Purpose: To retrospectively evaluate whether the enhancement patterns of pathologically proved clear cell, papillary, and chromophobe renal cell carcinomas (RCCs) measured on clinical dynamic contrast agent–enhanced magnetic resonance (MR) images permit accurate diagnosis of RCC subtype. Materials and Methods: This study was Institutional Review Board approved and HIPAA compliant; informed consent was waived. One hundred twelve patients (76 men, 36 women; age range, 25–88 years; mean age, 58.1 years) underwent MR imaging of 113 renal masses (mean diameter, 5.4 cm) with pathologic diagnoses of clear cell (n = 75), papillary (n = 28), or chromophobe (n = 10) RCC. A 1.5-T clinical MR protocol was used before and after (corticomedullary and nephrographic phases) intravenous administration of contrast agent. Region-of-interest measurements within tumor and uninvolved renal cortex were used to calculate percentage signal intensity change and tumor-to-cortex enhancement index. Subtype groups were compared by usi...

https://pubs.rsna.org/doi/pdf/10.1148/radiol.2503080995?frame=sidebar

Renal Cell Carcinoma: Dynamic Contrast-enhanced MR Imaging for Differentiation of Tumor Subtypes—Correlation with Pathologic Findings

Purpose: To retrospectively determine if solid renal cortical tumors can be differentiated on computed tomographic (CT) images on the basis of their morphologic features and enhancement patterns. Materials and Methods: Institutional review board approval was obtained and the informed consent requirement was waived for this HIPAA-compliant study. Between January 2004 and September 2005, 193 consecutive patients (age range, 19–95 years; 112 men, 81 women) with renal masses underwent total or partial nephrectomy and preoperative renal CT. Two radiologists retrospectively reviewed CT studies in an independent and blinded fashion. The pattern and degree of enhancement, lesion contour, presence of neovascularity, and calcifications were evaluated. Fisher exact tests, Pearson χ2 tests, multivariate logistic regression, and Wilcoxon rank sum tests were performed. Results: Of the 198 renal tumors (median size, 3.4 cm; range, 1.1–20.0 cm) included in this study, 108 (55%) were clear cell renal cell carcinomas (RCCs...

Solid Renal Cortical Tumors: Differentiation with CT

Purpose: To compare the diagnostic performance of diffusion-weighted (DW) magnetic resonance (MR) imaging with that of contrast material–enhanced (CE) MR imaging and to assess the performance of these examinations combined for the characterization of renal lesions, with MR follow-up and histopathologic analysis as the reference standards Materials and Methods: The institutional review board waived the requirement of informed patient consent for this retrospective HIPAA-compliant study One hundred nine renal lesions in 64 patients (46 men, 18 women; mean age, 607 years) were evaluated with CE MR imaging and breath-hold DW imaging performed with various b values Renal lesions were characterized with use of CE MR criteria, and apparent diffusion coefficients (ADCs) were measured The ADCs of benign and malignant lesions were compared at Mann-Whitney testing Receiver operating characteristic (ROC) analysis was performed to assess the accuracy of DW imaging and CE MR imaging in the diagnosis of renal cell

https://pubs.rsna.org/doi/pdf/10.1148/radiol.2512080880

Renal Lesions: Characterization with Diffusion-weighted Imaging versus Contrast-enhanced MR Imaging

Multiphasic multidetector CT, if validated in a large prospective trial, may assist in the discrimination of clear cell renal cell carcinoma (RCC) from oncocytoma, papillary RCC, and chromophobe RCC.

https://pubs.rsna.org/doi/pdf/10.1148/radiol.13112617

Clear cell renal cell carcinoma: discrimination from other renal cell carcinoma subtypes and oncocytoma at multiphasic multidetector CT.

Histopathological images contain morphological markers of disease progression that have diagnostic and predictive values. In this study, we demonstrate how deep learning framework can be used for an automatic classification of Renal Cell Carcinoma (RCC) subtypes, and for identification of features that predict survival outcome from digital histopathological images. Convolutional neural networks (CNN’s) trained on whole-slide images distinguish clear cell and chromophobe RCC from normal tissue with a classification accuracy of 93.39% and 87.34%, respectively. Further, a CNN trained to distinguish clear cell, chromophobe and papillary RCC achieves a classification accuracy of 94.07%. Here, we introduced a novel support vector machine-based method that helped to break the multi-class classification task into multiple binary classification tasks which not only improved the performance of the model but also helped to deal with data imbalance. Finally, we extracted the morphological features from high probability tumor regions identified by the CNN to predict patient survival outcome of most common clear cell RCC. The generated risk index based on both tumor shape and nuclei features are significantly associated with patient survival outcome. These results highlight that deep learning can play a role in both cancer diagnosis and prognosis.

/pdf/pan-renal-cell-carcinoma-classification-and-survival-dpkj9krfv6.pdf

Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning

OBJECTIVE. The purpose of our study was to evaluate quantitative multiphasic CT enhancement patterns of malignant renal neoplasms to enable lesion differentiation by their enhancement characteristics. We used a new method to standardize enhancement measurement in lesions on multiphasic CT not being influenced by intrinsic factors like cardiac output.CONCLUSION. The new correction method is a simple tool for excluding intrinsic influences on the enhancement of lesions. Quantitative enhancement evaluation with this method of the influence of intrinsic factors enables accurate differentiation between renal clear cell carcinoma and renal papillary carcinoma.

Differentiation of Renal Clear Cell Carcinoma and Renal Papillary Carcinoma Using Quantitative CT Enhancement Parameters

OBJECTIVE. Differences of attenuation and enhancement patterns in focal nodular hyperplasia and hepatocellular adenoma were evaluated and quantified using triphasic single-slice helical CT.MATERIALS AND METHODS. Forty-five histologically proven focal nodular hyperplasias in 27 patients and 18 hepatocellular adenomas in six patients were examined with helical CT. Quantitative evaluation included the following: attenuation of lesions, scar, and liver parenchyma during unenhanced, arterial (20 sec after injection), and portal venous phases (70 sec after injection); relative enhancement of lesions and liver (the ratio between attenuation in arterial phase and portal venous phase, respectively, and attenuation in unenhanced phase); and the prevalence of scar and its central vessel in focal nodular hyperplasia.RESULTS. The study showed no significant difference between mean attenuation values of focal nodular hyperplasia (mean ± SD, 51.2 ± 5.9 H) and hepatocellular adenoma (mean ± SD, 56.3 ± 7.8 H) in the unenh...

Focal nodular hyperplasia and hepatocellular adenoma of the liver: differentiation with multiphasic helical CT.

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Differentiation of Renal Clear Cell Carcinoma and Renal Papillary Carcinoma Using Quantitative CT Enhancement Parameters

Focal nodular hyperplasia and hepatocellular adenoma of the liver: differentiation with multiphasic helical CT.