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Purpose To investigate Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) approximations of target lesion tumor burden by comparing categorical treatment response according to conventional RECIST versus actual tumor volume measurements of RECIST target lesions. Materials and Methods This is a retrospective cohort study of individuals with metastatic renal cell carcinoma enrolled in a clinical trial (from 2003 to 2017) and includes individuals who underwent baseline and at least one follow-up chest, abdominal, and pelvic CT study and with at least one target lesion. Target lesion volume was assessed by (a) V model , a spherical model of conventional RECIST 1.1, which was extrapolated from RECIST diameter, and (b) V actual , manually contoured volume. Volumetric responses were determined by the sum of target lesion volumes (V model -sum TL and V actual -sum TL, respectively). Categorical volumetric thresholds were extrapolated from RECIST. McNemar tests were used to compare categorical volume responses. Results Target lesions were assessed at baseline (638 participants), week 9 (593 participants), and week 17 (508 participants). V model -sum TL classified more participants as having progressive disease (PD), compared with V actual -sum TL at week 9 (52 vs 31 participants) and week 17 (57 vs 39 participants), with significant overall response discordance ( P < .001). At week 9, 25 (48%) of 52 participants labeled with PD by V model -sum TL were classified as having stable disease by V actual -sum TL. Conclusion A model of RECIST 1.1 based on a single diameter measurement more frequently classified PD compared with response assessment by actual measured tumor volume. Keywords: Urinary, Kidney, Metastases, Oncology, Tumor Response, Volume Analysis, Outcomes Analysis ClinicalTrials.gov registration no. NCT01865747 © RSNA, 2023 Supplemental material is available for this article.

Purpose: Clear cell renal cell carcinoma (ccRCC) comprises nearly 90% of all diagnosed RCC subtypes and has the worst prognosis and highest metastatic potential. The strongest prognostic factors for patients with ccRCC include histological subtype and Fuhrman grade, which are incorporated into prognostic models. Since ccRCC is a highly vascularized tumor, there may be differences in enhancement patterns on multidetector CT (MDCT) due to the hemodynamics and microvessel density (MVD) of the lesions. This may provide a noninvasive method to characterize incidentally detected low- and high-grade ccRCCs on MDCT. The purpose of our study was to determine the correlation between MDCT enhancement parameters, ccRCC MVD, and Fuhrman grade to determine its utility and value in assessing tumor vascularity and grade in vivo., Methods: In this retrospective, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low-grade (LG), and 43 high-grade (HG) ccRCCs underwent preoperative four-phase MDCT. A 3D volume of interest (VOI) was obtained for every tumor and absolute enhancement and the wash-in/wash-out of enhancement for each phase was assessed. Immunohistochemistry on resected specimens was used to quantify MVD. Linear regression and Pearson correlation were used to investigate the strength of the association between 3D VOI enhancement and MVD. Stepwise logistic regression analysis determined independent predictors of HG ccRCC. Cut-off values and odds Ratio (OR) with 95% CIs were reported. The clinical, radiomic, and pathologic features with the highest performance in the stepwise logistic regression analysis were evaluated using receiver operator characteristics (ROC) and area under the curve (AUC)., Results: Absolute enhancement in the nephrographic phase < 52.1 Hounsfield Units (HU) (HR 0.979, 95% CI 0.964-0.994, p value = 0.006), lesion size > 4.3 cm (HR 1.450, 95% CI 1.211-1.738, p value < 0.001), and an intratumoral MVD < 15% (HR 0.932, 95% CI 0.867-1.002, p value = 0.058) were independent predictors of HG ccRCC with an AUC of 0.818 (95% CI 0.725-0.911). HG ccRCCs had a significant association between 3D VOI enhancement and MVD in each post-contrast phase (r 2  = 0.238 to 0.455, p < 0.05)., Conclusions: Absolute enhancement of the entire lesion obtained from a 3D VOI in the nephrographic phase on preoperative MDCT can provide quantitative data that are a significant, independent predictor of a high-grade clear cell RCC and can be used to assess tumor vascularity and grade in vivo.

