Interpretation, Reporting, and Clinical Applications of Liver MR Elastography.

Chronic liver disease is highly prevalent and often leads to fibrosis or cirrhosis and complications such as liver failure and hepatocellular carcinoma. The diagnosis and staging of liver fibrosis is crucial to determine management and mitigate complications. Liver biopsy for histologic assessment has limitations such as sampling bias and high interreader variability that reduce precision, which is particularly challenging in longitudinal monitoring. MR elastography (MRE) is considered the most accurate noninvasive technique for diagnosing and staging liver fibrosis. In MRE, low-frequency vibrations are applied to the abdomen, and the propagation of shear waves through the liver is analyzed to measure liver stiffness, a biomarker for the detection and staging of liver fibrosis. As MRE has become more widely used in clinical care and research, different contexts of use have emerged. This review focuses on the latest developments in the use of MRE for the assessment of liver fibrosis; provides guidance for image acquisition and interpretation; summarizes diagnostic performance, along with thresholds for diagnosis and staging of liver fibrosis; discusses current and emerging clinical applications; and describes the latest technical developments.

Risk Factors for Hospitalization Duration Longer Than 24 Hours Following Percutaneous Radiofrequency Ablation of Liver Tumours.

PURPOSE: Prior studies have described complications of radiofrequency ablation (RFA) of liver tumours. The aim of this study was to identify risk factors for hospitalization duration longer than 24 hours following RFA of liver tumours. METHODS: This retrospective, single-centre study included patients with liver tumours undergoing RFA between October 2017 and July 2020. Medical records were reviewed to collect patient, tumours, and procedure characteristics for each RFA session. The association between potential risk factors and duration of hospitalization (less than or more than 24 hours) was analyzed using univariate and multivariate logistic regressions. RESULTS: Our study included 291 patients (mean age: 65.2 ± 11.2 [standard deviation]; 201 men) undergoing 324 RFA sessions. Sixty-eight sessions (21.0%) resulted in hospitalization of more than 24 hours. Multivariate analysis identified each additional needle insertion per session (OR 1.4; 95% CI [1.1-1.9]; P = .02), RFA performed in segment V (OR 2.8; 95% CI [1.4-5.7]; P = .004), and use of artificial pneumothorax (OR 14.5; 95% CI [1.4-146.0]; P = .02) as potential risk factors. A history of hepatic encephalopathy (OR 2.6; 95% CI [1.1-6.0]; P = .03) was only significant in univariate analysis. Post-hoc, subgroup analysis of patients with hepatocellular carcinoma (69.8%) did not identify other risk factors. CONCLUSION: Risk factors for a hospitalization duration longer than 24 hours include a higher number of needle insertions per session, radiofrequency ablation in segment V, and use of an artificial pneumothorax.

Ultrasound Shear Wave Attenuation Imaging for Grading Liver Steatosis in Volunteers and Patients With Non-alcoholic Fatty Liver Disease: A Pilot Study.

OBJECTIVE: The aims of the work described here were to assess shear wave attenuation (SWA) in volunteers and patients with non-alcoholic fatty liver disease (NAFLD) and compare its diagnostic performance with that of shear wave dispersion (SWD), magnetic resonance imaging (MRI) proton density fat fraction (PDFF) and biopsy. METHODS: Forty-nine participants (13 volunteers and 36 NAFLD patients) were enrolled. Ultrasound and MRI examinations were performed in all participants. Biopsy was also performed in patients. SWA was used to assess histopathology grades as potential confounders. The areas under curves (AUCs) of SWA, SWD and MRI-PDFF were assessed in different steatosis grades by biopsy. Youden's thresholds of SWA were obtained for steatosis grading while using biopsy or MRI-PDFF as the reference standard. RESULTS: Spearman's correlations of SWA with histopathology (steatosis, inflammation, ballooning and fibrosis) were 0.89, 0.73, 0.62 and 0.31, respectively. Multiple linear regressions of SWA confirmed the correlation with steatosis grades (adjusted R2 = 0.77, p < 0.001). The AUCs of MRI-PDFF, SWA and SWD were respectively 0.97, 0.99 and 0.94 for S0 versus ≥S1 (p > 0.05); 0.94, 0.98 and 0.78 for ≤S1 versus ≥S2 (both MRI-PDFF and SWA were higher than SWD, p < 0.05); and 0.90, 0.93 and 0.68 for ≤S2 versus S3 (both SWA and MRI-PDFF were higher than SWD, p < 0.05). SWA's Youden thresholds (Np/m/Hz) (sensitivity, specificity) for S0 versus ≥S1, ≤S1 versus ≥S2 and ≤S2 versus S3 were 1.05 (1.00, 0.92), 1.37 (0.96, 0.96) and 1.51 (0.83, 0.87), respectively. These values were 1.16 (1.00, 0.81), 1.49 (0.91, 0.82) and 1.67 (0.87, 0.92) when considering MRI-PDFF as the reference standard. CONCLUSION: In this pilot study, SWA increased with increasing steatosis grades, and its diagnostic performance was higher than that of SWD but equivalent to that of MRI-PDFF.

