Predictive Value of Chemical-Shift MRI in Distinguishing Clear Cell Renal Cell Carcinoma From Non-Clear Cell Renal Cell Carcinoma and Minimal-Fat Angiomyolipoma. AJR Am J Roentgenol. 2015;205:W79-W86. [PMID: 26102422 DOI: 10.2214/ajr.14.13245]

Low-grade oncocytic tumor of the kidney: imaging features of a novel tumor entity

PURPOSES

Low-grade oncocytic tumor (LOT) is a rare renal tumor that has emerged from the spectrum of eosinophilic/oncocytic renal tumors and poses a diagnostic challenge due to its similarity to chromophobe renal cell carcinoma (CHRCC) and renal oncocytoma (RO). The imaging features of this novel tumor entity have not yet been clearly described. The purpose of this study was to describe the imaging features of LOT with radiologic-pathologic correlation.

METHODS

We conducted a retrospective observational study involving two expert centers. We identified 12 pathologically proven LOT with preoperative imaging available, including at least computed tomography (CT) or magnetic resonance imaging (MRI), from the past 12 years. Three experienced radiologists performed the imaging analysis independently.

RESULTS

All tumors presented well-defined borders. Nine of the 12 LOT exhibited an early peripheral enhancement with complete or almost complete centripetal fill-in on nephrographic or delayed phases without any particular shape. Three showed a homogeneous contrast enhancement. Macroscopic fat and calcifications were not observed in any of the tumors.

CONCLUSION

Early peripheral enhancement with complete or almost complete centripetal fill-in on nephrographic or delayed phases without any particular shape suggests a LOT diagnosis. Further analyses involving larger studies are needed to fully confirm these imaging characteristics. To date, a percutaneous biopsy should be performed before considering management.

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.

Machine Learning-Based Magnetic Resonance Radiomics Analysis for Predicting Low- and High-Grade Clear Cell Renal Cell Carcinoma

PURPOSE

To explore whether high- and low-grade clear cell renal cell carcinomas (ccRCC) can be distinguished using radiomics features extracted from magnetic resonance imaging.

METHODS

In this retrospective study, 154 patients with pathologically proven clear ccRCC underwent contrast-enhanced 3 T magnetic resonance imaging and were assigned to the development (n = 122) and test (n = 32) cohorts in a temporal-split setup. A total of 834 radiomics features were extracted from whole-tumor volumes using 3 sequences: T2-weighted imaging (T2WI), diffusion-weighted imaging, and contrast-enhanced T1-weighted imaging. A random forest regressor was used to extract important radiomics features that were subsequently used for model development using the random forest algorithm. Tumor size, apparent diffusion coefficient value, and percentage of tumor-to-renal parenchymal signal intensity drop in the tumors were recorded by 2 radiologists for quantitative analysis. The area under the receiver operating characteristic curve (AUC) was generated to predict ccRCC grade.

RESULTS

In the development cohort, the T2WI-based radiomics model demonstrated the highest performance (AUC, 0.82). The T2WI-based radiomics and radiologic feature hybrid model showed AUCs of 0.79 and 0.83, respectively. In the test cohort, the T2WI-based radiomics model achieved an AUC of 0.82. The range of AUCs of the hybrid model of T2WI-based radiomics and radiologic features was 0.73 to 0.80.

CONCLUSION

Magnetic resonance imaging-based classifier models using radiomics features and machine learning showed satisfactory diagnostic performance in distinguishing between high- and low-grade ccRCC, thereby serving as a helpful noninvasive tool for predicting ccRCC grade.

Primary renal myxoid liposarcoma with pancreatic invasion on 18F-FDG PET/CT: first case report and literature review

Background

Myxoid liposarcoma (MLS) is a rare malignant soft tissue sarcoma that predominantly manifests in the deep soft tissues of the extremities, particularly within the musculature of the thigh. Unlike other types of liposarcoma, MLS demonstrates a propensity for metastasis to atypical sites, including the lung parenchyma, soft tissues, retroperitoneum, mediastinum, breast, liver, thymus, lymph nodes, and bones. The definitive diagnosis primarily relies on histology with HE staining. Imaging modalities such as ultrasound, CT, MRI, and 18F-FDG PET/CT scans serve as valuable tools for tumor identification.

Case report

A 57-year-old man presented with symptoms of abdominal distention and vomiting 1 month ago. Contrast-enhancement CT revealed a heterogeneous hypodense mass in the upper-middle part of the left kidney, displaying irregular morphology and protrusion towards the exterior of the kidney, with abundant blood supply and had a maximum dimension of approximately 10.7 cm × 9.0 cm. Additionally, a rounded soft tissue density was identified in the pancreatic body. Multiplanar reconstruction demonstrated a connection between the pancreatic lesion and the kidney mass. 18F-FDG PET/CT was conducted for staging, revealing significant growth of the lesion in the upper-middle part of the left kidney, extending beyond the kidney and infiltrating the pancreatic body. The lesion demonstrated remarkably high 18F-FDG uptake (SUVmax = 10.2, MTV = 136.13 cm3, TLG = 484.62). The postoperative pathological examination confirmed the diagnosis of MLS. On the 10th day post-surgery, the patient presented with tumor recurrence and underwent another surgical resection. Unfortunately, during the operation, the patient experienced a sudden cardiac arrest and died.

Conclusion

Renal MLS with invasion into the pancreas is very rare in clinical practice. Due to the limited research on the utilization of 18F-FDG PET/CT in this particular context, given the rarity and low incidence of MLS, its role remains largely unexplored. As PET/CT imaging becomes increasingly prevalent, thorough imaging of disease sites becomes indispensable for the development of treatment protocols and the monitoring of treatment response.

Using the "2 standard deviations" rule with Dixon MRI to differentiate renal cell carcinoma types

BACKGROUND

Clear cell and non-clear cell renal cell carcinoma (RCC) are distinguishable based on microscopic fat, detectable by chemical shift MRI. However, these assessments are often subjective. Conversely, Dixon MRIs and the "2 standard deviations" rule (2SDR) are quantitative methods that may decrease diagnostic subjectivity. Therefore, this study assessed the value of the 2SDR for detecting microscopic fat and thus differentiating clear cell and non-clear cell RCC using Dixon MRI.