Background Progression-free survival (PFS) determined by Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) is the reference standard to assess efficacy of treatments in patients with clear cell renal cell carcinoma. Purpose To assess the most common components of radiologic progressive disease as defined by RECIST 1.1 in patients with clear cell renal cell carcinoma and how the progression events impact PFS. Materials and Methods This secondary analysis of the phase III METEOR trial conducted between 2013 and 2014 included patients with metastatic clear cell renal cell carcinoma, with at least one target lesion at baseline and one follow-up time point, who were determined according to RECIST 1.1 to have progressive disease. A chest, abdominal, and pelvic scan were acquired at each time point. Kruskal-Wallis analysis was used to test differences in median PFS among the RECIST 1.1 progression events. The Holm-Bonferroni method was used to compare the median PFS of the progression events for the family-wise error rate of 5% to adjust P values for multiple comparisons. Results Of the 395 patients (296 men, 98 women, and one patient with sex not reported; mean age, 61 years ± 10), 73 (18.5%) had progression due to non-target disease, 105 (26.6%) had new lesions, and 126 (31.9%) had progression of target lesions (defined by an increase in the sum of diameters). Patients with progression of non-target disease and those with new lesions had shorter PFS than patients with progression defined by the target lesions (median PFS, 2.8 months [95% confidence interval {CI}: 1.9 months, 3.7 months] and 3.6 months [95% CI: 3.3 months, 3.7 months] vs 5.4 months [95% CI: 5.0 months, 5.5 months], respectively [ P < .01]). Conclusion The most common causes for radiologic progression of renal cell carcinoma were based on non-target disease and new lesions rather than change in target lesions, despite this being considered uncommon in the Response Evaluation Criteria in Solid Tumors version 1.1 literature. © RSNA, 2019 See also the editorial by Kuhl in this issue.

Purpose: Currently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial overlap in the imaging findings of benign and malignant renal masses, particularly between clear cell RCC (ccRCC) and benign oncocytoma (ONC). Radiomics has attracted increased attention for its utility in pre-operative work-up on routine clinical images. Radiomics based approaches have converted medical images into mineable data and identified prognostic imaging signatures that machine learning algorithms can use to construct predictive models by learning the decision boundaries of the underlying data distribution. The TensorFlow™ framework from Google is a state-of-the-art open-source software library that can be used for training deep learning neural networks for performing machine learning tasks. The purpose of this study was to investigate the diagnostic value and feasibility of a deep learning-based renal lesion classifier using open-source Google TensorFlow™ Inception in differentiating ccRCC from ONC on routine four-phase MDCT in patients with pathologically confirmed renal masses., Methods: With institutional review board approval for this 1996 Health Insurance Portability and Accountability Act compliant retrospective study and a waiver of informed consent, we queried our institution's pathology, clinical, and radiology databases for histologically proven cases of ccRCC and ONC obtained between January 2000 and January 2016 scanned with a an intravenous contrast-enhanced four-phase renal mass protocol (unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases). To extract features to be used for the machine learning model, the entire renal mass was contoured in the axial plane in each of the four phases, resulting in a 3D volume of interest (VOI) representative of the entire renal mass. We investigated thirteen different approaches to convert the acquired VOI data into a set of images that adequately represented each tumor which was used to train the final layer of the neural network model. Training was performed over 4000 iterations. In each iteration, 90% of the data were designated as training data and the remaining 10% served as validation data and a leave-one-out cross-validation scheme was implemented. Accuracy, sensitivity, specificity, positive (PPV) and negative predictive (NPV) values, and CIs were calculated for the classification of the thirteen processing modes., Results: We analyzed 179 consecutive patients with 179 lesions (128 ccRCC and 51 ONC). The ccRCC cohort had a mean size of 3.8 cm (range 0.8-14.6 cm) and the ONC cohort had a mean lesion size of 3.9 cm (range 1.0-13.1 cm). The highest specificity and PPV (52.9% and 80.3%, respectively) were achieved in the EX phase when we analyzed the single mid-slice of the tumor in the axial, coronal and sagittal plane, and when we increased the number of mid-slices of the tumor to three, with an accuracy of 75.4%, which also increased the sensitivity to 88.3% and the PPV to 79.6%. Using the entire tumor volume also showed that classification performance was best in the EX phase with an accuracy of 74.4%, a sensitivity of 85.8% and a PPV of 80.1%. When the entire tumor volume, plus mid-slices from all phases and all planes presented as tiled images, were submitted to the final layer of the neural network we achieved a PPV of 82.5%., Conclusions: The best classification result was obtained in the EX phase among the thirteen classification methods tested. Our proof of concept study is the first step towards understanding the utility of machine learning in the differentiation of ccRCC from ONC on routine CT images. We hope this could lead to future investigation into the development of a multivariate machine learning model which may augment our ability to accurately predict renal lesion histology on imaging.

