Purpose To assess the determinants of technical failure of magnetic resonance (MR) elastography of the liver in a large single-center study. Materials and Methods This retrospective study was approved by the institutional review board. Seven hundred eighty-one MR elastography examinations performed in 691 consecutive patients (mean age, 58 years; male patients, 434 [62.8%]) in a single center between June 2013 and August 2014 were retrospectively evaluated. MR elastography was performed at 3.0 T (n = 443) or 1.5 T (n = 338) by using a gradient-recalled-echo pulse sequence. MR elastography and anatomic image analysis were performed by two observers. Additional observers measured liver T2* and fat fraction. Technical failure was defined as no pixel value with a confidence index higher than 95% and/or no apparent shear waves imaged. Logistic regression analysis was performed to assess potential predictive factors of technical failure of MR elastography. Results The technical failure rate of MR elastography at 1.5 T was 3.5% (12 of 338), while it was higher, 15.3% (68 of 443), at 3.0 T. On the basis of univariate analysis, body mass index, liver iron deposition, massive ascites, use of 3.0 T, presence of cirrhosis, and alcoholic liver disease were all significantly associated with failure of MR elastography (P < .004); but on the basis of multivariable analysis, only body mass index, liver iron deposition, massive ascites, and use of 3.0 T were significantly associated with failure of MR elastography (P < .004). Conclusion The technical failure rate of MR elastography with a gradient-recalled-echo pulse sequence was low at 1.5 T but substantially higher at 3.0 T. Massive ascites, iron deposition, and high body mass index were additional independent factors associated with failure of MR elastography of the liver with a two-dimensional gradient-recalled-echo pulse sequence. RSNA, 2017.
CT is the preferred imaging modality for assessment of pancreatic diseases. Recent advances in CT (dual-energy CT, CT perfusion, CT volumetry, and radiogenomics) and emerging computational algorithms (machine learning) have the potential to further increase the value of CT in pancreatic imaging.
PurposeTo assess intra-observer, inter-observer and inter-modality (CT vs. MRI) reproducibility of liver surface nodularity (LSN) scores measured with software used for detection of liver fibrosis.MethodsThis IRB-approved retrospective study included patients with both abdominal CT and MRI within 6 months of histopathologic sampling. Two independent observers used post-processing software to quantify LSN scores on axial non-contrast CT (NCT), axial contrast-enhanced CT (CECT), axial T2-weighted (T2W) HASTE, and axial and coronal post-gadoxetic acid T1-weighted (T1W) images obtained during the hepatobiliary phase (HBP). Ten slices were used to acquire the LSN scores. Intra-observer, inter-observer, and inter-modality (CT vs. MRI) reproducibility were assessed with intraclass correlation coefficient (ICC) and coefficients of variability (CV). Accuracy for detection of cirrhosis was evaluated for each technique.Results26 patients (M/F 19/7, mean age 57 years), including 7 with cirrhosis (26.9%), were assessed. Technical failure occurred with NCT (1/23, 4.3%) and T2 HASTE (8/28, 28.6%). Intra-observer reproducibility was excellent for NCT, CECT, axial and coronal T1W HBP [ICC ≥ 0.92, CV ≤ 8%]. Inter-observer reproducibility was also excellent for NCT and CECT (ICC ≥ 0.95, CV ≤ 7.3%) and for coronal T1W HBP (ICC = 0.84, CV = 5.6%). There was fair to moderate agreement between CT and MRI (ICC 0.20–0.44). There were significant differences in mean LSN scores between non-cirrhotic and cirrhotic patients with NCT (2.6 vs. 4.2, p = 0.04) and T1W HBP (3.7 vs. 4.6; p = 0.01) images, with AUCs of 0.81 and 0.82, respectively.ConclusionsLSN measurement is highly reproducible with NCT and post-contrast T1W HBP on MRI, with different results obtained between CT and MRI.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.