Tanya Wolfson

Purpose The Liver Imaging Reporting and Data System (LI-RADS, LR) provides a framework for diagnosing hepatocellular carcinoma (HCC, LR-5). However, not all HCCs meet LR-5 criteria and are instead categorized as LR-M, probably or definitely malignant but not specific for HCC, necessitating biopsy for diagnosis. The purpose is to identify factors associated with HCC in LR-M observations. Methods This is an IRB-approved, retrospective analysis of participants from 8 institutions that had a LR-M observation on CT or MRI with corresponding histopathologic diagnosis. Demographics and biochemical data were examined. Central review using the LI-RADS v2018 algorithm was performed. Kappa statistics defined inter-reader agreement. Random forest and logistic regression analyses generated a model for HCC diagnosis. Results 162 participants with 162 LR-M observations were included. 46% of observations (74/162) were HCC and 37% were cholangiocarcinoma (60/162). Two of 34 imaging features– observation size and intra-lesion iron– showed moderate to strong inter-reader agreement (Kappa ≥ 0.60) while the remainder showed weak or no agreement (Kappa < 0.60). Random forest analysis showed biochemical features to be more predictive of HCC than imaging features. Logistic regression analysis of a model based on INR and AFP provided a 72% sensitivity and 61% specificity for HCC by Youden’s index and a 90% specificity threshold yielded 38% sensitivity, 75% positive predictive value, and 66% negative predictive value. Conclusions Our results show INR and AFP are associated with HCC in LR-M observations. A high-specificity threshold may assist in the non-invasive diagnosis of HCC in the appropriate setting. Summary statement In certain at-risk patients with a LR-M observation on diagnostic imaging, serum AFP and INR maybe useful tools for the non-invasive diagnosis of HCC.

Objective To investigate if size measurements of liver observations is more variable in the arterial phase as suggested by LI-RADS and assess potential higher instability in categorization in this particular phase. Secondarily, to assess inter- and intra-reader agreement for size across phases. Materials and methods Patients with liver cirrhosis who underwent multi-arterial phase MRI between 2017 and 2018 were retrospectively selected. Three radiologists measured liver observations in each phase, independently, in a random order. Mean size between early and late arterial phases (AP), 2, 3 and 10 min delay and the number of observations crossing the LI-RADS size thresholds (10 and 20 mm) per phase were compared using McNemar’s test. Reader agreement was evaluated using intraclass correlation coefficient (ICC) and bootstrap-based comparisons. Bonferroni’s correction was applied to pairwise comparisons. Results 94 observations (LR-3, LR-4, LR-5, and LR-M) were included. Mean sizes (mm) were late AP: 19.9 (95% CI 17.2, 24.2), 2 min delay: 19.8 (95% CI 17.1, 24.0), 3 min delay: 19.8 (95% CI 17.2, 24.0), 10 min delay: 20.2 (95% CI 17.5, 24.5) (p = 0.10–0.88). There was no difference between phases in number of observations that could have changed category due to variability in size (p = 0.546–1.000). Inter- and intra-reader agreement was excellent (ICC = 0.952–0.981). Conclusion Measurements of focal liver observations were consistent across all post-contrast imaging phases and we found no higher instability in LI-RADS category in any particular phase. Inter- and intra-reader agreement for size was excellent for each phase. Based on these findings, size measurement could be allowed on any post-contrast phase, including the arterial phase, if deemed appropriate by the radiologist.

To determine whether LI-RADS ancillary features predict longitudinal LR-3 observation category changes.

Purpose MRI proton density fat fraction (PDFF) can be calculated using magnitude (MRI-M) or complex (MRI-C) MRI data. The purpose of this study was to identify, assess, and compare the accuracy of common PDFF thresholds for MRI-M and MRI-C for assessing hepatic steatosis in patients with obesity, using histology as reference. Methods This two-center prospective study included patients undergoing MRI-C- and MRI-M-PDFF estimations within 3 days before weight loss surgery. Liver biopsy was performed, and histology-determined steatosis grades were used as reference standard. Using receiver operating characteristics (ROC) analysis on data pooled from both methods, single common thresholds for diagnosing and differentiating none or mild (0–1) from moderate to severe steatosis (2–3) were selected as the ones achieving the highest sensitivity while providing at least 90% specificity. Selection methods were cross-validated. Performances were compared using McNemar’s tests. Results Of 81 included patients, 54 (67%) had steatosis. The common PDFF threshold for diagnosing steatosis was 5.4%, which provided a cross-validated 0.88 (95% CI 0.77–0.95) sensitivity and 0.92 (0.75–0.99) specificity for MRI-M and 0.87 sensitivity (0.75–0.94) with 0.81 (0.61–0.93) specificity for MRI-C. The common PDFF threshold to differentiate steatosis grades 0–1 from 2 to 3 was 14.7%, which provided cross-validated 0.86 (95% CI 0.59–0.98) sensitivity and 0.95 (0.87–0.99) specificity for MRI-M and 0.93 sensitivity (0.68–0.99) with 0.97(0.89–0.99) specificity for MRI-C. Conclusion If independently validated, diagnostic thresholds of 5.4% and 14.7% could be adopted for both techniques for detecting and differentiating none to mild from moderate to severe steatosis, respectively, with high diagnostic accuracy.