Purpose: The purpose of the study was to determine if enhancement features and qualitative imaging features on multiphasic multidetector computed tomography (MDCT) were associated with tumor grade in patients with clear cell renal cell carcinoma (ccRCC)., Methods: In this retrospective, IRB approved, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low grade (LG) and 43 high grade (HG) ccRCCs underwent preoperative four-phase MDCT in unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases. Previously published quantitative (absolute peak lesion enhancement, absolute peak lesion enhancement relative to normal enhancing renal cortex, 3D whole lesion enhancement and the wash-in/wash-out of enhancement within the 3D whole lesion ROI) and qualitative (enhancement pattern; presence of necrosis; pattern of; tumor margin; tumor-parenchymal interface, tumor-parenchymal interaction; intratumoral vascularity; collecting system infiltration; renal vein invasion; and calcification) assessments were obtained for each lesion independently by two fellowship-trained genitourinary radiologists. Comparisons between variables included χ 2 , ANOVA, and student t test. p values less than 0.05 were considered to be significant. Inter-reader agreement was obtained with the Gwet agreement coefficient (AC1) and standard error (SE) was reported., Results: No significant differences were observed between the LG and HG ccRCC cohorts with respect to absolute peak lesion enhancement and relative lesion enhancement ratio. There was a significant inverse correlation between low and high grade ccRCC and tumor enhancement the NP (71 HU vs. 54 HU, p < 0.001) and EX (52 HU vs. 39 HU, p < 0.001) phases using the 3D whole lesion ROI method. The percent wash-in of 3D enhancement from the UN to the CM phase was also significantly different between LG and HG ccRCCs (352% vs. 255%, p = 0.003). HG lesions showed significantly more calcification, necrosis, collecting system infiltration and ill-defined tumor margins (p < 0.05). Overall agreement between the two readers had a mean AC1 of 0.8172 (SE 0.0235)., Conclusions: Quantitatively, high grade ccRCC had significantly lower whole lesion enhancement in the NP and EX phases on MDCT. Qualitatively, high grade ccRCC were significantly more likely to be associated with calcifications, necrosis, collecting system infiltration, and an ill-defined tumor margin.

Purpose: To investigate whether multiphasic MDCT enhancement profiles can help to identify PTEN expression in clear cell renal cell carcinomas (ccRCCs). Lack of PTEN expression is associated with worsened overall survival, a more advanced Fuhrman grade, and a greater likelihood of lymph mode metastasis., Methods: With IRB approval for this retrospective study, we derived a cohort of 103 histologically proven ccRCCs with preoperative 4-phase renal mass MDCT from 2001-2013. Following manual segmentation, a computer-assisted detection algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase; a 0.5-cm-diameter region of interest was manually placed on uninvolved renal cortex in each phase. The relative attenuation of each lesion was calculated as [(Maximal lesion attenuation - cortex attenuation)/cortex attenuation] × 100. Absolute and relative attenuation in each phase were compared using t tests. The performance of multiphasic enhancement in identifying PTEN expression was assessed with logistic regression analysis., Results: PTEN-positive and PTEN-negative ccRCCs both exhibited peak enhancement in the corticomedullary phase. Relative corticomedullary phase attenuation was significantly greater for PTEN-negative ccRCCs in comparison to PTEN-positive ccRCCs (33.7 vs. 9.5, p = 0.03). After controlling for lesion stage and size, relative corticomedullary phase attenuation had an accuracy of 84% (86/103), specificity of 100% (84/84), sensitivity of 11% (2/19), positive predictive value of 100% (2/2), and negative predictive value of 83% (84/101) in identifying PTEN expression., Conclusion: Relative corticomedullary phase attenuation may help to identify PTEN expression in ccRCCs, if validated prospectively.

