Malignant Renal Masses Research Articles

Multiarm, non-randomised, single-centre feasibility study—investigation of the differential biology between benign and malignant renal masses using advanced magnetic resonance imaging techniques (IBM-Renal): protocol

IntroductionLocalised renal masses are an increasing burden on healthcare due to the rising number of cases. However, conventional imaging cannot reliably distinguish between benign and malignant renal masses, and renal...

MRI quantitative T1 and T2 mapping of the renal cortex: Assessment of normal values and potential usefulness for renal masses at 3 T

PurposeThe purpose of this monocentric retrospective study consisted in exploring the potential improvement of the assessment of renal masses on MRI by using the T1 (T1m) and T2 (T2m) mapping relaxation times. Materials and MethodsWe recorded the renal cortex values of 125 patients with normal kidneys (reference group) and 75 patients with renal masses on a clinical 3 T MR unit using T1m and T2m sequences.For the quantitative evaluation, measurements were performed by delineating ROIs on T1m and T2m sequences in renal cortex of the reference group and in renal masses.Interobserver agreement for the qualitative analysis of image quality was assessed using quadratic Cohen’s weighted kappa statistics (k).Student’s paired t-test and non-parametric Kruskal-Wallis test were used to compare our datasets in terms of T1m and T2m values. ResultsFor the cohort of reference group, mean renal cortex T1m and T2m values were 1,529 ± 83 ms and 98 ± 7 ms, respectively. No statistically significant differences were found for T1m and T2m in the reference group regardless of age, gender or eGRF categories.For the group with renal masses, mean T1m and T2m values were 1,667 ± 87 ms and 105 ± 8 ms; 1,621 ± 96 ms and 117 ± 6 ms, and 1,530 ± 62 ms and 85 ± 4 ms for renal cell carcinomas, angiomyolipomas, and oncocytomas, respectively. For T1m values, there was no significant difference (p = 0.37) among the three types of renal masses. Among histological subtypes we have found: RCC versus angiomyolipoma (p = 0.25), RCC versus oncocytoma (p = 0.15), and oncocytoma versus angiomyolipoma (p = 0.47).However, we have found a statistically significant difference for the T2m value (p = 0.0005). Among histological subtypes, only T2m values were statistically significant for each combination: RCC versus angiomyolipoma (p = 0.012), RCC versus oncocytoma (p = 0.0002), and oncocytoma versus angiomyolipoma (p = 0.003). ConclusionAs this is the largest normal patient cohort, the T1m and T2m values recorded could be proposed as reference values and can play a role in the differential diagnosis between benign and malignant renal tumoral masses.

Value of elastography in characterization of solid renal masses

BackgroundSolid renal masses often come to light as incidental findings during abdominal ultrasound examinations. Once detected, determining whether a renal mass is benign or malignant becomes imperative for informed decision-making regarding management and treatment strategies. In this investigation, the aim was to explore the diagnostic efficacy of real-time strain sonoelastography in assessing solid renal masses.MethodsThis prospective research was steered on 26 individuals diagnosed with a solid renal mass, as endorsed by pathological analysis after surgical removal or biopsy. Elastography was performed on all patients. The measurement of strain index values for tissues was achieved by placing regions of interest of equal or near-equal size on both the tumor (A) and the adjacent normal renal cortex (B).ResultsStrain elastography showed no correlation with patient’s age, size of mass and probe to mass distance with p > 0.05 all. Sensitivity analysis showed that strain index can significantly predict malignant renal masses (P = 0.003) using a cut-off point 2, with 92.9% area under curve, 95.2% sensitivity, 80% specificity, 80% negative predictive value, 95.2% positive predictive value, and overall diagnostic accuracy 92.3%. Strain index > 2 was an independent predictor for malignant renal masses (P = 0.025), odds ratio 7.29 when adjusting for other risk factors. Malignant renal masses were significantly higher strain index compared to benign lesions with (P = 0.001).ConclusionsStrain elastography is a valuable technique for distinguishing between malignant and benign solid renal tumors. Benign lesions have lower strain index values compared to malignant ones, making the strain index a useful screening tool for distinguishing between benign and malignant renal masses using cut-off point 2.

