ImmunoPET/CT imaging of clear cell renal cell carcinoma with [18F]RCCB6: a first-in-human study.

PURPOSE: The cluster of differentiation (CD70) is a potential biomarker of clear cell renal cell carcinoma (ccRCC). This study aims to develop CD70-targeted immuno-positron emission tomography/computed tomography (immunoPET/CT) imaging tracers and explore the diagnostic value in preclinical studies and the potential value in detecting metastases in ccRCC patients. METHODS: Four novel CD70-specific single-domain antibodies (sdAbs) were produced and labelled with 18F by the aluminium fluoride restrained complexing agent (AlF-RESCA) method to develop radiotracers. The visualisation properties of the tracers were evaluated in a subcutaneous ccRCC patient-derived xenograft (PDX) model. In a registered prospective clinical trial (NCT06148220), six patients with pathologically confirmed RCC were included and underwent immunoPET/CT examination exploiting one of the developed tracers (i.e., [18F]RCCB6). RESULTS: We engineered four sdAbs (His-tagged RCCB3 and RCCB6, His-tag-free RB3 and RB6) specifically targeting recombinant human CD70 without cross-reactivity to murine CD70. ImmunoPET/CT imaging with [18F]RCCB3 and [18F]RCCB6 demonstrated a high tumour-to-background ratio in a subcutaneous ccRCC PDX model, with the latter showing better diagnostic potential supported by higher tumour uptake and lower bone accumulation. In comparison, [18F]RB6, developed by sequence optimisation, has significantly lower kidney accumulation than that of [18F]RCCB6. In a pilot translational study, [18F]RCCB6 immunoPET/CT displayed ccRCC metastases in multiple patients and demonstrated improved imaging contrast and diagnostic value than 18F-FDG PET/CT in a patient with ccRCC. CONCLUSION: The work successfully developed a series of CD70-targeted immunoPET/CT imaging tracers. Of them, [18F]RCCB6 clearly and specifically identified inoculated ccRCCs in preclinical studies. Clinical translation of [18F]RCCB6 suggests potential for identifying recurrence and/or metastasis in ccRCC patients.

High-frame-rate contrast-enhanced ultrasound to differentiate between clear cell renal cell carcinoma and angiomyolipoma.

BACKGROUND: To investigate the diagnostic efficacy of high-frame-rate contrast-enhanced ultrasound (H-CEUS) in differentiating between clear cell renal cell carcinoma (CCRCC) and angiomyolipoma (AML). METHODS: A retrospective study was performed on the clinical data of 79 patients diagnosed with CCRCC and 31 patients diagnosed with AML at the First Affiliated Hospital of Nanchang University between October 2022 and December 2023. Conventional ultrasound (US) and H-CEUS examinations were conducted on all patients prior to surgery, dynamic images were recorded from the US, and the qualitative and quantitative parameters of H-CEUS were collected. The t-test, χ² test and non-parametric Mann-Whitney test were employed to assess differences in clinical data, US characteristics, and qualitative and quantitative parameters of H-CEUS between the CCRCC and AML groups. The independent risk factors of CCRCC were identified using binary logistic regression. The receiver operator characteristic (ROC) curve was constructed to evaluate the diagnostic effectiveness of clinical + US and H-CEUS in differentiating between CCRCC and AML. RESULTS: The CCRCC group and the AML group exhibited significant differences in patient gender, operation mode, nodular echo, and nodule blood flow (χ²=11.698, -, -,=10.582; P<0.001, <0.001, <0.001, and = 0.014, respectively). In addition, the H-CEUS qualitative analysis demonstrated significant differences between the AML group and the CCRCC group with respect to enhancement mode, regression mode, peak intensity, enhancement uniformity, no enhancement, and presence or absence of pseudocapsule (χ²=41.614, -, -, = 2.758, = 42.099, -; P<0.001, <0.001, <0.001, 0.097, <0.001, and <0.001, respectively). The Arrival time (AT) in the CCRCC group was significantly shorter than that in the AML group, as determined by quantitative analysis of H-CEUS (Z=-3.266, P = 0.001). Furthermore, the Peak intensity (PI), Ascent slope (AS), and The area under the curve (AUC) exhibited significantly higher values in the CCRCC group compared to the AML group (Z=-2.043,=-2.545,=-3.565; P = 0.041, = 0.011, and <0.001, respectively). Logistic regression analysis indicated that only gender, nodule echo, the pseudocapsule, AS, and AUC of H-CEUS were independent risk factors of CCRCC. The ROC curve revealed that combining gender and nodule echo yielded a sensitivity of 92.4%, specificity of 64.5%, and an AUC of 0.847 in distinguishing between CCRCC and AML. When combining the H-CEUS parameters of pseudocapsule, AS, and AUC, the sensitivity, specificity, and AUC for distinguishing between CCRCC and AML were 84.8%, 96.8%, and 0.918, respectively. No statistically significant difference was observed in the diagnostic effectiveness of the two methods (Z=-1.286, P = 0.198). However, H-CEUS demonstrated better AUC and specificity. CONCLUSIONS: H-CEUS enhances the sensitivity and specificity of differentiating between CCRCC and AML by improving the temporal resolution, offering a more precise diagnostic foundation for identifying the most appropriate therapy for patients.

