Pretreatment differentiation of renal cell carcinoma subtypes by CT: the influence of different tumor enhancement measurement approaches

Metanephric adenoma in children: A case report and literature review

Metanephric adenoma (MA) is a rare type of benign renal epithelial tumor that can develop at any age. Nonetheless, MA is extremely rare in children and only a few cases have been reported to date. The present study aimed to report the case of a 5-year-old female found to have a mass in the right kidney during a routine pre-enrollment physical examination. Computed tomography (CT) images revealed multiple high-density calcifications in the mass, and contrast-enhanced CT and magnetic resonance imaging demonstrated that the mass was significantly enhanced in the cortical phase and decreased in the medullary phase. Based on these findings, the mass was initially diagnosed as angiomyolipoma before surgery; however, postoperative pathology confirmed the mass to be a MA. MAs are typically a type of soft tissue mass with relatively uniform density or signal, showing delayed enhancement in contrast-enhanced scanning. However, the mass found in the present study presented diffused high-density calcification, which was obvious in the early phase of contrast-enhanced scanning but weakened in the delayed enhancement phase. In conclusion, the present case study demonstrated that MA should be considered as one of the imaging differential diagnoses of fat-poor angiomyolipoma, renal carcinoma and oncocytoma.

CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation

BACKGROUND

Although the central scar is an essential imaging characteristic of renal oncocytoma (RO), its utility in distinguishing RO from renal cell carcinoma (RCC) has not been well explored. The study aimed to evaluate whether the combination of CT characteristics of the peripheral tumor parenchyma (PTP) and central hypodense area (CHA) can differentiate typical RO with CHA from RCC.

METHODS

A total of 132 tumors on the initial dataset were retrospectively evaluated using four-phase CT. The excretory phases were performed more than 20 min after the contrast injection. In corticomedullary phase (CMP) images, all tumors had CHAs. These tumors were categorized into RO (n = 23), clear cell RCC (ccRCC) (n = 85), and non-ccRCC (n = 24) groups. The differences in these qualitative and quantitative CT features of CHA and PTP between ROs and ccRCCs/non-ccRCCs were statistically examined. Logistic regression filters the main factors for separating ROs from ccRCCs/non-ccRCCs. The prediction models omitting and incorporating CHA features were constructed and evaluated, respectively. The effectiveness of the prediction models including CHA characteristics was then confirmed through a validation dataset (8 ROs, 35 ccRCCs, and 10 non-ccRCCs).

RESULTS

The findings indicate that for differentiating ROs from ccRCCs and non-ccRCCs, prediction models with CHA characteristics surpassed models without CHA, with the corresponding areas under the curve (AUC) being 0.962 and 0.914 versus 0.952 and 0.839 respectively. In the prediction models that included CHA parameters, the relative enhancement ratio (RER) in CMP and enhancement inversion, as well as RER in nephrographic phase and enhancement inversion were the primary drivers for differentiating ROs from ccRCCs and non-ccRCCs, respectively. The prediction models with CHA characteristics had the comparable diagnostic ability on the validation dataset, with respective AUC values of 0.936 and 0.938 for differentiating ROs from ccRCCs and non-ccRCCs.

CONCLUSION

The prediction models with CHA characteristics can help better differentiate typical ROs from RCCs. When a mass with CHA is discovered, particularly if RO is suspected, EP images with longer delay scanning periods should be acquired to evaluate the enhancement inversion characteristics of CHA.

The role of diffusion-weighted MRI and contrast-enhanced MRI for differentiation between solid renal masses and renal cell carcinoma subtypes

PURPOSE

To assess the value of diffusion-weighted magnetic resonance imaging (DW-MRI) and contrast-enhanced MRI (CE-MRI) for differentiation between benign and malignant solid renal masses, renal cell carcinoma (RCC) subtypes, oncocytomas, and lipid-poor angiomyolipomas (LP-AML).

METHODS

Minimum or lowest 'apparent diffusion coefficient' (ADC₁) and representative ADC values (ADC₂) of 112 renal masses (n: 46 benign renal mass, n: 66 malignant renal mass) were measured on DW-MRI images (b 50, 400, 800 s/mm²). Signal intensity (SI) measurements were performed in normal renal parenchyma and most avid enhanced area of the renal masses at precontrast, corticomedullary, and nephrographic phases on CE-MRI. Contrast enhancement rate (CER) and contrast enhancement index (CEI) values of renal masses were compared between benign-malignant renal masses and RCC subtypes, oncocytomas, and LP-AMLs.

