Small Solid Renal Masses Research Articles

Prospective evaluation of the diagnostic efficacy of multiparametric MRI clear cell Likelihood Score in small solid renal masses and its predictive value for tumor grade

BackgroundThe detection of small renal masses has significantly increased due to the widespread use of cross-sectional imaging in recent years. Among these masses, clear cell renal cell carcinoma (ccRCC) is the most common subtype and progresses quickly, resulting in the advancement of the disease and the development of metastases. In this prospective study, our goal is to assess the effectiveness of multiparametric MRI clear cell Likelihood Score in small solid renal masses and its utility in predicting tumor grade.ResultsIn total, 103 patients (mean age 52.5 ± 13.16 years) with small solid renal masses of stage T1a (≤ 4 cm) were identified. Mean tumor size was 3.4 ± 0.6 cm. According to our study results, the clear cell Likelihood Score (ccLS) had sensitivity of 75.6%, specificity of 93.5%, PPV of 88.6%, NPV of 85.3% and accuracy of 86.4% in diagnosing ccRCC using a ccLS threshold of 4 and 5. As regard the assessment of ccLS threshold of 1 or 2 in excluding ccRCC pathological subtype, our study found that out of 29 patients with ccLS 1 or 2, there was only 1 ccRCC case with false result (3% false positive). It was also noted that there is significant relation between Arterial-to-delayed-enhancement-ratio (ADER) value and the grade of the ccRCC. The median interquartile range (IQR) of ADER parameter was statistically significant higher in grade II compared to grade I (Median was 1.6 and 0.9 respectively) and much higher in grade III compared to grades I and II (Median was 2.9) with P value < 0.001.ConclusionThis ccLS showed promising efficacy in prediction and exclusion of ccRCC subtype. Moreover, it aids in predicting the ccRCC grade.

Evaluation of a multiparametric renal CT algorithm for diagnosis of clear-cell renal cell carcinoma among small (≤ 4cm) solid renal masses.

To evaluate a recently proposed CT-based algorithm for diagnosis of clear-cell renal cell carcinoma (ccRCC) among small (≤ 4 cm) solid renal masses diagnosed by renal mass biopsy. This retrospective study included 51 small renal masses in 51 patients with renal-mass CT and biopsy between 2014 and 2021. Three radiologists independently evaluated corticomedullary phase CT for the following: heterogeneity and attenuation ratio (mass:renal cortex), which were used to inform the CT score (1-5). CT score ≥ 4 was considered positive for ccRCC. Diagnostic accuracy was calculated for each reader and overall using fixed effects logistic regression modelling. There were 51% (26/51) ccRCC and 49% (25/51) other masses. For diagnosis of ccRCC, area under curve (AUC), sensitivity, specificity, and positive predictive value (PPV) were 0.69 (95% confidence interval 0.61-0.76), 78% (68-86%), 59% (46-71%), and 67% (54-79%), respectively. CT score ≤ 2 had a negative predictive value 97% (92-99%) to exclude diagnosis of ccRCC. For diagnosis of papillary renal cell carcinoma (pRCC), CT score ≤ 2, AUC, sensitivity, specificity, and PPV were 0.89 (0.81-0.98), 81% (58-94%), 98% (93-99%), and 85% (62-97%), respectively. Pooled inter-observer agreement for CT scoring was moderate (Fleiss weighted kappa = 0.52). The CT scoring system for prediction of ccRCC was sensitive with a high negative predictive value and moderate agreement. The CT score is highly specific for diagnosis of pRCC. The CT score algorithm may help guide renal mass biopsy decisions in clinical practice, with high sensitivity to identify clear-cell tumors for biopsy to establish diagnosis and grade and high specificity to avoid biopsy in papillary tumors. • A CT score ≥ 4 had high sensitivity and negative predictive value for diagnosis of clear-cell renal cell carcinoma (RCC) among solid ≤ 4-cm renal masses. • A CT score ≤ 2 was highly specific for diagnosis of papillary RCC among solid ≤ 4-cm renal masses. • Inter-observer agreement for CT score was moderate.