METHODS

This retrospective study included patients with RCC who underwent preoperative Dixon MRI. The patients were grouped based on tumor type: clear cell RCC and non-clear cell RCC. The 2SDR value was calculated based on in-phase and opposed-phase images and then compared between the two groups. 2SDR values >0 indicated clear cell RCCs, whereas values <0 indicated non-clear cell RCC.

RESULTS

We included 151 patients; 114 patients had clear cell RCC, of which 106 had a 2SDR value >0. Furthermore, 37 patients had non-clear cell RCC, of which 3 had a 2SDR value >0. The 2SDR value was significantly higher in the clear cell RCC group than in the non-clear cell RCC group (p = 0.000). Overall, 93.0% (106/114) and 8.1% (3/37) of patients with clear cell and non-clear cell RCC, respectively, had microscopic fat. The evaluation indices for this 2SDR method were: accuracy: 92.72%, sensitivity: 92.98%, specificity: 91.89%, positive predictive value: 97.25%, and negative predictive value: 80.95%.

CONCLUSIONS

2SDR values calculated from Dixon magnetic resonance images can differentiate clear cell from non-clear cell RCCs by detecting microscopic fat.

PRECIS

The "2 standard deviations" rule value calculated from Dixon MR images differentiates clear cell from non-clear cell renal cell carcinoma with high efficiency by detecting microscopic fat.

Imaging of pediatric liver tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee White Paper

Primary hepatic malignancies are relatively rare in the pediatric population, accounting for approximately 1%-2% of all pediatric tumors. Hepatoblastoma and hepatocellular carcinoma are the most common primary liver malignancies in children under the age of 5 years and over the age of 10 years, respectively. This paper provides consensus-based imaging recommendations for evaluation of patients with primary hepatic malignancies at diagnosis and follow-up during and after therapy.

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.

Multiparametric magnetic resonance imaging for characterizing renal tumors: A validation study of the algorithm presented by Cornelis et al

Objectives

In the last decade, the incidence of renal cell carcinoma (RCC) has been rising, with the greatest increase observed for solid tumors. Magnetic resonance imaging (MRI) protocols and algorithms have recently been available for classifying RCC subtypes and benign subtypes. The objective of this study was to prospectively validate the MRI algorithm presented by Cornelis et al. for RCC classification.

Material and Methods

Over a 7-month period, 38 patients with 44 renal tumors were prospectively included in the study and received an MRI examination in addition to the conventional investigation program. The MRI sequences were: T2-weighted, dual chemical shift MRI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced T1-weighted in wash-in and wash-out phases. The images were evaluated according to the algorithm by two experienced, blinded radiologists, and the histopathological diagnosis served as the gold standard.

Results

Of 44 tumors in 38 patients, only 8 tumors (18.2%) received the same MRI diagnosis according to the algorithm as the histopathological diagnosis. MRI diagnosed 16 angiomyolipoma, 14 clear cell RCC (ccRCC), 12 chromophobe RCC (chRCC), and two papillary RCC (pRCC), while histopathological examination diagnosed 24 ccRCC, four pRCC, one chRCC, and one mixed tumor of both pRCC and chRCC. Malignant tumors were statistically significantly larger than the benign (3.16 ± 1.34 cm vs. 2.00 ± 1.04 cm, P = 0.006).

Conclusion

This prospective study could not reproduce Cornelis et al.'s results and does not support differentiating renal masses using multiparametric MRI without percutaneous biopsy in the future. The MRI algorithm showed few promising results to categorize renal tumors, indicating histopathology for clinical decisions and follow-up regimes of renal masses are still required.

MRI-Based Radiomics and Urine Creatinine for the Differentiation of Renal Angiomyolipoma With Minimal Fat From Renal Cell Carcinoma: A Preliminary Study

Objectives

Standard magnetic resonance imaging (MRI) techniques are different to distinguish minimal fat angiomyolipoma (mf-AML) with minimal fat from renal cell carcinoma (RCC). Here we aimed to evaluate the diagnostic performance of MRI-based radiomics in the differentiation of fat-poor AMLs from other renal neoplasms.

Methods

A total of 69 patients with solid renal tumors without macroscopic fat and with a pathologic diagnosis of RCC (n=50) or mf-AML (n=19) who underwent conventional MRI and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) were included. Clinical data including age, sex, tumor location, urine creatinine, and urea nitrogen were collected from medical records. The apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were measured from renal tumors. We used the ITK-SNAP software to manually delineate the regions of interest on T2-weighted imaging (T2WI) and IVIM-DWI from the largest cross-sectional area of the tumor. We extracted 396 radiomics features by the Analysis Kit software for each MR sequence. The hand-crafted features were selected by using the Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO). Diagnostic models were built by logistic regression analysis. Receiver operating characteristic curve analysis was performed using five-fold cross-validation and the mean area under the curve (AUC) values were calculated and compared between the models to obtain the optimal model for the differentiation of mf-AML and RCC. Decision curve analysis (DCA) was used to evaluate the clinical utility of the models.

Results

Clinical model based on urine creatinine achieved an AUC of 0.802 (95%CI: 0.761-0.843). IVIM-based model based on f value achieved an AUC of 0.692 (95%CI: 0.627-0.757). T2WI-radiomics model achieved an AUC of 0.883 (95%CI: 0.852-0.914). IVIM-radiomics model achieved an AUC of 0.874 (95%CI: 0.841-0.907). Combined radiomics model achieved an AUC of 0.919 (95%CI: 0.894-0.944). Clinical-radiomics model yielded the best performance, with an AUC of 0.931 (95%CI: 0.907-0.955). The calibration curve and DCA confirmed that the clinical-radiomics model had a good consistency and clinical usefulness.

Conclusion

The clinical-radiomics model may be served as a noninvasive diagnostic tool to differentiate mf-AML with RCC, which might facilitate the clinical decision-making process.

Fat-only Dixon: how to use it in body MRI

The Dixon method for fat/water separation is widely used to obtain uniform fat suppression using the water-only reconstruction. However, the fat-only reconstruction is potentially neglected in clinical practice, either not sent to the PACS or ignored upon imaging review. Fat-only Dixon provides a valuable tool for rapid screening for microscopic fat and problem-solving of lesions of interest. This work will review the physics of Dixon fat/water separation, some clinical applications, artifacts, and protocol design considerations of Dixon imaging, and how to integrate the Dixon method into the clinical practice of body MRI.