RESULTS

There was no significant difference between ADC₁, ADC₂ values, and SI of benign and malignant renal masses (p = 0.721, p = 0.255, p = 0.872). Mean ADC₁ and ADC₂ values of clear cell RCCs were significantly higher than nonclear cell RCCs (p = 0.005 p = 0.002). Mean CER value of clear cell RCCs was significantly higher than nonclear cell RCCs in nephrographic phase (p = 0.003). Mean CEI values of clear cell RCCs were significantly higher than nonclear cell RCCs in the corticomedullary and nephrographic phase (p = 0.027 vs. 0.008). LP-AMLs were differentiated from other renal masses with wash-out phenomenon.

CONCLUSION

Combined usage of ADC, SI, CER, and CEI values may be useful for discrimination between RCC subtypes, oncocytomas, and lipid-poor AMLs.

Renal Oncocytoma: An Algorithm for Diagnosis and Management

Renal oncocytoma is an uncommon tumor that exhibits numerous features which are characteristic but not necessarily unique. Percutaneous biopsy is a safe method of diagnosis. However, differentiation from other tumor subtypes often requires sophisticated analysis and is not universally feasible. This is why, surgical management can be considered as a first-line treatment or after surveillance. Potential triggers for change in management are: tumor size >3 cm, stage progression, kinetics of size progression (>5 mm/y), and clinical change in patient or tumor factors. Long-term follow-up data are lacking and greater centralization should be considered to reach adequate management.

Caspase 3 as a Novel Marker to Distinguish Chromophobe Renal Cell Carcinoma from Oncocytoma

Despite advances in our understanding of the biology of chromophobe renal cell carcinoma (ChRCC) and renal oncocytoma (RO), the differential diagnosis among these tumors remains one of the most problematic in renal pathology. Today, CK7 is the most recommended marker to distinguish these entities, however it appears insufficiently accurate by itself. This study aimed to find an easily accessible IHC stain that might out-compete CK7 in this field. Expressions of CK7, cyclin D1, p16, survivin, CD138, Ki-67 and caspase 3 (CASP3) were analyzed in a total of 27 cases (20 ROs and 7 ChRCCs). Immunoreactivity was assessed based on a combined score of the extent and intensity of staining. Compared to RO, a higher percentage of the total ChRCCs stained positive for CK7 (67% vs. 22%, respectively) and CASP3 (86% vs. 25%) (P < 0.005). The differences in staining with cyclin D1, p16, survivin, CD138 and Ki-67 turned out to be statistically insignificant in differentiating ChRCC from RO. CASP3 is a promising marker in distinguishing ChRCC from RO and may represent an alternative for CK7. Cyclin D1, p16, survivin, CD138 and Ki-67 cannot be used to distinguish these neoplasms.

Role of Contrast Enhancement and Corrected Attenuation Values of Renal Tumors in Predicting Renal Cell Carcinoma (RCC) Subtypes: Protocol for a Triphasic Multi-Slice Computed Tomography (CT) Procedure

BACKGROUND

To distinguish RCC subtypes based on contrast enhancement features of CT images.

MATERIAL/METHODS

In total, 59 lesions from 57 patients were included. All patients underwent multi-slice CT imaging with a triphasic protocol, which included non-contrast, corticomedullary, nephrographic and urographic phases. Contrast enhancement features of renal masses were evaluated in terms of CT attenuation values (AV) and differences in contrast density; the aorta or renal parenchyma were evaluated based on corrected or relative values.

RESULTS

Clear cell RCC (ccRCC) showed more intense contrast enhancement than other RCC subtypes. When differentiating ccRCC from other RCC subtypes, a cut-off AV of 86-89 HU, aorta-based corrected AV of 89-95 HU and renal parenchyma-based corrected AV of 87-95 HU showed a diagnostic accuracy of 81-86%, 86-88% and 74-78%, respectively, in the corticomedullary phase. Furthermore, a cutoff of 2.42-2.72 for the relative contrast enhancement ratio, a cutoff of 2.59-2.74 for the aorta-based corrected relative contrast enhancement ratio and a cutoff of 2.63-2.76 for the renal parenchyma-based attenuation ratio showed a diagnostic accuracy of 83-88%, 88-90% and 81%, respectively.

