Transient elastography (TE), shear wave elastography, and/or magnetic resonance elastography (MRE), each providing liver stiffness measurement (LSM), are the most studied imaging-based noninvasive liver disease assessment (NILDA) techniques. To support the American Association for the Study of Liver Diseases guidelines on NILDA, we summarized the evidence on the accuracy of these LSM methods to stage liver fibrosis (F).

A comprehensive search for studies assessing LSM by TE, shear wave elastography, or MRE for the identification of significant fibrosis (F2-4), advanced fibrosis (F3-4), or cirrhosis (F4), using histopathology as the standard of reference by liver disease etiology in adults or children from inception to April 2022 was performed. We excluded studies with <50 patients with a single disease entity and mixed liver disease etiologies (with the exception of HCV/HIV coinfection). Out of 9447 studies, 240 with 61,193 patients were included in this systematic review. In adults, sensitivities for the identification of F2-4 ranged from 51% to 95%, for F3-4 from 70% to 100%, and for F4 from 60% to 100% across all techniques/diseases, whereas specificities ranged from 36% to 100%, 74% to 100%, and 67% to 99%, respectively. The largest body of evidence available was for TE; MRE appeared to be the most accurate method. Imaging-based NILDA outperformed blood-based NILDA in most comparisons, particularly for the identification of F3-4/F4. In the pediatric population, imaging-based NILDA is likely as accurate as in adults.

LSM from TE, shear wave elastography, and MRE shows acceptable to outstanding accuracy for the detection of liver fibrosis across various liver disease etiologies. Accuracy increased from F2-4 to F3-4 and was the highest for F4. Further research is needed to better standardize the use of imaging-based NILDA, particularly in pediatric liver diseases.

To study the potential of viscoelastic parameters such as liver stiffness, loss tangent (marker of viscous properties) and viscoelastic dispersion to detect hepatic inflammation by in-vivo and ex-vivo MR elastography (MRE) at low and high vibration frequencies.

15 patients scheduled for liver tumor resection surgery were prospectively enrolled in this IRB-approved study and underwent multifrequency in-vivo MRE (30-60Hz) at 1.5-T prior to surgery. Immediately after liver resection, tumor-free tissue specimens were examined with ex-vivo MRE (0.8-2.8 kHz) at 0.5-T and histopathologic analysis including NAFLD activity score (NAS) and inflammation score (I-score) as sum of histological sub-features of inflammation.

In-vivo, in regions where tissue samples were obtained, the loss tangent correlated with the I-score (R = 0.728; p = 0.002) and c-dispersion (stiffness dispersion over frequency) correlated with lobular inflammation (R = -0.559; p = 0.030). In a subgroup of patients without prior chemotherapy, c-dispersion correlated with I-score also in the whole liver (R = -0.682; p = 0.043). ROC analysis of the loss tangent for predicting the I-score showed a high AUC for I ≥ 1 (0.944; p = 0.021), I ≥ 2 (0.804; p = 0.049) and I ≥ 3 (0.944; p = 0.021). Ex-vivo MRE was not sensitive to inflammation, whereas strong correlations were observed between fibrosis and stiffness (R = 0.589; p = 0.021), penetration rate (R = 0.589; p = 0.021), loss tangent (R = -0.629; p = 0.012), and viscoelastic model parameters (spring-pot powerlaw exponent, R = -0.528; p = 0.043; spring-pot shear modulus, R = 0.589; p = 0.021).

Our results suggest that c-dispersion of the liver is sensitive to inflammation when measured in-vivo in the low dynamic range (30-60Hz), while at higher frequencies (0.8-2.8 kHz) viscoelastic parameters are dominated by fibrosis.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously referred to as non-alcoholic fatty liver disease (NAFLD), is a leading cause of chronic liver disease, affecting up to 30% of the global population. MASLD is strongly associated with metabolic risk factors such as obesity and type 2 diabetes, and can progress to advanced stages including cirrhosis and hepatocellular carcinoma. Early diagnosis and accurate staging of fibrosis are critical in managing the disease and preventing complications. While liver biopsy has long been considered the gold standard for assessing fibrosis, it is invasive and carries associated risks. In response, non-invasive tests (NITs) have emerged as essential alternatives for the diagnosis and monitoring of MASLD. Key methods include blood-based biomarkers such as the Fibrosis-4 (FIB-4) score, NAFLD Fibrosis Score (NFS), and Enhanced Liver Fibrosis (ELF) test, as well as imaging modalities like vibration-controlled transient elastography (VCTE) and magnetic resonance elastography (MRE). These tests provide safer, more accessible methods for identifying liver fibrosis and guiding clinical management. They are integral in assessing disease severity, guiding treatment decisions, and monitoring disease progression, particularly in light of emerging therapies. NITs have become increasingly recommended by clinical guidelines as they reduce the need for invasive procedures like liver biopsy, improving patient care and outcomes. In conclusion, non-invasive testing plays a crucial role in the effective management of MASLD, offering reliable alternatives for diagnosis and monitoring while minimizing risks associated with traditional invasive methods.