Ectopic adrenocortical adenoma in the renal hilum mimicking a renal cell carcinoma

Ectopic adrenocortical tissue can arise along the path of embryonic migration, such as the celiac axis, broad ligament, adnexa of the testis, and spermatic cord. Occasionally, ectopic adrenocortical tissues undergo marked hyperplasia and develop into ectopic adrenocortical adenomas. This report describes the case of a 60-year-old man who was incidentally found to have a lipid-containing mass with early enhancement and delayed washout in the right renal hilum. A renal cell carcinoma was suspected, and robot-assisted partial nephrectomy was performed, but the final diagnosis was an ectopic adrenocortical adenoma. We should include ectopic adrenocortical adenoma in the differential diagnosis when we find a lipid-containing tumor adjacent to the kidney.

The Potential of Visceral Adipose Tissue in Distinguishing Clear Cell Renal Cell Carcinoma from Renal Angiomyolipoma with Minimal Fat

Purpose

To overcome the challenge of preoperative differentiation between clear cell renal cell carcinoma (ccRCC) and renal angiomyolipoma with minimal fat (RMFAML), we evaluated the potential of visceral adipose tissue (VAT) in distinguishing RMFAML from ccRCC.

Patients and Methods

Patients (191) were divided into ccRCC and RMFAML groups according to postoperative pathology. Umbilical horizontal computed tomography (CT) images were used for visceral fat area (VFA), subcutaneous fat area (SFA) and total fat area (TFA) measurements. Logistic regression was used to identify risk factors for ccRCC. Areas under the receiver operating characteristic (ROC) curve (AUCs) were compared to identify the most valuable indicator for identifying ccRCC and RMFAML.

Results

In total, 166 patients had ccRCC, and 25 had RMFAML. ccRCC and RMFAML patients showed significant differences in age (P<0.001), sex (P<0.001), hypertension (P=0.027), BMI (P<0.001), SFA (P=0.046), VFA (P<0.001) and TFA (P<0.001). According to multiple logistic regression analysis, male sex [4.311 (1.469~12.653), p=0.008]; older age [1.047 (1.008~1.088), p=0.017]; and higher BMI [1.305 (1.088~1.566), p=0.004], SFA [1.013 (1.003~1.023), p=0.008], VFA [1.026 (1.012~1.041), p<0.001] and TFA [1.011 (1.005~1.017), p=0.001] were associated with ccRCC. The AUCs of sex (male), age, BMI, TFA, VFA, and SFA were 0.726, 0.687, 0.783, 0.769, 0.840, and 0.645, respectively. The VFA cut-off value was 69.99 cm². The sensitivity and specificity of higher VFA (≥69.99 cm²) for ccRCC diagnosis were 79.52% and 80.00%, respectively.

Conclusion

In differentiating ccRCC from RMFAML, male sex, older age, and higher BMI, TFA, SFA, and VFA are risk factors for ccRCC. VFA is the most effective indicator for identifying ccRCC.

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.

MR characteristics of mucinous tubular and spindle cell carcinoma (MTSCC) of the kidney: comparison with clear cell and papillary subtypes of renal cell carcinoma

PURPOSE

To describe MR features of mucinous tubular spindle cell carcinoma (MTSCC) of the kidney that may help differentiate from clear cell renal cell carcinoma (ccRCC) and papillary RCC (pRCC).

METHODS

15 MTSCCs were retrospectively evaluated by MR with T2-weighted image without fat suppression (n = 15) and dynamic contrast-enhanced (DCE), fat-suppressed T1-weighted GRE (n = 11). Size-matched ccRCC (n = 30) and pRCC (n = 30) were evaluated as control. T2 ratio was calculated as the signal intensity (SI) ratio of the lesion to the renal cortex on T2W images. Enhancement ratio (ER) was calculated as (SI_post - SI_pre)/(SI_pre), where SI_pre (SI_post) is the SI of the entire lesion on each phase of DCE images. Early nodular enhancement was subjectively evaluated in MTSCC. T2 ratio and ER were compared using the Mann-Whitney U test with Bonferroni correction.

RESULTS

The mean value of T2 ratio was highest in ccRCC (1.24), followed by MTSCC (1.02), and pRCC (0.84). Difference of T2 ratio was significant between ccRCC and pRCC (p < 0.001), but not between MTSCC and ccRCC (p = 0.4) or between MTSCC and pRCC (p = 0.2). The mean ER of MTSCC, ccRCC and pRCC were 1.33, 1.53 and 0.38 in corticomedullary phase (CMP), 1.60, 1.61 and 0.69 in nephrographic phase (NGP) and 1.79, 1.35 and 0.77 in excretory phase (EP), respectively. ERs were significantly different between MTSCC and pRCC in CMP (p = 0.01), NGP (p = 0.003), and EP (p = 0.002). Early nodular enhancement was observed in 4/11 MTSCC (36%), 17/30 ccRCC (57%), and 2/30 pRCC (7%).

CONCLUSIONS

MTSCC has distinct MR features that can help differentiate from ccRCC and pRCC. MTSCC enhances more avidly compared to pRCC and shows gradual progressive enhancement.

CT differentiation of fat-poor angiomyolipomas from papillary renal cell carcinomas: development of a predictive model

PURPOSE

To identify specific contrast-enhanced CT (CECT) findings and develop a predictive model with logistic regression to differentiate fat-poor angiomyolipomas (fpAML) from papillary renal cell carcinomas (pRCC).

METHODS

This is a single-institution retrospective study that assess CT features of histologically proven 67 pRCC and 13 fpAML. CECT variables were studied by means of univariate logistic regression. Variables included patients' demographics, tumor attenuation (unenhanced and at arterial, venous and excretory post-contrast phases), type of enhancement, morphological features (axial long and short diameters, long-short axis ratio (LSR) and tumor to kidney angle interface) and presence of visible calcifications or vessels. Those variables with a p ≤ 0.05 underwent standard stepwise logistic regression to find predictive combinations of clinical variables. Best models were evaluated by AUROC curves and were subjected to Leave-one-out cross validation to assess their robustness.