Differentiation of focal nodular hyperplasia and hepatocellular adenoma using qualitative and quantitative imaging features and classification and regression tree analysis.

PURPOSE: To assess qualitative and quantitative analysis of gadoxetate disodium-enhanced hepatobiliary phase MR imaging (MRI) and assess the performance of classification and regression tree analysis for the differentiation of focal nodular hyperplasia (FNH) and hepatocellular adenoma (HCA). MATERIALS AND METHODS: This retrospective study was approved by our local ethics committee. One hundred seventy patients suspected of having FNH or HCA underwent gadoxetate disodium-enhanced MRI. The reference standard was either pathology or follow-up imaging. Two readers reviewed images to identify qualitative imaging features and measure signal intensity on unenhanced, dynamic, and hepatobiliary phase images. For quantitative analysis, contrast enhancement ratio (CER), lesion-to-liver contrast (LLC), signal intensity ratio (SIR), and relative signal enhancement ratio (RSER) were calculated. A classification and regression tree (CART) analysis was developed. RESULTS: Eighty-five patients met the inclusion criteria, with a total of 97 FNHs and 43 HCAs. For qualitative analysis, the T1 signal intensity on the hepatobiliary phase provided the highest overall classification performance (91.9% sensitivity, 90.1% specificity, and 90.9% accuracy). For quantitative analysis, RSER in the hepatobiliary phase with a threshold of 0.723 provided the highest classification performance (92.6% sensitivity and 89.4% specificity) to differentiate FNHs from HCAs. A CART model based on five qualitative imaging features provided an accuracy of 94.4% (95% confidence interval 90.0-98.9%). CONCLUSION: Gadoxetate disodium-enhanced hepatobiliary phase provides high diagnostic performance as demonstrated in quantitative and qualitative analysis in differentiation of FNH and HCA, supported by a CART decision model.

Findings on Diagnostic Magnetic Resonance Imaging Before Radiotherapy for Prostate Cancer.

PURPOSE: Pre-treatment diagnostic magnetic resonance imaging (MRI) is used in prostate cancer detection and staging; however, little is known about its potential for radiotherapy treatment decision, or its prognostic value. We investigated the findings on pre-treatment MRI and its potential influence on treatment decisions, and its ability to predict biochemical recurrence in patients treated with radiotherapy. METHODS: Files of patients treated by radiotherapy from 2014 to 2022 were searched for if they had had an MRI within 12 months before radiotherapy. Prostate Imaging Reporting & Data System (PI-RADS) score, index lesion diameter and the presence of organ confined disease or extra-prostatic extension were correlated with their Cancer of the Prostate Risk Assessment (CAPRA) score. Distribution of radiological and clinical features between groups were estimated using a chi-squared test. RESULTS: Out of 1280 patients, 314 (24.5%) had an MRI. The distribution depended on the treatment received: 22.5% who received low-dose rate (LDR) brachytherapy as monotherapy, 24.0% treated with high-dose rate (HDR) boost and 32.0% treated with external-beam radiotherapy (EBRT) (P = .017). The CAPRA score significantly correlated with the PI-RADS score (r = .342, P < .01) and the diameter of the index lesion (r = .473, P < .01). A clinically significant number of 22% patients with CAPRA ≤ 3 disease presented with lesions ≥15 mm and were less likely to be treated with LDR monotherapy (P < .01). 39 patients had a recurrence, only 5 had an MRI: 4 had a lesion of ≥20 mm and 3 a seminal vesicle invasion. CONCLUSION: More than twenty percent of patients with CAPRA ≤3 presented on MRI a ≥15 mm lesion. An MRI could potentially affect treatment choice, and although exploratory our results suggest an important prognostic potential.