Background: E-cigarettes are purchased through multiple channels, including general retail, online, and specialty smoke and vape shops. We examine how e-cigarette users’ primary purchase place relates to e-cigarette use and smoking cessation behaviors. Methods: Probability-based samples of the U.S. population who were current e-cigarette users were surveyed in 2014 (N = 879) and 2016 (N = 743), with responses combined for most analyses. E-cigarette use and smoking cessation behaviors were compared across users’ primary purchase place. Results: Higher percentages of vape shop (59.1%) and internet (42.9%) customers were current daily users of e-cigarettes compared to retail (19.7%) and smoke shop (23.2%) customers (p-values < 0.001). Higher percentages of vape shop (40.2%) and internet (35.1%) customers were also former smokers, compared to 17.7% of retail and 19.3% of smoke shop customers (p’s < 0.001). Among those smoking 12 months prior to survey, smoking cessation rates were higher for vape shop (22.2%) and internet customers (22.5%) than for retail customers (10.7%, p = 0.010 and p = 0.022, respectively), even though retail customers were more likely to use FDA-approved smoking cessation aids. The percentage of customers purchasing from vape shops increased from 20.4% in 2014 to 37.6% in 2016, surpassing general retail (27.7%) as the most likely channel in 2016. Conclusions: E-cigarette customers differed in significant ways by channels of purchase, most notably in their smoking cessation behaviors. Previous population studies have relied mostly on retail channel data, which accounted for less than 30% of all products sold by 2016. Future studies of e-cigarette use should consider a broader set of channels.

Magnetic resonance elastography (MRE) is a promising technique for noninvasive assessment of fibrosis, a major determinant of outcome in nonalcoholic fatty liver disease (NAFLD). However, data in children are limited. The purpose of this study was to determine the accuracy of MRE for the detection of fibrosis and advanced fibrosis in children with NAFLD and to assess agreement between manual and novel automated reading methods. We performed a prospective, multicenter study of two‐dimensional (2D) MRE in children with NAFLD. MR elastograms were analyzed manually at two reading centers, and using a new automated technique. Analysis using each approach was done independently. Correlations were determined between MRE analysis methods and fibrosis stage. Thresholds for classifying the presence of fibrosis and of advanced fibrosis were computed and cross‐validated. In 90 children with a mean age of 13.1 ± 2.4 years, median hepatic stiffness was 2.35 kPa. Stiffness values derived by each reading center were strongly correlated with each other (r = 0.83). All three analyses were significantly correlated with fibrosis stage (center 1, ρ = 0.53; center 2, ρ = 0.55; and automated analysis, ρ = 0.52; P < 0.001). Overall cross‐validated accuracy for detecting any fibrosis was 72.2% for all methods (95% confidence interval [CI], 61.8%‐81.1%). Overall cross‐validated accuracy for assessing advanced fibrosis was 88.9% (95% CI, 80.5%‐94.5%) for center 1, 90.0% (95% CI, 81.9%‐95.3%) for center 2, and 86.7% (95% CI, 77.9%‐92.9%) for automated analysis. Conclusion: 2D MRE can estimate hepatic stiffness in children with NAFLD. Further refinement and validation of automated analysis techniques will be an important step in standardizing MRE. How to best integrate MRE into clinical protocols for the assessment of NAFLD in children will require prospective evaluation. (Hepatology 2017;66:1474–1485)

In the problem of large-scale multiple testing the p-plot is a graphically based competitor to the notoriously weak Bonferroni method. The p-plot is less stringent and more revealing in that it gives a gauge of how many hypotheses are decidedly false. The method is elucidated and extended here: the bootstrap reveals bias and sampling error in the usual point estimates, a bootstrap-based confidence interval for the gauge is given, as well as two acceptably powerful blanket tests of significance. Guidelines for use are given, and interpretational pitfalls pointed out, in the discussion of a case study linking premortem neuropsychological and postmortem neuropathologic data in an HIV cohort study. (JINS, 1999, 5, 510–517)