RESULTS

Odds ratio (OR) between pRCC and fpAML was statistically significant for patient's gender, tumor attenuation in arterial, venous and excretory phases, tumor's long diameter, short diameter, LSR, type of enhancement, presence of intratumoral vessels and tumor-kidney angle interface. The best predictive model resulted in an area under the curve (AUC) of 0.971 and included gender, tumor-kidney angle interface and venous attenuation with the following equation: Log(p/1 - p) = - 2.834 + 4.052 * gender +  - 0.066 * AngleInterface + 0.074 * VenousphaseHU.

CONCLUSIONS

The combination of patients' gender, tumor to kidney angle interface and venous enhancement helps to distinguish fpAML from pRCC.

The Incidental Renal Mass- Update on Characterization and Management

Renal masses are commonly encountered on cross-sectional imaging examinations performed for nonrenal indications. Although most can be dismissed as benign cysts, a subset will be either indeterminate or suspicious; in many cases, imaging cannot be used to reliably differentiate between benign and malignant masses. On-going research in defining characteristics of common renal masses on advanced imaging shows promise in offering solutions to this issue. A recent update of the Bosniak classification (used to categorize cystic renal masses) was proposed with the goals of decreasing imaging follow-up in likely benign cystic masses, and therefore avoiding unnecessary surgical resection of such masses.

Ratio of maximum to minimum tumor diameter can predict the pathology type of renal cell carcinoma before surgery

INTRODUCTION

Previous reports have described several methods and markers used to distinguish pathologic subtypes of renal cell carcinoma (RCC). This study aimed to evaluate the utility of the ratio of maximum to minimum tumor diameter (ROD) in predicting pathologic subtypes of RCC.

METHODS

Data from patients with RCC who underwent surgery between January 2015 and December 2019 were reviewed retrospectively. The cutoff value for ROD was calculated using receiver operating characteristic (ROC) curve analysis.

RESULTS

In the clear cell RCC (ccRCC) and non-ccRCC groups, the optimal ROD cutoff value to predict ccRCC was determined to be 1.201 (sensitivity, 90.7%; specificity, 76.1%; area under the ROC curve [AUC], 0.827; p < 0.001). In the non-ccRCC group, the cutoff value for ROD in predicting papillary RCC was 1.092 (sensitivity, 87.9%; specificity, 40.5%; AUC, 0.637; p = 0.003). Compared with patients with ROD <1.201, more patients in the ccRCC group exhibited tumors with an ROD ⩾1.201 (14.2% versus 85.8%, respectively; p < 0.001). Multivariate analysis of preoperative features revealed that ROD ⩾1.201 was an independent predictive factor for ccRCC. In addition, patients with ROD ⩾1.201 had higher percentages of Fuhrman grade III/IV (91.2% versus 8.8%; p = 0.014), tumor necrosis (86.7% versus 13.3%; p = 0.012) and sarcomatoid differentiation (90.6% versus 9.4%; p < 0.001).

CONCLUSIONS

ROD was a novel indicator for preoperatively predicting histologic type in patients with RCC. ROD cutoff values of 1.201 and 1.092 were the most discriminative for ccRCC and papillary RCC, respectively. Moreover, ROD ⩾1.201 was associated with high Fuhrman grade, sarcomatoid features, and tumor necrosis.

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.

Contrast-enhanced magnetic resonance (MR) T1 mapping with low-dose gadolinium-diethylenetriamine pentaacetic acid (Gd-DTPA) is promising in identifying clear cell renal cell carcinoma histopathological grade and differentiating fat-poor angiomyolipoma

Background

This study aimed to identify clear cell renal cell carcinoma (ccRCC) histopathological grade and differentiate it from fat-poor angiomyolipoma (AML). This was achieved through contrast-enhanced magnetic resonance (MR) T1 mapping with intravenous low-dose gadolinium-diethylenetriamine pentaacetic acid (Gd-DTPA).

Methods

In total, 56 consecutive patients received MR scanning between January 2016 and December 2018 using the pre- and post- contrast-enhanced T1 mapping sequences with low-dose Gd-DTPA (0.036 mmol/kg). RCCs were pathologically proven in 40 patients after surgery and graded according to the International Society of Urological Pathology (ISUP) classification system. Ten AMLs were pathologically proven by surgery histopathology and six AMLs were diagnosed by magnetic resonance imaging (MRI). Patients were followed up for more than half a year. The mean T1 values of the renal lesion and ipsilateral normal renal parenchyma were measured before and after Gd-DTPA administration (T1p and T1e). The reduction of T1 value (T1d) and the ratio of its reduction (T1d %) were calculated and compared.

Results

In 40 ccRCCs, higher-grade [International Society of Urologic Pathology (ISUP) grade 3 and 4] and lower-grade (ISUP grade 1 and 2) ccRCCs were noted in 13 and 27 patients, respectively. The mean T1p was 1,514.8±139.4 ms and the mean T1d was 907.7±193.7 ms in the higher-grade ccRCCs, which were significantly higher than in the lower-grade ccRCCs (T1p =1,251.7±151.5 ms and T1d =648.5±218.2 ms, respectively; P<0.001). Fat-poor AMLs had higher T1p (1,677.3±104.8 ms) and T1e (865.6±251.5 ms) as compared to ccRCCs (P<0.001). Combined T1p + T1d showed the highest area under the curve (AUC) (0.912) in the differentiation of higher-grade ccRCCs from lower-grade ccRCCs (P=0.010). Combined T1p + T1e had the highest AUC (0.956) in the differentiation between ccRCCs and fat-poor AMLs (P=0.010). All T1 mapping metrics could discriminate between normal renal parenchyma and renal lesions (P<0.001). No significant difference was found in the T1p and T1e at different parts of the ipsilateral normal renal parenchyma. Interobserver agreement for quantitative longitudinal relaxation time in the T1 maps was excellent.

Conclusions

Contrast-enhanced T1 mapping with low-dose Gd-DTPA may provide a more reliable and accurate approach in identifying ccRCCs histopathological grade and differentiating ccRCCs from fat-poor AMLs.