External Validation of a Five-Tiered CT Algorithm for the Diagnosis of Clear Cell Renal Cell Carcinoma: A Retrospective Five-Reader Study.

BACKGROUND. In 2022, a five-tiered CT algorithm was proposed for predicting whether a small (cT1a) solid renal mass represents clear cell renal cell carcinoma (ccRCC). OBJECTIVE. The purpose of this external validation study was to evaluate the proposed CT algorithm for diagnosis of ccRCC among small solid renal masses. METHODS. This retrospective study included 93 patients (median age, 62 years; 42 women, 51 men) with 97 small solid renal masses that were seen on corticomedullary phase contrast-enhanced CT performed between January 2012 and July 2022 and subsequently underwent surgical resection. Five readers (three attending radiologists, two clinical fellows) independently evaluated masses for the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score; these scores were used to derive the CT score by use of the previously proposed CT algorithm. The CT score's sensitivity, specificity, and PPV for ccRCC were calculated at threshold of 4 or greater, and the NPV for ccRCC was calculated at a threshold of 3 or greater (consistent with thresholds in studies of the MRI-based clear cell likelihood score and the CT algorithm's initial study). The CT score's sensitivity and specificity for papillary RCC were calculated at a threshold of 2 or less. Interreader agreement was assessed using the Gwet agreement coefficient (AC1). RESULTS. Overall, 61 of 97 masses (63%) were malignant and 43 of 97 (44%) were ccRCC. Across readers, CT score had sensitivity ranging from 47% to 95% (pooled sensitivity, 74% [95% CI, 68-80%]), specificity ranging from 19% to 83% (pooled specificity, 59% [95% CI, 52-67%]), PPV ranging from 48% to 76% (pooled PPV, 59% [95% CI, 49-71%]), and NPV ranging from 83% to 100% (pooled NPV, 90% [95% CI, 84-95%]), for ccRCC. A CT score of 2 or less had sensitivity ranging from 44% to 100% and specificity ranging from 77% to 98% for papillary RCC (representing nine of 97 masses). Interreader agreement was substantial for attenuation score (AC1 = 0.70), poor for heterogeneity score (AC1 = 0.17), fair for five-tiered CT score (AC1 = 0.32), and fair for dichotomous CT score at a threshold of 4 or greater (AC1 = 0.24 [95% CI, 0.14-0.33]). CONCLUSION. The five-tiered CT algorithm for evaluation of small solid renal masses was tested in an external sample and showed high NPV for ccRCC. CLINICAL IMPACT. The CT algorithm may be used for risk stratification and patient selection for active surveillance by identifying patients unlikely to have ccRCC.

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

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

Contrast-enhanced ultrasonography in the differential diagnosis of complex renal cysts and small renal masses

BackgroundRenal masses can be divided into complex cysts and solid lesions. The Bosniak classification divides renal cysts into IV categories bases on different criteria. Based on this characterization, a decision about further management can be made. Sonography or contrast-enhanced sonography is one of the standard diagnostic procedures for renal cysts and is a useful method for classification into the Bosniak categories.ObjectivesThis review describes cystic kidney lesions and their differentiation using contrast-enhanced sonography, which is intended to support further management.Materials and methodsA selective literature search and evaluation of the own patient collective were carried out for the preparation of the review.ConclusionContrast-enhanced sonography is a simple and inexpensive technique. In the evaluation of complex renal cysts and small solid renal masses, it allows rapid determination of the appropriate therapeutic approach, especially since additional information about the vascularization of the renal masses is obtained.

Diagnostic Value of Qualitative and Quantitative Contrast-Enhanced Ultrasound for Pathological Subtypes of Small Solid Renal Masses.