CONCLUSIONS

The most reliable parameters for differentiating ccRCC from other RCC subtypes are aorta-based corrected AV and aorta-based corrected relative contrast enhancement values in the corticomedullary phase.

Quantitative computer-aided diagnostic algorithm for automated detection of peak lesion attenuation in differentiating clear cell from papillary and chromophobe renal cell carcinoma, oncocytoma, and fat-poor angiomyolipoma on multiphasic multidetector computed tomography

OBJECTIVE

To evaluate the performance of a novel, quantitative computer-aided diagnostic (CAD) algorithm on four-phase multidetector computed tomography (MDCT) to detect peak lesion attenuation to enable differentiation of clear cell renal cell carcinoma (ccRCC) from chromophobe RCC (chRCC), papillary RCC (pRCC), oncocytoma, and fat-poor angiomyolipoma (fp-AML).

MATERIALS AND METHODS

We queried our clinical databases to obtain a cohort of histologically proven renal masses with preoperative MDCT with four phases [unenhanced (U), corticomedullary (CM), nephrographic (NP), and excretory (E)]. A whole lesion 3D contour was obtained in all four phases. The CAD algorithm determined a region of interest (ROI) of peak lesion attenuation within the 3D lesion contour. For comparison, a manual ROI was separately placed in the most enhancing portion of the lesion by visual inspection for a reference standard, and in uninvolved renal cortex. Relative lesion attenuation for both CAD and manual methods was obtained by normalizing the CAD peak lesion attenuation ROI (and the reference standard manually placed ROI) to uninvolved renal cortex with the formula [(peak lesion attenuation ROI - cortex ROI)/cortex ROI] × 100%. ROC analysis and area under the curve (AUC) were used to assess diagnostic performance. Bland-Altman analysis was used to compare peak ROI between CAD and manual method.

RESULTS

The study cohort comprised 200 patients with 200 unique renal masses: 106 (53%) ccRCC, 32 (16%) oncocytomas, 18 (9%) chRCCs, 34 (17%) pRCCs, and 10 (5%) fp-AMLs. In the CM phase, CAD-derived ROI enabled characterization of ccRCC from chRCC, pRCC, oncocytoma, and fp-AML with AUCs of 0.850 (95% CI 0.732-0.968), 0.959 (95% CI 0.930-0.989), 0.792 (95% CI 0.716-0.869), and 0.825 (95% CI 0.703-0.948), respectively. On Bland-Altman analysis, there was excellent agreement of CAD and manual methods with mean differences between 14 and 26 HU in each phase.

CONCLUSION

A novel, quantitative CAD algorithm enabled robust peak HU lesion detection and discrimination of ccRCC from other renal lesions with similar performance compared to the manual method.

Dynamic Contrast-enhanced MRI in Renal Tumors: Common Subtype Differentiation using Pharmacokinetics

Preoperative renal tumor subtype differentiation is important for radiology and urology in clinical practice. Pharmacokinetic data (K^trans & V_e, etc.) derived from dynamic contrast-enhanced MRI (DCE-MRI) have been used to investigate tumor vessel permeability. In this prospective study on DCE-MRI pharmacokinetic studies, we enrolled patients with five common renal tumor subtypes: clear cell renal cell carcinoma (ccRCC; n = 65), papillary renal cell carcinoma (pRCC; n = 12), chromophobic renal cell carcinoma (cRCC; n = 9), uroepithelial carcinoma (UEC; n = 14), and fat-poor angiomyolipoma (fpAML; n = 10). The results show that K^trans of ccRCC, pRCC, cRCC, UEC and fpAML (0.459 ± 0.190 min⁻¹, 0.206 ± 0.127 min⁻¹, 0.311 ± 0.111 min⁻¹, 0.235 ± 0.116 min⁻¹, 0.511 ± 0.159 min⁻¹, respectively) were different, but V_e was not. K^trans could distinguish ccRCC from non-ccRCC (pRCC & cRCC) with a sensitivity of 76.9% and a specificity of 71.4%, respectively, as well as to differentiate fpAML from non-ccRCC with a sensitivity of 100% and a specificity of 76.2%, respectively. Our findings suggest that DCE-MRI pharmacokinetics are promising for differential diagnosis of renal tumors, especially for RCC subtype characterization and differentiation between fpAML and non-ccRCC, which may facilitate the treatment of renal tumors.