Objective: The purpose of this study was to determine whether qualitative MDCT features are associated with the carbonic anhydrase IX (CAIX) score of clear cell renal cell carcinoma (RCC). The CAIX score has been previously found to have prognostic significance for disease-free survival, overall survival, and lymph node involvement., Materials and Methods: A cohort of 105 histologically proven clear cell RCCs in patients who underwent preoperative four-phase renal mass MDCT was derived from 2001 to 2013. Two genitourinary radiologists evaluated each lesion for the gross appearance of intratumoral vascularity, calcification, enhancement pattern, necrosis, margin, collecting system invasion, and renal vein invasion. Immunohistochemical analysis was used to determine the CAIX score (defined as the positive staining percentage multiplied by the staining intensity). Logistic and linear regression analyses were performed., Results: In a linear regression model controlled for lesion size and stage, the gross appearance of intratumoral vascularity had a significant positive association with CAIX score (β = 38.33, p = 0.010). In a logistic regression model controlled for lesion size and stage, the gross appearance of intratumoral vascularity had an odds ratio of 2.85 (p = 0.019) in differentiating clear cell RCCs with a CAIX score of 200-300 from clear cell RCCs with a CAIX score of 0-199., Conclusion: In clear cell RCCs, the gross appearance of intratumoral vascularity at MDCT was significantly associated with CAIX score, a prognostically significant molecular marker. Current assessment of CAIX score requires pathologic tissue sampling and immunohistochemical analysis. A noninvasive imaging biomarker that may help predict CAIX score may be of great clinical value.

Purpose: To investigate if multiphasic multidetector computed tomography (MDCT) enhancement profiles can distinguish clear cell renal cell carcinomas (ccRCCs) with high carbonic anhydrase-IX (CA-IX) expression from ccRCCs with low CA-IX expression., Methods: With IRB approval for this retrospective study, we derived a cohort of 105 histologically proven ccRCCs with preoperative 4-phase renal mass MDCT from 2001 to 2013. Following manual segmentation, the computer-assisted detection algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase. CA-IX expression level was determined by immunohistochemical staining of tumor specimens. In the high and low CA-IX expression subgroups, the magnitude of enhancement and washout were compared using t tests; the performance of contrast washout in differentiating between subgroups was assessed with logistic regression analysis., Results: ccRCCs with high and low CA-IX expression both exhibited peak enhancement in the corticomedullary phase. ccRCCs with high CA-IX expression demonstrated significantly greater relative nephrographic washout than those with low CA-IX expression (18.4% vs. 7.8%, p = 0.03). ccRCCs with high CA-IX expression had greater relative excretory washout than ccRCCs with low CA-IX expression with a trend toward significance (33.4% vs. 25.2%, p = 0.05). After controlling for tumor size and stage, for distinguishing ccRCCs with high and low CA-IX expression, relative excretory washout had a sensitivity, negative predictive value, accuracy, and positive predictive value of 99% (65/66), 88% (7/8), 69% (72/105), and 67% (65/97), respectively., Conclusion: Relative nephrographic and excretory washout may have the potential to help distinguish ccRCCs with high and low CA-IX expression, but this requires further validation.