To assess the diagnostic value of qualitative and quantitative contrast-enhanced ultrasound (CEUS) for pathological subtypes of small solid renal masses (sSRMs). Patients with sSRMs confirmed by surgical pathology from January 2019 to November 2021 were retrospectively identified. All patients were divided into 3 groups: clear cell renal cell carcinoma (ccRCC) group, none-ccRCC group (renal cell carcinoma other than ccRCC), and angiomyolipoma (AML) group. The mass position, size, echogenicity and blood flow signals were compared. The speed of wash-in, wash-out, the degree of peak enhancement and the homogeneity at peak enhancement, the presence of pseudocapsule sign in CEUS imaging were qualitatively evaluated. Peak enhancement, wash-in area under the curve (WiAUC), rise time, time to peak, wash-in rate (WiR), wash-in perfusion index (WiPI) and tumor-to-cortex enhancement ratio of the above parameters in CEUS imaging were quantitatively evaluated. Of 105 patients, 105 sSRMs (66 ccRCC, 18 none-ccRCC, 21 AML) were enrolled in this study. No significant differences were found on location, size and echogenicity among 3 groups (all P > .05). The proportion of fast-washout and hypo-enhancement were highest in none-ccRCC group. Heterogeneous enhancement was detected in 87.88% in ccRCC group which is significantly higher than other 2 groups. Hundred percent of the AML showed no pseudocapsule sign, which is the highest among the 3 groups. Peak enhancement, WiAUC, WiR, WiPI of ccRCC group were the highest among the 3 groups. Qualitative and quantitative CEUS not only has the diagnostic value in distinguishing AML from malignant sSRMs, but also helps to differentiate the pathological subtypes of sSRMs.

Development of a Multiparametric Renal CT Algorithm for Diagnosis of Clear Cell Renal Cell Carcinoma Among Small (≤ 4 cm) Solid Renal Masses.

BACKGROUND. The MRI clear cell likelihood score predicts the likelihood that a renal mass is clear cell renal cell carcinoma (ccRCC). A CT-based algorithm has not yet been established. OBJECTIVE. The purpose of our study was to develop and evaluate a CT-based algorithm for diagnosing ccRCC among small (≤ 4 cm) solid renal masses. METHODS. This retrospective study included 148 patients (73 men, 75 women; mean age, 58 ± 12 [SD] years) with 148 small (≤ 4 cm) solid (> 25% enhancing tissue) renal masses that underwent renal mass CT (unenhanced, corticomedullary, and nephrographic phases) before resection between January 2016 and December 2019. Two radiologists independently evaluated CT examinations and recorded calcification, mass attenuation in all phases, mass-to-cortex corticomedullary attenuation ratio, and heterogeneity score (score on a 5-point Likert scale, assessed in corticomedullary phase). Features associated with ccRCC were identified by multivariable logistic regression analysis and then used to create a five-tiered CT score for diagnosing ccRCC. RESULTS. The masses comprised 53% (78/148) ccRCC and 47% (70/148) other histologic diagnoses. The mass-to-cortex corticomedullary attenuation ratio was higher for ccRCC than for other diagnoses (reader 1: 0.84 ± 0.68 vs 0.68 ± 0.65, p = .02; reader 2: 0.75 ± 0.29 vs 0.59 ± 0.25, p = .02). The heterogeneity score was higher for ccRCC than other diagnoses (reader 1: 4.0 ± 1.1 vs 1.5 ± 1.6, p < .001; reader 2: 4.4 ± 0.9 vs 3.3 ± 1.5, p < .001). Other features showed no difference. A five-tiered diagnostic algorithm including the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score had interobserver agreement of 0.71 (weighted κ) and achieved an AUC for diagnosing ccRCC of 0.75 (95% CI, 0.68-0.82) for reader 1 and 0.72 (95% CI, 0.66-0.82) for reader 2. A CT score of 4 or greater achieved sensitivity, specificity, and PPV of 71% (95% CI, 59-80%), 79% (95% CI, 67-87%), and 79% (95% CI, 67-87%) for reader 1 and 42% (95% CI, 31-54%), 81% (95% CI, 70-90%), and 72% (95% CI, 56-84%) for reader 2. A CT score of 2 or less had NPV of 85% (95% CI, 69-95%) for reader 1 and 88% (95% CI, 69-97%) for reader 2. CONCLUSION. A five-tiered renal CT algorithm, including the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score, had substantial interobserver agreement, moderate AUC and PPV, and high NPV for diagnosing ccRCC. CLINICAL IMPACT. The CT algorithm, if validated, may represent a useful clinical tool for diagnosing ccRCC.