Magnetic resonance elastography (MRE) is recognized as the most precise imaging technology for assessing liver fibrosis in individuals with metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to investigate the clinical factors and pathological characteristics that may impact LSM in MASLD patients.

This cross-sectional study recruited 124 patients who concurrently performed MRE, MRI-PDFF, and biopsy-proven MASLD. Linear regression models, Spearman's correlation, and subgroup analysis were employed to identify the variables affecting LSM.

The AUROC (95 % CI) of MRE for diagnosing fibrosis stage ≥ 1, 2, 3, and 4 was 0.80 (0.70-0.90), 0.76 (0.66-0.85), 0.92 (0.86-0.99), and 0.99 (0.99-1.00), with corresponding cutoffs of 2.56, 2.88, 3.35, and 4.76 kPa, respectively. Multivariate analyses revealed that AST was the only independent clinical variable significantly correlated with LSM. Furthermore, LSM exhibited a notable association with the grade of lobular inflammation and hepatocellular ballooning. Subgroup analysis showed that when AST ≥ 2 ULN or inflammation grade ≥ 2, LSM of patients with early fibrosis stages showed a slight but significant increase.

MRE demonstrates significant diagnostic accuracy in predicting liver fibrosis stages for MASLD patients, especially for advanced liver fibrosis and cirrhosis. However, elevated AST and the severity of liver inflammation may impact its accuracy in staging early liver fibrosis.

This study aimed to evaluate the technical success rate and stiffness measurement reliability of two specific hepatic magnetic resonance elastography (MRE) sequences dedicated to solving susceptibility artifacts in patients with various degrees of hepatic iron overload.

Thirty-seven patients with iron-overloaded liver confirmed by R2* value measurement who underwent two-dimensional (2D) spin-echo (SE) MRE and 2D SE-echo-planar-imaging (EPI) MRE were reviewed retrospectively. According to four categories based on R2* value (mild, moderate, severe elevation, and extremely severe iron overload), we compared the success rate, quality score, and liver stiffness of the two sequences. In addition, Spearman's correlation was performed to evaluate the relationship between the R2* value and liver stiffness.

The overall success rates of SE MRE and SE-EPI MRE in patients with hepatic iron overload were 91.89% and 78.38%, respectively, and 100% and 78.57%, respectively, for severe elevation iron overload. In all patients, the MRE quality scores were 54 and 48 for SE MRE and SE-EPI MRE, respectively (P = 0.107). There were no significant differences in liver stiffness measurements between the two MRE methods in patients with mild, moderate, and severe elevation iron-overloaded livers (P > 0.6 for all), respectively. For both MRE methods, R2* value had no significant effect on the liver stiffness measurements (correlation coefficient <0.1, P >0.6 for both).

In the mild and moderate elevation iron-overloaded liver, both SE MRE and fast SE-EPI MRE can provide successful and reliable liver stiffness measurement. In severe elevation iron-overloaded livers, SE MRE may be a better choice than SE-EPI MRE.

The capability of MR elastography (MRE) to differentiate fibrosis and inflammation, and to provide precise diagnoses is crucial, whereas the coexistence of fibrosis and inflammation may obscure the diagnostic accuracy.

In this retrospective study, from June 2020 to December 2022, chronic viral hepatitis patients who underwent multifrequency MRE (mMRE) were included in, and further divided into, training and validation cohorts. The hepatic viscoelastic parameters [shear wave speed (c) and loss angle (φ) of the complex shear modulus] were obtained from mMRE. The logistic regression and receiver operating characteristic (ROC) curves were generated to evaluate performance of viscoelastic parameters for fibrosis and inflammation.

A total of 233 patients were assigned to training cohort and validation cohorts (mean age, 52 years ± 13 (SD); 51 women; training cohort, n = 170 (73%), and validation cohort, n = 63 (27%)). Liver c exhibited superior performance in detecting fibrosis with ROC (95% confidence interval) of ≥ S1 (0.96 (0.92-0.99)), ≥ S2 (0.86 (0.78-0.92)), ≥ S3 (0.89 (0.84-0.95)), and S4 (0.88 (0.83-0.93)). Similarly, φ was effective in diagnosing inflammation with ROC values of ≥ G2 (0.72 (0.63-0.81)), ≥ G3 (0.88 (0.83-0.94)), and G4 (0.92 (0.87-0.98)). And great predictive discrimination for fibrosis and inflammation were shown in validation cohort (all AUCs > 0.75).

