Can Current Preoperative Imaging Be Used to Detect Microvascular Invasion of XXXX ?

@entity5 @entity157 @entity1 @entity3
UNASSIGNED: Purpose To determine the accuracy of imaging features, such as @entity5 dimension, multinodularity, nonsmooth @entity5 margins, peritumoral enhancement, and radiogenomic algorithm based on the association between imaging features (internal arteries and hypoattenuating halos) and gene expression that the authors called two-trait predictor of @entity3 (TTPVI), in the prediction of microvascular invasion (MVI) in @entity157 ( @entity157 ). Materials and Methods This single-center retrospective study was approved by the institutional review board, and the requirement for informed consent was waived. One hundred twenty-five @entity1 (median age, 63 years; interquartile range, 53-71 years) with a diagnosis of @entity157 and indications for hepatic resection were included. Two observers independently reviewed radiologic images to evaluate the following features for MVI: maximum diameter, number of lesions, @entity5 margins, TTPVI, and peritumoral enhancement. Interobserver agreement was checked, and diagnostic accuracy of radiologic features was investigated. Results The total number of @entity157 nodules was 140. Large @entity5 size, nonsmooth @entity5 margins, TTPVI, and peritumoral enhancement were significantly related to the presence of MVI (P < .05 in all cases and for both observers). Multinodularity was not significantly related (P = .158). Moreover, the diagnostic accuracy of the three "worrisome" radiologic features (nonsmooth @entity5 margins, peritumoral enhancement, and TTPVI) was associated with @entity5 size: The negative predictive value of the absence of worrisome features decreased from 0.84 for observer 1 and 0.91 for observer 2 for @entity5 smaller than 2 cm to 0.56 and 0.71, respectively, for @entity5 larger than 5 cm, whereas the presence of all three worrisome features returned to a positive predictive value of 0.95 for observer 1 and 0.96 for observer 2 independent of @entity5 size, with no significant interobserver differences (P > .10). Conclusion "Worrisome" imaging features, such as @entity5 dimension, nonsmooth @entity5 margins, peritumoral enhancement, and TTPVI, have high accuracy in the prediction of MVI in @entity157 . (  ) RSNA, 2015 Online supplemental material is available for this article.