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

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

Editorial Comment: Managing Small Renal Masses—A Shifting Paradigm

This Editorial Comment discusses the following AJR article: Association of Clear Cell Likelihood Score on MRI and Growth Kinetics of Small Solid Renal Masses on Active Surveillance.

Association of Clear Cell Likelihood Score on MRI and Growth Kinetics of Small Solid Renal Masses on Active Surveillance.

BACKGROUND. The lack of validated imaging markers to characterize biologic aggressiveness of small renal masses (SRMs)-defined as those categorized as cT1a and 4 cm and smaller-hinders medical decision-making among available initial management strategies. OBJECTIVE. The purpose of this article was to explore the association of the clear cell likelihood score (ccLS) on MRI with growth rates and progression of SRMs. METHODS. This retrospective study included consecutive SRMs assigned a ccLS on clinical MRI examinations performed between June 2016 and November 2019 at an academic tertiary-care medical center or its affiliated safety net hospital system. The ccLS reports the likelihood that the SRM represents clear cell renal cell carcinoma (ccRCC) from 1 (very unlikely) to 5 (very likely). The ccLS was extracted from clinical reports. Tumor size measurements were extracted from available prior and follow-up cross-sectional imaging examinations, through June 2020. Serial tumor size measurements were fit to linear and exponential growth curves. Estimated growth rates were grouped by the assigned ccLS. Tumor progression was defined by development of large size (> 4 cm in at least two consecutive measurements) and/or rapid growth (doubling of volume within 1 year). Differences among ccLS groups were evaluated using Kruskal-Wallis tests. Correlations between ccLS and growth rate were evaluated by Spearman correlation (ρ). RESULTS. Growth rates of 386 SRMs (100 ccLS 1-2, 75 ccLS 3, and 211 ccLS 4-5) from 339 patients (median age, 65 years; 198 men, 141 women) were analyzed. Median follow-up was 1.2 years. The ccLS was correlated with growth rates by size (ρ = 0.19; p < .001; ccLS 4-5, 9%/year; ccLS 1-2, 5%/year; p < .001) and by volume (ρ = 0.14; p = .006; ccLS 4-5, 29%/year; ccLS 1-2, 16%/year; p < .001). Disease progression (observed in 49 SRMs) was not significantly associated with ccLS group (p = .61). Two patients (0.6%) developed metastases during active surveillance: one ccLS 1 was a type 2 papillary renal cell carcinoma and one ccLS 4 was ccRCC. CONCLUSION. Growth is associated with ccLS in SRMs, with higher ccLS correlating with faster growth. CLINICAL IMPACT. SRMs with lower ccLS may be considered for active surveillance, whereas SRMs with higher ccLS may warrant earlier intervention. The noninvasive ccLS derived from MRI correlates with growth rate of SRMs and may help guide personalized management.

Unenhanced MRI for Surveillance of Small Solid Renal Masses: Additional Evidence Is Needed

Unenhanced MRI for Surveillance of Small Solid Renal Masses: Additional Evidence Is Needed

The added value of contrast-enhanced ultrasound in evaluation of indeterminate small solid renal masses and risk stratification of cystic renal lesions.