Preoperative evaluation of renal cell carcinoma by using 18F-FDG PET/CT

PURPOSE

This study aimed to characterize the FDG uptake of renal cell carcinoma (RCC) by the pathological subtype and nuclear grade.

PATIENTS AND METHODS

We retrospectively identified patients who underwent F-FDG PET and subsequent partial or radical nephrectomy for renal tumors. The relationships of the SUV of renal tumor with subtypes, nuclear grade, and clinicopathological variables were investigated.

RESULTS

Ninety-two tumors were analyzed, including 52 low-grade (G1 and G2) and 18 high-grade (G3 and G4) clear cell RCC; 7 chromophobe, 5 papillary, and 1 unclassified RCC; and 9 benign tumors (7 angiomyolipoma and 2 oncocytoma). The SUVs of high-grade clear cell RCC (mean ± SD, 6.8 ± 5.1) and papillary RCC (6.6 ± 3.7) were significantly higher than that of the controls (2.2 ± 0.3). The SUV of high-grade clear cell RCC was higher than that of low-grade tumors (median, 4.0 vs. 2.2; P < 0.001). The optimal SUV cutoff value of 3.0 helped to differentiate high-grade from low-grade clear cell RCC, with 89% sensitivity and 87% specificity. On multiple regression analysis, a high grade was the most significant predictor of SUV for clear cell RCC.

CONCLUSIONS

FDG uptake higher than that observed in normal kidney tissues suggests a high-grade clear cell RCC or papillary RCC subtype. FDG-PET using SUV may have a role in prediction of pathological grade of renal tumor.

Assessment of Semiquantitative Parameters of Dynamic Contrast-Enhanced Perfusion MR Imaging in Differentiation of Subtypes of Renal Cell Carcinoma

Background

To assess semiquantitative parameters of dynamic contrast-enhanced perfusion MR imaging (DCE) in differentiation of subtypes of renal cell carcinoma (RCC).

Material/Methods

Prospective study conducted upon 34 patients (27 M, 7 F, aged 25–72 ys: mean 45 ys) with RCC. Abdominal dynamic contrast-enhanced gradient-recalled echo MR sequence after administration of gadopentetate dimeglumine was obtained. The time signal intensity curve (TIC) of the lesion was created with calculation of enhancement ratio (ER), and washout ratio (WR).

Results

The subtypes of RCC were as follows: clear cell carcinomas (n=23), papillary carcinomas (n=6), and chromophobe carcinomas (n=5). The mean ER of clear cell, papillary and chromophobe RCC were 188±49.7, 35±8.9, and 120±41.6 respectively. The mean WR of clear cell, papillary and chromophobe RCCs were 28.6±6.8, 47.6±5.7 and 42.7±10, respectively. There was a significant difference in ER (P=0.001) and WR (P=0.001) between clear cell RCC and other subtypes of RCC. The threshold values of ER and WR used for differentiating clear cell RCC from other subtypes of RCC were 142 and 38 with areas under the curve of 0.937 and 0.895, respectively.

Conclusions

We concluded that ER and WR are semiquantitative perfusion parameters useful in differentiation of clear cell RCC from chromophobe and papillary RCCs.

Quantitative evaluation of contrast-enhanced ultrasound for differentiation of renal cell carcinoma subtypes and angiomyolipoma

PURPOSE

To investigate the value of quantitative parameters of contrast-enhanced ultrasound (CEUS) in the differentiation of subtypes of renal cell carcinoma (RCC) and angiomyolipoma (AML).

METHODS

The quantitative characteristics of 341 RCCs and 88 AMLs were analyzed with quantitative software (SonoLiver). Quantitative analysis was conducted in the whole tumor (ROItumor) and the maximum enhanced area of the tumor (ROImax), acquiring the parameters of maximum intensity (IMAX), rise time (RT), time to peak (TTP), mean transit time (mTT), and area under the curve (AUC), were derived and analyzed. The difference values between ROImax and normal renal cortex (ΔPar.s, including ΔIMAX, ΔRT, ΔTTP, ΔmTT, ΔAUC) were compared among renal histotypes.