Objective: The objective of our study was to investigate whether multiphasic MDCT enhancement can help identify clear cell renal cell carcinomas (RCCs) with the loss of the Y chromosome., Materials and Methods: We derived a cohort of 43 clear cell RCCs in men who underwent preoperative four-phase renal mass MDCT from October 2000 to August 2013. Each lesion was segmented in its entirety on axial images. A computer-assisted detection algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase. A 0.5-cm-diameter ROI was manually placed on uninvolved renal cortex in each phase. The relative attenuation of each lesion was calculated as follows: [(maximal lesion attenuation - cortex attenuation) / cortex attenuation] × 100. Absolute attenuation and relative attenuation in each phase were compared using t tests., Results: Both clear cell RCCs with the loss of the Y chromosome and clear cell RCCs without the loss of the Y chromosome exhibited peak enhancement in the corticomedullary phase. However, relative nephrographic attenuation of clear cell RCCs with the loss of Y was significantly less than that of clear cell RCCs without the loss of Y (mean, -8.9 vs 8.4 respectively; p = 0.013). A relative nephrographic attenuation threshold of -1.6 identified the loss of Y with an accuracy of 70% (30/43), sensitivity of 73% (16/22), and specificity of 67% (14/21)., Conclusion: Multiphasic MDCT enhancement may assist in identifying the loss of the Y chromosome in clear cell RCCs; this result should be validated in a large prospective trial.

Purpose: To investigate whether multiphasic MDCT enhancement can help differentiate type 1 papillary renal cell carcinoma (RCC) from type 2 papillary RCC., Methods: With IRB approval for this HIPAA-compliant retrospective study, we derived a cohort of 36 type 1 papillary RCCs and 33 type 2 papillary RCCs with preoperative multiphasic MDCT with up to four phases (unenhanced, corticomedullary, nephrographic, and excretory) from 2000 to 2013. Following segmentation, a computer-assisted detection (CAD) algorithm selected a 0.5 cm-diameter region of maximal attenuation within each lesion in each phase; a 0.5 cm-diameter region of interest was manually placed on uninvolved renal cortex in each phase. The relative attenuation of each lesion was calculated as [(Lesion attenuation-cortex attenuation)/cortex attenuation] × 100. Absolute and relative attenuation values were compared using Mann-Whitney tests with Bonferroni correction for multiple comparisons., Results: Relative excretory phase attenuation of type 2 papillary RCCs was significantly greater than that of type 1 papillary RCCs (2.0 vs. -18.3, p = 0.005). Relative excretory phase attenuation differentiated type 1 papillary RCCs from type 2 papillary RCCs with an accuracy of 73% (36/49), sensitivity of 87% (26/30), positive predictive value of 74% (26/35), and negative predictive value of 71% (10/14)., Conclusion: Multiphasic MDCT enhancement may assist in differentiating type 1 papillary RCCs from type 2 papillary RCCs, if prospectively validated.

Objective: To evaluate the performance of a novel, quantitative computer-aided diagnostic (CAD) algorithm on four-phase multidetector computed tomography (MDCT) to detect peak lesion attenuation to enable differentiation of clear cell renal cell carcinoma (ccRCC) from chromophobe RCC (chRCC), papillary RCC (pRCC), oncocytoma, and fat-poor angiomyolipoma (fp-AML)., Materials and Methods: We queried our clinical databases to obtain a cohort of histologically proven renal masses with preoperative MDCT with four phases [unenhanced (U), corticomedullary (CM), nephrographic (NP), and excretory (E)]. A whole lesion 3D contour was obtained in all four phases. The CAD algorithm determined a region of interest (ROI) of peak lesion attenuation within the 3D lesion contour. For comparison, a manual ROI was separately placed in the most enhancing portion of the lesion by visual inspection for a reference standard, and in uninvolved renal cortex. Relative lesion attenuation for both CAD and manual methods was obtained by normalizing the CAD peak lesion attenuation ROI (and the reference standard manually placed ROI) to uninvolved renal cortex with the formula [(peak lesion attenuation ROI - cortex ROI)/cortex ROI] × 100%. ROC analysis and area under the curve (AUC) were used to assess diagnostic performance. Bland-Altman analysis was used to compare peak ROI between CAD and manual method., Results: The study cohort comprised 200 patients with 200 unique renal masses: 106 (53%) ccRCC, 32 (16%) oncocytomas, 18 (9%) chRCCs, 34 (17%) pRCCs, and 10 (5%) fp-AMLs. In the CM phase, CAD-derived ROI enabled characterization of ccRCC from chRCC, pRCC, oncocytoma, and fp-AML with AUCs of 0.850 (95% CI 0.732-0.968), 0.959 (95% CI 0.930-0.989), 0.792 (95% CI 0.716-0.869), and 0.825 (95% CI 0.703-0.948), respectively. On Bland-Altman analysis, there was excellent agreement of CAD and manual methods with mean differences between 14 and 26 HU in each phase., Conclusion: A novel, quantitative CAD algorithm enabled robust peak HU lesion detection and discrimination of ccRCC from other renal lesions with similar performance compared to the manual method.