To investigate accuracy of contrast-enhanced ultrasound (CEUS) to characterize indeterminate small solid renal masses (sSRMs), excluding lipid-rich AMLs, and cystic renal masses (CRMs) according to the proposed Bosniak Classification 2019 MATERIALS AND METHODS: CEUS of pathology-proven CRMs and sSRMs (without definite enhancement or macroscopic fat on CT/MRI), and CRMs with ≥18 months follow-up were retrospectively reviewed. Two radiologists blindly categorized CRMs according to new Bosniak Classification on CT/MRI. On CEUS, two other radiologists evaluated arterial-phase enhancement of sSRMs relative to renal cortex and categorized CRMs following new Bosniak Classification. Fisher's exact/chi-squared test was used to compare categorical variables, and Cohen κ statistics for inter-observer agreement RESULTS: A total of 237 patients had 241 lesions: 161 pathology-proven sSRMs (122 malignant and 39 benign), 29 pathology-proven CRMs, 51 CRMs with adequate follow-up. Arterial-phase enhancement < renal cortex predicted malignancy with specificity of 97.4% (38/39) (CI 85.6-99.9%), and positive predictive value (PPV) of 98.2% (54/55) (CI 90.4-99.9%). Inter-observer kappa was 0.95. In pathology-proven CRMS, sensitivity of CEUS vs CT/MRI was 100% (15/15) (CI 79.6-100%) vs 60% (9/15) (CI 35.8-80.1%) (p value = .002) and negative predictive value (NPV) 100% (2/2) (CI 17.8-100%) vs 25% (2/8 ) (CI 4.4-59.1%) (p value < 0.0001), with similar specificity (50%) and PPV- 88.2% (15/17) (CI 65.7-97.9%) vs 81.8% (9/11) (CI 52.3-96.8%) ( p value = 0.586). Bosniak Classification inter-observer kappa was 0.92 for CEUS vs 0.68 for CT/MRI (p value = 0.009). In our cohort, CEUS had high specificity and PPV to diagnose RCC in sSRMs excluding lipid-rich AML. CEUS had significantly higher sensitivity/NPV to diagnose malignancy in CRMs as compared to CT/MRI. • Once lipid-rich AML is excluded by the other modalities, sSRM arterial phase hypo-enhancement relative to renal cortex on CEUS yielded high specificity (97.4%) and PPV (98.2%) to diagnose RCC. • When applying the proposed Bosniak Classification 2019, CEUS showed higher sensitivity compared to CT/MRI (100% vs 60%), p value=.0024, in the stratification of cystic renal masses to diagnose malignancy. • CEUS may reduce the number of CT/MRI Bosniak IIF lesions by assigning them to either II or III/IV categories.

Differentiation of Small (≤ 4 cm) Renal Masses on Multiphase Contrast-Enhanced CT by Deep Learning.

OBJECTIVE. This study evaluated the utility of a deep learning method for determining whether a small (≤ 4 cm) solid renal mass was benign or malignant on multiphase contrast-enhanced CT. MATERIALS AND METHODS. This retrospective study included 1807 image sets from 168 pathologically diagnosed small (≤ 4 cm) solid renal masses with four CT phases (unenhanced, corticomedullary, nephrogenic, and excretory) in 159 patients between 2012 and 2016. Masses were classified as malignant (n = 136) or benign (n = 32). The dataset was randomly divided into five subsets: four were used for augmentation and supervised training (48,832 images), and one was used for testing (281 images). The Inception-v3 architecture convolutional neural network (CNN) model was used. The AUC for malignancy and accuracy at optimal cutoff values of output data were evaluated in six different CNN models. Multivariate logistic regression analysis was also performed. RESULTS. Malignant and benign lesions showed no significant difference of size. The AUC value of corticomedullary phase was higher than that of other phases (corticomedullary vs excretory, p = 0.022). The highest accuracy (88%) was achieved in corticomedullary phase images. Multivariate analysis revealed that the CNN model of corticomedullary phase was a significant predictor for malignancy compared with other CNN models, age, sex, and lesion size. CONCLUSION. A deep learning method with a CNN allowed acceptable differentiation of small (≤ 4 cm) solid renal masses in dynamic CT images, especially in the corticomedullary image model.