The viscoelastic parameters derived from multifrequency MRE could realize simultaneous detection of hepatic fibrosis and inflammation.

Fibrosis and inflammation coexist in chronic liver disease which obscures the diagnostic performance of MR elastography, whereas the viscoelastic parameters derived from multifrequency MR elastography could realize simultaneous detection of hepatic fibrosis and inflammation.

• Hepatic biomechanical parameters derived from multifrequency MR elastography could effectively detect fibrosis and inflammation. • Liver stiffness is useful for detecting fibrosis independent of inflammatory activity. • Fibrosis could affect the diagnostic efficacy of liver viscosity in inflammation, especially in early-grade of inflammation.

Viral hepatitis was previously the most common cause of chronic liver disease. However, in recent years, nonalcoholic fatty liver disease (NAFLD) cases have been increasing, especially in developed countries. NAFLD is histologically characterized by fat, fibrosis, and inflammation in the liver, eventually leading to cirrhosis and hepatocellular carcinoma. Although biopsy is the gold standard for the assessment of the liver parenchyma, quantitative evaluation methods, such as ultrasound, CT, and MRI, have been reported to have good diagnostic performances. The quantification of liver fat, fibrosis, and inflammation is expected to be clinically useful in terms of the prognosis, early intervention, and treatment response for the management of NAFLD. The aim of this review was to discuss the basics and prospects of MRI-based tissue quantifications of the liver, mainly focusing on proton density fat fraction for the quantification of fat deposition, MR elastography for the quantification of fibrosis, and multifrequency MR elastography for the evaluation of inflammation.

We conducted an individual patient data meta-analysis to establish stiffness cut-off values for magnetic resonance elastography (MRE) in staging liver fibrosis and to assess potential confounding factors.

A systematic review of the literature identified studies reporting MRE data in patients with NAFLD. Data were obtained from the corresponding authors. The pooled diagnostic cut-off value for the various fibrosis stages was determined in a two-stage meta-analysis. Multilevel modelling methods were used to analyse potential confounding factors influencing the diagnostic accuracy of MRE in staging liver fibrosis.

Eight independent cohorts comprising 798 patients were included in the meta-analysis. The area under the receiver operating characteristic curve (AUROC) for MRE in detecting significant fibrosis was 0.92 (sensitivity, 79%; specificity, 89%). For advanced fibrosis, the AUROC was 0.92 (sensitivity, 87%; specificity, 88%). For cirrhosis, the AUROC was 0.94 (sensitivity, 88%, specificity, 89%). Cut-offs were defined to explore concordance between MRE and histopathology: ≥F2, 3.14 kPa (pretest probability, 39.4%); ≥F3, 3.53 kPa (pretest probability, 24.1%); and F4, 4.45 kPa (pretest probability, 8.7%). In generalized linear mixed model analysis, histological steatohepatitis with higher inflammatory activity (odds ratio 2.448, 95% CI 1.180-5.079, p <0.05) and high gamma-glutamyl transferase (GGT) concentration (>120U/L) (odds ratio 3.388, 95% CI 1.577-7.278, p <0.01] were significantly associated with elevated liver stiffness, and thus affecting accuracy in staging early fibrosis (F0-F1). Steatosis, as measured by magnetic resonance imaging proton density fat fraction, and body mass index(BMI) were not confounders.

MRE has excellent diagnostic performance for significant, advanced fibrosis and cirrhosis in patients with NAFLD. Elevated inflammatory activity and GGT level may lead to overestimation of early liver fibrosis, but anthropometric measures such as BMI or the degree of steatosis do not.

This individual patient data meta-analysis of eight international cohorts, including 798 patients, demonstrated that MRE achieves excellent diagnostic accuracy for significant, advanced fibrosis and cirrhosis in patients with NAFLD. Cut-off values (significant fibrosis, 3.14 kPa; advanced fibrosis, 3.53 kPa; and cirrhosis, 4.45 kPa) were established. Elevated inflammatory activity and gamma-glutamyltransferase level may affect the diagnostic accuracy of MRE, leading to overestimation of liver fibrosis in early stages. We observed no impact of diabetes, obesity, or any other metabolic disorder on the diagnostic accuracy of MRE.

