ratio (RER), heterogeneous degree of tumor (HDT) and standardized heterogeneous ratio (SHR) were obtained by using different ROIs [small: ROI (1), smaller: ROI (2), large: ROI (3)], and the differences of these quantitative data between AML.wovf and ccRCC were statistically analyzed. Multivariate regression was used to screen the main factors for differentiation in each scanning phase, and the prediction models were established and evaluated.

Results

Among the quantitative parameters determined by different ROIs, the degree of enhancement measured by ROI (2) and the enhanced heterogeneity measured by ROI (3) performed better than ROI (1) in distinguishing AML.wovf from ccRCC. The receiver operating characteristic (ROC) curves showed that the area under the curve (AUC) of RER_CMP (2), RER_NP (2) measured by ROI (2) and HDT_CMP and SHR_CMP measured by ROI (3) were higher (AUC = 0.876, 0.849, 0.837 and 0.800). Prediction models that incorporated demographic data, morphological features and quantitative data derived from the enhanced phase were superior to quantitative data derived from the pre-contrast phase in differentiating between AML.wovf and ccRCC. Among them, the model in CMP was the best prediction model with the highest AUC (AUC = 0.986).

Conclusion

The combination of quantitative data obtained by specific ROI in CMP can be used as a simple quantitative tool to distinguish AML.wovf from ccRCC, which has a high diagnostic value after combining demographic data and morphological features.

A review of clinical and MR imaging features of renal lipid-poor angiomyolipomas

BACKGROUND

Lipid-poor angiomyolipomas (lpAMLs) constitute up to 5% of renal angiomyolipomas and are challenging to differentiate from malignant renal lesions on imaging alone. This review aims to identify clinical and MRI features which can be utilized to improve specificity and diagnostic accuracy for detecting lpAMLs in patients being considered for active surveillance rather than intervention.

FINDINGS

Young age, female sex, and small lesion size are associated with lpAMLs in studies evaluating indeterminate renal lesions. The accuracy of criteria using T2-weighted imaging, diffusion-weighted imaging, chemical shift imaging, dynamic contrast enhancement, multiparametric imaging, and radiomics are reviewed. Low T2 signal intensity is a particularly important MRI feature for lpAML. In studies with low T2 signal intensity, homogeneous early enhancement is a typical feature with an arterial-to-delay enhancement ratio > 1.5. Intratumoral hemorrhage with decrease in signal intensity on in-phase chemical shift imaging may be particularly useful for differentiating papillary renal cell carcinomas from lpAMLs in low T2 signal intensity lesions. Combining clinical and multiparametric MRI features can result in near-perfect specificity for lpAML. In select patients, clinical and MRI features can result in a high specificity and diagnostic accuracy for lpAMLs. These lesions can be considered for active surveillance rather than invasive diagnostic and therapeutic procedures such as biopsy or 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.

Univariate Analysis of Short-Chain Fatty Acids Related to Sudden Infant Death Syndrome

Sudden infant death syndrome (SIDS) is defined as the death of a child under one year of age, during sleep, without apparent cause, after exhaustive investigation, so it is a diagnosis of exclusion. SIDS is the principal cause of death in industrialized countries. Inborn errors of metabolism (IEM) have been related to SIDS. These errors are a group of conditions characterized by the accumulation of toxic substances usually produced by an enzyme defect and there are thousands of them and included are the disorders of the β-oxidation cycle, similarly to what can affect the metabolism of different types of fatty acid chain (within these, short chain fatty acids (SCFAs)). In this work, an analysis of postmortem SCFAs profiles of children who died due to SIDS is proposed. Initially, a set of features containing SCFAs information, obtained from the NIH Common Fund's National Metabolomics Data Repository (NMDR) is submitted to an univariate analysis, developing a model based on the relationship between each feature and the binary output (death due to SIDS or not), obtaining 11 univariate models. Then, each model is validated, calculating their receiver operating characteristic curve (ROC curve) and area under the ROC curve (AUC) value. For those features whose models presented an AUC value higher than 0.650, a new multivariate model is constructed, in order to validate its behavior in comparison to the univariate models. In addition, a comparison between this multivariate model and a model developed based on the whole set of features is finally performed. From the results, it can be observed that each SCFA which comprises of the SFCAs profile, has a relationship with SIDS and could help in risk identification.

ACR Appropriateness Criteria® Indeterminate Renal Mass

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

Magnetic resonance imaging features of minimal-fat angiomyolipoma and causes of preoperative misdiagnosis

BACKGROUND

Minimal-fat angiomyolipoma (mf-AML) is often misdiagnosed as renal cell carcinoma before surgery.