CT features based preoperative predictors of aggressive pathology for clinical T1 solid renal cell carcinoma and the development of nomogram model.

BACKGROUND: We aimed to identify preoperative predictors of aggressive pathology for cT1 solid renal cell carcinoma (RCC) by combining clinical features with qualitative and quantitative CT parameters, and developed a nomogram model. METHODS: We conducted a retrospective study of 776 cT1 solid RCC patients treated with partial nephrectomy (PN) or radical nephrectomy (RN) between 2018 and 2022. All patients underwent four-phase contrast-enhanced CT scans and the CT parameters were obtained by two experienced radiologists using region of interest (ROI). Aggressive pathology was defined as patients with nuclear grade III-IV; upstage to pT3a; type II papillary renal cell carcinoma (pRCC), collecting duct or renal medullary carcinoma, unclassified RCC or sarcomatoid/rhabdoid features. Univariate and multivariate logistic analyses were used to determine significant predictors and develop the nomogram model. To evaluate the accuracy and clinical utility of the nomogram model, we used the receiver operating characteristic (ROC) curve, calibration plot, decision curve analysis (DCA), risk stratification, and subgroup analysis. RESULTS: Of the 776 cT1 solid RCC patients, 250 (32.2%) had aggressive pathological features. The interclass correlation coefficient (ICC) of CT parameters accessed by two reviewers ranged from 0.758 to 0.982. Logistic regression analyses showed that neutrophil-to-lymphocyte ratio (NLR), distance to the collecting system, CT necrosis, tumor margin irregularity, peritumoral neovascularity, and RER-NP were independent predictive factors associated with aggressive pathology. We built the nomogram model using these significant variables, which had an area under the curve (AUC) of 0.854 in the ROC curve. CONCLUSIONS: Our research demonstrated that preoperative four-phase contrast-enhanced CT was critical for predicting aggressive pathology in cT1 solid RCC, and the constructed nomogram was useful in guiding patient treatment and postoperative follow-up.

Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging and Venous Tumor Thrombus Consistency in Renal Cell Carcinoma.

BACKGROUND: Venous tumor thrombus (VTT) consistency of renal cell carcinoma (RCC) is an important consideration in nephrectomy plus thrombectomy. However, evaluation of VTT consistency through preoperative MR imaging is lacking. PURPOSE: To evaluate VTT consistency of RCC through intravoxel incoherent motion-diffusion weighted imaging (IVIM-DWI) derived parameters (Dt , Dp , f, and ADC) and the apparent diffusion coefficient (ADC) value. STUDY TYPE: Retrospective. POPULATION: One hundred and nineteen patients (aged 55.8 ± 11.5 years, 85 male) with histologically-proven RCC and VTT who underwent radical resection. FIELD STRENGTH/SEQUENCES: 3.0-T; two-dimensional single-shot diffusion-weighted echo planar imaging sequence at 9 b-values (0-800 s/mm2 ). ASSESSMENT: IVIM parameters and ADC values of the primary tumor and the VTT were calculated. The VTT consistency (friable vs. solid) was determined through intraoperative findings of two urologists. The accuracy of VTT consistency classification based on the individual IVIM parameters of primary tumors and of VTT, and based on models combining parameters, was assessed. Type of operation, intra-operative blood loss, and operation length were recorded. STATISTICAL TESTS: Shapiro-Wilk test; Mann-Whitney U test; Student's t-test; Chi-square test; Receiver operating characteristic (ROC) analysis. Statistical significance level was P < 0.05. RESULTS: Of the enrolled 119 patients, 33 patients (27.7%) had friable VTT. Patients with friable VTT were significantly more likely to experience open surgery, have significantly more intraoperative blood loss, and significantly longer operative duration. The area under the ROC curve (AUC) values of Dt of the primary tumor and VTT in classifying VTT consistency were 0.758 (95% CI 0.671-0.832) and 0.712 (95% CI 0.622-0.792), respectively. The AUC value of the model combining Dp and Dt of VTT was 0.800 (95% CI 0.717-0.868). Furthermore, the AUC of the model combining Dp and Dt of VTT and Dt of the primary tumor was 0.886 (95% CI 0.814-0.937). CONCLUSION: IVIM-derived parameters had the potential to predict VTT consistency of RCC. EVIDENCE LEVEL: 3 Technical Efficacy: Stage 2.