Quantitative imaging biomarkers of liver disease measured by using MRI and US are emerging as important clinical tools in the management of patients with chronic liver disease (CLD). Because of their high accuracy and noninvasive nature, in many cases, these techniques have replaced liver biopsy for the diagnosis, quantitative staging, and treatment monitoring of patients with CLD. The most commonly evaluated imaging biomarkers are surrogates for liver fibrosis, fat, and iron. MR elastography is now routinely performed to evaluate for liver fibrosis and typically combined with MRI-based liver fat and iron quantification to exclude or grade hepatic steatosis and iron overload, respectively. US elastography is also widely performed to evaluate for liver fibrosis and has the advantage of lower equipment cost and greater availability compared with those of MRI. Emerging US fat quantification methods can be performed along with US elastography. The author group, consisting of members of the Society of Abdominal Radiology (SAR) Liver Fibrosis Disease-Focused Panel (DFP), the SAR Hepatic Iron Overload DFP, and the European Society of Radiology, review the basics of liver fibrosis, fat, and iron quantification with MRI and liver fibrosis and fat quantification with US. The authors cover technical requirements, typical case display, quality control and proper measurement technique and case interpretation guidelines, pitfalls, and confounding factors. The authors aim to provide a practical guide for radiologists interpreting these examinations. © RSNA, 2023 See the invited commentary by Ronot in this issue. Quiz questions for this article are available in the supplemental material.

to evaluate the performance of magnetic resonance elastography (MRE) to stage liver fibrosis in patients with histologically confirmed nonalcoholic fatty liver disease (NAFLD) and to assess the impact of potential confounding factors in MRE diagnostic accuracy. The secondary objective was to compare MRE with other non-invasive methods for staging fibrosis such as transient elastography (TE) and non-invasive scores (APRI and FIB-4).

sixty-five histologically confirmed NAFLD patients were prospectively enrolled at the Hospital Universitario Virgen del Rocío (Seville, Spain). Liver stiffness was measured by MRE, TE and non-invasive scores (APRI and FIB-4). Fibrosis was assessed by liver biopsy using the steatosis, activity and fibrosis (SAF) score. Patients were classified into three groups according to the consistency between MRE and histopathological findings: underestimation, concordance and overestimation groups. Areas under the ROC curve (AUROC) and diagnostic performance were evaluated.

the area under the ROC curve (AUROC) of MRE in advanced fibrosis (≥ F3) was 0.90 (0.82-0.97), while TE AUROC was 0.82 (0.72-0.93) (p = 0.22) and lower for the non-invasive test (FIB-4 0.67 and APRI 0.62). Inflammatory activity, steatosis grade and higher levels of liver biochemistry appeared to overestimate MRE results in the univariate analysis, but only gamma-glutamyl transferase (GGT) was statistically significant in the multivariate analysis (p < 0.01). Age, sex, body mass index (BMI), weight, diabetes mellitus (DM), high blood pressure (HBP), platelets or lipidic profile did not affect MRE accuracy.

MRE is an effective and non-invasive method for detecting and staging liver fibrosis in NAFLD patients. MRE is more accurate than TE and allows the study of liver anatomy. Histological inflammation and surrogate biomarkers of inflammation can overestimate liver stiffness, but only GGT was statistically significant in the multivariate analysis. Important features of NAFLD patients such as obesity, DM, or lipidic profile did not affect MRE accuracy.

The hepatic diseases are extremely common in clinical practice. The correct classification of liver fibrosis is extremely important, as it influences therapy and predicts disease outcomes. The purpose of this study is to compare the diagnostic performance of point-shear wave elastography (pSWE) and magnetic resonance elastography (MRE) in the hepatic fibrosis diagnostic. A meta-analysis was carried out based on articles published until October 2020. The articles are available at following databases: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Scientific Electronic Library Online, LILACS, Scopus, and CINAHL. Diagnostic performances were analyzed per METAVIR F2, using 3.5kPa as target fibrosis. Assessment of the methodological quality of the incorporated papers by the QUADAS-2 tool for pSWE and MRE. A total 2,153 studies articles were evaluated and 44 studies, comprising 6,081 patients with individual data, were included in the meta-analysis: 28 studies for pSWE and 16 studies for MRE. The pooled sensitivity and specificity were 0.86 (95%CI 0.80-0.90) and 0.88 (95%CI 0.85-0.91), respectively, for pSWE, compared with 0.94 (95%CI 0.89-0.97) and 0.95 (95%CI 0.89-0.98) respectively, for MRE. The pooled SROC curve for pSWE shows in the area under the curve (AUC) of 0.93 (95%CI 0.90-0.95), whereas the AUC for MRE was 0.98 (95%CI 0.96-0.99). The diagnostic odds ratio for pSWE and MRE were 41 (95%CI 24-72) and 293 (95%CI 86-1000), respectively. There was statistically significant heterogeneity for pSWE sensitivity (I² = 85.26, P<0.001) and specificity (I² = 89.46, P<0.001). The heterogeneity for MRE also was significant for sensitivity (I² = 73.28, P<0.001) and specificity (I² = 87.24, P<0.001). Therefore, both pSWE and MRE are suitable modalities for assessing liver fibrosis. In addition, MRE is a more accurate imaging technique than pSWE and can be used as alternative to invasive biopsy.