Effect of magnetic resonance imaging pre-processing on the performance of model-based prostate tumor probability mapping.

Objective. Multi-parametric magnetic resonance imaging (mpMRI) has become an important tool for the detection of prostate cancer in the past two decades. Despite the high sensitivity of MRI for tissue characterization, it often suffers from a lack of specificity. Several well-established pre-processing tools are publicly available for improving image quality and removing both intra- and inter-patient variability in order to increase the diagnostic accuracy of MRI. To date, most of these pre-processing tools have largely been assessed individually. In this study we present a systematic evaluation of a multi-step mpMRI pre-processing pipeline to automate tumor localization within the prostate using a previously trained model.Approach. The study was conducted on 31 treatment-naïve prostate cancer patients with a PI-RADS-v2 compliant mpMRI examination. Multiple methods were compared for each pre-processing step: (1) bias field correction, (2) normalization, and (3) deformable multi-modal registration. Optimal parameter values were estimated for each step on the basis of relevant individual metrics. Tumor localization was then carried out via a model-based approach that takes both mpMRI and prior clinical knowledge features as input. A sequential optimization approach was adopted for determining the optimal parameters and techniques in each step of the pipeline.Main results. The application of bias field correction alone increased the accuracy of tumor localization (area under the curve (AUC) = 0.77;p-value = 0.004) over unprocessed data (AUC = 0.74). Adding normalization to the pre-processing pipeline further improved diagnostic accuracy of the model to an AUC of 0.85 (p-value = 0.000 12). Multi-modal registration of apparent diffusion coefficient images to T2-weighted images improved the alignment of tumor locations in all but one patient, resulting in a slight decrease in accuracy (AUC = 0.84;p-value = 0.30).Significance. Overall, our findings suggest that the combined effect of multiple pre-processing steps with optimal values has the ability to improve the quantitative classification of prostate cancer using mpMRI. Clinical trials: NCT03378856 and NCT03367702.

Quantitative ultrasound, elastography, and machine learning for assessment of steatosis, inflammation, and fibrosis in chronic liver disease.

OBJECTIVE: To develop a quantitative ultrasound (QUS)- and elastography-based model to improve classification of steatosis grade, inflammation grade, and fibrosis stage in patients with chronic liver disease in comparison with shear wave elastography alone, using histopathology as the reference standard. METHODS: This ancillary study to a prospective institutional review-board approved study included 82 patients with non-alcoholic fatty liver disease, chronic hepatitis B or C virus, or autoimmune hepatitis. Elastography measurements, homodyned K-distribution parametric maps, and total attenuation coefficient slope were recorded. Random forests classification and bootstrapping were used to identify combinations of parameters that provided the highest diagnostic accuracy. Receiver operating characteristic (ROC) curves were computed. RESULTS: For classification of steatosis grade S0 vs. S1-3, S0-1 vs. S2-3, S0-2 vs. S3, area under the receiver operating characteristic curve (AUC) were respectively 0.60, 0.63, and 0.62 with elasticity alone, and 0.90, 0.81, and 0.78 with the best tested model combining QUS and elastography features. For classification of inflammation grade A0 vs. A1-3, A0-1 vs. A2-3, A0-2 vs. A3, AUCs were respectively 0.56, 0.62, and 0.64 with elasticity alone, and 0.75, 0.68, and 0.69 with the best model. For classification of liver fibrosis stage F0 vs. F1-4, F0-1 vs. F2-4, F0-2 vs. F3-4, F0-3 vs. F4, AUCs were respectively 0.66, 0.77, 0.72, and 0.74 with elasticity alone, and 0.72, 0.77, 0.77, and 0.75 with the best model. CONCLUSION: Random forest models incorporating QUS and shear wave elastography increased the classification accuracy of liver steatosis, inflammation, and fibrosis when compared to shear wave elastography alone.

MRI-based R2* mapping in patients with suspected or known iron overload.