Non-Invasive Tumor Grade Evaluation in Von Hippel-Lindau-Associated Clear Cell Renal Cell Carcinoma: A Magnetic Resonance Imaging-Based Study.

BACKGROUND: Pathology grading is an essential step for the treatment and evaluation of the prognosis in patients with clear cell renal cell carcinoma (ccRCC). PURPOSE: To investigate the utility of texture analysis in evaluating Fuhrman grades of renal tumors in patients with Von Hippel-Lindau (VHL)-associated ccRCC, aiming to improve non-invasive diagnosis and personalized treatment. STUDY TYPE: Retrospective analysis of a prospectively maintained cohort. POPULATION: One hundred and thirty-six patients, 84 (61%) males and 52 (39%) females with pathology-proven ccRCC with a mean age of 52.8 ± 12.7 from 2010 to 2023. FIELD STRENGTH AND SEQUENCES: 1.5 and 3 T MRIs. Segmentations were performed on the T1-weighted 3-minute delayed sequence and then registered on pre-contrast, T1-weighted arterial and venous sequences. ASSESSMENT: A total of 404 lesions, 345 low-grade tumors, and 59 high-grade tumors were segmented using ITK-SNAP on a T1-weighted 3-minute delayed sequence of MRI. Radiomics features were extracted from pre-contrast, T1-weighted arterial, venous, and delayed post-contrast sequences. Preprocessing techniques were employed to address class imbalances. Features were then rescaled to normalize the numeric values. We developed a stacked model combining random forest and XGBoost to assess tumor grades using radiomics signatures. STATISTICAL TESTS: The model's performance was evaluated using positive predictive value (PPV), sensitivity, F1 score, area under the curve of receiver operating characteristic curve, and Matthews correlation coefficient. Using Monte Carlo technique, the average performance of 100 benchmarks of 85% train and 15% test was reported. RESULTS: The best model displayed an accuracy of 0.79. For low-grade tumor detection, a sensitivity of 0.79, a PPV of 0.95, and an F1 score of 0.86 were obtained. For high-grade tumor detection, a sensitivity of 0.78, PPV of 0.39, and F1 score of 0.52 were reported. DATA CONCLUSION: Radiomics analysis shows promise in classifying pathology grades non-invasively for patients with VHL-associated ccRCC, potentially leading to better diagnosis and personalized treatment. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

A CAIX Dual-Targeting Small-Molecule Probe for Noninvasive Imaging of ccRCC.

Carbonic anhydrase IX (CAIX), a zinc metal transmembrane protein, is highly expressed in 95% of clear cell renal cell carcinomas (ccRCCs). A positron emission tomography (PET) probe designed to target CAIX in nuclear medicine imaging technology can achieve precise positioning, is noninvasive, and can be used to monitor CAIX expression in lesions in real time. In this study, we constructed a novel acetazolamide dual-targeted small-molecule probe [68Ga]Ga-LF-4, which targets CAIX by binding to a specific amino acid sequence. After attenuation correction, the radiolabeling yield reached 66.95 ± 0.57% (n = 5) after 15 min of reaction and the radiochemical purity reached 99% (n = 5). [68Ga]Ga-LF-4 has good in vitro and in vivo stability, and in vivo safety and high affinity for CAIX, with a Kd value of 6.62 nM. Moreover, [68Ga]Ga-LF-4 could be quickly cleared from the blood in vivo. The biodistribution study revealed that the [68Ga]Ga-LF-4 signal was concentrated in the heart, lung, and kidney after administration, which was the same as that observed in the micro-PET/CT study. In a ccRCC patient-derived xenograft (PDX) model, the signal significantly accumulated in the tumor after administration, where it was retained for up to 4 h. After competitive blockade with LF-4, uptake at the tumor site was significantly reduced. The SUVmax of the probe [68Ga]Ga-LF-4 at the ccRCC tumor site was three times greater than that in the PC3 group with low CAIX expression at 30 min (ccRCC vs PC3:1.86 ± 0.03 vs 0.62 ± 0.01, t = 48.2, P < 0.0001). These results indicate that [68Ga]Ga-LF-4 is a novel small-molecule probe that targets CAIX and can be used to image localized and metastatic ccRCC lesions.

Deep learning using contrast-enhanced ultrasound images to predict the nuclear grade of clear cell renal cell carcinoma.