RESULTS

All time-related parameters (including RT, TTP and mTT) of ROImax were shorter than the corresponding parameters of ROItumor in RCC subtypes (all p<0.05), but made no statistical difference in AMLs (all p>0.05). There were significant differences of all ΔPar.s among RCC subtypes and AML (all p<0.01). ΔIMAX and ΔAUC showed the trend that ccRCC>AML>pRCC=chRCC. ΔTTP showed AML=pRCC=chRCC>ccRCC, ΔRT and ΔmTT showed AML>pRCC=chRCC=ccRCC. ΔmTT could distinguish RCC from AML with the area under the ROC curve (AUC) of 0.86. The AUC of ΔIMAX and ΔAUC was 0.89 and 0.92 vs 0.85 and 0.85 for discriminating between pRCC (or chRCC) and AML vs ccRCC and AML.

CONCLUSIONS

Quantitative analysis of CEUS is a useful modality in AML and RCC subtypes' differentiation, by using ΔmTT, ΔIMAX and ΔAUC.

Advances of multidetector computed tomography in the characterization and staging of renal cell carcinoma

Renal cell carcinoma (RCC) accounts for approximately 90%-95% of kidney tumors. With the widespread use of cross-sectional imaging modalities, more than half of RCCs are detected incidentally, often diagnosed at an early stage. This may allow the planning of more conservative treatment strategies. Computed tomography (CT) is considered the examination of choice for the detection and staging of RCC. Multidetector CT (MDCT) with the improvement of spatial resolution and the ability to obtain multiphase imaging, multiplanar and three-dimensional reconstructions in any desired plane brought about further improvement in the evaluation of RCC. Differentiation of RCC from benign renal tumors based on MDCT features is improved. Tumor enhancement characteristics on MDCT have been found closely to correlate with the histologic subtype of RCC, the nuclear grade and the cytogenetic characteristics of clear cell RCC. Important information, including tumor size, localization, and organ involvement, presence and extent of venous thrombus, possible invasion of adjacent organs or lymph nodes, and presence of distant metastases are provided by MDCT examination. The preoperative evaluation of patients with RCC was improved by depicting the presence or absence of renal pseudocapsule and by assessing the possible neoplastic infiltration of the perirenal fat tissue and/or renal sinus fat compartment.

CT imaging spectrum and the histopathological features of adult metanephric adenoma

OBJECTIVE

To retrospectively evaluate the radiopathological features of adult metanephric adenoma (MA) and explore whether MA can be differentiated on CT images, including the basis of their morphological features and enhancement patterns.

METHODS

18 consecutive MA cases (age range, 18-66 years; 9 males and 9 females) were pathologically proven and recruited in our study between January 2004 and June 2014. Unenhanced and contrast-enhanced CT were performed and correlated with corresponding pathological findings to differentiate between MA and other renal tumours. The enhancement pattern, lesion contour and presence of calcifications were evaluated.

RESULTS

On unenhanced CT scan, the most common (n = 15, 83.3%) CT imaging characteristics were the presence of homogeneity and well-defined solid renal masses; the minority (n = 3, 16.7%) were heterogeneous or centrally located low-attenuation masses. Contrast-enhanced CT image revealed hypoattenuating heterogeneous masses with varying degrees of contrast enhancement in 16 (88.9%) cases, in contrast to those without increased attenuation in 2 (11.1%) cases. Scattered calcification was found only in one case (5.6%). Pathological results revealed that a total of 6 (33.3%) cases had concomitant malignant carcinoma components; 2 (11.1%) patients had malignant MA; and pure MA was found in 10 cases, with a surprisingly high proportion of malignant tumours.

CONCLUSION

The positive-predictive values of "high" enhancement seemed relatively characteristic for the diagnosis of malignant and composite MA.

ADVANCES IN KNOWLEDGE

Radiopathological features of adult MA and exploring whether MA can be differentiated on CT images, including the basis of their morphological features and enhancement patterns.