Can we Avoid the Unnecessary Loss of nephrons in the Management of Small Solid Renal Masses? Additional Clinical Parameters to Predict Benign-malign Distinction.

Objectives:We aimed to investigate the predictive value of additional parameters for distinguishing benign-malign tumors and to prevent the loss of nephrons in small (≤4 cm) solid renal masses.Methods:The data of 56 patients underwent partial or radical nephrectomy between September 2009 and December 2017 due to diagnosis of localized renal cell carcinoma were retrospectively analyzed. Demographic datas, histopathological tumor types, neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), platelet/lymphocyte ratio (PLR), red blood cell distribution width (RDW), mean platelet volume (MPV), the Framingham risk score and its components, postoperative follow-up results were recorded. Patients were divided into two groups as benign and malign.Results:Among 56 patients with a median age of 60 (min: 35-max: 74) years, 13 patients had benign and 43 patients had malign pathologies. MLR (p=0.011), NLR (p=0.032), PLR (p=0.006), MPV (p=0.025), eGFR (p=0.019) and the Framingham score (p=0.008) were significantly higher in malign group. Among the components constituting the Framingham score, only presence of smoking (p=0.032), presence of hypertension (p=0.041) and total cholesterol values (p=0.021) were significantly higher. In multivariate analysis, NLR>2.02 (OR: 7.184, p=0.037), PLR>109.65 (OR: 12.692, p=0.002), MPV>3.44 (OR: 10.543, p=0.046) and Framingham score >10.5 (OR: 12.287, p=0.007) were found as predictive factors for distinguishing small solid renal masses concerning malignancy.Conclusion:We think that NLR, PLR, MPV and the Framingham scores may be used in the clinical evaluation of small solid renal masses. In this way, we may prevent the unnecessary loss of nephrons in benign masses with suspicion of malignancy.

Subtype Differentiation of Small (≤ 4 cm) Solid Renal Mass Using Volumetric Histogram Analysis of DWI at 3-T MRI.

The purpose of this article is to evaluate the utility of volumetric histogram analysis of apparent diffusion coefficient (ADC) derived from reduced-FOV DWI for small (≤ 4 cm) solid renal mass subtypes at 3-T MRI. This retrospective study included 38 clear cell renal cell carcinomas (RCCs), 16 papillary RCCs, 18 chromophobe RCCs, 13 minimal fat angiomyolipomas (AMLs), and seven oncocytomas evaluated with preoperative MRI. Volumetric ADC maps were generated using all slices of the reduced-FOV DW images to obtain histogram parameters, including mean, median, 10th percentile, 25th percentile, 75th percentile, 90th percentile, and SD ADC values, as well as skewness, kurtosis, and entropy. Comparisons of these parameters were made by one-way ANOVA, t test, and ROC curves analysis. ADC histogram parameters differentiated eight of 10 pairs of renal tumors. Three subtype pairs (clear cell RCC vs papillary RCC, clear cell RCC vs chromophobe RCC, and clear cell RCC vs minimal fat AML) were differentiated by mean ADC. However, five other subtype pairs (clear cell RCC vs oncocytoma, papillary RCC vs minimal fat AML, papillary RCC vs oncocytoma, chromophobe RCC vs minimal fat AML, and chromophobe RCC vs oncocytoma) were differentiated by histogram distribution parameters exclusively (all p < 0.05). Mean ADC, median ADC, 75th and 90th percentile ADC, SD ADC, and entropy of malignant tumors were significantly higher than those of benign tumors (all p < 0.05). Combination of mean ADC with histogram parameters yielded the highest AUC (0.851; sensitivity, 80.0%; specificity, 86.1%). Quantitative volumetric ADC histogram analysis may help differentiate various subtypes of small solid renal tumors, including benign and malignant lesions.

CT and MRI of small renal masses.