AIM

To analyze the magnetic resonance imaging (MRI) features of mf-AML and the causes of misdiagnosis by MRI before operation.

METHODS

A retrospective analysis was performed on ten patients with mf-AML confirmed by surgical pathology, all of whom underwent preoperative MRI examination to analyze the morphological characteristics and MRI signals of the tumor.

RESULTS

MRI revealed a circular-like mass in 4/10 (40%) patients, an oval mass in 6/10 patients (60%), a mass with a capsule in 9/10 patients (90%), and a mass with a lipid component in 7/10 patients (70%). The diameter of the masses in all ten patients was from 11 to 47 mm; the diameter was between 11 mm and 40 mm in 8/10 (80%) patients and between 40 mm and 47 mm in 2/10 (20%) patients.

CONCLUSION

An oval morphological characteristic is strong evidence for the diagnosis of mf-AML, while a capsule and lipids are atypical manifestations of mf-AML.

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.

Quantitative Analysis of Multiphase Contrast-Enhanced CT Images: A Pilot Study of Preoperative Prediction of Fat-Poor Angiomyolipoma and Renal Cell Carcinoma

OBJECTIVE. The objective of our study was to preoperatively predict fat-poor angiomyolipoma (fp-AML) and renal cell carcinoma (RCC) by conducting quantitative analysis of contrast-enhanced CT images. MATERIALS AND METHODS. One hundred fifteen patients with a pathologic diagnosis of fp-AML or RCC from a single institution were randomly allocated into a train set (tumor size: mean ± SD, 4.50 ± 2.62 cm) and test set (tumor size: 4.32 ± 2.73 cm) after data augmentation. High-dimensional histogram-based features, texture-based features, and Laws features were first extracted from CT images and were then combined as different combinations sets to construct a logistic prediction model based on the least absolute shrinkage and selection operator procedure for the prediction of fp-AML and RCC. Prediction performances were assessed by classification accuracy, area under the ROC curve (AUC), positive predictive value, negative predictive value, true-positive rate, and false-positive rate (FPR). In addition, we also investigated the effects of different gray-scales of quantitative features on prediction performances. RESULTS. The following combination sets of features achieved satisfying performances in the test set: histogram-based features (mean AUC = 0.8492, mean classification accuracy = 91.01%); histogram-based features and texture-based features (mean AUC = 0.9244, mean classification accuracy = 91.81%); histogram-based features and Laws features (mean AUC = 0.8546, mean classification accuracy = 88.76%); and histogram-based features, texture-based features, and Laws features (mean AUC = 0.8925, mean classification accuracy = 90.36%). The different quantitative gray-scales did not have an obvious effect on prediction performances. CONCLUSION. The integration of histogram-based features with texture-based features and Laws features provided a potential biomarker for the preoperative diagnosis of fp-AML and RCC. The accurate diagnosis of benign or malignant renal masses would help to make the clinical decision for radical surgery or close follow-up.

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.

Renal and adrenal masses containing fat at MRI: Proposed nomenclature by the society of abdominal radiology disease-focused panel on renal cell carcinoma

This article proposes a consensus nomenclature for fat-containing renal and adrenal masses at MRI to reduce variability, improve understanding, and enhance communication when describing imaging findings. The MRI appearance of "macroscopic fat" occurs due to a sufficient number of aggregated adipocytes and results in one or more of: 1) intratumoral signal intensity (SI) loss using fat-suppression techniques, or 2) chemical shift artifact of the second kind causing linear or curvilinear India-ink (etching) artifact within or at the periphery of a mass at macroscopic fat-water interfaces. "Macroscopic fat" is most commonly observed in adrenal myelolipoma and renal angiomyolipoma (AML) and only rarely encountered in other adrenal cortical tumors and renal cell carcinomas (RCC). Nonlinear noncurvilinear signal intensity loss on opposed-phase (OP) compared with in-phase (IP) chemical shift MRI (CSI) may be referred to as "microscopic fat" and is due to: a) an insufficient amount of adipocytes, or b) the presence of fat within tumor cells. Determining whether the signal intensity loss observed on CSI is due to insufficient adipocytes or fat within tumor cells cannot be accomplished using CSI alone; however, it can be inferred when other imaging features strongly suggest a particular diagnosis. Fat-poor AML are homogeneously hypointense on T₂ -weighted (T₂ W) imaging and avidly enhancing; signal intensity loss at OP CSI is uncommon, but when present is usually focal and is caused by an insufficient number of adipocytes within adjacent voxels. Conversely, clear-cell RCC are heterogeneously hyperintense on T₂ W imaging and avidly enhancing, with the signal intensity loss observed on OP CSI being typically diffuse and due to fat within tumor cells. Adrenal adenomas, adrenal cortical carcinoma, and adrenal metastases from fat-containing primary malignancies also show signal intensity loss on OP CSI due to fat within tumor cells and not from intratumoral adipocytes. Level of Evidence: 5 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019;49:917-926.

