Purpose: To compare the diagnostic accuracy of magnetic resonance imaging elastography (MRE) and anatomic MRI features in the diagnosis of severe hepatic fibrosis and cirrhosis.Materials and Methods: Three readers independently assessed presence of morphological changes associated with hepatic fibrosis in 72 patients with liver biopsy including: caudate to right lobe ratios, nodularity, portal venous hypertension (PVH) stigmata, posterior hepatic notch, expanded gallbladder fossa, and right hepatic vein caliber. Three readers measured shear stiffness values using quantitative shear stiffness maps (elastograms). Sensitivity, specificity, and diagnostic accuracy of stiffness values and each morphological feature were calculated. Interreader agreement was summarized using weighted kappa statistics. Intraclass correlation coefficient was used to assess interreader reproducibility of stiffness measurements. Binary logistic regression was used to assess interreader variability for dichotomized stiffness values and each morphological feature.Results: Using 5.9 kPa as a cutoff for differentiating F3‐F4 from F0‐2 stages, overall sensitivity, specificity, and diagnostic accuracy for MRE were 85.4%, 88.4%, and 87%, respectively. Overall interreader agreement for stiffness values was substantial, with an insignificant difference (P = 0.74) in the frequency of differentiating F3‐4 from F0‐2 fibrosis. Only hepatic nodularity and PVH stigmata showed moderately high overall accuracy of 69.4% and 72.2%. Interreader agreement was substantial only for PVH stigmata, moderate for C/R m, deep notch, and expanded gallbladder fossa. Only posterior hepatic notch (P = 0.82) showed no significant difference in reader rating.Conclusion: MRE is a noninvasive, accurate, and reproducible technique compared with conventional features of detecting severe hepatic fibrosis. J. Magn. Reson. Imaging 2012;35:1356–1364.

Improvements in radiologic imaging technology and therapeutic options available for management of tumors have necessitated the revision of guidelines for the imaging-based assessment of tumor response to therapy. The purpose of this article is to familiarize radiologists with the modifications to the Response Evaluation Criteria in Solid Tumors (RECIST) that have been incorporated in the latest version of the guidelines, RECIST 1.1. The most important differences between this version and the previous one, RECIST 1.0, include reductions in the maximum number of lesions per patient and per organ that may be targeted for measurement, augmentation of the criteria defining progressive disease, additional guidelines for reporting findings of lesions that are too small to measure and for measuring lesions that appear to have fragmented or coalesced at follow-up imaging, new criteria for characterizing lymphadenopathy, new criteria for selecting bone lesions and cystic lesions as targets for measurement, and the inclusion of findings at positron emission tomography among the indicators of disease response.

Aim: To determine whether socioeconomic status (SES; educational attainment and income) explains the racial gap in cancer beliefs, cognitions, and emotions in a national sample of American adults. Methods: For this cross-sectional study, data came from the Health Information National Trends Survey (HINTS) 2017, which included a nationally representative sample of American adults. The study enrolled 2277 adults who were either non-Hispanic Black (n = 409) or non-Hispanic White (n = 1868). Race, demographic factors (age and gender), SES (i.e., educational attainment and income), health access (insurance status, usual source of care), family history of cancer, fatalistic cancer beliefs, perceived risk of cancer, and cancer worries were measured. We ran structural equation models (SEMs) for data analysis. Results: Race and SES were associated with perceived risk of cancer, cancer worries, and fatalistic cancer beliefs, suggesting that non-Hispanic Blacks, low educational attainment and low income were associated with higher fatalistic cancer beliefs, lower perceived risk of cancer, and less cancer worries. Educational attainment and income only partially mediated the effects of race on cancer beliefs, emotions, and cognitions. Race was directly associated with fatalistic cancer beliefs, perceived risk of cancer, and cancer worries, net of SES. Conclusions: Racial gap in SES is not the only reason behind racial gap in cancer beliefs, cognitions, and emotions. Racial gap in cancer related beliefs, emotions, and cognitions is the result of race and SES rather than race or SES. Elimination of racial gap in socioeconomic status will not be enough for elimination of racial disparities in cancer beliefs, cognitions, and emotions in the United States.