To assess feasibility of training a convolutional neural network (CNN) to automate liver segmentation across different imaging modalities and techniques used in clinical practice and to apply this technique to enable automation of liver biometry. Materials and Methods: A two-dimensional U-Net CNN was trained for liver segmentation in two stages by using 330 abdominal MRI and CT examinations. First, the neural network was trained with unenhanced multiecho spoiled gradient-echo images from 300 MRI examinations to yield multiple signal weightings. Then, transfer learning was used to generalize the CNN with additional images from 30 contrast material-enhanced MRI and CT examinations. Performance of the CNN was assessed by using a distinct multiinstitutional dataset curated from multiple sources (498 subjects). Segmentation accuracy was evaluated by computing Dice scores. These segmentations were used to compute liver volume from CT and T1-weighted MRI examinations and to estimate hepatic proton density fat fraction (PDFF) from multiecho T2*-weighted MRI examinations. Quantitative volumetry and PDFF estimates were compared between automated and manual segmentation by using Pearson correlation and Bland-Altman statistics. Results: Dice scores were 0.94 ± 0.06 for CT (n = 230), 0.95 ± 0.03 (n = 100) for T1-weighted MRI, and 0.92 ± 0.05 for T2*weighted MRI (n = 168). Liver volume measured with manual and automated segmentation agreed closely for CT (95% limits of agreement: −298 mL, 180 mL) and T1-weighted MRI (95% limits of agreement: −358 mL, 180 mL). Hepatic PDFF measured by the two segmentations also agreed closely (95% limits of agreement: −0.62%, 0.80%). Conclusion: By using a transfer-learning strategy, this study has demonstrated the feasibility of a CNN to be generalized to perform liver segmentation across different imaging techniques and modalities. With further refinement and validation, CNNs may have broad applicability for multimodal liver volumetry and hepatic tissue characterization.

Supported by a research scholarship from the Fonds de Recherche du Québec-Santé and Fondation de l'association des radiologistes du Québec (FRQS-ARQ #26993).q RSNA, 2017 Purpose:To determine in a large multicenter multireader setting the interreader reliability of Liver Imaging Reporting and Data System (LI-RADS) version 2014 categories, the major imaging features seen with computed tomography (CT) and magnetic resonance (MR) imaging, and the potential effect of reader demographics on agreement with a preselected nonconsecutive image set. Materials and Methods:Institutional review board approval was obtained, and patient consent was waived for this retrospective study. Ten image sets, comprising 38-40 unique studies (equal number of CT and MR imaging studies, uniformly distributed LI-RADS categories), were randomly allocated to readers. Images were acquired in unenhanced and standard contrast material-enhanced phases, with observation diameter and growth data provided. Readers completed a demographic survey, assigned LI-RADS version 2014 categories, and assessed major features. Intraclass correlation coefficient (ICC) assessed with mixed-model regression analyses was the metric for interreader reliability of assigning categories and major features. Results: Conclusion:ICC is good for final LI-RADS categorization and high for major feature characterization, with minimal reader demographic effect. Of note, our results using selected image sets from nonconsecutive examinations are not necessarily comparable with those of prior studies that used consecutive examination series.q RSNA, 2017

Background: Currently the treatment of non-alcoholic fatty liver disease (NAFLD) is based on weight loss through lifestyle changes, such as exercise combined with calorie-restricted dieting. Objectives: To assess the effects of a commercially available weight loss program based on a very low-calorie ketogenic diet (VLCKD) on visceral adipose tissue (VAT) and liver fat content compared to a standard low-calorie (LC) diet. As a secondary aim, we evaluated the effect on liver stiffness measurements. Methods: Open, randomized controlled, prospective pilot study. Patients were randomized and treated either with an LC or a VLCKD and received orientation and encouragement to physical activity equally for both groups. VAT, liver fat fraction, and liver stiffness were measured at baseline and after 2 months of treatment using magnetic resonance imaging. Paired t-tests were used for comparison of continuous variables between visits and unpaired test between groups. Categorical variables were compared using the χ 2-test. Pearson correlation was used to assess the association between VAT, anthropometric measures, and hepatic fat fraction. A significance level of the results was established at p < 0.05. Results: Thirty-nine patients (20 with VLCKD and 19 with LC) were evaluated at baseline and 2 months of intervention. Relative weight loss at 2 months was −9.59 ± 2.87% in the VLCKD group and −1.87 ± 2.4% in the LC group (p < 0.001). Mean reductions in VAT were −32.0 cm 2 for VLCKD group and −12.58 cm 2 for LC group (p < 0.05). Reductions in liver fat fraction were significantly more pronounced in the VLCKD group than in the LC group (4.77 vs. 0.79%; p < 0.005). Cunha et al. VLCKD for Visceral Fat and NAFLD Conclusion: Patients undergoing a VLCKD achieved superior weight loss, with significant VAT and liver fat fraction reductions when compared to the standard LC diet. The weight loss and rapid mobilization of liver fat demonstrated with VLCKD could serve as an effective alternative for the treatment of NAFLD.

Describe the at-risk patient groups and guideline recommendations for HCC surveillance.List the key differences among the three strategies for abbreviated MRI for HCC surveillance: nonenhanced, dynamic contrast-enhanced, and hepatobiliary phase contrast-enhanced abbreviated MRI.Discuss the abbreviated MRI protocols that are tailored for detection of HCC and involve the use of fewer sequences than a complete multiphase MRI examination.

In clinical setting, there is a high correlation between the GRE and SE MRE stiffness measurements, independently of the degree of liver fat infiltration measured by PDFF. A strong correlation between SE-MRE sequences is found even in patients with iron overload.  Advances in knowledge: Our study addresses liver iron and fat content simultaneously to describing the technical feasibility and correlation between different MRE sequences in consecutive unselected patients refereed for liver MRI. EPI SE-MRE should be considered an optimal alternative to assess liver fibrosis in patients in whom GRE-MRE failures, such as iron-overloaded, in pediatric, elderly, or severely ill populations.