PURPOSE: To assess the effectiveness of a deep learning model using contrastenhanced ultrasound (CEUS) images in distinguishing between low-grade (grade I and II) and high-grade (grade III and IV) clear cell renal cell carcinoma (ccRCC). METHODS: A retrospective study was conducted using CEUS images of 177 Fuhrmangraded ccRCCs (93 low-grade and 84 high-grade) from May 2017 to December 2020. A total of 6412 CEUS images were captured from the videos and normalized for subsequent analysis. A deep learning model using the RepVGG architecture was proposed to differentiate between low-grade and high-grade ccRCC. The model's performance was evaluated based on sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver operating characteristic curve (AUC). Class activation mapping (CAM) was used to visualize the specific areas that contribute to the model's predictions. RESULTS: For discriminating high-grade ccRCC from low-grade, the deep learning model achieved a sensitivity of 74.8%, specificity of 79.1%, accuracy of 77.0%, and an AUC of 0.852 in the test set. CONCLUSION: The deep learning model based on CEUS images can accurately differentiate between low-grade and high-grade ccRCC in a non-invasive manner.

Development and validation of a clinical and ultrasound features-based nomogram for preoperative differentiation of renal urothelial carcinoma and central renal cell carcinoma.

PURPOSE: This study aimed to develop and validate an ultrasound (US)-based nomogram for the preoperative differentiation of renal urothelial carcinoma (rUC) from central renal cell carcinoma (c-RCC). METHODS: Clinical data and US images of 655 patients with 655 histologically confirmed malignant renal tumors (521 c-RCCs and 134 rUCs) were collected and divided into training (n = 455) and validation (n = 200) cohorts according to examination dates. Conventional US and contrast-enhanced US (CEUS) tumor features were analyzed to determine those that could discriminate rUC from c-RCC. Least absolute shrinkage and selection operator regression was applied to screen clinical and US features for the differentiation of rUC from c-RCC. Using multivariate logistic regression analysis, a diagnostic model of rUC was constructed and visualized as a nomogram. The diagnostic model's performance was assessed in the training and validation cohorts by calculating the area under the receiver operating characteristic curve (AUC) and calibration plot. Decision curve analysis (DCA) was used to assess the clinical usefulness of the US-based nomogram. RESULTS: Seven features of both clinical features and ultrasound imaging were selected to build the diagnostic model. The nomogram achieved favorable discrimination in the training (AUC = 0.996, 95% CI: 0.993-0.999) and validation (AUC = 0.995, 95% CI: 0.974, 1.000) cohorts, and good calibration (Brier scores: 0.019 and 0.016, respectively). DCA demonstrated the clinical usefulness of the US-based nomogram. CONCLUSION: A noninvasive clinical and US-based nomogram combining conventional US and CEUS features possesses good predictive value for differentiating rUC from c-RCC.

Locoregional Therapies in Immunologically "Cold" Tumors: Opportunities and Clinical Trial Design Considerations.

Immunotherapy has revolutionized cancer management, but many tumors, particularly immunologically "cold" tumors, remain resistant to the therapy. The combination of conventional systemic immunotherapies and locoregional interventional radiology approaches is being explored to transform these cold tumors into immunologically active "hot" ones. The present article uses the example of chromophobe renal cell carcinoma (ChRCC), a renal cell carcinoma subtype resistant to current systemic immunotherapies, to address practical and conceptual challenges that have prevented the activation of clinical trials specifically designed for this malignancy to date. The practical framework discussed herein can help overcome logistic and funding limitations and facilitate the development of biology-informed clinical trials tailored to specific rare diseases such as ChRCC.

Three-dimensional computed tomography-based resection process map for robot-assisted partial nephrectomy: propensity score matching of a single-center retrospective study.

BACKGROUND AND OBJECTIVES: We aimed to examine the effect of preoperative three-dimensional (3D) computed tomography (CT)-based resection process map (RPM) imaging on the outcomes of robot-assisted partial nephrectomy (RAPN). METHODS: We retrospectively analyzed 177 patients (RPM group, n = 92; non-RPM group, n = 85) who underwent this surgery between November 2012 and April 2022. Patient-specific contrast-enhanced CT images were used to construct an RPM, a 3D representation of the kidney showing the planned tumor resection and a 5 mm safety margin. Outcome analyses were performed using propensity score matching. The primary endpoint was the trifecta achievement rate. RESULTS: We extracted 90 cases. The trifecta achievement rate showed no significant differences between the RPM (73.3%) and non-RPM groups (73.3%). However, the RPM group had fewer Grade 3 and higher complications (0.0% vs. 13.3%, p = 0.026). The da Vinci Xi (OR 3.38, p = 0.016) and tumor diameter (OR 0.95, p = 0.013) were independent factors affecting trifecta achievement in multivariate analysis. Using RPM imaging was associated with the absence of Grade 3 and higher perioperative complications (OR 5.33, p = 0.036) in univariate analysis. CONCLUSIONS: Using preoperative 3D CT-based RPM images before RAPN may not affect trifecta achievement, but may reduce serious complication occurrence by providing detailed information on tumor resection.

