The role of ancillary features for diagnosing hepatocellular carcinoma on CT: based on the Liver Imaging Reporting and Data System version 2017 algorithm.

AIM: To investigate the diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS) version 2017 for diagnosing hepatocellular carcinoma (HCC), by using major features only and combined major and ancillary features on computed tomography (CT). MATERIALS AND METHODS: A total of 147 HCC, 35 non-HCC malignancy, and 37 benign lesions in 205 patients at high risk of HCC were evaluated retrospectively, and the diagnostic performance of LI-RADS for diagnosing HCC were compared between using major features only and adopting major and ancillary features in combination. RESULTS: When using LR-5 as a predictor for diagnosing HCC, the diagnostic specificity (90.3% versus 91.7%), positive predictive value (92.3% versus 93.3%), and accuracy (68% versus 68.8%) were increased based on major and ancillary features in combination than just using major features on CT. When using LR-4/5 as a predictor for diagnosing HCC, the diagnostic sensitivity (78.9% versus 85.7%), negative predictive value (64.4% versus 72%), and accuracy (78.5% versus 82.2%) were increased while preserving a high specificity (77.8% versus 75%), according to major and ancillary features in combination rather than just using major features on CT. The LI-RADS categories of 8.7% (19/219) lesions were adjusted by adding the ancillary features on CT. CONCLUSION: Adding the ancillary features visible on CT can improve the diagnostic performance of the LI-RADS v2017 algorithm for diagnosing HCC, especially for LR-3 lesions.

[Study of formula for calculating body surface areas of the Chinese adults].

The body surface area of 100 Chinese adults (50 for each sex) was measured with the paper cast method and compared to the results estimated by the Stevenson's "height-weight-surface" formula. Our results shows that Stevenson's formula is no longer suitable for the Chinese. Our formulae for Chinese are as follows: SI=0.0061 x H + 0.0124 x W - 0.0099 (for both sexes), SII=0.0057 x H + 0.0121 - W + 0.0882 (for male), SIII=0.0073 H + 0.0127 x W - 0.2106 (for female) H: body height, W: body weight, S: body surface area