Evaluation of a free-breathing respiratory-triggered (Navigator) 3-D T1-weighted (T1W) gradient recalled echo sequence (LAVA) for detection of enhancement in cystic and solid renal masses

OBJECTIVES

To evaluate free-breathing Navigator-triggered 3-D T1-weighted MRI (NAV-LAVA) compared to breath-hold (BH)-LAVA among cystic and solid renal masses.

MATERIALS AND METHODS

With an IRB waiver, 44 patients with 105 renal masses (71 non-enhancing cysts and 14 cystic and 20 solid renal masses) underwent MRI between 2016 and 2017 where BH-LAVA and NAV-LAVA were performed. Subtraction images were generated for BH-LAVA and NAV-LAVA using pre- and 3-min post-gadolinium-enhanced images and were evaluated by two blinded radiologists for overall image quality, image sharpness, motion artifact, and quality of subtraction (using 5-point Likert scales) and presence/absence of enhancement. Percentage signal intensity change (Δ%SI) = ([SI.post-gadolinium-SI.pre-gadolinium]/SI.pre-gadolinium)*100, was measured on BH-LAVA and NAV-LAVA. Likert scores were compared using Wilcoxon's sign-rank test and accuracy for detection of enhancement compared using receiver operator characteristic (ROC) analysis.

RESULTS

Overall image quality (p = 0.002-0.141), image sharpness (p = 0.002-0.031), and motion artifact were better (p = 0.002) comparing BH-LAVA to NAV-LAVA for both radiologists; however, quality of image subtraction did not differ between groups (p = 0.09-0.14). Sensitivity/specificity/area under ROC curve for enhancement in cystic and solid renal masses using subtraction and %SIΔ were (1) BH-LAVA: 64.7%/98.6%/0.82 (radiologist 1), 61.8%/95.8%/0.79 (radiologist 2), and 70.6%/81.7%/0.76 (%SIΔ) versus 2) NAV-LAVA: 58.8%/95.8%/0.79 (radiologist 1, p = 0.16), 58.8%/88.7%/0.73 (radiologist 2, p = 0.37), and 73.5%/76.1%/0.75 (%SIΔ, p = 0.74).

CONCLUSIONS

NAV-LAVA showed similar quality of subtraction and ability to detect enhancement compared to BH-LAVA in renal masses albeit with lower image quality, image sharpness, and increased motion artifact. NAV-LAVA may be considered in renal MRI for patients where BH is suboptimal.

KEY POINTS

• Free-breathing Navigator (NAV) 3-D subtraction MRI is comparable to breath-hold (BH) images. • Accuracy for subjective and quantitative diagnosis of enhancement in renal masses on NAV 3-D T1W is comparable to BH MRI. • NAV 3-D T1W renal MRI is useful in patients who may not be able to adequately BH.

Sonographic Features of Small (< 4 cm) Renal Tumors With Low Signal Intensity on T2-Weighted MR Images: Differentiating Minimal-Fat Angiomyolipoma From Renal Cell Carcinoma

OBJECTIVE

The purpose of this study is to characterize and assess the diagnostic utility of sonographic features of minimal-fat angiomyolipoma (AML) and renal cell carcinoma (RCC) with regard to small (< 4 cm) renal masses with a predominantly low signal intensity (SI) on T2-weighted MR images.

MATERIALS AND METHODS

Fifty small renal masses with a predominantly low SI on T2-weighted MR images and no macroscopic fat, all of which had US images available, were assessed. MRI variables (T2 ratio, signal intensity index [SII], and tumor-to-spleen ratio on chemical-shift images), CT features (enhancement patterns and attenuations values on unenhanced images and images obtained in the corticomedullary and nephrographic phases), and sonographic features (echogenicity, heterogeneity, and the presence of acoustic shadowing, a hypoechoic rim, or an intratumoral cyst) were recorded in a blinded manner. Echo-genicity was classified as hypo-, iso-, or hyperechoic compared with the renal parenchyma or markedly hyperchoic when equivalent to that of the renal sinus fat.

