Differentiation of fat-poor angiomyolipoma from clear cell renal cell carcinoma in contrast-enhanced MDCT images using quantitative feature classification

2017 ◽  
Vol 44 (7) ◽  
pp. 3604-3614 ◽  
Author(s):  
Han Sang Lee ◽  
Helen Hong ◽  
Dae Chul Jung ◽  
Seunghyun Park ◽  
Junmo Kim
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Feature Classification ◽  
Cell Renal Cell Carcinoma ◽  
Quantitative Feature ◽  
Contrast Enhanced

Dynamic contrast-enhanced MRI to predict intratumoral molecular heterogeneity in clear cell renal cell carcinoma.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 4580-4580
Author(s):  
Durga Udayakumar ◽  
Ze Zhang ◽  
Durgesh Dwivedi ◽  
Yin Xi ◽  
Tao Wang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Molecular Heterogeneity ◽  
Cell Renal Cell Carcinoma ◽  
Post Contrast ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

4580 Background: Mutation/inactivation of VHL in clear cell renal cell carcinoma (ccRCC) leads to upregulation of hypoxia inducible factors ( HIFs) and angiogenesis. However, ccRCC is characterized by high intra-tumor heterogeneity (ITH). Random small samples such as those in percutaneous biopsies are likely limited for characterization of molecular alterations in heterogeneous ccRCCs. We hypothesize that whole-tumor dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) is useful to noninvasively identify ITH in ccRCC. Methods: This IRB-approved, prospective, HIPAA-compliant study, included 62 ccRCCs. 3T DCE MRI was obtained prior to nephrectomy. Surgical specimens were sectioned to match MRI acquisition plane. 182 snap frozen samples (49 tumors) and adjacent uninvolved renal parenchyma (URP) were collected. RNA isolations, cDNA library preparation and mRNA sequencing were performed using standard protocols. RNA expression in 81 tumor samples were correlated (Spearman ranked) with % enhancement in a region of interest (ROI) drawn in the same location of the tumor on pre- and 3 different post-contrast DCE MRI phases. Gene function overrepresentation (OR) analyses were done on top positively and negatively correlated genes. False discovery rate (FDR) < 0.1 was considered statistically significant. Results: Principal component analysis of > 20,000 genes indicated distinct gene expression in tumors from URP. Unsupervised clustering showed enrichment of ccA samples (better prognosis) compared to ccB samples (worse prognosis). Importantly, ccA and ccB samples coexisted in 25% of tumors. DCE-MRI % enhancement correlated with expression of > 300 genes (p < 0.003, FDR < 0.1). OR analyses placed angiogenic pathway gene processes and the immune/inflammatory response processes within the top 5 positively- and negatively-correlated gene functions, respectively. HIF2 target genes correlated positively with % enhancement. Conclusions: DCE MRI detects specific molecular signatures and may help overcome the challenges of ITH in ccRCC. Further research is needed to explore the potential role of DCE MRI to assess response to antiangiogenic and immune-based therapies.

scholarly journals Tumor grade of clear cell renal cell carcinoma assessed by contrast-enhanced computed tomography

SpringerPlus ◽  
2014 ◽  
Vol 3 (1) ◽  
Author(s):  
Kousei Ishigami ◽  
Leandro V. Leite ◽  
Marius G. Pakalniskis ◽  
Daniel K. Lee ◽  
Danniele G. Holanda ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Tumor Grade ◽  
Cell Renal Cell Carcinoma ◽  
Contrast Enhanced ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

scholarly journals Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Lei Yan ◽  
Guangjie Yang ◽  
Jingjing Cui ◽  
Wenjie Miao ◽  
Yangyang Wang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Clinical Factors ◽  
Cell Renal Cell Carcinoma ◽  
Incremental Value ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced

PurposeTo develop and validate the radiomics nomogram that combines clinical factors and radiomics features to estimate overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC), and assess the incremental value of radiomics for OS estimation.Materials and MethodsOne hundred ninety-four ccRCC cases were included in the training cohort and 188 ccRCC patients from another hospital as the test cohort. Three-dimensional region-of-interest segmentation was manually segmented on multiphasic contrast-enhanced abdominal CT images. Radiomics score (Rad-score) was calculated from a formula generated via least absolute shrinkage and selection operator (LASSO) Cox regression, after which the association between the Rad-score and OS was explored. The radiomics nomogram (clinical factors + Rad-score) was developed to demonstrate the incremental value of the Rad-score to the clinical nomogram for individualized OS estimation, which was then evaluated in relation to calibration and discrimination.ResultsRad-score, calculated using a linear combination of the 11 screened features multiplied by their respective LASSO Cox coefficients, was significantly associated with OS. Calibration curves showed good agreement between the OS predicted by the nomograms and observed outcomes. The radiomics nomogram presented higher discrimination capability compared to clinical nomogram in the training (C-index: 0.884; 95% CI: 0.808–0.940 vs. 0.803; 95% CI: 0.705–0.899, P &lt; 0.05) and test cohorts (C-index: 0.859; 95% CI: 0.800–0.921 vs. 0.846; 95% CI: 0.777–0.915, P &lt; 0.05).ConclusionsThe radiomics nomogram may be used for predicting OS in patients with ccRCC, and radiomics is useful to assist quantitative and personalized treatment.

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