Predictive Value of In Vivo MR Spectroscopy With Semilocalization by Adiabatic Selective Refocusing in Differentiating Clear Cell Renal Cell Carcinoma From Other Subtypes

OBJECTIVE. The purpose of this study is to evaluate the diagnostic value of in vivo MR spectroscopy (MRS) with semilocalization by adiabatic selective refocusing (semi-LASER MRS) in differentiating clear cell renal cell carcinoma (RCC) from the non-clear cell subtype. SUBJECTS AND METHODS. Sixteen patients with biopsy-proven RCC or masses highly suspicious for RCC were prospectively recruited to participate in the study. Single-voxel ¹H spectra were acquired using a 3-T MRI system, with a semi-LASER sequence acquired for renal tumors in 14 patients and for healthy renal tissue (control tissue) in 12 patients. Offline processing of the MR spectra was performed. MRI and spectra analysis were performed independently by radiologists who were blinded to the reference histopathologic findings. RESULTS. Semi-LASER MRS was diagnostic for nine of 11 patients (82%) with histopathologically proven clear cell RCC, showing a strong lipid peak in seven patients and a weaker lipid resonance in two others, whereas control spectra showed weakly positive findings in only one patient. MRS findings were negative for lipid resonance in two of three patients (67%) with non-clear cell tumors and were weakly positive in another patient. Semi-LASER MRS had a high sensitivity and positive predictive value of 82% and 90%, respectively, in addition to a specificity of 67%, a negative predictive value of 50%, and overall accuracy of 79% for the detection of clear cell RCC. Lipid resonance was detected by MRS for four of six clear cell RCCs with no intravoxel fat on chemical-shift MRI. CONCLUSION. The preliminary results of the present study show that semi-LASER MRS is promising for the noninvasive discrimination of clear cell RCC from non-clear cell RCC on the basis of detection of lipid resonance and that it provides an incremental yield compared with chemical-shift MRI.

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.

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.

A case of primary clear cell hepatocellular carcinoma comprised mostly of clear cells

Clear cell hepatocellular carcinoma (CHCC) is defined as a tumor which contains more than 50% of clear cells. However, CHCC with more than 90% of clear cells are extremely rare. We report a case of a 65-year-old woman who was found to have a solitary mass, which was histologically diagnosed as clear cell hepatocellular carcinoma composed of 90% or more clear cells. The tumor presented rim arterial phase hyperenhancement in computed tomography, magnetic resonance imaging, and computed tomography during hepatic arteriography, and was classified as LR-M category according to The Liver Imaging Reporting and Data System version 2018(LI-RADS v2018). This tumor may mimic other tumors with similar radiographic features, such as intrahepatic cholangiocellular carcinoma and metastatic tumor.

Update on Indications for Percutaneous Renal Mass Biopsy in the Era of Advanced CT and MRI

OBJECTIVE. The objective of this article is to review the burgeoning role of percutaneous renal mass biopsy (RMB). CONCLUSION. Percutaneous RMB is safe, accurate, and indicated for an expanded list of clinical scenarios. The chief scenarios among them are to prevent treatment of benign masses and help select patients for active surveillance (AS). Imaging characterization of renal masses has improved; however, management decisions often depend on a histologic diagnosis and an assessment of biologic behavior of renal cancers, both of which are currently best achieved with RMB.

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.

Renal Angiomyolipoma Based on New Classification: How to Differentiate It From Renal Cell Carcinoma

OBJECTIVE

The purpose of this article is to describe useful imaging features for differentiating angiomyolipoma (AML) subtypes from renal cell carcinoma subtypes.

CONCLUSION

A newer radiologic classification of renal AML consists of fat-rich AML (≤ -10 HU), fat-poor AML (> -10 HU; tumor-to-spleen ratio < 0.71; signal intensity index, > 16.5%), and fat-invisible AML (> -10 HU; tumor-to-spleen ratio, > 0.71; signal intensity index, < 16.5%). Each subtype must be differentiated from the renal cell carcinoma subtype because of overlapping imaging features.

The activation of BDNF reduced inflammation in a spinal cord injury model by TrkB/p38 MAPK signaling

The aim of the present study was to investigate the pro-inflammation effects of brain-derived neurotrophic factor (BDNF) signaling in promoting inflammation following spinal cord injury (SCI) in rats. Reverse transcription-quantitative polymerase chain reaction was used to detect the expression of BDNF in SCI rats. The Basso, Beattie and Bresnahan (BBB) test was used and the water content of spinal cord were assessed to determine the effects of BDNF on SCI. BDNF expression was increased in SCI rats. In an in vitro model, overexpression of BDNF induced the protein expression of tyrosine kinase receptor B (TrkB) and suppressed that of phosphorylated (p-)p38, and reduced inflammation, as indicated by tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, IL-18, inducible nitric oxide synthase (iNOS) and cyclooxygenase (COX)-2 levels. Conversely, the TrkB inhibitor ANA-12 suppressed the protein expression of TrkB and induced that of p-p38, and promoted inflammation (as indicated by TNF-α, IL-1β, IL-6, IL-18, iNOS and COX-2 levels) in an in vitro model of SCI by BDNF overexpression. In addition, the p38 inhibitor TA-0, suppressed p38 protein expression and reduced inflammation in an in vitro model of SCI by BDNF overexpression. Together, these data suggest that the pro-inflammation effects of BDNF/TrkB promoted inflammation in SCI through p38 signaling in rats.

Quantitative multiparametric MR analysis of small renal lesions: correlation with surgical pathology

PURPOSE

The purpose of the study is to evaluate the utility of apparent diffusion coefficient (ADC), chemical shift signal intensity index (SII), and contrast enhancement in distinguishing between benign lesions and renal cell carcinoma (RCC) and between subtypes of renal lesions.

METHODS

This retrospective study included 98 renal lesions (≤ 3 cm) on MRI with correlative surgical pathology. Scanner field strength, lesion location, and size were recorded. Two readers blinded to surgical pathology independently measured ADC ratio (ADC lesion/ADC non-lesion kidney), SII, and absolute/relative enhancement in the corticomedullary and nephrographic phases of contrast.

RESULTS

There were 76 malignant and 22 benign lesions. 42 RCC were clear cell (ccRCC), 19 papillary (pRCC), 5 chromophobe (cbRCC). Benign lesions included both solid and cystic lesions. Interreader agreement for all variables was good-excellent (ICC 0.70-0.91). There was no difference in ADC or SII between benign and malignant lesions. There was greater absolute corticomedullary enhancement of benign versus malignant lesions (150.0 ± 111.5 vs. 81.1 ± 74.8, p = 0.0115), which did not persist when excluding pRCC. For lesion subtype differentiation, ADC_ratio for pRCC was lower than benign lesions (0.74 ± 0.35 vs. 1.03 ± 0.46, p = 0.0246). ccRCC demonstrated greater SII than other RCC (0.09 ± 0.22 vs. 0.001 ± 0.26, p = 0.0412). Oncocytomas and angiomyolipoma (AML) showed greater absolute corticomedullary enhancement than ccRCC and pRCC (145.6 ± 65.2 vs. 107.2 ± 85.3, p = 0.043 and 186.2 ± 93.9 vs. 37.6 ± 35.3, p = 0.0108), respectively.

