Normalized Dual-Energy Iodine Ratio Best Differentiates Renal Cell Carcinoma Subtypes Among Quantitative Imaging Biomarkers From Perfusion CT and Dual-Energy CT

2020 ◽  
Vol 215 (6) ◽  
pp. 1389-1397
Author(s):  
Dinesh Manoharan ◽  
Arjunlokesh Netaji ◽  
Kanika Diwan ◽  
Sanjay Sharma
2020 ◽  
Vol 214 (4) ◽  
pp. 808-816
Author(s):  
Dinesh Manoharan ◽  
Arjunlokesh Netaji ◽  
Chandan J. Das ◽  
Sanjay Sharma

2019 ◽  
Author(s):  
Chunling Zhang ◽  
Ning Wang ◽  
Xinyou Su ◽  
Kun Li ◽  
Dexin Yu ◽  
...  

2019 ◽  
Vol 30 (4) ◽  
pp. 2091-2102 ◽  
Author(s):  
Amar Udare ◽  
Daniel Walker ◽  
Satheesh Krishna ◽  
Robert Chatelain ◽  
Matthew DF McInnes ◽  
...  

Author(s):  
Zahra Khodabakhshi ◽  
Mehdi Amini ◽  
Shayan Mostafaei ◽  
Atlas Haddadi Avval ◽  
Mostafa Nazari ◽  
...  

AbstractThe aim of this work is to investigate the applicability of radiomic features alone and in combination with clinical information for the prediction of renal cell carcinoma (RCC) patients’ overall survival after partial or radical nephrectomy. Clinical studies of 210 RCC patients from The Cancer Imaging Archive (TCIA) who underwent either partial or radical nephrectomy were included in this study. Regions of interest (ROIs) were manually defined on CT images. A total of 225 radiomic features were extracted and analyzed along with the 59 clinical features. An elastic net penalized Cox regression was used for feature selection. Accelerated failure time (AFT) with the shared frailty model was used to determine the effects of the selected features on the overall survival time. Eleven radiomic and twelve clinical features were selected based on their non-zero coefficients. Tumor grade, tumor malignancy, and pathology t-stage were the most significant predictors of overall survival (OS) among the clinical features (p < 0.002, < 0.02, and < 0.018, respectively). The most significant predictors of OS among the selected radiomic features were flatness, area density, and median (p < 0.02, < 0.02, and < 0.05, respectively). Along with important clinical features, such as tumor heterogeneity and tumor grade, imaging biomarkers such as tumor flatness, area density, and median are significantly correlated with OS of RCC patients.


2020 ◽  
Vol 61 (12) ◽  
pp. 1708-1716
Author(s):  
Bruno R Tegel ◽  
Steffen Huber ◽  
Lynn J Savic ◽  
MingDe Lin ◽  
Bernhard Gebauer ◽  
...  

Background The prognosis of patients with renal cell carcinoma (RCC) depends greatly on the presence of extra-renal metastases. Purpose To investigate the value of total tumor volume (TTV) and enhancing tumor volume (ETV) as three-dimensional (3D) quantitative imaging biomarkers for disease aggressiveness in patients with RCC. Material and Methods Retrospective, HIPAA-compliant, IRB-approved study including 37 patients with RCC treated with image-guided thermal ablation during 2007–2015. TNM stage, RENAL Nephrometry Score, largest tumor diameter, TTV, and ETV were assessed on cross-sectional imaging at baseline and correlated with outcome measurements. The primary outcome was time-to-occurrence of extra-renal metastases and the secondary outcome was progression-free survival (PFS). Correlation was assessed using a Cox regression model and differences in outcomes were shown by Kaplan–Meier plots with significance and odds ratios (OR) calculated by Log-rank test/generalized Wilcoxon and continuity-corrected Woolf logit method. Results Patients with a TTV or ETV > 5 cm3 were more likely to develop distant metastases compared to patients with TTV (OR 6.69, 95% confidence interval [CI] 0.33–134.4, P=0.022) or ETV (OR 8.48, 95% CI 0.42–170.1, P=0.016) < 5 cm3. Additionally, PFS was significantly worse in patients with larger ETV ( P = 0.039; median PFS 51.87 months vs. 69.97 months). In contrast, stratification by median value of the established, caliper-based measurements showed no significant correlation with outcome parameters. Conclusion ETV, as surrogate of lesion vascularity, is a sensitive imaging biomarker for occurrence of extra-renal metastatic disease and PFS in patients with RCC.


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