Preoperative proteinuria correlates with renal function after partial nephrectomy for renal cell carcinoma

PurposePreoperative proteinuria is a prognostic factor of chronic kidney disease (CKD). We assessed the association between preoperative proteinuria and postoperative renal function after partial nephrectomy (PN).MethodsWe retrospectively reviewed our records of patients with a single malignant renal mass who underwent PN between 2000 and 2021. Patients with data on preoperative proteinuria were included. Baseline characteristics and eGFR differences over time between patients with and without proteinuria were evaluated. Univariate and multivariable logistic regression models (LRM) tested for presence of CKDIII or higher at 12-month and at last follow-up.ResultsTwo hundred ninety-five patients were included. Twenty-two of them had preoperative proteinuria. No differences of age, smoking status, hypertension or diabetes, tumor size and use of ischemia were observed. Patients with proteinuria had a higher rate of CKD-III at baseline. At a median follow-up of 46.5 months (IQR 19–82), 117 patients developed de novo CKD-III, without differences in the two groups. No differences in decline in eGFR were observed. At univariate LRM, predictors of CKD-III at 12 months after PN were preoperative proteinuria (OR 3.2, 95%CI 1.4–7.8, p = 0.005), age and baseline eGFR, while predictors of CKD-III at last follow-up were age and baseline eGFR. At multivariable LRM, only baseline eGFR predicted CKD-III at 12-month and at last-follow-up.ConclusionsPreoperative eGFR is the only independent predictor of long-term renal function after PN. Preoperative proteinuria correlates with renal function at 12 months. Proteinuria should be assessed before PN to identify patients at higher risk of renal functional deterioration in the 12 months following PN.

Contrast-enhanced ultrasound (CEUS): applications from the kidneys to the bladder.

Contrast-enhanced ultrasound (CEUS) is an advanced ultrasound (US) technique utilizing ultrasound contrast agents (UCAs) to provide detailed visualization of anatomic and vascular architecture, including the depiction of microcirculation. CEUS has been well-established in echocardiography and imaging of focal hepatic lesions and recent studies have also shown the utility of CEUS in non-hepatic applications like the urinary system. The updated guidelines by the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) from 2018 describe the use of CEUS for non-hepatic applications. CEUS' excellent safety profile and spatial resolution make it a superior modality to conventional US and is often comparable and even superior to CECT in some instances. In comparison to other cross-sectional imaging modalities such as CECT or MRI, CEUS offers a safe (by virtue of non-nephrotoxic US contrast agents), accurate, cost-efficient, readily available, and a quick means of evaluation of multiple pathologies of the urinary system. CEUS also has the potential to reduce the overall economic burden on patients requiring long-term follow-up due to its low cost as compared to CT or MRI techniques. This comprehensive review focuses on the applications of CEUS in evaluating the urinary system from the kidneys to the urinary bladder. CEUS can be utilized in the kidney to evaluate complex cystic lesions, indeterminate lesions, pseudotumors (vs solid renal tumors), renal infections, and renal ischemic disorders. Additionally, CEUS has also been utilized in evaluating renal transplants. In the urinary bladder, CEUS is extremely useful in differentiating a bladder hematoma and bladder cancer when conventional US techniques show equivocal results. Quantitative parameters of time-intensity curves (TICs) of CEUS examinations have also been studied to stage and grade bladder cancers. Although promising, further research is needed to definitively stage bladder cancers and classify them as muscle-invasive or non-muscle invasive using quantitative CEUS to guide appropriate intervention. CEUS has been very effective in the classification of cystic renal lesions, however, further research is needed in differentiating benign from malignant renal masses.

Update on Renal Cell Carcinoma Diagnosis with Novel Imaging Approaches.

