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A multicenter assessment of interreader reliability of LI-RADS version 2018 for MRI and CT
Background: Various limitations have impacted research evaluating reader agreement
for Liver Imaging-Reporting and Data System (LI-RADS).
Purpose: To assess reader agreement of LI-RADS in an international multi-center, multireader setting using scrollable images.
Materials and Methods: This retrospective study used de-identified clinical multiphase
CT and MRI examinations and reports with at least one untreated observation from six
institutions and three countries; only qualifying examinations were submitted.
Examination dates were October 2017 – August 2018 at the coordinating center. One
untreated observation per examination was randomly selected using observation
identifiers, and its clinically assigned features were extracted from the report. The
corresponding LI-RADS v2018 category was computed as a re-scored clinical read. Each
examination was randomly assigned to two of 43 research readers who independently
scored the observation. Agreement for an ordinal modified four-category LI-RADS scale
(LR-1/2, LR-3, LR-4, LR-5/M/tumor in vein) was computed using intra-class correlation
coefficients (ICC). Agreement was also computed for dichotomized malignancy (LR-4/LR5/LR-M/LR-tumor in vein), LR-5, and LR-M. Agreement was compared between researchversus-research reads and research-versus-clinical reads.
Results: 484 patients (mean age, 62 years ±10 [SD]; 156 women; 93 CT, 391 MRI) were
included. ICCs for ordinal LI-RADS, dichotomized malignancy, LR-5, and LR-M were 0.68
(95% CI: 0.62, 0.74), 0.63 (95% CI: 0.56, 0.71), 0.58 (95% CI: 0.50, 0.66), and 0.46 (95%
CI: 0.31, 0.61) respectively. Research-versus-research reader agreement was higher
than research-versus-clinical agreement for modified four-category LI-RADS (ICC, 0.68
vs. 0.62, P = .03) and for dichotomized malignancy (ICC, 0.63 vs. 0.53, P = .005), but not
for LR-5 (P = .14) or LR-M (P = .94).
Conclusion: There was moderate agreement for Liver Imaging-Reporting and Data
System v2018 overall. For some comparisons, research-versus-research reader
agreement was higher than research-versus-clinical reader agreement, indicating
differences between the clinical and research environments that warrant further study
Quantitative characterization of hepatocellular carcinoma and metastatic liver tumor by CT perfusion
Dual-Energy CT Images: Pearls and Pitfalls
Dual-energy CT (DECT) is a tremendous innovation in CT technology that allows creation of numerous imaging datasets by enabling discrete acquisitions at more than one energy level. The wide range of images generated from a single DECT acquisition provides several benefits such as improved lesion detection and characterization, superior determination of material composition, reduction in the dose of iodine, and more robust quantification. Technological advances and the proliferation of various processing methods have led to the availability of diverse vendor-based DECT approaches, each with a different acquisition and image reconstruction process. The images generated from various DECT scanners differ from those from conventional single-energy CT because of differences in their acquisition techniques, material decomposition methods, image reconstruction algorithms, and postprocessing methods. DECT images such as virtual monochromatic images, material density images, and virtual unenhanced images have different imaging appearances, texture features, and quantitative capabilities. This heterogeneity creates challenges in their routine interpretation and has certain associated pitfalls. Some artifacts such as residual iodine on virtual unenhanced images and an appearance of pseudopneumatosis in a gas-distended bowel loop on material-density iodine images are specific to DECT, while others such as pseudoenhancement seen on virtual monochromatic images are also observed at single-energy CT. Recognizing the potential pitfalls associated with DECT is necessary for appropriate and accurate interpretation of the results of this increasingly important imaging tool. (C) RSNA, 202
Recognizing and Minimizing Artifacts at Dual-Energy CT
Dual-energy CT (DECT) is an exciting innovation in CT technology with profound capabilities to improve diagnosis and add value to patient care. Significant advances in this technology over the past decade have improved our ability to successfully adopt DECT into the clinical routine. To enable effective use of DECT, one must be aware of the pitfalls and artifacts related to this technology. Understanding the underlying technical basis of artifacts and the strategies to mitigate them requires optimization of scan protocols and parameters. The ability of radiologists and technologists to anticipate their occurrence and provide recommendations for proper selection of patients, intravenous and oral contrast media, and scan acquisition parameters is key to obtaining good-quality DECT images. In addition, choosing appropriate reconstruction algorithms such as image kernel, postprocessing parameters, and appropriate display settings is critical for preventing quantitative and qualitative interpretive errors. Therefore, knowledge of the appearances of these artifacts is essential to prevent errors and allows maximization of the potential of DECT. In this review article, the authors aim to provide a comprehensive and practical overview of possible artifacts that may be encountered at DECT across all currently available commercial clinical platforms. They also provide a pictorial overview of the diagnostic pitfalls and outline strategies for mitigating or preventing the occurrence of artifacts, when possible. The broadening scope of DECT applications necessitates up-to-date familiarity with these technologies to realize their full diagnostic potential. (C) RSNA, 202