RESULTS

Minimal-fat AML and RCC were confirmed in 22 and 28 patients, respectively. T2 ratios were significantly lower for minimal-fat AML versus RCCs (p = 0.044). Minimal-fat AMLs exhibited echogenicities that were considered hypoechoic (31.8%), isoechoic (4.5%), hyperechoic (18.2%), or markedly hyperechoic (45.5%). No RCC showed marked hyperechogenicity. CT attenuation values were significantly higher for the minimal-fat AMLs seen in all imaging phases. When the combination of the T2 ratio, nephrographic phase attenuation, and echogenicity was assessed, the AUC value was 0.93 (95% CI, 0.81-0.98), which was a significant increase over the AUC value of 0.83 (95% CI, 0.69-0.92) for noted the combination of the T2 ratio and nephrographic phase attenuation.

CONCLUSION

Additional reviews of the echogenicity of small renal masses with low SI on T2-weighted MR images may aid the diagnosis of minimal-fat AML.

Imaging of Solid Renal Masses

The increase in serendipitous detection of solid renal masses on imaging has not resulted in a reduction in mortality from renal cell carcinoma. Consequently, efforts for improved lesion characterization have been pursued and incorporated into management algorithms for distinguishing clinically significant tumors from those with favorable histology or benign conditions. Although diagnostic imaging strategies have evolved for optimized lesion detection, distinction between benign tumors and both indolent and aggressive malignant neoplasms remain an important diagnostic challenge. Recent advances in cross-sectional imaging have expanded the role of these tests in the noninvasive characterization of solid renal tumors.

Characterization of Small Renal Tumors With Magnetic Resonance Elastography: A Feasibility Study

OBJECTIVES

The aim of this study was to explore the feasibility of magnetic resonance elastography (MRE) for characterizing indeterminate small renal tumors (SRTs) as part of a multiparametric magnetic resonance (MR) imaging protocol.

MATERIALS AND METHODS

After institutional review board approval and informed consent were obtained, 21 prospective adults (15 men; median age, 55 years; age range, 25-72 years) with SRT were enrolled. Tumors (2-5 cm Ø) were imaged using 3-directional, gradient echo MRE. Viscoelastic parametric maps (shear wave velocity [c] and attenuation [α]) were analyzed by 2 independent radiologists. Interobserver agreement (Bland-Altman statistics and intraclass correlation coefficients) was assessed. Anatomical T2-weighted, dynamic contrast-enhanced (DCE) and diffusion sequences completed the acquisition protocol. Imaging parameters were compared between groups (Mann-Whitney U test).

RESULTS

Quality of MRE was good in 18 cases (mean nonlinearity <50%), including 1 papillary renal cell carcinoma and 1 metanephric adenoma. A cohort of 5 oncocytomas and 11 clear-cell renal cell carcinomas (ccRCCs) was analyzed for statistical differences. The MRE viscoelastic parameters were the strongest imaging discriminators: oncocytomas displayed significantly lower shear velocity c (median, 0.77 m/s; interquartile range [IQR], 0.76-0.79) (P = 0.007) and higher shear attenuation α (median, 0.087 mm; IQR, 0.082-0.087) (P = 0.008) than ccRCC (medians, 0.92 m/s and 0.066 mm; IQR, 0.84-0.97 and 0.054-0.074, respectively). T2 signal intensity ratio (tumor/renal cortex) was lower in oncocytomas (P = 0.02). The DCE and diffusion MR parameters overlapped substantially (P ≥ 0.1). Oncocytomas displayed a consistent MRE viscoelastic profile, corresponding to data point clustering in a bidimensional scatter plot. Values for MRE intraclass correlation coefficient were 0.982 for c and 0.984 for α, indicating excellent interobserver agreement.

CONCLUSIONS

Magnetic resonance elastography is feasible for SRT characterization; MRE viscoelastic parameters were stronger discriminators between oncocytoma and ccRCC than anatomical, DCE and diffusion MR imaging parameters.

Differentiation between papillary renal cell carcinoma and fat-poor angiomyolipoma: a preliminary study assessing detection of intratumoral hemorrhage with chemical shift MRI and T2*-weighted gradient echo