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

Evaluation of image-pro plus assisted superb microvascular imaging for differential diagnosis of renal masses

ObjectivePrevious research on diagnostic assessment by superb microvascular imaging (SMI) were based on qualitative or semi-quantitative assessments of vascularity, which may be subjective and unrepeatable by different sonographers. This study aimed to evaluate diagnostic performance of SMI Image-pro Plus (IPP) based vascular index (VI) for malignant renal masses. MethodWe retrospectively reviewed 222 masses in 214 patients who underwent SMI between August 2019 and August 2022 in our study. We evaluated the diagnostic performance of blood flow via Alder grade, VI based on both IPP and SMI. ResultsThe kappa consistency of the Adler grade and VI for renal masses was classified among different observers were 0.765 and 0.824. The intra-observers correlation ecoefficiency (ICC) were 0.727 and 0.874. Benign renal masses were mainly Adler grade 0, grade I, and grade II, VI was 4.30 ± 4.27 (Range 0.98–16.42); while malignant masses were mainly Adler grade III, VI was 14.95 ± 10.94 (Range 0.79–56.89). VI was higher in malignant than benign masses (t = 15.638, P < 0.01). Among the malignant masses, the mean VI in clear cell renal cell carcinoma was higher than that in papillary renal cell carcinoma and chromophobe renal cell carcinoma (F = 30.659, P < 0.01). The sensitivity, specificity and accuracy of SMI were 80.00%, 71.15%, and 78.64%, respectively. The sensitivity, specificity, and accuracy were 60.59%, 88.46%, and 80.18% by using a VI of 7.95 as the cutoff value to identify malignant lesions from benign masses yielded. VI had better diagnostic efficiency than ultrasonic characteristics and Adler grade in benign and malignant differential diagnosis (Z = 4.851, P < 0.01; Z = 2.732, P < 0.01). ConclusionVI was higher in malignant than benign in renal masses. In malignant masses, VI in CCRCC was higher than that in papillary renal cell carcinoma and ChRCC. As a noninvasive examination, it had important clinical significance in the differential diagnosis of renal masses. VI from IPP may assist sonographer in distinguish renal malignances as a quantitative tool for vascularity.

Comparing Sonazoid contrast-enhanced ultrasound to contrast-enhanced CT and MRI for differentially diagnosing renal lesions: a prospective multicenter study.

To evaluate the diagnostic performance of contrast-enhanced (CE) ultrasound using Sonazoid (SNZ-CEUS) by comparing with contrast-enhanced computed tomography (CE-CT) and contrast-enhanced magnetic resonance imaging (CE-MRI) for differentiating benign and malignant renal masses. 306 consecutive patients (from 7 centers) with renal masses (40 benign tumors, 266 malignant tumors) diagnosed by both SNZ-CEUS, CE-CT or CE-MRI were enrolled between September 2020 and February 2021. The examinations were performed within 7days, but the sequence was not fixed. Histologic results were available for 301 of 306 (98.37%) lesions and 5 lesions were considered benign after at least 2year follow-up without change in size and image characteristics. The diagnostic performances were evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and compared by McNemar's test. In the head-to-head comparison, SNZ-CEUS and CE-MRI had comparable sensitivity (95.60 vs. 94.51%, P = 0.997), specificity (65.22 vs. 73.91%, P = 0.752), positive predictive value (91.58 vs. 93.48%) and negative predictive value (78.95 vs. 77.27%); SNZ-CEUS and CE-CT showed similar sensitivity (97.31 vs. 96.24%, P = 0.724); however, SNZ-CEUS had relatively lower than specificity than CE-CT (59.09 vs. 68.18%, P = 0.683). For nodules > 4cm, CE-MRI demonstrated higher specificity than SNZ-CEUS (90.91 vs. 72.73%, P = 0.617) without compromise the sensitivity. SNZ-CEUS, CE-CT, and CE-MRI demonstrate desirable and comparable sensitivity for the differentiation of renal mass. However, the specificity of all three imaging modalities is not satisfactory. SNZ-CEUS may be a suitable alternative modality for patients with renal dysfunction and those allergic to gadolinium or iodine-based agents.

Differentiating Benign from Malignant Cystic Renal Masses using CT Texture-based Machine Learning Algorithms.

Differentiating Benign from Malignant Cystic Renal Masses using CT Texture-based Machine Learning Algorithms.

Use of Droplet Digital Polymerase Chain Reaction to Identify Biomarkers for Differentiation of Benign and Malignant Renal Masses.