BACKGROUND. Hepatic steatosis has been found not to affect liver stiffness measurements (LSM) from MR elastography (MRE). However, the effect of steatosis on LSM from 2D shear-wave elastography (SWE) remains controversial. OBJECTIVE. The purpose of this study was to evaluate the effect of hepatic steatosis on the diagnostic performance of LSM from 2D SWE (LSM2D SWE) for evaluation of liver fibrosis with LSM from MRE (LSMMRE) as the reference standard. METHODS. This retrospective study included 888 patients (442 women, 446 men; median age, 67 years) with chronic liver disease who underwent LSM by both 2D SWE and MRE within a 3-month window. Steatosis was also assessed on ultrasound examinations by ultrasound-guided attenuation parameter (UGAP) and on MRI examinations by proton density fat fraction (PDFF). Fibrosis stages and steatosis grades were classified according to previously established thresholds. The effect of steatosis on LSM2D SWE was evaluated by Kruskal-Wallis tests with post hoc tests and ROC analysis. RESULTS. LSM2D SWE were significantly higher in patients with severe steatosis than those without steatosis by MRI PDFF among patients with F0 fibrosis (5.5 kPa [IQR, 4.7-6.0 kPa] vs 4.7 kPa [IQR, 4.2-5.5 kPa], p = .009) and F1 fibrosis (6.3 kPa [IQR, 6.0-7.2 kPa] vs 5.9 kPa [IQR, 5.0-6.6 kPa], p = .009). LSM2D SWE were significantly higher in patients with severe steatosis than those without steatosis by UGAP among patients with F1 fibrosis (6.6 kPa [IQR, 5.9-7.3 kPa] vs 5.9 kPa [IQR, 5.1-6.5 kPa], p = .008). Otherwise, LSM2D SWE did not vary significantly across steatosis grades at a given fibrosis stage (all p > .05). Sensitivity and specificity for ≥ F1 fibrosis were 63.8% and 91.5% in patients without versus 60.4% and 80.9% in patients with severe steatosis by MRI PDFF and were 62.4% and 91.5% in patients without versus 72.1% and 78.3% in patients with severe steatosis by UGAP. CONCLUSION. Severe hepatic steatosis may result in overestimation of LSM2D SWE in patients without or with mild steatosis, reducing the specificity of liver fibrosis detection. CLINICAL IMPACT. Assessment of UGAP at 2D SWE may help identify patients in whom LSM2D SWE should be assessed with caution. In patients with no or mild steatosis by 2D SWE and severe steatosis by UGAP, MRE helps provide a more reliable measure of liver fibrosis.

Chronic liver diseases, resulting from chronic injuries of various causes, lead to cirrhosis with life-threatening complications including liver failure, portal hypertension, hepatocellular carcinoma. A key unmet medical need is robust non-invasive biomarkers to predict patient outcome, stratify patients for risk of disease progression and monitor response to emerging therapies. Quantitative imaging biomarkers have already been developed, for instance, liver elastography for staging fibrosis or proton density fat fraction on magnetic resonance imaging for liver steatosis. Yet, major improvements, in the field of image acquisition and analysis, are still required to be able to accurately characterize the liver parenchyma, monitor its changes and predict any pejorative evolution across disease progression. Artificial intelligence has the potential to augment the exploitation of massive multi-parametric data to extract valuable information and achieve precision medicine. Machine learning algorithms have been developed to assess non-invasively certain histological characteristics of chronic liver diseases, including fibrosis and steatosis. Although still at an early stage of development, artificial intelligence-based imaging biomarkers provide novel opportunities to predict the risk of progression from early-stage chronic liver diseases toward cirrhosis-related complications, with the ultimate perspective of precision medicine. This review provides an overview of emerging quantitative imaging techniques and the application of artificial intelligence for biomarker discovery in chronic liver disease.