CONCLUSIONS

While corticomedullary-phase enhancement was a differentiating feature, quantitative metrics from diffusion and chemical shift imaging cannot reliably differentiate benign from malignant lesions. Quantitative assessment may be useful in differentiating some benign and malignant lesion subtypes.

Magnetic resonance imaging (MRI) of the renal sinus

This article presents methods to improve MR imaging approach of disorders of the renal sinus which are relatively uncommon and can be technically challenging. Multi-planar Single-shot T2-weighted (T2W) Fast Spin-Echo sequences are recommended to optimally assess anatomic relations of disease. Multi-planar 3D-T1W Gradient Recalled Echo imaging before and after Gadolinium administration depicts the presence and type of enhancement and relation to arterial, venous, and collecting system structures. To improve urographic phase MRI, concentrated Gadolinium in the collecting systems should be diluted. Diffusion-Weighted Imaging (DWI) should be performed before Gadolinium administration to minimize T2* effects. Renal sinus cysts are common but can occasionally be confused for dilated collecting system or calyceal diverticula, with the latter communicating with the collecting system and filling on urographic phase imaging. Vascular lesions (e.g., aneurysm, fistulas) may mimic cystic (or solid) lesions on non-enhanced MRI but can be suspected by noting similar signal intensity to the blood pool and diagnosis can be confirmed with MR angiogram/venogram. Multilocular cystic nephroma commonly extends to the renal sinus, however, to date are indistinguishable from cystic renal cell carcinoma (RCC). Solid hilar tumors are most commonly RCC and urothelial cell carcinoma (UCC). Hilar RCC are heterogeneous, hypervascular with epicenter in the renal cortex compared to UCC which are centered in the collecting system, homogeneously hypovascular, and show profound restricted diffusion. Diagnosis of renal sinus invasion in RCC is critically important as it is the most common imaging cause of pre-operative under-staging of disease. Fat is a normal component of the renal sinus; however, amount of sinus fat correlates with cardiovascular disease and is also seen in lipomatosis. Fat-containing hilar lesions include lipomas, angiomyolipomas, and less commonly other tumors which engulf sinus fat. Mesenchymal hilar tumors are rare. MR imaging diagnosis is generally not possible, although anatomic relations should be described to guide diagnosis by percutaneous biopsy or surgery.

Differentiation between pancreatic metastases from clear cell renal cell carcinoma and pancreatic neuroendocrine tumor using double-echo chemical shift imaging

PURPOSE

The purpose of the study was to retrospectively analyze whether double-echo gradient-echo (GRE) chemical shift imaging (CSI) can differentiate between pancreatic metastases from clear cell renal cell carcinoma (PM-ccRCC) and pancreatic neuroendocrine tumor (pNET).

METHODS

Institutional review board approval and informed consent were waived. CSI, T2WI, DWI, and DCE magnetic resonance imaging (MRI) were performed in patients with PM-ccRCC and pNET. Eleven patients with PM-ccRCC and 24 patients with pNET were enrolled into this retrospective study. The signal intensity was measured in the pancreatic tumor and spleen on in-phase and opposed-phase images. The signal intensity index (SII) and tumor-to-spleen ratio (TSR) in PM-ccRCC and pNET were calculated and compared. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic accuracy of SII and TSR in the differentiation between PM-ccRCC and pNET.

RESULTS

The SII between PM-ccRCC and pNET (20.3% ± 16.8% vs. - 3.2% ± 11.4%) was significantly different (P < 0.001), as was the TSR (- 19.2% ± 16.6% vs. 6.0% ± 13.8%) (P < 0.001). The area under the ROC curve was 0.917 for the SII and 0.902 for the TSR. Additionally, an SII threshold value of 8.1% permitted the differentiation of PM-ccRCC from pNET with a sensitivity of 90.9%, a specificity of 91.7%, a positive predictive value of 90.1%, a negative predictive value of 91.7%, and an accuracy of 91.4%. A TSR cut-off value of - 4.7% enabled the differentiation of the two groups with a sensitivity of 79.2%, a specificity of 90.9%, a positive predictive value of 90.9%, a negative predictive value of 79.2% and an accuracy of 82.9%.

CONCLUSION

Double-echo GRE chemical shift MR imaging can accurately differentiate between PM-ccRCC and pNET.

Interpreting body MRI cases: classic findings in abdominal MRI

Few things in radiology are "pathognomonic" in their appearance or presentation. However, having an awareness of those findings which are specific to a certain entity is important when interpreting imaging studies. These classic findings can be identified with many imaging modalities, but no modality provides as many recognizable observations as an MRI. This results from the large variety of pulse sequences that provide high contrast resolution, prior to and following contrast administration. In this article, the most classically recognized abdominal findings are presented including the following: Liver: Cyst, hemangioma, focal nodular hyperplasia, hepatic adenoma, hemosiderosis, hepatocellular carcinoma. Spleen: Cyst, hemangioma, lymphangioma, hemosiderosis, Gandy-Gamna bodies. Biliary system: Biliary stones and choledocholithiasis, pneumobilia, choledochal cyst. Gallbladder: Adenomyomatosis, sludge, surgical clips in the gallbladder fossa. Pancreas: Pancreatic divisum, intraductal papillary mucinous neoplasm, pseudocyst, autoimmune pancreatitis, chronic pancreatitis, adenocarcinoma. Kidneys: Simple cyst, hemorrhagic cyst, renal sinus cyst, angiomyolipoma, solid mass.

Efficacy of 3D VIBE Dixon fat quantification for differentiating clear-cell from non-clear-cell renal cell carcinoma

AIM

To assess the efficacy of three-dimensional (3D) volumetric interpolated breath-hold examination (VIBE) magnetic resonance imaging (MRI) with Dixon quantification for differentiating clear-cell from non-clear-cell types of renal cell carcinoma (RCC).