PURPOSE: R2* relaxometry is a quantitative method for assessment of iron overload. The purpose is to analyze the cross-sectional relationships between R2* in organs across patients with primary and secondary iron overload. Secondary analyses were conducted to analyze R2* according to treatment regimen. METHODS: This is a retrospective, cross-sectional, institutional review board-approved study of eighty-one adult patients with known or suspected iron overload. R2* was measured by segmenting the liver, spleen, bone marrow, pancreas, renal cortex, renal medulla, and myocardium using breath-hold multi-echo gradient-recalled echo imaging at 1.5 T. Phlebotomy, transfusion, and chelation therapy were documented. Analyses included correlation, Kruskal-Wallis, and post hoc Dunn tests. p < 0.01 was considered significant. RESULTS: Correlations between liver R2* and that of the spleen, bone marrow, pancreas, and heart were respectively 0.49, 0.33, 0.27, and 0.34. R2* differed between patients with primary and secondary overload in the liver (p < 0.001), spleen (p < 0.001), bone marrow (p < 0.01), renal cortex (p < 0.001), and renal medulla (p < 0.001). Liver, spleen, and bone marrow R2* were higher in thalassemia than in hereditary hemochromatosis (all p < 0.01). Renal cortex R2* was higher in sickle cell disease than in hereditary hemochromatosis (p < 0.001) and in thalassemia (p < 0.001). Overall, there was a trend toward lower liver R2* in patients assigned to phlebotomy and higher liver R2* in patients assigned to transfusion and chelation therapy. CONCLUSION: R2* relaxometry revealed differences in degree or distribution of iron overload between organs, underlying etiologies, and treatment.

Intravoxel incoherent motion diffusion-weighted MRI for the characterization of inflammation in chronic liver disease.

OBJECTIVE: To evaluate the diagnostic performance of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for grading hepatic inflammation. METHODS: In this retrospective cross-sectional dual-center study, 91 patients with chronic liver disease were recruited between September 2014 and September 2018. Patients underwent 3.0-T MRI examinations within 6 weeks from a liver biopsy. IVIM parameters, perfusion fraction (f), diffusion coefficient (D), and pseudo-diffusion coefficient (D*), were estimated using a voxel-wise nonlinear regression on DWI series (10 b-values from 0 to 800 s/mm2). The reference standard was histopathological analysis of hepatic inflammation grade, steatosis grade, and fibrosis stage. Intraclass correlation coefficients (ICC), univariate and multivariate correlation analyses, and areas under receiver operating characteristic curves (AUC) were assessed. RESULTS: Parameters f, D, and D* had ICCs of 0.860, 0.839, and 0.916, respectively. Correlations of f, D, and D* with inflammation grade were ρ = - 0.70, p < 0.0001; ρ = 0.10, p = 0.35; and ρ = - 0.27, p = 0.010, respectively. When adjusting for fibrosis and steatosis, the correlation between f and inflammation (p < 0.0001) remained, and that between f and fibrosis was also significant to a lesser extent (p = 0.002). AUCs of f, D, and D* for distinguishing inflammation grades 0 vs. ≥ 1 were 0.84, 0.53, and 0.70; ≤ 1 vs. ≥ 2 were 0.88, 0.57, and 0.60; and ≤ 2 vs. 3 were 0.86, 0.54, and 0.65, respectively. CONCLUSION: Perfusion fraction f strongly correlated, D very weakly correlated, and D* weakly correlated with inflammation. Among all IVIM parameters, f accurately graded inflammation and showed promise as a biomarker of hepatic inflammation. KEY POINTS: • IVIM parameters derived from DWI series with 10 b-values are reproducible for liver tissue characterization. • This retrospective two-center study showed that perfusion fraction provided good diagnostic performance for distinguishing dichotomized grades of inflammation. • Fibrosis is a significant confounder on the association between inflammation and perfusion fraction.

MRI cine-tagging of cardiac-induced motion for noninvasive staging of liver fibrosis.