Background Recent literature suggests that intratumoral hemorrhage detection may be helpful in differentiating papillary renal cell carcinoma (pRCC) from fat-poor angiomyolipoma (fpAML). Purpose To determine whether intratumoral hemorrhage detected using chemical shift magnetic resonance imaging (MRI) and T2*-weighted (T2*W) gradient echo (GRE) can be used to differentiate pRCC from fpAML. Material and Methods This retrospective study included 42 patients with pRCC (n = 28) and fpAML (n = 14) who underwent MRI followed by surgery. Two blinded radiologists independently assessed the presence of intratumoral hemorrhage using chemical shift MRI (decrease in signal intensity from opposed- to in-phase) and T2*W GRE ("blooming"). Consensus reading was determined for discrepant cases. MRI findings were compared using Chi-square test. Inter-observer agreement was assessed using kappa statistics. Results Inter-observer agreement was substantial for both sequences ( k = 0.622 and 0.793, P < 0.001). For chemical shift MRI, the prevalence of intratumoral hemorrhage was significantly greater in pRCC than in fpAML (71.4% versus 28.6%, P = 0.019 for reader 1; 64.3% versus 14.3%, P = 0.003 for reader 2; and 75% versus 21.4%, P = 0.002 for the consensus). T2*W GRE showed a similar tendency (46.4% versus 14.3%, P = 0.049 for both readers; and 50% versus 14.3%, P = 0.042 for the consensus). Using the consensus reading, sensitivity and specificity of determining pRCC were 75% and 78.6% for chemical shift MRI and 50% and 85.7% for T2*W GRE. Conclusion The prevalence of intratumoral hemorrhage identified from chemical shift MRI or T2*W GRE was significantly different between pRCC and fpAML. These hemorrhage-sensitive MRI sequences may be used as an adjunctive tool for discriminating between the two entities.

Characterization of small (<4cm) solid renal masses by computed tomography and magnetic resonance imaging: Current evidence and further development

Diagnosis of renal cell carcinomas (RCC) subtypes on computed tomography (CT) and magnetic resonance imaging (MRI) is clinically important. There is increased evidence that confident imaging diagnosis is now possible while standardization of the protocols is still required. Fat-poor angiomyolipoma show homogeneously increased unenhanced attenuation, homogeneously low signal on T2-weighted MRI and apparent diffusion coefficient (ADC) map, may contain microscopic fat and are classically avidly enhancing. Papillary RCC are also typically hyperattenuating and of low signal on T2-weighted MRI and ADC map; however, their gradual progressive enhancement after intravenous administration of contrast material is a differentiating feature. Clear cell RCC are avidly enhancing and may show intracellular lipid; however, these tumors are heterogeneous and are of characteristically increased signal on T2-weighted MRI. Oncocytomas and chromophobe tumors (collectively oncocytic neoplasms) show intermediate imaging findings on CT and MRI and are the most difficult subtype to characterize accurately; however, both show intermediately increased signal on T2-weighted with more gradual enhancement compared to clear cell RCC. Chromophobe tumors tend to be more homogeneous compared to oncocytomas, which can be heterogeneous, but other described features (e.g. scar, segmental enhancement inversion) overlap considerably between tumors. Tumor grade is another important consideration in small solid renal masses with emerging studies on both CT and MRI suggesting that high grade tumors may be separated from lower grade disease based upon imaging features.

Are growth patterns on MRI in small (< 4 cm) solid renal masses useful for predicting benign histology?

PURPOSE

To evaluate previously described growth patterns in < 4 cm solid renal masses.

MATERIALS AND METHODS

With IRB approval, 63 renal cell carcinomas (RCC; clear cell n = 22, papillary n = 28, chromophobe n = 13) and 36 benign masses [minimal-fat (mf) angiomyolipoma (AML) n = 13, oncocytoma n = 23) from a single institution were independently evaluated by two blinded radiologists (R1/R2) using T2-weighted MRI for (1) the angular interface sign (AIS), (2) bubble-over sign (BOS), (3) percentage (%) exophytic growth and (4) long-to-short axis ratio. Comparisons were performed using ANOVA, chi-square and multi-variate regression.

RESULTS

AIS was present in 11.1% (7/63) -9.5% (6/63) R1/R2 RCC compared to 13.9% (5/36) -19.4% (7/36) R1/R2 benign masses (p = 0.68 and 0.16). BOS was present in 11.1% (7/63) -3.2% (2/63) R1/R2 RCC compared to 16.7% (6/36) -8.3% (3/36) R1/R2 benign masses (p = 0.432 and 0.261). Agreement was moderate (K = 0.50 and 0.55). mf-AML [66 ± 32% (range 0-100%)] and oncocytoma [53 ± 26% (0-90%)] had larger % exophytic growth compared to RCC [32 ± 23% (0-80%)] (p < 0.001). No RCC had 90-100% exophytic growth, present in 38.5% (5/13) mf-AMLs and 17.4% (4/23) oncocytomas. The long-to-short axis did not differ between groups (p = 0.053).

CONCLUSIONS

Benign masses show greater % exophytic growth whereas other growth patterns are not useful. Future studies evaluating % exophytic growth using multi-variate MR analysis in renal masses are required.