DESI-MSI-guided exploration of metabolic-phenotypic relationships reveals a correlation between PI 38:3 and proliferating cells in clear cell renal cell carcinoma via single-section co-registration of multimodal imaging.

A workflow has been evaluated that utilizes a single tissue section to obtain spatially co-registered, molecular, and phenotypical information suitable for AI-enabled image analysis. Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was used to obtain molecular information followed by conventional histological staining and immunolabelling. The impact of varying DESI-MSI conditions (e.g., heated transfer line (HTL) temperature, scan rate, acquisition time) on the detection of small molecules and lipids as well as on tissue integrity crucial for integration into typical clinical pathology workflows was assessed in human kidney. Increasing the heated transfer line temperature from 150 to 450 °C resulted in a 1.8-fold enhancement in lipid signal at a scan rate of 10 scans/s, while preserving histological features. Moreover, increasing the acquisition speed to 30 scans/s yielded superior lipid signal when compared to 10 scans/s at 150 °C. Tissue morphology and protein epitopes remained intact allowing full histological assessment and further multiplex phenotyping by immunofluorescence (mIF) and immunohistochemistry (mIHC) of the same section. The successful integration of the workflow incorporating DESI-MSI, H&E, and immunolabelling on a single tissue section revealed an accumulation of ascorbic acid in regions of focal chronic inflammatory cell infiltrate within non-cancerous kidney tissue. Additionally, a strong positive correlation between PI 38:3 and proliferating cells was observed in clear cell renal cell carcinoma (ccRCC) showing the utility of this approach in uncovering molecular associations in disease pathology.

Evaluation of PET/CT imaging with [89Zr]Zr-DFO-girentuximab: a phase 1 clinical study in Japanese patients with renal cell carcinoma (Zirdac-JP).

BACKGROUND: PET/CT imaging with Zirconium-89 labeled [89Zr]Zr-DFO-girentuximab, which targets tumor antigen CAIX, may aid in the differentiation and characterization of clear cell renal cell carcinomas (RCC) and other renal and extrarenal lesions, and has been studied in European and American cohorts. We report results from a phase I study that evaluated the safety profile, biodistribution, and dosimetry of [89Zr]Zr-DFO-girentuximab in Japanese patients with suspected RCC. METHODS: Eligible adult patients received 37 MBq (± 10%; 10 mg mass dose) of intravenous [89Zr]Zr-DFO-girentuximab. Safety and tolerability profile was assessed based on adverse events, concomitant medications, physical examination, vital signs, hematology, serum chemistry, urinalysis, human anti-chimeric antibody measurement, and 12-lead electrocardiograms at predefined intervals. Biodistribution and normal organ and tumor dosimetry were evaluated with PET/CT images acquired at 0.5, 4, 24, 72 h and Day 5 ± 2 d after administration. RESULTS: [89Zr]Zr-DFO-girentuximab was administered in six patients as per protocol. No treatment-emergent adverse events were reported. Dosimetry analysis showed that radioactivity was widely distributed in the body, and that the absorbed dose in healthy organs was highest in the liver (mean ± standard deviation) (1.365 ± 0.245 mGy/MBq), kidney (1.126 ± 0.190 mGy/MBq), heart wall (1.096 ± 0.232 mGy/MBq), and spleen (1.072 ± 0.466 mGy/MBq). The mean effective dose, adjusted by the radioactive dose administered, was 0.470 mSv/MBq. The radiation dose was highly accumulated in the targeted tumor, while any abnormal accumulation in other organs was not reported. CONCLUSIONS: This study demonstrates that [89Zr]Zr-DFO-girentuximab administered to Japanese patients with suspected RCC has a favorable safety profile and is well tolerated and has a similar dosimetry profile to previously studied populations.

CT-derived radiomics predict the growth rate of renal tumours in von Hippel-Lindau syndrome.