BACKGROUND: MR elastography is a noninvasive technique that provides high diagnostic accuracy for the staging of liver fibrosis; however, it requires external hardware and mainly assesses the right lobe. PURPOSE: To evaluate the diagnostic performance of MRI cine-tagging for staging fibrosis in the left liver lobe, using biopsy as the reference standard. STUDY TYPE: Institutional Review Board (IRB)-approved two-center prospective study. POPULATION: Seventy-six patients with chronic liver disease who underwent an MRI cine-tagging examination and a liver biopsy within a 6-week interval. FIELD STRENGTH/SEQUENCE: 2D-GRE multislice sequence at 3.0T with spatial modulation of the magnetization preparation sequence and peripheral pulse-wave triggering on two coronal slices chosen underneath the heart apex to capture maximal deformation with consecutive breath-holds adapted to patient cardiac frequency. ASSESSMENT: A region of interest was selected in the liver close to the heart apex. Maximal strain was evaluated with the harmonic phase (HARP) technique. STATISTICAL TESTS: Spearman's correlation, Kruskal-Wallis test, Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were performed. RESULTS: Liver strain measured on tagged images decreased with higher histological fibrosis stage (ρ = -0.68, P < 0.0001). Strain values were significantly different between all fibrosis stages (P < 0.0001), and between groups of fibrosis stages ≤F3 vs. F4 (P < 0.05). Areas under the ROC curves were 0.95 (95% confidence interval: 0.89-1.00) to distinguish fibrosis stages F0 vs. F4, 0.81 (0.70-0.92) for stages F0 vs. ≥F1, 0.84 (0.76-0.93) for stages ≤F1 vs. ≥F2, 0.86 (0.78-0.94) for stages ≤F2 vs. ≥F3, and 0.87 (0.77-0.96) for stages ≤F3 vs. F4. DATA CONCLUSION: MRI cine-tagging is a promising technique for measuring liver strain without additional elastography hardware. It could be used to assess the left liver lobe as a complement to current techniques assessing the right lobe. LEVEL OF EVIDENCE: 1 Technical Efficacy: 3 J. Magn. Reson. Imaging 2020;51:1570-1580.

Assessment of hepatocellular carcinoma treatment response with LI-RADS: a pictorial review.

Computed tomography (CT) and magnetic resonance imaging (MRI) play critical roles for assessing treatment response of hepatocellular carcinoma (HCC) after locoregional therapy. Interpretation is challenging because posttreatment imaging findings depend on the type of treatment, magnitude of treatment response, time interval after treatment, and other factors. To help radiologists interpret and report treatment response in a clear, simple, and standardized manner, the Liver Imaging Reporting and Data System (LI-RADS) has developed a Treatment Response (LR-TR) algorithm. Introduced in 2017, the system provides criteria to categorize response of HCC to locoregional treatment (e.g., chemical ablation, energy-based ablation, transcatheter therapy, and radiation therapy). LR-TR categories include Nonevaluable, Nonviable, Equivocal, and Viable. LR-TR does not apply to patients on systemic therapies. This article reviews the LR-TR algorithm; discusses locoregional therapies for HCC, treatment concepts, and expected posttreatment findings; and illustrates LI-RADS treatment response assessment with CT and MRI.

Prospective comparison of transient, point shear wave, and magnetic resonance elastography for staging liver fibrosis.

OBJECTIVES: To perform head-to-head comparisons of the feasibility and diagnostic performance of transient elastography (TE), point shear-wave elastography (pSWE), and magnetic resonance elastography (MRE). METHODS: This prospective, cross-sectional, dual-center imaging study included 100 patients with known or suspected chronic liver disease caused by hepatitis B or C virus, nonalcoholic fatty liver disease, or autoimmune hepatitis identified between 2014 and 2018. Liver stiffness measured with the three elastographic techniques was obtained within 6 weeks of a liver biopsy. Confounding effects of inflammation and steatosis on association between fibrosis and liver stiffness were assessed. Obuchowski scores and AUCs for staging fibrosis were evaluated and the latter were compared using the DeLong method. RESULTS: TE, pSWE, and MRE were technically feasible and reliable in 92%, 79%, and 91% subjects, respectively. At univariate analysis, liver stiffness measured by all techniques increased with fibrosis stages and inflammation and decreased with steatosis. For classification of dichotomized fibrosis stages, the AUCs were significantly higher for distinguishing stages F0 vs. ≥ F1 with MRE than with TE (0.88 vs. 0.71; p < 0.05) or pSWE (0.88 vs. 0.73; p < 0.05), and for distinguishing stages ≤ F1 vs. ≥ F2 with MRE than with TE (0.85 vs. 0.75; p < 0.05). TE, pSWE, and MRE Obuchowski scores for staging fibrosis stages were respectively 0.89 (95% CI 0.85-0.93), 0.90 (95% CI 0.85-0.94), and 0.94 (95% CI 0.91-0.96). CONCLUSION: MRE provided a higher diagnostic performance than TE and pSWE for staging early stages of liver fibrosis. TRIAL REGISTRATION: NCT02044523 KEY POINTS: • The technical failure rate was similar between MRE and US-based elastography techniques. • Liver stiffness measured by MRE and US-based elastography techniques increased with fibrosis stages and inflammation and decreased with steatosis. • MRE provided a diagnostic accuracy higher than US-based elastography techniques for staging of early stages of histology-determined liver fibrosis.