Several microRNAs (miRNAs) have been identified as cell-free biomarkers for detecting renal cell carcinoma (RCC). Droplet digital polymerase chain reaction (ddPCR) is a unique technology for nucleic acid quantification. It has the potential for superior precision, reproducibility, and diagnostic performance in identifying circulating miRNA biomarkers compared to conventional quantitative real-time PCR (qRT-PCR). This study aims to evaluate the performance of ddPCR compared to qRT- PCR in identifying miRNA biomarkers that differentiate malignant from benign renal masses. Potential biomarkers of RCC were identified from a literature review. RNA was extracted from the plasma of 56 patients. All the samples underwent analysis via ddPCR as well as qRT-PCR, and expression levels were recorded for the following miRNAs: miR-93, -144, -210, -221, and -222. Tumors were grouped into low-grade ccRCC, high-grade ccRCC, papillary RCC, and benign masses (primarily angiomyolipoma). The miRNA miR-210 (p = 0.034) and the combination of miRs-210 and miR-222 (p = 0.003) were expressed at significantly higher rates among those with RCC than those with benign masses, as measured by ddPCR. Using the combination of miR-210 and miR-222, ddPCR identified significant differences between the subgroups: papillary RCC versus benign (p = 0.03), low-grade ccRCC versus benign (p = 0.026), and high-grade ccRCC versus benign (p = 0.002). The only significant difference between these subgroups using qRT-PCR was between high-grade ccRCC and benign (p = 0.045). All the AUCs were significant when comparing each RCC subgroup with benign for both PCR technologies. Using a combination of miR-210 and miR-222, ddPCR identified significant differences between benign and malignant renal masses that were not identified as significant by conventional qRT-PCR.

Nanobody-loaded nanobubbles targeting the G250 antigen with ultrasound/photoacoustic/fluorescence multimodal imaging capabilities for specifically enhanced imaging of RCC.

Clinicians have attempted to discover a noninvasive, easy-to-perform, and accurate method to distinguish benign and malignant renal masses. The targeted nanobubbles (NBs) we constructed that target the specific membrane antigen of renal cell carcinoma (RCC), G250, and contain indocyanine green (ICG) provide multimodal enhanced imaging capability in ultrasound/photoacoustic/fluorescence for RCC which may possibly solve this problem. In this study, we encapsulated ICG in the lipid shell of the NBs by mechanical oscillation, then anti-G250 nanobodies (AGN) were coupled to the surfaces by the biotin-streptavidin bridge method, and the nanobubble named AGN/ICG-NB was completely constructed. The average particle diameter of the prepared AGN/ICG-NBs was (427.2 ± 4.50) nm, and the zeta potential was (-13.33 ± 1.01) mV. Immunofluorescence and flow cytometry confirmed the specific binding capability of AGN/ICG-NBs to G250-positive cells. In vitro imaging experiments confirmed the multimodal imaging capability of AGN/ICG-NBs, and the in vivo imaging experiments demonstrated the specifically enhanced ability of AGN/ICG-NBs for ultrasound/photoacoustic/fluorescence imaging of human-derived RCC tumors. The biosafety of AGN/ICG-NB was verified by CCK-8 assay, organ H&E staining and blood biochemical indices. In conclusion, the targeted nanobubbles we prepared with ultrasound/photoacoustic/fluorescence multimodal imaging capabilities provide a potentially feasible approach to address the need for early diagnosis and differential diagnosis of renal masses.

Enhanced and unenhanced: Radiomics models for discriminating between benign and malignant cystic renal masses on CT images: A multi-center study.

Machine learning algorithms used to classify cystic renal masses (CRMs) nave not been applied to unenhanced CT images, and their diagnostic accuracy had not been compared against radiologists. This retrospective study aimed to develop radiomics models that discriminate between benign and malignant CRMs in a triple phase computed tomography (CT) protocol and compare the diagnostic accuracy of the radiomics approach with experienced radiologists. Predictive models were established using a training set and validation set of unenhanced and enhanced (arterial phase [AP] and venous phase [VP]) CT images of benign and malignant CRMs. The diagnostic capabilities of the models and experienced radiologists were compared using Receiver Operating Characteristic (ROC) curves. On unenhanced, AP and VP CT images in the validation set, the AUC, specificity, sensitivity and accuracy for discriminating between benign and malignant CRMs were 90.0 (95%CI: 81-98%), 90.0%, 90.5% and 90.2%; 93.0% (95%CI: 86-99%), 86.7%, 95.2% and 88.3%; and 95.0% (95%CI: 90%-100%), 93.3%, 90.5% and 92.1%, respectively, for the radiomics models. Diagnostic accuracy of the radiomics models differed significantly on unenhanced images in the training set vs. each radiologist (p = 0.001 and 0.003) but not in the validation set (p = 0.230 and 0.590); differed significantly on AP images in the validation set vs. each radiologist (p = 0.007 and 0.007) but not in the training set (p = 0.663 and 0.663); and there were no differences on VP images in the training or validation sets vs. each radiologist (training set: p = 0.453 and 0.051, validation set: p = 0.236 and 0.786). Radiomics models may have clinical utility for discriminating between benign and malignant CRMs on unenhanced and enhanced CT images. The performance of the radiomics model on unenhanced CT images was similar to experienced radiologists, implying it has potential as a screening and diagnostic tool for CRMs.