KEY POINTS

• Greater exophytic growth is associated with benignity among solid renal masses. • Only minimal fat AMLs and oncocytomas had 90-100% exophytic growth. • The angular interface sign was not useful to differentiate benign masses from RCC. • The bubble-over sign was not useful to differentiate benign masses from RCC. • Subjective analysis of growth patterns had fair-to-moderate agreement.

Diagnostic Performance and Interreader Agreement of a Standardized MR Imaging Approach in the Prediction of Small Renal Mass Histology

Purpose To assess the diagnostic performance and interreader agreement of a standardized diagnostic algorithm in determining the histologic type of small (≤4 cm) renal masses (SRMs) with multiparametric magnetic resonance (MR) imaging. Materials and Methods This single-center retrospective HIPAA-compliant institutional review board-approved study included 103 patients with 109 SRMs resected between December 2011 and July 2015. The requirement for informed consent was waived. Presurgical renal MR images were reviewed by seven radiologists with diverse experience. Eleven MR imaging features were assessed, and a standardized diagnostic algorithm was used to determine the most likely histologic diagnosis, which was compared with histopathology results after surgery. Interreader variability was tested with the Cohen κ statistic. Regression models using MR imaging features were used to predict the histopathologic diagnosis with 5% significance level. Results Clear cell renal cell carcinoma (RCC) and papillary RCC were diagnosed, with sensitivities of 85% (47 of 55) and 80% (20 of 25), respectively, and specificities of 76% (41 of 54) and 94% (79 of 84), respectively. Interreader agreement was moderate to substantial (clear cell RCC, κ = 0.58; papillary RCC, κ = 0.73). Signal intensity (SI) of the lesion on T2-weighted MR images and degree of contrast enhancement (CE) during the corticomedullary phase were independent predictors of clear cell RCC (SI odds ratio [OR]: 3.19; 95% confidence interval [CI]: 1.4, 7.1; P = .003; CE OR, 4.45; 95% CI: 1.8, 10.8; P < .001) and papillary RCC (CE OR, 0.053; 95% CI: 0.02, 0.2; P < .001), and both had substantial interreader agreement (SI, κ = 0.69; CE, κ = 0.71). Poorer performance was observed for chromophobe histology, oncocytomas, and minimal fat angiomyolipomas, (sensitivity range, 14%-67%; specificity range, 97%-99%), with fair to moderate interreader agreement (κ range = 0.23-0.43). Segmental enhancement inversion was an independent predictor of oncocytomas (OR, 16.21; 95% CI: 1.0, 275.4; P = .049), with moderate interreader agreement (κ = 0.49). Conclusion The proposed standardized MR imaging-based diagnostic algorithm had diagnostic accuracy of 81% (88 of 109) and 91% (99 of 109) in the diagnosis of clear cell RCC and papillary RCC, respectively, while achieving moderate to substantial interreader agreement among seven radiologists. ^© RSNA, 2018 Online supplemental material is available for this article.

CT and MR imaging for solid renal mass characterization

As our understanding has expanded that relatively large fraction of incidentally discovered renal masses, especially in small size, are benign or indolent even if malignant, there is growing acceptance of more conservative management including active surveillance for small renal masses. As for advanced renal cell carcinomas (RCCs), nonsurgical and subtype specific treatment options such as immunotherapy and targeted therapy is developing. On these backgrounds, renal mass characterization including differentiation of benign from malignant tumors, RCC subtyping and prediction of RCC aggressiveness is receiving much attention and a variety of imaging techniques and analytic methods are being investigated. In addition to conventional imaging techniques, integration of texture analysis, functional imaging (i.e. diffusion weighted and perfusion imaging) and multivariate diagnostic methods including machine learning have provided promising results for these purposes in research fields, although standardization and external, multi-institutional validations are needed.

Chemical shift magnetic resonance imaging for distinguishing minimal-fat renal angiomyolipoma from renal cell carcinoma: a meta-analysis

OBJECTIVES

To determine the performance of chemical shift signal intensity index (CS-SII) values for distinguishing minimal-fat renal angiomyolipoma (mfAML) from renal cell carcinoma (RCC) and to assess RCC subtype characterisation.

METHODS

We identified eligible studies on CS magnetic resonance imaging (CS-MRI) of focal renal lesions via PubMed, Embase, and the Cochrane Library. CS-SII values were extracted by lesion type and evaluated using linear mixed model-based meta-regression. RCC subtypes were analysed. Two-sided p value <0.05 indicated statistical significance. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool.