Dynamic contrast-enhanced MRI to assess hepatocellular carcinoma response to Transarterial chemoembolization using LI-RADS criteria: A pilot study.

PURPOSE: To identify quantitative dynamic contrast-enhanced (DCE)-MRI perfusion parameters indicating tumor response of hepatocellular carcinoma (HCC) to transarterial chemoembolization (TACE). MATERIALS AND METHODS: This prospective pilot study was approved by our institutional review board; written and informed consent was obtained for each participant. Patients underwent DCE-MRI examinations before and after TACE. A variable flip-angle unenhanced 3D mDixon sequence was performed for T1 mapping. A dynamic 4D mDixon sequence was performed after contrast injection for assessing dynamic signal enhancement. Nonparametric analysis was conducted on the time-intensity curves. Parametric analysis was performed on the time-concentration curves using a dual-input single-compartment model. Treatment response according to Liver Reporting and Data System (LI-RADS) v2018 was used as the reference standard. The comparisons within groups (before vs. after treatment) and between groups (nonviable vs. equivocal or viable tumor) were performed using nonparametric bootstrap taking into account the clustering effect of lesions in patients. RESULTS: Twenty-eight patients with 52 HCCs (size: 10-104 mm) were evaluated. For nonviable tumors (n = 27), time to peak increased from 62.5 ±â€¯18.2 s before to 83.3 ±â€¯12.8 s after treatment (P< 0.01). For equivocal or viable tumors (n = 25), time to peak and mean transit time significantly increased (from 54.4 ±â€¯24.1 s to 69.5 ±â€¯18.9 s, P < 0.01 and from 14.2 ±â€¯11.8 s to 33.9 ±â€¯36.8 s, P= 0.01, respectively) and the transfer constant from the extracellular and extravascular space to the central vein significantly decreased from 14.8 ±â€¯14.1 to 8.1 ±â€¯9.1 s-1 after treatment (P= 0.01). CONCLUSION: This prospective pilot DCE-MRI study showed that time to peak significantly changed after TACE treatment for both groups (nonviable tumors and equivocal or viable tumors). In our cohort, several perfusion parameters may provide an objective marker for differentiation of treatment response after TACE in HCC patients.

Cost-Utility Analysis of Imaging for Surveillance and Diagnosis of Hepatocellular Carcinoma.

OBJECTIVE. The purpose of this study is to compare imaging-based surveillance and diagnostic strategies in patients at risk for hepatocellular carcinoma (HCC) while taking into account technically inadequate examinations and patient compliance. MATERIALS AND METHODS. A Markov model simulated seven strategies for HCC surveillance and diagnosis in patients with cirrhosis: strategy A, ultrasound (US) for surveillance and CT for diagnosis; strategy B, US for surveillance and complete MRI for diagnosis; strategy C, US for surveillance and CT for inadequate or positive surveillance; strategy D, US for surveillance and complete MRI for inadequate or positive surveillance; strategy E, surveillance and diagnosis with CT followed by complete MRI for inadequate surveillance; strategy F, surveillance and diagnosis with complete MRI followed by CT for inadequate surveillance; and strategy G, surveillance with abbreviated MRI followed by CT for inadequate surveillance or complete MRI for positive surveillance. Two compliance scenarios were evaluated: optimal and conservative. For each scenario, the most cost-effective strategy was based on a willingness-to-pay threshold of $50,000 (Canadian) per quality-adjusted life year (QALY). Sensitivity analyses were performed. RESULTS. Base-case analysis revealed that strategy E was the most cost-effective when compliance was optimal ($13,631/QALY), and strategy G was the most cost-effective when compliance was conservative ($39,681/QALY). Sensitivity analyses supported the base-case analysis in the optimal compliance scenario, but several parameters altered the most cost-effective strategy in the conservative compliance scenario. CONCLUSION. In an optimal compliance scenario, CT for HCC surveillance and diagnosis and complete MRI for inadequate CT was most cost-effective. In a conservative compliance scenario, abbreviated MRI may be an alternative to US-based surveillance.