Diagnostic liquid biopsy biomarkers in renal cell cancer.

The clinical presentation of renal cell cancer (RCC) is shifting towards incidental and early detection, creating new challenges in RCC diagnosis. Overtreatment might be reduced with the development of new diagnostic biomarkers to distinguish benign from malignant small renal masses (SRMs). Differently from tissue biopsies, liquid biopsies are obtained from a patient's blood or urine and, therefore, are minimally invasive and suitable for longitudinal monitoring. The most promising types of liquid biopsy biomarkers for RCC diagnosis are circulating tumour cells, extracellular vesicles (EVs) and cell-free DNA. Circulating tumour cell assays have the highest specificity, with low processing time and costs. However, the biological characteristics and low sensitivity limit the use of these markers in SRM diagnostics. Cell-free DNA might complement the diagnosis of high-volume RCC, but the potential for clinical application in SRMs is limited. EVs have the highest biological abundance and the highest sensitivity in identifying low-volume disease; moreover, the molecular characteristics of these markers make EVs suitable for multiple analytical applications. Thus, currently, EV assays have the greatest potential for diagnostic application in RCC (including identification of SRMs). All these liquid biomarkers have potential in clinical practice, pending validation studies. Biomarker implementation will be needed to alsoimprove characterization of RCC subtypes. Last, diagnostic biomarkers might be extended to prognostic or predictive applications.

Small Renal Masses: Developing a Robust Radiomic Signature.

(1) Background and (2) Methods: In this retrospective, observational, monocentric study, we selected a cohort of eighty-five patients (age range 38-87 years old, 51 men), enrolled between January 2014 and December 2020, with a newly diagnosed renal mass smaller than 4 cm (SRM) that later underwent nephrectomy surgery (partial or total) or tumorectomy with an associated histopatological study of the lesion. The radiomic features (RFs) of eighty-five SRMs were extracted from abdominal CTs bought in the portal venous phase using three different CT scanners. Lesions were manually segmented by an abdominal radiologist. Image analysis was performed with the Pyradiomic library of 3D-Slicer. A total of 108 RFs were included for each volume. A machine learning model based on radiomic features was developed to distinguish between benign and malignant small renal masses. The pipeline included redundant RFs elimination, RFs standardization, dataset balancing, exclusion of non-reproducible RFs, feature selection (FS), model training, model tuning and validation of unseen data. (3) Results: The study population was composed of fifty-one RCCs and thirty-four benign lesions (twenty-five oncocytomas, seven lipid-poor angiomyolipomas and two renal leiomyomas). The final radiomic signature included 10 RFs. The average performance of the model on unseen data was 0.79 ± 0.12 for ROC-AUC, 0.73 ± 0.12 for accuracy, 0.78 ± 0.19 for sensitivity and 0.63 ± 0.15 for specificity. (4) Conclusions: Using a robust pipeline, we found that the developed RFs signature is capable of distinguishing RCCs from benign renal tumors.