The aim of this study was to detect a response difference in primary (PLC) and secondary liver tumors (SLC) with magnetic resonance elastography (MRE) after TACE therapy. Thirty-one patients (25/31 male; mean age 69.6 years [range: 39-85 years]) with repeated TACE therapy of HCC were compared with twenty-seven patients (27/27 female; mean age 61.2 years [range 39-81 years]) with repeated TACE therapy of metastatic liver disease due to breast cancer. Both groups underwent either one (n = 31) or two (n = 27) repetitive magnetic resonance imaging (MRI) and MRE exams in 4- to 6-week intervals using a 1.5-T-scanner. MRE-based liver stiffness and size measurements were evaluated in tumorous lesions and in healthy liver lobe controls. PLC showed a significantly larger tumor size compared to SLC (26.4 cm2 vs. 11 cm2, p = 0.007) and a higher degree of stiffness (5.8 kPa vs. 5.1 kPa, p = 0.04). Both tumors decreased in size during the cycles (PLC: p = 0.8 and SLC: p < 0.0001) and lesions showed an increase in stiffness (PLC: p = 0.002 and SLC: p = 0.006). MRE demonstrates that PLC and SLC have similar responses to TACE therapy. PLC had a greater increase in stiffness and SLC got smaller. An increasing stiffness and decrease in size could show a good response.

There is an urgent need of non-invasive tests (NITs) for monitoring treatment response and disease progression in chronic liver disease. Liver stiffness (LS) evaluated by transient elastography (TE), shear wave elastography (SWE), and magnetic resonance elastography (MRE) and serum markers e.g. APRI and FIB-4 scores were assessed at baseline and the 1-year follow-up. In all, 89 chronic hepatitis C virus (HCV) patients with sustained virological response and 93 non-alcoholic fatty liver disease (NAFLD) patients were included. There was a significantly strong correlation among imaging techniques. Using MRE as the reference standard, the area under the receiver operating characteristics curves for TE, SWE, APRI, and FIB-4 in detecting stage1-4 fibrosis were 0.88-0.95, 0.87-0.96, 0.83-0.89, and 0.79-0.92, respectively. In chronic HCV patients, the values of TE, SWE, MRE, APRI and FIB-4 significantly decreased from baseline to the 1-year follow-up. Liver steatosis did not significantly change over time. In NAFLD, compared to obese patients, non-obese patients had less LS and steatosis at baseline, and these values did not show significant changes at the 1-year follow-up. Our study suggests that the current NITs have a good correlation and accuracy in monitoring the treatment outcomes in patients with chronic liver diseases.

To develop a model for predicting post-operative major complications in patients with hepatocellular carcinoma (HCC).

In all, 186 consecutive patients with pre-operative MR elastography were included. Complications were categorised using Clavien‒Dindo classification, with major complications defined as ≥Grade 3. Liver-stiffness measurement (LSM) values were measured on elastogram. The indocyanine green clearance rate of liver remnant (ICG-Krem) was based on the results of CT volumetry, intraoperative data, and ICG-K value. For an easy application to the prediction model, the continuous variables were converted to categories. Moreover, logistic regression analysis and fivefold cross-validation were performed. The prediction model's discriminative performance was evaluated using the area under the receiver operating characteristic curve (AUC), and the calibration of the model was assessed by the Hosmer‒Lemeshow test.

43 of 186 patients (23.1%) had major complications. The multivariate analysis demonstrated that LSM, albumin-bilirubin (ALBI) score, intraoperative blood loss, and ICG-Krem were significantly associated with major complications. The median AUC of the five validation subsets was 0.878. The Hosmer-Lemeshow test confirmed no evidence of inadequate fit (p = 0.13, 0.19, 0.59, 0.59, and 0.73) on the fivefold cross-validation. The prediction model for major complications was as follows: -2.876 + 2.912 [LSM (>5.3 kPa)]+1.538 [ALBI score (>-2.28)]+0.531 [Intraoperative blood loss (>860 ml)]+0.257 [ICG-Krem (<0.10)].

The proposed prediction model can be used to predict post-operative major complications in patients with HCC.

The proposed prediction model can be used in routine clinical practice to identify post-operative major complications in patients with HCC and to strategise appropriate treatments of HCC.

To investigate associations between histology and hepatic mechanical properties measured using multiparametric magnetic resonance elastography (MRE) in adults with known or suspected nonalcoholic fatty liver disease (NAFLD) without histologic fibrosis.

This was a retrospective analysis of 88 adults who underwent 3T MR exams including hepatic MRE and MR imaging to estimate proton density fat fraction (MRI-PDFF) within 180 days of liver biopsy. Associations between MRE mechanical properties (mean shear stiffness (|G*|) by 2D and 3D MRE, and storage modulus (G'), loss modulus (G″), wave attenuation (α), and damping ratio (ζ) by 3D MRE) and histologic, demographic and anthropometric data were assessed.

In univariate analyses, patients with lobular inflammation grade ≥ 2 had higher 2D |G*| and 3D G″ than those with grade ≤ 1 (p = 0.04). |G*| (both 2D and 3D), G', and G″ increased with age (rho = 0.25 to 0.31; p ≤ 0.03). In multivariable regression analyses, the association between inflammation grade ≥ 2 remained significant for 2D |G*| (p = 0.01) but not for 3D G″ (p = 0.06); age, sex, or BMI did not affect the MRE-inflammation relationship (p > 0.20).