AIM: To predict renal tumour growth patterns in von Hippel-Lindau syndrome by utilising radiomic features to assist in developing personalised surveillance plans leading to better patient outcomes. MATERIALS AND METHODS: The study evaluated 78 renal tumours in 55 patients with histopathologically-confirmed clear cell renal cell carcinomas (ccRCCs), which were segmented and radiomics were extracted. Volumetric doubling time (VDT) classified the tumours into fast-growing (VDT <365 days) or slow-growing (VDT ≥365 days). Volumetric and diametric growth analyses were compared between the groups. Multiple logistic regression and random forest classifiers were used to select the best features and models based on their correlation and predictability of VDT. RESULTS: Fifty-five patients (mean age 42.2 ± 12.2 years, 27 men) with a mean time difference of 3.8 ± 2 years between the baseline and preoperative scans were studied. Twenty-five tumours were fast-growing (low VDT, i.e., <365 days), and 53 tumours were slow-growing (high VDT, i.e., ≥365 days). The median volumetric and diametric growth rates were 1.71 cm3/year and 0.31 cm/year. The best feature using univariate analysis was wavelet-HLL_glcm_ldmn (area under the receiver operating characteristic [ROC] curve [AUC] of 0.80, p<0.0001), and with the random forest classifier, it was log-sigma-0-5-mm-3D_glszm_ZonePercentage (AUC: 79). The AUC of the ROC curves using multiple logistic regression was 0.74, and with the random forest classifier was 0.73. CONCLUSION: Radiomic features correlated with VDT and were able to predict the growth pattern of renal tumours in patients with VHL syndrome.

Characterization of Demographical Histologic Diversity in Small Renal Masses With the Clear Cell Likelihood Score.

OBJECTIVE: This study aimed to develop a diagnostic model to estimate the distribution of small renal mass (SRM; ≤4 cm) histologic subtypes for patients with different demographic backgrounds and clear cell likelihood score (ccLS) designations. MATERIALS AND METHODS: A bi-institution retrospective cohort study was conducted where 347 patients (366 SRMs) underwent magnetic resonance imaging and received a ccLS before pathologic confirmation between June 2016 and November 2021. Age, sex, race, ethnicity, socioeconomic status, body mass index (BMI), and the ccLS were tabulated. The socioeconomic status for each patient was determined using the Area Deprivation Index associated with their residential address. The magnetic resonance imaging-derived ccLS assists in the characterization of SRMs by providing a likelihood of clear cell renal cell carcinoma (ccRCC). Pathological subtypes were grouped into four categories (ccRCC, papillary renal cell carcinoma, other renal cell carcinomas, or benign). Generalized estimating equations were used to estimate probabilities of the pathological subtypes across different patient subgroups. RESULTS: Race and ethnicity, BMI, and ccLS were significant predictors of histology (all P < 0.001). Obese (BMI, ≥30 kg/m 2 ) Hispanic patients with ccLS of ≥4 had the highest estimated rate of ccRCC (97.1%), and normal-weight (BMI, <25 kg/m 2 ) non-Hispanic Black patients with ccLS ≤2 had the lowest (0.2%). The highest estimated rates of papillary renal cell carcinoma were found in overweight (BMI, 25-30 kg/m 2 ) non-Hispanic Black patients with ccLS ≤2 (92.3%), and the lowest, in obese Hispanic patients with ccLS ≥4 (<0.1%). CONCLUSIONS: Patient race, ethnicity, BMI, and ccLS offer synergistic information to estimate the probabilities of SRM histologic subtypes.

Qualitative and quantitative assessment of non-clear cell renal cell carcinoma using contrast-enhanced ultrasound.

BACKGROUND: Non-clear cell renal cell carcinoma (nccRCC) represents a rare form of renal cell carcinoma (RCC) in the clinic. It is now understood that contrast-enhanced ultrasound (CEUS) exhibits diverse manifestations and can be prone to misdiagnosis. Therefore, summarizing the distinctive features of contrast-enhanced ultrasonography is essential for differentiation from ccRCC. OBJECTIVE: This study aims to evaluate the diagnostic efficacy of qualitative and quantitative CEUS in diagnosing nccRCC to enhance our understanding of this condition. METHODS: We conducted a retrospective analysis of 21 patients with confirmed nccRCC following surgery and assessed the characteristic conventional ultrasound and CEUS imaging features. The paired Wilcoxon signed-rank sum test was employed to compare differences in CEUS time-intensity curve (TIC) parameters between the lesions and the normal renal cortex. RESULTS: Routine ultrasound revealed the following primary characteristics in the 21 nccRCC cases: hypoechoic appearance (10/21, 47.6%), absence of liquefaction (18/21, 66.7%), regular shape (19/21, 90.5%), clear boundaries (21/21, 100%), and absence of calcification (17/21, 81%). Color Doppler flow imaging (CDFI) indicated a low blood flow signal (only 1 case of grade III). Qualitative CEUS analysis demonstrated that nccRCC predominantly exhibited slow progression (76.1%), fast washout (57%), uniformity (61.9%), low enhancement (71.5%), and ring enhancement (61.9%). Quantitative CEUS analysis revealed that parameters such as PE, WiAUC, mTTI, WiR, WiPI, WoAUC, WiWoAUC, and WOR in the lesions were significantly lower than those in the normal renal cortex (Z=-3.980, -3.563, -2.427, -3.389, -3.980, -3.493, -3.528, -2.763, P < 0.001, < 0.001, = 0.015, = 0.001, < 0.001, < 0.001, < 0.001, = 0.006). However, there were no significant differences in RT, TTP, FT, or QOF (all P > 0.05). CONCLUSION: nccRCC exhibits distinctive CEUS characteristics, including slow progression, fast washout, low homogeneity enhancement, and ring enhancement, which can aid in distinguishing nccRCC from ccRCC.

