Dual-energy computed tomographic (DECT) technology offers enhanced capabilities that may benefit oncologic imaging in the abdomen. By using two different energies, dual-energy CT allows material decomposition on the basis of energy-dependent attenuation profiles of specific materials. Although image acquisition with dual-energy CT is similar to that with single-energy CT, comprehensive postprocessing is able to generate not only images that are similar to single-energy CT (SECT) images, but a variety of other images, such as virtual unenhanced (VUE), virtual monochromatic (VMC), and material-specific iodine images. An increase in the conspicuity of iodine on low-energy VMC images and material-specific iodine images may aid detection and characterization of tumors. Use of VMC images of a desired energy level (40-140 keV) improves lesion-to-background contrast and the quality of vascular imaging for preoperative planning. Material-specific iodine images enable differentiation of hypoattenuating tumors from hypo- or hyperattenuating cysts and facilitate detection of isoattenuating tumors, such as pancreatic masses and peritoneal disease, thereby defining tumor targets for imaging-guided therapy. Moreover, quantitative iodine mapping may serve as a surrogate biomarker for monitoring effects of the treatment. Dual-energy CT is an innovative imaging technique that enhances the capabilities of CT in evaluating oncology patients.
Purpose
Detection of small renal masses is increasing with the use of cross-sectional imaging, although many incidental lesions have negligible metastatic potential. Among malignant masses, clear cell renal cell carcinoma is the most prevalent and aggressive subtype, and a method to identify such histology would aid in risk stratification. Our goal was to evaluate a likelihood scale for multiparametric magnetic resonance imaging in the diagnosis of clear cell histology.
Methods
Patients with cT1a masses who underwent MRI and partial or radical nephrectomy from December 2011 to July 2015 were retrospectively reviewed. Seven radiologists with different levels of experience and blinded to final pathology independently reviewed studies based on a predefined algorithm, and applied a clear cell likelihood score: 1) definitely not, 2) probably not, 3) equivocal, 4) probably, and 5) definitely. Binary classification determined the accuracy of clear cell versus ‘all other’ histologies, and inter-observer agreement was calculated with a weighted κ statistic.
Results
In total, 110 patients with 121 masses were identified. Mean tumor size was 2.4 cm and 50% were clear cell. Defining clear cell as scores ≥4 demonstrated sensitivity and specificity of 78% and 80%, respectively, while scores ≥3 were 95% and 58%, respectively. Inter-observer agreement was moderate to good, with a mean κ of 0.53.
Conclusions
A clear cell likelihood score with MRI can reasonably identify clear cell histology in small renal masses, and may reduce the number of diagnostic renal mass biopsies. Standardization of imaging protocols and reporting criteria are needed to improve inter-observer reliability.
70-keV images from ssDECT provide higher contrast enhancement and improved image quality for aorto-iliac CT when compared to SE-CT at 120 kVp. WD images are an effective substitute for TNE images with a potential for dose reduction.
Single-source dual-energy computed tomography can accurately predict UA and non-UA stone composition in vitro and in vivo. Substratification of non-UA stones of pure composition can be made in vitro and in vivo. In stones of mixed composition, the Zeff values reflect the dominant composition.
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