RESULTS

Eleven articles involving 850 patients were included. Minimal-fat AML had significantly higher CS-SII value than RCC (p < 0.05); there were no significant differences between mfAML and clear cell RCC (cc-RCC) (p = 0.112). Clear cell RCC had a significantly higher CS-SII value than papillary RCC (p-RCC) (p < 0.001) and chromophobe RCC (ch-RCC) (p = 0.045). The methodological quality was relatively high, and Begg's test data points indicated no obvious publication bias.

CONCLUSIONS

The CS-SII value for differentiating mfAML from cc-RCC remains unproven, but is a promising method for differentiating cc-RCC from p-RCC and ch-RCC.

KEY POINTS

• RCC CS-SII values are significantly lower than those of mfAML overall. • CS-SII values cannot aid differentiation between mfAML and cc-RCC. • CS-SII values might help characterise RCC subtypes.

The Risks of Renal Angiomyolipoma: Reviewing the Evidence

Renal angiomyolipoma (RAML), though a rare benign tumor, may impose a significant morbidity or even mortality due to its unique characteristics and the complications subsequent to its treatment. The classic tumor variant is composed of smooth muscular, vascular, and fatty components. The most straightforward diagnosis is when the fat component is abundant and gives a characteristic appearance on different imaging studies. In fat-poor lesions, however, the diagnosis is difficult and presumed a renal cell carcinoma. Yet, some variants of RAML, though rare, express an aggressive behavior leading to metastasis and mortality. The challenge lies in the early detection of benign variants and identifying aggressive lesions for proper management. Another challenge is when the vascular tissue component predominates and poses a risk of hemorrhage that may extend to the retroperitoneum in a massive life-threatening condition. The predicament here is to identify the characteristics of tumors at risk of bleeding and provide a prophylactic treatment. According to the clinical presentation, different treatment modalities, prophylactic or therapeutic, are available that span the spectrum of observation, embolization, or surgery. Renal impairment may result from extensive tumor burden or as a complication of the management itself. Improvement of diagnostic techniques, super-selective embolization, nephron-sparing surgery, and late treatment with the mammalian target of rapamycin inhibitors have provided more effective and safe management strategies. In this review, we examine the evidence pertaining to the risks imposed by RAML to the patients and identify merits and hazards associated with different treatment modalities.

Renal angiomyolipoma without visible fat: Can we make the diagnosis using CT and MRI?

Renal angiomyolipomas without visible fat (AML.wovf) are benign masses that are incidentally discovered mainly in women. AML.wovf are typically homogeneously hyperdense on unenhanced CT without calcification or haemorrhage. Unenhanced CT pixel analysis is not useful for diagnosis. AML.wovf are characteristically homogeneously hypointense on T2-weighted (T2W)-MRI and apparent diffusion coefficient (ADC) maps. Despite early reports, only a minority of AML.wovf show signal intensity drop on chemical-shift MRI due to microscopic fat. AML.wovf most commonly show avid early enhancement with washout kinetics at contrast-enhanced CT and MRI. The combination of homogeneously low T2W and/or ADC signal intensity with avid early enhancement and washout is highly accurate for diagnosis of AML.wovf.

KEY POINTS

• AML.wovf are small incidental benign renal masses occurring mainly in women. • AML.wovf are homogeneously hyperdense with low signal on T2W-MRI and ADC map. • AML.wovf typically show avid early enhancement with washout kinetics. • Combining features on CT/MRI is accurate for diagnosis of AML.wovf.

CT imaging of solid renal masses: pitfalls and solutions

Computed tomography (CT) remains the first-line imaging test for the characterisation of renal masses; however, CT has inherent limitations, which if unrecognised, may result in errors. The purpose of this manuscript is to present 10 pitfalls in the CT evaluation of solid renal masses. Thin section non-contrast enhanced CT (NECT) is required to confirm the presence of macroscopic fat and diagnosis of angiomyolipoma (AML). Renal cell carcinoma (RCC) can mimic renal cysts at NECT when measuring <20 HU, but are usually heterogeneous with irregular margins. Haemorrhagic cysts (HC) may simulate solid lesions at NECT; however, a homogeneous lesion measuring >70 HU is essentially diagnostic of HC. Homogeneous lesions measuring 20-70 HU at NECT or >20 HU at contrast-enhanced (CE) CT, are indeterminate, requiring further evaluation. Dual-energy CT (DECT) can accurately characterise these lesions at baseline through virtual NECT, iodine overlay images, or quantitative iodine concentration analysis without recalling the patient. A minority of hypo-enhancing renal masses (most commonly papillary RCC) show indeterminate or absent enhancement at multiphase CT. Follow-up, CE ultrasound or magnetic resonance imaging (MRI) is required to further characterise these lesions. Small (<3 cm) endophytic cysts commonly show pseudo-enhancement, which may simulate RCC; this can be overcome with DECT or MRI. In small (<4 cm) solid renal masses, 20% of lesions are benign, chiefly AML without visible fat or oncocytoma. Low-dose techniques may simulate lesion heterogeneity due to increased image noise, which can be ameliorated through the appropriate use of iterative reconstruction algorithms.