Small renal masses are increasingly detected incidentally at imaging. They vary widely in histology and aggressiveness, and include benign renal tumors and renal cell carcinomas that can be either indolent or aggressive. Imaging plays a key role in the characterization of these small renal masses. While a confident diagnosis can be made in many cases, some renal masses are indeterminate at imaging and can present as diagnostic dilemmas for both the radiologists and the referring clinicians. This article will summarize the current evidence of imaging features that correlate with the biology of small solid renal masses, and discuss key approaches in imaging characterization of these masses using CT and MRI.

Characterization of small (

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.

Solid Small Renal Mass Without Gross Fat: CT Criteria for Achieving Excellent Positive Predictive Value for Renal Cell Carcinoma.

The purpose of this study was to evaluate CT criteria for achieving high positive predictive value (PPV) for renal cell carcinoma (RCC) in patients with solid small renal masses (SRMs) less than 4 cm without macroscopic fat. One hundred fifty consecutive patients with a solid SRM without macroscopic fat (mean size ± SD, 2.5 ± 0.8 cm) who underwent CT including unenhanced, corticomedullary (CMP), and nephrographic phases (NP) were evaluated. Pathologically proven solid SRMs without macroscopic fat were classified into RCC (n = 131) and not RCC (n = 19). A "persistent low" sign was defined as a focal area or areas of low attenuation seen at the same location within the lesion on both CMP and NP imaging. Calcification, shape, and lesion attenuation on unenhanced CT were analyzed by two independent readers. PPV of CT criteria (calcification [criterion 1] or spherical shape, lower or equal attenuation, and persistent low sign [criterion 2]) for RCC was 98.3% (58/59) for reader 1 and 100% (53/53) for reader 2. Weighted kappa of interreader agreement was 1.000 for calcification, 0.966 of lower or equal attenuation, 0.834 for spherical shape, 0.823 for persistent low sign, and 0.829 for CT criteria. Interpretation of CT allowed reproducible and excellent PPV for RCC. Current CT criteria may effectively shorten the management process for solid SRMs without macroscopic fat by reducing unnecessary biopsy for a substantial number of RCCs showing typical CT findings.

Percutaneous image-guided biopsies of small renal tumors: Current practice and perspectives.

Percutaneous image-guided biopsies help better select patients with renal tumors smaller than 4cm. These biopsies are performed to reduce the risks of overtreatment and to discriminate between patients who need ablation therapy and those who require active surveillance. Percutaneous image-guided biopsies are effective for a definitive diagnosis with little risk of complications when cautions are observed. With the current addition of multiparametric imaging, standardized biopsy protocols may further help adapt therapeutic decisions. The aim of this review is to report the current indications and techniques of biopsy performed in case of small solid renal masses and to clarify the optimal conditions for the realization of these biopsies.

CA9 as a biomarker in preoperative biopsy of small solid renal masses for diagnosis of clear cell renal cell carcinoma

Purpose: The purpose of our study was to test the utility of CA9 expression in preoperative biopsy samples to identify the ccRCC.Materials and methods: A total of 55 patients with a small solid renal mass (≤4 cm) entered into this study. The immunohistochemical staining (51 samples) and RT-PCR (33 samples) were performed to detect CA9 expression.Results: For immunohistochemistry detection, CA9 was positive in 31/34 of biopsy samples of ccRCCs. CA9 was also positive in five suspected diagnosis of ccRCC. For RT-PCR detection, CA9 was positive in 25/25 biopsy samples of ccRCCs. The diagnostic accuracy of CA9 expression for ccRCC was 100%. RT-PCR was performed in four biopsies where immunohistochemistry could not be performed because of limited tissue materials or necrosis. Two ccRCCs with a negative staining by immunohistochemistry were CA9 positive by RT-PCR.Conclusions: CA9 may be potentially useful biomarker in help making a diagnosis of ccRCC in the biopsy of renal mass. RT-PCR might be a preferred method to immunohistochemistry for the detection of CA9 in renal biopsy samples.