LI-RADS for CT diagnosis of hepatocellular carcinoma: performance of major and ancillary features.

PURPOSE: To evaluate the diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS) v2017 major features, the impact of ancillary features, and categories on contrast-enhanced computed tomography (CECT) for the diagnosis of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: This retrospective study included 59 patients (104 observations including 72 HCCs) with clinical suspicion of HCC undergoing CECT between 2013 and 2016. Two radiologists independently assessed major and ancillary imaging features for each liver observation and assigned a LI-RADS category based on major features only and in combination with ancillary features. The composite reference standard included pathology or imaging. Per-lesion estimates of diagnostic performance of major features, ancillary features, and LI-RADS categories were assessed by generalized estimating equation models. RESULTS: Major features (arterial phase hyperenhancement, washout, capsule, and threshold growth) respectively had a sensitivity of 86.1%, 81.6%, 20.7%, and 26.1% and specificity of 39.3%, 67.9%, 89.9%, and 85.0% for HCC. Ancillary features (ultrasound visibility as discrete nodule, subthreshold growth, and fat in mass more than adjacent liver) respectively had a sensitivity of 42.6%, 50.8%, and 15.1% and a specificity of 79.2%, 66.9%, and 96.4% for HCC. Ancillary features modified the final category in 4 of 104 observations. For HCC diagnosis, categories LR-3, LR-4, LR-5, and LR-TIV (tumor in vein) had a sensitivity of 5.3%, 29.0%, 53.7%, and 10.7%; and a specificity of 49.1%, 84.4%, 97.3%, and 96.4%, respectively. CONCLUSION: On CT, LR-5 category has near-perfect specificity for the diagnosis of HCC and ancillary features modifies the final category in few observations.

LI-RADS Version 2018 Ancillary Features at MRI.

The Liver Imaging Reporting and Data System (LI-RADS) standardizes performance of liver imaging in patients at risk for hepatocellular carcinoma (HCC) as well as interpretation and reporting of the results. Developed by experts in liver imaging and supported by the American College of Radiology, LI-RADS assigns to observations categories that reflect the relative probability of benignity, HCC, or other malignancy. While category assignment is based mainly on major imaging features, ancillary features may be applied to improve detection and characterization, increase confidence, or adjust LI-RADS categories. Ancillary features are classified as favoring malignancy in general, HCC in particular, or benignity. Those favoring malignancy in general or HCC in particular may be used to upgrade by a maximum of one category up to LR-4; those favoring benignity may be used to downgrade by a maximum of one category. If there are conflicting ancillary features (ie, one or more favoring malignancy and one or more favoring benignity), the category should not be adjusted. Ancillary features may be seen at diagnostic CT, MRI performed with extracellular agents, or MRI performed with hepatobiliary agents, with the exception of one ancillary feature assessed at US. This article focuses on LI-RADS version 2018 ancillary features seen at MRI. Specific topics include rules for ancillary feature application; definitions, rationale, and illustrations with clinical MRI examples; summary of evidence and diagnostic performance; pitfalls; and future directions. ©RSNA, 2018.

LI-RADS for MR Imaging Diagnosis of Hepatocellular Carcinoma: Performance of Major and Ancillary Features.