Objective: The objective of our study was to investigate the performance of relative enhancement on multiphasic MRI to differentiate clear cell renal cell carcinoma (RCC) from other RCC subtypes (papillary and chromophobe) and oncocytoma., Materials and Methods: For this study, we derived a cohort of 34 clear cell RCCs, nine oncocytomas, 12 papillary RCCs, and 10 chromophobe RCCs with a preoperative multiphasic dynamic contrast-enhanced MRI study with up to four phases (i.e., unenhanced, corticomedullary, nephrographic, excretory) from 2005 to 2016. These groups were evaluated for multiphasic enhancement and were compared using Kruskal-Wallis and Mann-Whitney tests. ROC curves were constructed and logistic regression analyses were performed to evaluate the performance of multiphasic enhancement in differentiating clear cell RCCs from the other three groups., Results: Clear cell RCCs exhibited significantly greater relative signal intensity compared with uninvolved renal cortex in the corticomedullary phase (mean, 2.9) than oncocytomas (-21.7, p = 0.001), papillary RCCs (-53.0, p < 0.001), and chromophobe RCCs (-21.0, p < 0.001). Relative signal intensity in the corticomedullary phase differentiated clear cell RCCs from oncocytomas with an AUC of 0.90 and with an accuracy of 84% (32/38), sensitivity of 90% (27/30), and specificity of 63% (5/8) after controlling for lesion size, patient age, and patient sex. Relative corticomedullary signal intensity differentiated clear cell RCCs from oncocytomas and other RCC subtypes with an AUC of 0.93 and with an accuracy of 90% (53/59), sensitivity of 90% (27/30), and specificity of 90% (26/29) after controlling for lesion size, patient age, and patient sex., Conclusion: Multiphasic MRI enhancement may assist in differentiating clear cell RCC from oncocytomas and other RCC subtypes, if validated in prospective studies.

Purpose: To determine whether multiphasic MDCT enhancement can help identify the gain of chromosome 12 in clear cell renal cell carcinomas (RCCs)., Methods: With IRB approval for this HIPAA-compliant case control study, we derived a cohort of 65 clear cell RCCs with preoperative four-phase renal mass MDCT from October 2000 to August 2013. Each lesion was segmented in its entirety on axial images in all phases. A computer-assisted detection (CAD) algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase. Attenuation in each phase between clear cell RCCs with and without the gain of 12 was compared using t-tests., Results: While the entire cohort of clear cell RCCs exhibited peak enhancement in the corticomedullary phase, the subcohort of lesions with the gain of 12 exhibited significantly greater enhancement in the nephrographic (179 vs. 145 HU, p = 0.004) and excretory phases (147 vs. 118 HU, p = 0.004) than the subcohort of lesions without the gain of 12. A nephrographic threshold of 186 HU identified the gain of 12 with an accuracy of 86% (56/65), specificity of 93% (51/55), and negative predictive value of 91% (51/56)., Conclusion: Multiphasic MDCT enhancement, specifically enhancement in the nephrographic and excretory phases, may potentially assist in identifying the gain of 12 in clear cell RCCs.