CT findings and clinical characteristics in distinguishing renal urothelial carcinoma mimicking renal cell carcinoma from clear cell renal cell carcinoma.

BACKGROUND: We aimed to characterize the clinical and multiphase computed tomography (CT) features, which can distinguish renal urothelial carcinoma (RUC) mimicking renal cell carcinoma (RCC) from clear cell renal cell carcinoma (ccRCC) with collecting system invasion (CSI). METHODS: Data from 56 patients with RUC (46 men and 10 women) and 366 patients with ccRCC (262 men and 104 women) were collected and assessed retrospectively. The median age was 65.50 (IQR: 56.25-69.75) and 53.50 (IQR: 42.25-62.5) years, respectively. Univariate and multivariate logistic regression analyses were performed on clinical and CT characteristics to determine independent factors for distinguishing RUC and ccRCC, and an integrated predictive model was constructed. Differential diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUC). RESULTS: The independent predictors for differentiating RUC from ccRCC were infiltrative growth pattern, hydronephrosis, heterogeneous enhancement, preserving reniform contour, and hematuria. The differential diagnostic performance of the integrated predictive model-1 (AUC: 0.947, sensitivity: 89.07%, specificity: 89.29%) and model-2 (AUC: 0.960, sensitivity: 92.1%, specificity: 89.3%) were both better than that of the infiltrative growth pattern (AUC: 0.830, sensitivity: 71.9%, specificity: 92.9%), heterogeneous enhancement (AUC: 0.771, sensitivity: 86.3%, specificity: 67.9%), preserving reniform contour (AUC = 0.758, sensitivity: 85.5%, specificity: 66.1%), hydronephrosis (AUC: 0.733, sensitivity: 87.7%, specificity: 58.9%), or hematuria (AUC: 0.706, sensitivity: 79.5%, specificity: 51.8%). CONCLUSION: The CT and clinical characteristics showed extraordinary discriminative abilities in the differential diagnosis of RUC and ccRCC, which might provide helpful information for clinical decision-making.

Composite eosinophilic solid and cystic renal cell carcinoma and clear cell renal cell carcinoma: a rare case report and literature review.

BACKGROUND: Eosinophilic solid and cystic renal cell carcinoma (ESC-RCC) is a novel subtype of renal cell carcinoma characterized by its relatively low incidence and indolent behavior. We report a rare case of ESC-RCC concurrent with clear cell renal cell carcinoma (ccRCC) in a single kidney. CASE PRESENTATION: A 48-year-old male, was found to have a mixed echogenic mass in the left kidney during a physical examination. He has no history of hematuria and flank pain. An abdominal CT scan revealed a 3.0 * 1.9 * 2.5 cm3 mass with unclearly bordered at the lower pole of the left kidney. Abdominal MRI showed two nodules of different sizes in the left kidney, suggesting the possibility of a tumor. The patient underwent a subtotal nephrectomy, and the postoperative pathological results indicated ESC-RCC combined with ccRCC. The patient recovered well without tumor recurrence during the 12-month follow-up. CONCLUSION: We reported a case of renal composite tumors, comprising the rare ESC-RCC and the more common ccRCC. Imaging combined with postoperative pathological examination is crucial for the definitive diagnosis of these rare tumors.

Ultrasound contrast-enhanced radiomics model for preoperative prediction of the tumor grade of clear cell renal cell carcinoma: an exploratory study.