MATERIALS AND METHODS

The 3D VIBE Dixon renal MRI examinations of 44 patients with 45 histologically confirmed RCCs was analysed. The fat fractions and signal intensity indexes (SI_index) of the solid portions of clear-cell and non-clear-cell RCCs were measured and compared using Student's t-test and receiver operating characteristic (ROC) curves. The agreement of measurements among observers was evaluated by the intraclass correlation coefficient (ICC), and Bland-Altman plots.

RESULTS

The mean values of fat fraction (13.16±7.16%) and SI_index (22.64±15.7%) in clear-cell RCCs were significantly higher than that in non-clear-cell RCCs (7.7±2% and 7.9±4.8%; p<0.001, respectively). With the area under the ROC curve (AUC) of the fat fraction at 0.811, 75% (95% CI: 55.1-89.43%) sensitivity and 76.5% (95% CI: 50.1-93.2%) specificity for diagnosing clear-cell RCC were obtained at a cut-off fat fraction value of 8.9%. With a cut-off value of 8.89%, the diagnostic sensitivity and specificity were 85.7% (95% CI: 67.3-96%) and 70.6% (95% CI: 44-89.7%), respectively. The AUC of the SI_index was 0.870 (0.766-0.973). ICC and Bland-Altman plots show excellent agreement of the tumour fat fraction and SI_index measurement between the two observers.

CONCLUSION

Intracellular lipid content analysis using the 3D Dixon technique can help to differentiate clear-cell from non-clear-cell RCCs.

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.

Differentiating solid, non-macroscopic fat containing, enhancing renal masses using fast Fourier transform analysis of multiphase CT

OBJECTIVE

To test the feasibility of two-dimensional fast Fourier transforms (FFT)-based imaging metrics in differentiating solid, non-macroscopic fat containing, enhancing renal masses using contrast-enhanced CT images. We quantify image-based intratumoral textural variations (indicator of tumor heterogeneity) using frequency-based (FFT) imaging metrics.

METHODS

In this Institutional Review Board approved, Health Insurance Portability and Accountability Act -compliant, retrospective case-control study, we evaluated 156 patients with predominantly solid, non-macroscopic fat containing, enhancing renal masses identified between June 2009 and June 2016. 110 cases (70%) were malignant RCC, including clear cell, papillary and chromophobe subtypes and, 46 cases (30%) were benign renal masses: oncocytoma and lipid-poor angiomyolipoma. Whole lesions were manually segmented using Synapse 3D (Fujifilm, CT) and co-registered from the multiphase CT acquisitions for each tumor. Pathological diagnosis of all tumors was obtained following surgical resection. Matlab function, FFT2 was used to perform the image to frequency transformation.

RESULTS

A Wilcoxon rank sum test showed that FFT-based metrics were significantly (p < 0.005) different between 1. benign vs malignant renal masses, 2. oncocytoma vs clear cell renal cell carcinoma and 3. oncocytoma vs lipid-poor angiomyolipoma. Receiver operator characteristics analysis revealed reasonable discrimination (area under the curve >0.7, p < 0.05) within these three groups of comparisons.

CONCLUSION

In combination with other metrics, FFT-metrics may improve patient management and potentially help differentiate other renal tumors. Advances in knowledge: We report for the first time that FFT-based metrics can differentiate between some solid, non-macroscopic fat containing, enhancing renal masses using their contrast-enhanced CT data.

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.

Angiomyolipoma of the Kidneys: Current Perspectives and Challenges in Diagnostic Imaging and Image-Guided Therapy

Angiomyolipomas (AML) are benign tumors of the kidneys frequently encountered in radiologic practice in large tertiary centers. In comparison to renal cell carcinomas (RCC), AML are seldom treated unless they are large, undergo malignant transformation or develop complications like acute hemorrhage. The common garden triphasic (classic) AML is an easy diagnosis, however, some variants lack macroscopic fat in which case the radiologic differentiation from RCC becomes challenging. Several imaging features, both qualitative and quantitative, have been described in differentiating the 2 entities. Although minimal fat AML is not entirely a radiologic diagnosis, the suspicion raised on imaging necessitates sampling and potentially avoids an unwanted surgery. Recently a new variant, epitheloid AML has been described which often has atypical imaging features and is at a higher risk for malignant transformation. Apart from the diagnosis, the radiologist also needs to convey information regarding nephrometric scores which help in surgical decision-making. Recently, more and more AMLs are managed with selective arterial embolization and percutaneous ablation, both of which are associated with less morbidity when compared to surgery. The purpose of this article is to review the imaging and pathologic features of classic AML as well as the differentiation of minimal fat AML from RCC. In addition, an overview of nephrometric scoring and image-guided interventions is also provided.

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.

Fat status detection and histotypes differentiation in solid renal masses using Dixon technique

PURPOSE

To detect fat status and differentiate histotypes of renal masses by using Dixon technique.

MATERIALS AND METHODS

This study included 134 solid renal masses. Signal intensity index (SII) and fat fraction (FF) in different histotypes were compared.

RESULTS

Only angiomyolipoma (AML), clear cell renal cell carcinoma (RCC), and papillary RCC were confirmed to contain fat. The FF of 16.8% can effectively differentiate AML from clear cell RCC, so did the SII of 9.2% can differentiate clear cell RCC from non-clear cell RCC and rare benign histotypes.

CONCLUSION

Dixon technique successfully evaluated the fat status and histotypes of renal masses.

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.

Renal Angiomyolipoma: Radiologic Classification and Imaging Features According to the Amount of Fat

OBJECTIVE

The purposes of this article are to introduce the radiologic classifications of renal angiomyolipoma (AML) and the clinical implications, to show the imaging features of each type of AML, and to describe which types of AML should be biopsied.

CONCLUSION

Renal AML can be classified according to amount of fat as fat rich, fat poor, or fat invisible. To detect fat, one needs to thoroughly evaluate the entire AML by controlling the size and shape of the ROI. Fat-invisible AML should be biopsied, and fat-poor AML requires further investigation to determine whether biopsy is necessary to differentiate it from renal cell carcinoma. If differentiation between AML and renal cell carcinoma is not clear with CT and MRI, percutaneous biopsy may be performed.

Patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: Introducing the BEARS index

Purpose

To create a simple model using clinical variables for predicting lipid-poor angiomyolipoma (AML) in patients with small renal masses presumed to be renal cell carcinoma (RCC) from preoperative imaging.