2D |G*| and 3D G″ were weakly associated with moderate or severe lobular inflammation in patients with known or suspected NAFLD without fibrosis. With further validation and refinement, these properties might become useful biomarkers of inflammation. Age adjustment may help MRE interpretation, at least in patients with early-stage disease.

• Moderate to severe lobular inflammation was associated with hepatic elevated shear stiffness and elevated loss modulus (p =0.04) in patients with known or suspected NAFLD without liver fibrosis; this suggests that with further technical refinement these MRE-assessed mechanical properties may permit detection of inflammation before the onset of fibrosis in NAFLD. • Increasing age is associated with higher hepatic shear stiffness, and storage and loss moduli (rho = 0.25 to 0.31; p ≤ 0.03); this suggests that age adjustment may help interpret MRE results, at least in patients with early-stage NAFLD.

Two-dimensional shear wave elastography (2D-SWE) is a new ultrasound-based elastography method to evaluate liver fibrosis in the daily practice. However, the utility of 2D-SWE among the other liver fibrosis markers is unclear.

We enrolled 141 consecutive patients with hepatitis C virus infection, 66 men and 75 women (median age, 67 years), who underwent liver biopsy and 2D-SWE (LOGIQ E9, GE Healthcare, Wauwatosa, WI, USA). We compared the diagnostic accuracy of the 2D-SWE with those of magnetic resonance elastography (MRE; MR-Touch, GE Healthcare, Milwaukee, WI, USA), Mac-2 binding protein glycosylation isomer (M2BPGi), fibrosis-4 index (FIB-4) and platelet counts (PLT), using the histologic METAVIR scoring as the reference standard.

The areas under the receiver operating characteristics curves (AUROCs) of 2D-SWE, MRE, M2BPGi, FIB-4 and PLT for ≥F2, ≥F3 and F4 were 0.86, 0.88, 0.79, 0.81 and 0.77; 0.92, 0.93, 0.86, 0.87 and 0.83; and 0.91, 0.97, 0.85, 0.85 and 0.82, respectively. For diagnosing ≥F2 and ≥F3, the AUROCs of 2D-SWE and those of MRE showed no significant differences, and both 2D-SWE and MRE showed significantly higher AUROCs than the other markers. For diagnosing F4, the AUROC of MRE was significantly higher than those of other fibrosis markers.

2D-SWE has an excellent diagnostic accuracy equivalent to that of MRE for assessing significant (≥F2) and severe (≥F3) fibrosis. MRE demonstrated a higher AUROC than 2D-SWE, but this last one has advantages such as lower cost, fewer contraindications and greater ease of performance than MRE.

Hepatitis B virus (HBV) infection continues to be a worldwide public health problem. In Mexico, at least three million adults are estimated to have acquired hepatitis B (total hepatitis B core antibody [anti-HBc]-positive), and of those, 300,000 active carriers (hepatitis B surface antigen [HBsAg]-positive) could require treatment. Because HBV is preventable through vaccination, its universal application should be emphasized. HBV infection is a major risk factor for developing hepatocellular carcinoma. Semi-annual liver ultrasound and serum alpha-fetoprotein testing favor early detection of that cancer and should be carried out in all patients with chronic HBV infection, regardless of the presence of advanced fibrosis or cirrhosis. Currently, nucleoside/nucleotide analogues that have a high barrier to resistance are the first-line therapies.

The purpose of this study was to assess the diagnostic value of multifrequency MR elastography for grading necro-inflammation in the liver. Fifty participants with chronic hepatitis B or C were recruited for this institutional review board-approved study. Their liver was examined with multifrequency MR elastography. The storage, shear and loss moduli, and the damping ratio were measured at 56 Hz. The multifrequency wave dispersion coefficient of the shear modulus was calculated. The measurements were compared to reference markers of necro-inflammation and fibrosis with Spearman correlations and multiple regression analysis. Diagnostic accuracy was assessed. At multiple regression analysis, necro-inflammation was the only determinant of the multifrequency dispersion coefficient, whereas fibrosis was the only determinant of the storage, loss and shear moduli. The multifrequency dispersion coefficient had the largest AUC for necro-inflammatory activity A ≥ 2 [0.84 (0.71-0.93) vs. storage modulus AUC: 0.65 (0.50-0.79), p = 0.03], whereas the storage modulus had the largest AUC for fibrosis F ≥ 2 [AUC (95% confidence intervals) 0.91 (0.79-0.98)] and cirrhosis F4 [0.97 (0.88-1.00)]. The measurement of the multifrequency dispersion coefficient at three-dimensional MR elastography has the potential to grade liver necro-inflammation in patients with chronic vial hepatitis.