BACKGROUND: This study aims to explore machine learning(ML) methods for non-invasive assessment of WHO/ISUP nuclear grading in clear cell renal cell carcinoma(ccRCC) using contrast-enhanced ultrasound(CEUS) radiomics. METHODS: This retrospective study included 122 patients diagnosed as ccRCC after surgical resection. They were divided into a training set (n = 86) and a testing set(n = 36). CEUS radiographic features were extracted from CEUS images, and XGBoost ML models (US, CP, and MP model) with independent features at different phases were established. Multivariate regression analysis was performed on the characteristics of different radiomics phases to determine the indicators used for developing the prediction model of the combined CEUS model and establishing the XGBoost model. The training set was used to train the above four kinds of radiomics models, which were then tested in the testing set. Radiologists evaluated tumor characteristics, established a CEUS reading model, and compared the diagnostic efficacy of CEUS reading model with independent characteristics and combined CEUS model prediction models. RESULTS: The combined CEUS radiomics model demonstrated the best performance in the training set, with an area under the curve (AUC) of 0.84, accuracy of 0.779, sensitivity of 0.717, specificity of 0.879, positive predictive value (PPV) of 0.905, and negative predictive value (NPV) of0.659. In the testing set, the AUC was 0.811, with an accuracy of 0.784, sensitivity of 0.783, specificity of 0.786, PPV of 0.857, and NPV of 0.688. CONCLUSIONS: The radiomics model based on CEUS exhibits high accuracy in non-invasive prediction of ccRCC. This model can be utilized for non-invasive detection of WHO/ISUP nuclear grading of ccRCC and can serve as an effective tool to assist clinical decision-making processes.

Renal cell carcinoma with an "uncoiling" tumor thrombus: intraoperative shift from level III to level IV.

BACKGROUND: The gold standard treatment for renal cell carcinoma (RCC) with tumor thrombus (TT) is complete surgical excision. The surgery is complex and challenging to the surgeon, especially with large tumor thrombus extending into the inferior vena cava (IVC) and right atrium. Traditionally, these difficult cases required the use of cardiopulmonary bypass (CPB) with or without deep hypothermic cardiac arrest, but in recent years, different surgical techniques derived from the field of liver transplantation have been used in efforts to avoid CPB. CASE PRESENTATION: We present a case of RCC with TT level IIIc (extending above major hepatic veins) that "uncoiled" intraoperatively into the right atrium after division of the IVC ligament, transforming into a level IV TT. Despite the new TT extension, the surgery was successfully completed exclusively through an abdominal approach without CPB and while using intraoperative transesophageal echocardiography (TEE) monitoring and a cardiothoracic team standby. CONCLUSIONS: This case highlights the need for a multidisciplinary approach and the utility of intraoperative continous TEE monitoring which helped to visualize the change of the TT venous extension, allowing the surgical teamto modify their surgical approach as needed avoiding a catastrophic event.

Clinical T1/2 renal cell carcinoma: multiparametric dynamic contrast-enhanced MRI features-based model for the prediction of individual adverse pathology.

BACKGROUND: The detection of renal cell carcinoma (RCC) has been rising due to the enhanced utilization of cross-sectional imaging and incidentally discovered lesions with adverse pathology demonstrate potential for metastasis. The purpose of our study was to determine the clinical and multiparametric dynamic contrast-enhanced magnetic resonance imaging (CEMRI) associated independent predictors of adverse pathology for cT1/2 RCC and develop the predictive model. METHODS: We recruited 105 cT1/2 RCC patients between 2018 and 2022, all of whom underwent preoperative CEMRI and had complete clinicopathological data. Adverse pathology was defined as RCC patients with nuclear grade III-IV; pT3a upstage; type II papillary RCC, collecting duct or renal medullary carcinoma, unclassified RCC; sarcomatoid/rhabdoid features. The qualitative and quantitative CEMRI parameters were independently reviewed by two radiologists. Univariate and multivariate binary logistic regression analyses were utilized to determine the independent predictors of adverse pathology for cT1/2 RCC and construct the predictive model. The receiver operating characteristic (ROC) curve, confusion matrix, calibration plot, and decision curve analysis (DCA) were conducted to compare the diagnostic performance of different predictive models. The individual risk scores and linear predicted probabilities were calculated for risk stratification, and the Kaplan-Meier curve and log-rank tests were used for survival analysis. RESULTS: Overall, 45 patients were pathologically confirmed as RCC with adverse pathology. Clinical characteristics, including gender, and CEMRI parameters, including RENAL score, tumor margin irregularity, necrosis, and tumor apparent diffusion coefficient (ADC) value were identified as independent predictors of adverse pathology for cT1/2 RCC. The clinical-CEMRI predictive model yielded an area under the curve (AUC) of the ROC curve of 0.907, which outperformed the clinical model or CEMRI signature model alone. Good calibration, better clinical usefulness, excellent risk stratification ability of adverse pathology and prognosis were also achieved for the clinical-CEMRI predictive model. CONCLUSIONS: The proposed clinical-CEMRI predictive model offers the potential for preoperative prediction of adverse pathology for cT1/2 RCC. With the ability to forecast adverse pathology, the predictive model could significantly benefit patients and clinicians alike by providing enhanced guidance for treatment planning and decision-making.