Imaging of Solid Renal Masses

Detection of solid renal masses has increased, although it has not resulted in significant mortality reduction from renal cell carcinoma. Efforts for improved lesion characterization have been pursued and incorporated in management algorithms, in order to distinguish clinically significant tumors from favorable or benign conditions. Concurrently, imaging methods have produced evidence supporting their role as useful tools not only in lesion detection but also characterization. In addition, newer modalities, such as contrast-enhanced ultrasonography, and advanced applications of MR imaging, are being investigated. This article reviews the current role of different imaging methods in the characterization of solid renal masses.

Differentiation of Clear Cell Renal Cell Carcinoma From Other Renal Cortical Tumors by Use of a Quantitative Multiparametric MRI Approach

OBJECTIVE

The purpose of this study was to develop a quantitative multiparametric MRI approach to differentiating clear cell renal cell carcinoma (RCC) from other renal cortical tumors.

MATERIALS AND METHODS

This retrospective study included 119 patients with 124 histopathologically confirmed renal cortical tumors who underwent preoperative MRI including DWI, contrast-enhanced, and chemical-shift sequences before nephrectomy. Two radiologists independently assessed each tumor volumetrically, and apparent diffusion coefficient values, parameters from multiphasic contrast-enhanced MRI (peak enhancement, upslope, downslope, AUC), and chemical-shift indexes were calculated. Univariate and multivariable logistic regression analyses were performed to identify parameters associated with clear cell RCC.

RESULTS

Interreader agreement was excellent (intraclass correlation coefficient, 0.815-0.994). The parameters apparent diffusion coefficient (reader 1 AUC, 0.804; reader 2, 0.807), peak enhancement (reader 1 AUC, 0.629; reader 2, 0.606), and downslope (reader 1 AUC, 0.575; reader 2, 0.561) were significantly associated with discriminating clear cell RCC from other renal cortical tumors. The combination of all three parameters further increased diagnostic accuracy (reader 1 AUC, 0.889; reader 2, 0.907; both p ≤ 0.001), yielding sensitivities of 0.897 for reader 1 and 0.897 for reader 2, and specificities of 0.762 for reader 1 and 0.738 for reader 2 in the identification of clear cell RCC. With maximized sensitivity, specificities of 0.429 and 0.262 were reached for readers 1 and 2, respectively.

CONCLUSION

A quantitative multiparametric approach statistically significantly improves diagnostic performance in differentiating clear cell RCC from other renal cortical tumors.

Small (< 4 cm) Renal Tumors With Predominantly Low Signal Intensity on T2-Weighted Images: Differentiation of Minimal-Fat Angiomyolipoma From Renal Cell Carcinoma

OBJECTIVE

The purpose of this study was to retrospectively investigate the utility of multiparametric MRI in differentiating minimal-fat angiomyolipoma (AML) from renal cell carcinoma (RCC) in small renal tumors with predominantly low signal intensity on T2-weighted MR images.

MATERIALS AND METHODS

Fifty-six patients with pathologically identified renal tumors (1-4 cm) with predominantly low signal intensity on T2-weighted images without visible fat on unenhanced CT images were enrolled. Clinical and MRI variables (tumor-to-renal cortex signal intensity [SI] ratio on T2-weighted images [T2 ratio], apparent diffusion coefficient [ADC], and SI index) on chemical-shift images were evaluated.

RESULTS

The ADC was significantly lower in RCC than in minimal-fat AML (p = 0.001). The T2 ratio and signal intensity index were not significantly different between RCC (p = 0.31) and minimal-fat AML (p = 0.74). Multivariate analysis showed that ADC (odds ratio [OR], 0.01; p = 0.02) and male sex (OR, 46.7; p < 0.001) were the independent predictors of RCC. For differentiating minimal-fat AML from RCC, the ROC AUC of ADC was 0.781. When ADC and sex were combined, the AUC significantly increased to 0.937 with a cutoff value of 1.129 × 10^-3 mm²/s. For making the diagnosis of minimal-fat AML if the ADC was greater than the threshold, sensitivity was 89.7% and specificity was 88.2% (p = 0.02).

CONCLUSION

In small renal tumors with predominantly low SI on T2-weighted images, ADC is useful for differentiating minimal-fat AML from RCC. Combining ADC with male sex increases the accuracy of RCC prediction.