Materials and Methods

A series of patients undergoing partial nephrectomy (PN) for renal masses ≤4 cm was identified using a prospectively maintained database. Patients were excluded if standard preoperative imaging was not consistent with RCC. Chi square and Mann-Whitney U analyses were used to evaluate differences in characteristics between patients with AML and other types of pathology. A logistic regression model was constructed for multivariable analysis of predictors of lipid-poor AML.

Results

A total of 730 patients were identified that underwent PN for renal masses ≤4 cm between 2007–2015, including 35 with lipid-poor AML and 620 with RCC. In multivariable analysis, the following features predicted AML: female sex (odds ratio, 6.89; 95% confidence interval, 2.35–20.92; p<0.001), age <56 years (2.84; 1.21–6.66; p=0.02), and tumor size <2 cm (5.87; 2.70–12.77; p<0.001). Sex, age, and tumor size were used to construct the BEnign Angiomyolipoma Renal Susceptibility (BEARS) index with the following point values for each particular risk factor: female sex (2 points), age <56 years (1 point), and tumor size <2 cm (2 points). Within the study population, the BEARS index distinguished AML from malignant lesions with an area under the curve of 0.84.

Conclusions

Young female patients with small tumors are at risk for having lipid-poor AML despite preoperative imaging consistent with RCC. Identification of these patients may reduce the incidence of unnecessary PN for benign renal lesions.

Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging to Identify Clear Cell Renal Cell Carcinoma in cT1a Renal Masses

PURPOSE

The detection of small renal masses is increasing with the use of cross-sectional imaging, although many incidental lesions have negligible metastatic potential. Among malignant masses clear cell renal cell carcinoma is the most prevalent and aggressive subtype. A method to identify such histology would aid in risk stratification. Our goal was to evaluate a likelihood scale for multiparametric magnetic resonance imaging in the diagnosis of clear cell histology.

MATERIALS AND METHODS

We retrospectively reviewed the records of patients with cT1a masses who underwent magnetic resonance imaging and partial or radical nephrectomy from December 2011 to July 2015. Seven radiologists with different levels of experience who were blinded to final pathology findings independently reviewed studies based on a predefined algorithm. They applied a clear cell likelihood score, including 1-definitely not, 2-probably not, 3-equivocal, 4-probably and 5-definitely. Binary classification was used to determine the accuracy of clear cell vs all other histologies. Interobserver agreement was calculated with the weighted κ statistic.

RESULTS

A total of 110 patients with 121 masses were identified. Mean tumor size was 2.4 cm and 50% of the lesions were clear cell. Defining clear cell as scores of 4 or greater demonstrated 78% sensitivity and 80% specificity while scores of 3 or greater showed 95% sensitivity and 58% specificity. Interobserver agreement was moderate to good with a mean κ of 0.53.

CONCLUSIONS

A clear cell likelihood score used with magnetic resonance imaging can reasonably identify clear cell histology in small renal masses and may decrease the number of diagnostic renal mass biopsies. Standardization of imaging protocols and reporting criteria is needed to improve interobserver reliability.

Reporting standards for the imaging-based diagnosis of renal masses on CT and MRI: a national survey of academic abdominal radiologists and urologists

PURPOSE

To define important elements of a structured radiology report of a CT or MRI performed to evaluate an indeterminate renal mass.

METHODS

IRB approval was waived for this multi-site prospective quality improvement study. A 35-question survey investigating elements of a CT or MRI report describing a renal mass was created through an iterative process by the Society of Abdominal Radiology Disease-Focused Panel on renal cell carcinoma. Surveys were distributed to consenting abdominal radiologists and urologists at nine academic institutions. Consensus within and between specialties was defined as ≥70% agreement. Respondent rates were compared with Chi Square test.

RESULTS

The response rate was 68% (117/171; 55% [39/71] urologists, 78% [78/100] radiologists). Inter-specialty consensus was that the following were essential: mass size with comparison to prior imaging, mass type (cystic vs. solid), presence of fat, presence of enhancement, and radiologic stage. Urologists were more likely to prefer the Nephrometry score (75% [27/36] vs. 22% [17/76], p < 0.0001), quantitative reporting of enhancement on CT (85% [32/38] vs. 46% [36/77], p < 0.0001), and mass position with respect to the renal polar lines (67% [24/36] vs. 36% [27/76], p = 0.002). There was inter-specialty consensus that the Bosniak classification for cystic masses was preferred. Most urologists (60% [21/35]) preferred management recommendations be omitted for solid masses or Bosniak III-IV cystic masses.

CONCLUSIONS

Important elements to include in a CT or MRI report of an indeterminate renal mass are critical diagnostic features, the Bosniak classification if relevant, and the most likely specific diagnosis when feasible; including management recommendations is controversial.

Predictors of growth kinetics and outcomes in small renal masses (SRM ≤4 cm in size): Tayside Active Surveillance Cohort (TASC) Study

OBJECTIVE

To determine outcomes of small renal masses (≤4 cm) on active surveillance and explore factors which can influence their growth.

PATIENTS AND METHODS

Two hundred twenty six patients between January 2007 and December 2014 were analysed using cross-linked methodology of healthcare data and independent review. Cancer specific and non-specific survival were the primary outcomes. Growth kinetics, factors influencing growth and need for interventions were secondary outcomes.

RESULTS

101 (64.4%) solid and 4 (5.9%) cystic SRMs showed growth. 43 (19.02%) of SRMs required treatment interventions. Seven patients (7/158; 4.4%) died due to renal cancer at a median follow-up of 21.7 (SD 10.6, min 6-42) months, all in solid category. Independent review of serial radiological imaging of these seven cases showed two patients had subtle metastatic disease at the initial presentation, and 5 of the 7 did not adhere to recommended imaging regime. 33 (33/158; 20.8%) died due to other causes including non-renal cancers (14/158; 8.8%). Multivariate analyses showed that lower eGFR at baseline, co-morbidities and tumour location were independently associated with growth in size.

CONCLUSIONS

A higher cancer-specific mortality was seen in the present study compared to the reported literature. Independent critical review of imaging of cases with poor outcome underscored the importance of adherence to a robust protocol including follow up. Comorbid conditions had a significant impact on growth and overall survival of patients with SRMs.