Computed Tomographic Evaluation of Renal Mass with Histopathological Correlation

Renal cell carcinoma (RCC) is the seventh most common cancer and the most common primary renal malignant neoplasm in adults. Computed Tomography (CT) is of a great value in differentiating malignant from benign masses of RCC. This cross-sectional study was conducted among 61 clinically suspected cases of renal mass at Sir Salimullah Medical College and Mitford Hospital (SSMC and Mitford Hospital) in the Department of Radiology and Imaging in collaboration with the Department of Urology and Pathology, from July ’2011 to June’ 2013. However, in 05 cases, histopathological reports were not available and 07 patients refused surgery after enrolling. Finally, histopathology reports were collected from 49 patients and they were considered as study subjects. Aim of the study was to evaluate the accuracy of CT scan findings in compere with the histopathological report for the diagnosis of renal mass and to differentiate its benign and malignant forms. The age range of the patients was 2 to 73 years, where more than two-third (69.38%) were male and rest of them were female. Maximum number of malignant cases observed in the age range of 50-59 years. In comparison, inflammatory and benign conditions dominate in early age group, mostly before 40 years. Among 49 cases, 41 (83.68%) cases were diagnosed as malignant renal mass by CT scan, 01 (2.04) case was missed, which was confirmed by histopathology. Rest 07 (14.28%) patients were diagnosed as benign both in CT scan and histopathology. The sensitivity of CT for malignant renal mass was found 97.62% and specificity was 100%. The positive and negative predictive values of CT were 87.5% and 97.59% respectively. Computed tomography is a valid diagnostic modality for differentiating benign and malignant renal mass. Bangladesh Med J. 2021 Sept; 51(1): 41-46

Chromophobe: A rare histological variant of renal cell carcinoma

Background: Renal cell carcinoma (RCC) is an adenocarcima of the kidney. It is a highly heterogeneous disease with sixteen known subtypes out of which five predominate. The most common subtype is clear cell RCC which accounts for 75-85%. The chromophobe subtype of RCC is rarely seen. It is reported to constitute 4-5% of RCC subtype. This study was aimed at reporting the first case of chromophobe renal cell carcinoma in our community a rare histological subtype of RCC which was discovered incidentally. Our objective was to describe the clinical, histological and immunohistochemical evaluation of a case of chromophobe RCC.&#x0D; Case report: We present a 60-year-old man who was seen at the surgical outpatient department of our center with a request for general health check-up. He had basic laboratory and imaging investigations. These were essentially normal except for an incidental finding of a left renal mass on abdominopelvic sonogram. Computed tomography urography showed a suspected clinically localized malignant left renal mass. Histological and immunohistochemistry are consistent with a chromophobe RCC. His clinic follow-up remains unremarkable.&#x0D; Conclusion: We reported the clinical, histological and immunohistochemical evaluation of a rare case of chromophobe RCC. This was discovered incidentally following general health check. He had open radical nephrectomy and clinic follow-up 1 year after discharge has been uneventful.

Homolateral and synchronic clear cell and papillary type of renal cell carcinoma Diagnostic hints and review of literature

Commonest solid mass of kidney is renal cell carcinoma, constituting 2-3% of all adult cancers. Synchronous malignant and benign renal tumours bilaterally have been described in a few studies. However, homolateral and synchronic appearance of malignant renal masses is extremely rare and there have been only a few case reports that had different subtypes of malignant renal neoplasms of the same kidney on histopathology. In this report, we present a 66-year-old male patient who had two different histological variants, ie, papillary RCC and clear cell RCC in his right kidney, and underwent radical nephrectomy. Our aim is to provide radiological diagnostic hints and review the literature relevant to this rare case, as the awareness of its occurrence can help in early diagnosis and deciding an appropriate management course.

Cystic Renal Masses: characterization with Diffusion- Weighted Imaging versus ContrastEnhanced Magnetic Resonance Imaging

