Hyperechoic Renal Masses: Differentiation of Angiomyolipomas from Renal Cell Carcinomas using Tumor Size and Ultrasound Radiomics.

A retrospective single-center study was performed to assess the performance of ultrasound image-based texture analysis in differentiating angiomyolipoma (AML) from renal cell carcinoma (RCC) on incidental hyperechoic renal lesions. Ultrasound reports of patients from 2012 to 2017 were queried, and those with a hyperechoic renal mass <5 cm in diameter with further imaging characterization and/or pathological correlation were included. Quantitative texture analysis was performed using a model including 18 texture features. Univariate logistic regression was used to identify texture variables differing significantly between AML and RCC, and the performance of the model was measured using the area under the receiver operating characteristic (ROC) curve. One hundred thirty hyperechoic renal masses in 127 patients characterized as RCCs (25 [19%]) and AMLs (105 [81%]) were included. Size (odds ratio [OR] = 0.12, 95% confidence interval [CI]: 0.04-0.43, p < 0.001) and 4 of 18 texture features, including entropy (OR = 0.09, 95% CI: 0.01-0.81, p = 0.03), gray-level non-uniformity (OR = 0.12, 95% CI: 0.02-0.72, p = 0.02), long-run emphasis (OR = 0.49, 95% CI: 0.27-0.91, p = 0.02) and run-length non-uniformity (OR = 2.18, 95% CI: 1.14-4.16, p = 0.02) were able to differentiate AMLs from RCCs. The area under the ROC curve for the performance of the model, including texture features and size, was 0.945 (p < 0.001). Ultrasound image-based textural analysis enables differentiation of hyperechoic RCCs from AMLs with high accuracy, which improves further when combined with tumor size.

Computed Tomography-Guided Tumor Ablation: Analysis and Optimization of Computed Tomography Technique With Various Ablation Devices.

PURPOSE: Ablation device-associated computed tomography beam hardening artifacts can make tumor margin visualization and its relationship to the ablation applicator tip challenging. Determine optimal scanning conditions for currently-used applicators. MATERIALS AND METHODS: Eleven applicators were placed in ex vivo cow livers with implanted mock tumors, surrounded by bolus gel. Various computed tomography scans were performed at 440 mA with 5 mm thickness changing kVp (80, 100, 120, 140), scan time (0.5, 0.7, 1.0, 2.0 seconds), adaptive statistical iterative reconstruction (ASiR) (30, 60, 90), scan type (helical, axial), pitch (0.5, 0.94, 1.37, 1.75), and reconstruction algorithm (soft, standard, lung). Two radiologists blindly scored the images for image quality and artifact quantitatively. RESULTS: Cool-tip single (CTS) RF electrode (Covidien) performed significantly better than all other devices in both perceived image quality and artifact while Boston Scientific 4.0 RF electrode (Boston Scientific) underperformed (all P < 0.001), when not controlling for any other factors. An effect for artifact (P < 0.001) was found for kVp and device: for most conditions, 80 kVp was rated significantly lower than all other levels, whereas 120 and 140 performed significantly better than 100 and 80. No significant effect with ASiR level and device was found for the artifact. There was an effect observed for artifact (P < 0.001) between scan time and probe: for most devices, 0.5 seconds was rated significantly lower than all other scan times, but CTS was resilient-showing no difference from other scan times. Algorithm did not show any significant effects. Taking into account ASiR, kVp, and time, CTS outperformed all other devices. CONCLUSIONS: Higher kVp and scan times reduce device artifacts. It appears that CTS performs the best, even when considering ASiR, kVp, pitch, scan type, and scan time.