Purpose To evaluate the performance of major features, ancillary features, and categories of Liver Imaging Reporting and Data System (LI-RADS) version 2014 at magnetic resonance (MR) imaging for the diagnosis of hepatocellular carcinoma (HCC). Materials and Methods This retrospective institutional review board-approved study included patients with liver MR imaging and at least one pathologically proved lesion. Between 2004 and 2016, 102 patients (275 observations including 113 HCCs) met inclusion criteria. Two radiologists independently assessed major and ancillary imaging features for each liver observation and assigned a LI-RADS category. Per-lesion estimates of diagnostic performance of major features, ancillary features, and LI-RADS categories were assessed by using generalized estimating equation models. Results Major features (arterial phase hyperenhancement, washout, capsule, and threshold growth) had a sensitivity of 88.5%, 60.6%, 32.9%, and 41.6%, and a specificity of 18.6%, 84.8%, 98.8%, and 83.2% for HCC, respectively. Ancillary features (mild-moderate T2 hyperintensity, restricted diffusion, mosaic architecture, intralesional fat, lesional fat sparing, blood products, and subthreshold growth) had a sensitivity of 62.2%, 54.8%, 9.9%, 30.9%, 23.1%, 2.8%, and 48.3%, and a specificity of 79.4%, 90.6%, 99.4%, 94.2%, 83.1%, 99.3%, and 91.4% for HCC, respectively. The LR-5 or LR-5 V categories had a per-lesion sensitivity of 50.8% and a specificity of 95.8% for HCC, respectively. The LR-4, LR-5, or LR-5 V categories (determined by using major features only vs combination of major and ancillary features) had a per-lesion sensitivity of 75.9% and 87.9% and a per-lesion specificity of 87.5% and 86.2%, respectively. Conclusion The use of ancillary features in combination with major features increases the sensitivity while preserving a high specificity for the diagnosis of HCC.

Liver Iron Quantification with MR Imaging: A Primer for Radiologists.

Iron overload is a systemic disorder and is either primary (genetic) or secondary (exogenous iron administration). Primary iron overload is most commonly associated with hereditary hemochromatosis and secondary iron overload with ineffective erythropoiesis (predominantly caused by ß-thalassemia major and sickle cell disease) that requires long-term transfusion therapy, leading to transfusional hemosiderosis. Iron overload may lead to liver cirrhosis and hepatocellular carcinoma, in addition to cardiac and endocrine complications. The liver is one of the main iron storage organs and the first to show iron overload. Therefore, detection and quantification of liver iron overload are critical to initiate treatment and prevent complications. Liver biopsy was the historical reference standard for detection and quantification of liver iron content. Magnetic resonance (MR) imaging is now commonly used for liver iron quantification, including assessment of distribution, detection, grading, and monitoring of treatment response in iron overload. Several MR imaging techniques have been developed for iron quantification, each with advantages and limitations. The liver-to-muscle signal intensity ratio technique is simple and widely available; however, it assumes that the reference tissue is normal. Transverse magnetization (also known as R2) relaxometry is validated but is prone to respiratory motion artifacts due to a long acquisition time, is presently available only for 1.5-T imaging, and requires additional cost and delay for off-line analysis. The R2* technique has fast acquisition time, demonstrates a wide range of liver iron content, and is available for 1.5-T and 3.0-T imaging but requires additional postprocessing software. Quantitative susceptibility mapping has the highest sensitivity for detecting iron deposition; however, it is still investigational, and the correlation with liver iron content is not yet established. ©RSNA, 2018.

Diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI for assessment of anal fistula activity.

OBJECTIVE: To evaluate intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) sequences for quantitative characterization of anal fistula activity. METHODS: This retrospective study was approved by the institutional review board. One hundred and two patients underwent MRI for clinical suspicion of anal fistula. Forty-three patients with demonstrable anal fistulas met the inclusion criteria. Quantitative analysis included measurement of DCE and IVIM parameters. The reference standard was clinical activity based on medical records. Statistical analyses included Bayesian analysis with Markov Chain Monte Carlo, multivariable logistic regression, and receiver operating characteristic analyses. RESULTS: Brevity of enhancement, defined as the time difference between the wash-in and wash-out, was longer in active than inactive fistulas (p = 0.02). Regression coefficients of multivariable logistic regression analysis revealed that brevity of enhancement increased and normalized perfusion area under curve decreased with presence of active fistulas (p = 0.03 and p = 0.04, respectively). By cross-validation, a logistic regression model that included quantitative perfusion parameters (DCE and IVIM) performed significantly better than IVIM only (p < 0.001). Area under the curves for distinguishing patients with active from those with inactive fistulas were 0.669 (95% confidence interval [CI]: 0.500, 0.838) for a model with IVIM only, 0.860 (95% CI: 0.742, 0.977) for a model with IVIM and brevity of enhancement, and 0.921 (95% CI: 0.846, 0.997) for a model with IVIM and all DCE parameters. CONCLUSION: The inclusion of brevity of enhancement measured by DCE-MRI improved assessment of anal fistula activity over IVIM-DWI only.