Infiltrative Renal Masses: Clinical Challenges

CT-based radiomics signature for differentiating pyelocaliceal upper urinary tract urothelial carcinoma from infiltrative renal cell carcinoma

Objectives

To develop a CT-based radiomics model and a combined model for preoperatively discriminating infiltrative renal cell carcinoma (RCC) and pyelocaliceal upper urinary tract urothelial carcinoma (UTUC), which invades the renal parenchyma.

Materials and methods

Eighty patients (37 pathologically proven infiltrative RCCs and 43 pathologically proven pyelocaliceal UTUCs) were retrospectively enrolled and randomly divided into a training set (n = 56) and a testing set (n = 24) at a ratio of 7:3. Traditional CT imaging characteristics in the portal venous phase were collected by two radiologists (SPH and ZXL, who have 4 and 30 years of experience in abdominal radiology, respectively). Patient demographics and traditional CT imaging characteristics were used to construct the clinical model. The radiomics score was calculated based on the radiomics features extracted from the portal venous CT images and the random forest (RF) algorithm to construct the radiomics model. The combined model was constructed using the radiomics score and significant clinical factors according to the multivariate logistic regression. The diagnostic efficacy of the models was evaluated using receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC).

Results

The RF score based on the eight validated features extracted from the portal venous CT images was used to build the radiomics model. Painless hematuria as an independent risk factor was used to build the clinical model. The combined model was constructed using the RF score and the selected clinical factor. Both the radiomics model and combined model showed higher efficacy in differentiating infiltrative RCC and pyelocaliceal UTUC in the training and testing cohorts with AUC values of 0.95 and 0.90, respectively, for the radiomics model and 0.99 and 0.90, respectively, for the combined model. The decision curves of the combined model as well as the radiomics model indicated an overall net benefit over the clinical model. Both the radiomics model and the combined model achieved a notable reduction in false-positive and false-negativerates, resulting in significantly higher accuracy compared to the visual assessments in both the training and testing cohorts.

Conclusion

The radiomics model and combined model had the potential to accurately differentiate infiltrative RCC and pyelocaliceal UTUC, which invades the renal parenchyma, and provide a new potentially non-invasive method to guide surgery strategies.

Parenchymal Volume Replacement by Renal Cell Carcinoma Prior to Intervention: Predictive Factors and Functional Implications

OBJECTIVE

To analyze predictors, extent and functional implications associated with renal parenchymal volume replacement (PVR) by renal cell carcinoma (RCC) prior to intervention. This phenomenon is well-recognized yet not adequately studied, and, if severe, can influence management.

MATERIALS AND METHODS

A retrospective review was performed of partial nephrectomy (PN) and radical nephrectomy (RN) patients with available preoperative nuclear-renal-scan and imaging demonstrating solitary RCC with normal contralateral kidney. Normal renal parenchymal volume of each kidney was measured by free-hand scripting from preoperative axial images. Primary endpoint was percent PVR which was estimated assuming that the contralateral-kidney serves as a control: PVR = (volume contralateral kidney - volume ipsilateral kidney) normalized by volume contralateral kidney. Multivariable linear-regression analysis assessed factors associated with preoperative PVR. Further analysis evaluated the functional effect of PVR prior to surgery.

RESULTS

146 PN and 136 RN patients with necessary studies were analyzed. For RN, the median PVR was 15% and a quarter of patients had PVR ≥27%. In contrast, PVR was negligible in PN patients for whom median preoperative parenchymal volumes were nearly identical in the ipsilateral/contralateral kidneys (179/180cc, respectively). PVR inversely correlated with preoperative renal function in the ipsilateral kidney (P <.01). Tumor-size (P <.01), stage (P = .03), and endophytic properties (P = .03) associated with PVR on multivariable-analysis.

CONCLUSION

Our data suggest that substantial replacement of normal parenchyma by RCC occurs in many patients selected for RN and can contribute to preexisting renal-insufficiency. PVR prior to intervention is mainly driven by tumor characteristics in RN patients, but is negligible in most PN patients.