Purpose To compare the diagnostic performance of magnetic resonance imaging (MRI), and MRI with diffusion-weighted imaging (DWI) in the characterization of cystic renal lesions. Materials and Methods Thirty-six adult patients underwent MRI (at 1.5 T), and DWI (at b-values of 0, 400 and 800 s/mm2) for characterization of 63 cystic renal lesions. There were 16 malignant renal cystic lesions (9 cystic clear cell RCC, 4 cystic papillary RCC, 3 massively necrotic RCC) opposite to 37 benign renal cystic lesions, 6 renal abscesses and 4 renal hemorrhagic cysts. A composite reference standards including histology, typical imaging criteria, and follow-up imaging was employed. To determine the diagnostic performance of imaging modalities, area-under-curve (AUC) was calculated by receiver-operating-characteristic analysis and compared. Fisher's exact test was used to compare the diagnostic accuracies and confidence levels with MRI, and MRI + DWI. Furthermore, DWI-ADC cutoff point to detect malignant cystic renal lesions, had been estimated and its diagnostic performance had been tested in term of sensitivity and specificity, PPD and NPV as compared to that of CE-MRI Results AUC for CE-MRI (0.915) and DW-MRI (0.834) in the differentiation between benign and malignant lesions (among all study cases) were within corresponding 95% confidence interval (CI) (P &amp;gt; 0.5), furthermore A cutoff ADC point of ≤ 2.26 x10 − 3 mm2/s can be considered as diagnostic threshold for malignant cystic renal lesion lesions (among all study cases) with 87.5% sensitivity, 87.2% specificity, 70.0% PPV, 95.3% NPV, opposite to 100% sensitivity, 82.9% specificity, 66.7% PPV, 100% NPV for the CE-MRI. AUC for CE-MRI (0.976) and DW-MRI (0.917) in the differentiation between benign and malignant lesions (after exclusion of renal abscess and renal hemorrhagic cysts from study cases) were within corresponding 95% confidence interval (CI) (P = &amp;gt;0.5), A cutoff ADC point of ≤ 2.84 x10 − 3 mm2/s could be considered as diagnostic threshold for malignant cystic renal lesion lesions (after exclusion of renal abscess and renal hemorrhagic cysts from study cases) with 93.7% sensitivity, 91.9% specificity, 83.3 PPV, 97.1 NPV, opposite to 100% sensitivity, 95.12% specificity, 88.9% PPV, 100% NPV for the CE-MRI. Conclusions Our study showed that malignant cystic renal masses had tendency toward restricted diffusivity and significant lower ADCs in comparison to benign ones, and diagnostic performance of DWI-ADC at b-value of 0-400-800 s/mm2 appeared as efficient as that of CE-MRI in differential between benign and malignant cystic lesions, especially when usage of contrast medium is contraindicated, however there is noticeable ADC overlapping among some malignant and benign lesions, specifically for renal carcinomas versus renal abscesses as well as for renal cell carcinoma versus renal hemorrhagic cysts, For such situation we need to consider clinical data, follow up notes, and correlates with findings of conventional MRI to optimize the characterization of cystic renal lesion before establishment of proper management plan.

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.

Ultrasound Elastography for the Differentiation of Benign and Malignant Solid Renal Masses: A Systematic Review and Meta-Analysis

The incidental finding of small renal masses in CT and MRI examinations can present a diagnostic challenge. Renal cell carcinoma (RCC) and angiomyolipoma (AML) are the most common incidental malignant and benign renal lesions but may present with similar US features. US elastography is a non-invasive technique that can assess tissue elasticity, has shown promising results in many clinical settings, and could be able to differentiate between benign and malignant renal lesions based on tissue stiffness. The purpose of this article is to systematically review the applications of US elastography in the characterization of solid renal masses and to derive and compare the summary estimates of different stiffness values across different lesion subtypes. In December 2022, a systematic search was carried out on the MEDLINE (PubMed) and EMBASE databases to retrieve studies on the application of US elastography in the characterization of solid renal masses. After article selection by three researchers, 14 studies entered qualitative synthesis. A total of 1190 patients were included, and the elastography data of 959 lesions were examined: 317/959 (33%) benign and 642/959 (67%) malignant. Among the malignancies, 590 (91%) were RCC, whereas, among the 317 benign lesions, 244 (77%) were AML. All lesions were classified using a histopathological (biopsy or operative specimen) or imaging (US follow-up/CT/MRI) reference standard. After data extraction and methodological quality evaluation, quantitative synthesis was performed on 12 studies, 4 using strain elastography (SE) and 8 using shear wave elastography (SWE), with single- and double-arm random-effects meta-analyses. Lesion stiffness measured with SE was available in four studies, with an RCC strain ratio higher than the AML strain ratio both in an indirect comparison (Cochran’s Q test p = 0.014) and in a direct comparison (p = 0.021). Conversely, the SWE measurements of RCC and AML stiffness did not significantly differ either at an indirect comparison (p = 0.055) or direct comparison (p = 0.114).