Two-dimensional shear wave elastography (2D-SWE), magnetic resonance elastography (MRE), aspartate transaminase-to-platelet ratio index (APRI), fibrosis index based on 4 factors (FIB-4), and King's score have been proposed for diagnosing fibrosis.

Literature databases were searched until October 1st, 2020. The summary area under the receiver operating characteristic curve (AUROC), the summary diagnostic odds ratios, and the summary sensitivities and specificities were used to assess the performance of these noninvasive methods for staging fibrosis.

Our final data contained 72 studies. The prevalence of significant fibrosis, advanced fibrosis, and cirrhosis was 58.3%, 36.2%, and 20.5%, respectively, in chronic hepatitis B (CHB). For 2D-SWE and MRE, the summary AUROCs were 0.89 and 0.97, 0.95 and 0.97, and 0.94 and 0.97 for significant fibrosis, advanced fibrosis, and cirrhosis, respectively. The summary AUROCs using APRI and FIB-4 for detecting significant fibrosis, advanced fibrosis, and cirrhosis were 0.76 and 0.75, 0.74 and 0.77, and 0.77 and 0.82, respectively. The summary AUROCs of King's score for detecting significant fibrosis and cirrhosis were 0.77 and 0.83, respectively.

MRE and 2D-SWE may show the best diagnostic accuracy for predicting fibrosis in CHB. Among the three serum markers, King's score may be more useful for diagnosing fibrosis.

Hepatitis B virus (HBV) infection continues to be a worldwide public health problem. In Mexico, at least three million adults are estimated to have acquired hepatitis B (total hepatitis B core antibody [anti-HBc]-positive), and of those, 300,000 active carriers (hepatitis B surface antigen [HBsAg]-positive) could require treatment. Because HBV is preventable through vaccination, its universal application should be emphasized. HBV infection is a major risk factor for developing hepatocellular carcinoma. Semi-annual liver ultrasound and serum alpha-fetoprotein testing favor early detection of that cancer and should be carried out in all patients with chronic HBV infection, regardless of the presence of advanced fibrosis or cirrhosis. Currently, nucleoside/nucleotide analogues that have a high barrier to resistance are the first-line therapies.

To compare the diagnostic performance of diffusion-weighted imaging (DWI), gradient-recalled echo-based magnetic resonance elastography (GRE-MRE), and spin-echo echo-planar imaging-based MRE (SE-EPI-MRE) in liver fibrosis staging.

A systematic literature search was done to collect studies on the performance of DWI, GRE-MRE, and SE-EPI-MRE for diagnosing liver fibrosis. Pooled sensitivity, specificity, diagnostic odds ratio, positive and negative likelihood ratio, and a summary receiver operating characteristic (ROC) curve were estimated with a bivariate random effects model. Subgroup analyses on various study characteristics were performed.

Sixty studies with a total of 6620 patients were included in the meta-analysis. Pooled sensitivity and specificity of GRE-MRE and SE-EPI-MRE showed high diagnostic accuracy and did not differ significantly. The area under the summary ROC curve for all stages of fibrosis differed significantly between DWI (0.83-0.88) and either GRE-MRE (0.95-0.97) or SE-EPI-MRE (0.95-0.99). Substantial heterogeneity was detected for all three imaging methods.

Both GRE-MRE and SE-EPI-MRE are highly accurate for detection of each liver fibrosis stage, with high potential to replace liver biopsy. Although DWI had a moderate accuracy in distinguishing liver fibrosis, it could be regarded as an alternative to MRE, since it is widely available and easily implemented in routine liver MRI.

To retrospectively compare the predictive value of computed tomography volumetry (CTV), magnetic resonance elastography (MRE) of the liver, and their combination for major complications after liver resection.

We enrolled 108 consecutive patients who underwent anatomical liver resection for liver tumors and preoperative contrast-enhanced CT and MRE. The future liver remnant (FLR) ratio was calculated by CTV, while the liver stiffness measurement (LSM) was obtained by MRE. FLR ratio alone, LSM alone, and combined FLR ratio and LSM were evaluated to predict major complications (Clavien-Dindo grade ≥ IIIa). Univariate and multivariate analyses of hepatic biochemical parameters and imaging data were performed to identify predictors of major complications. Receiver operating characteristic analyses of FLR ratio, LSM, and their combination were performed, and the sensitivity and specificity were calculated.

Twenty-two (20.4%) of the 108 patients experienced major complications. According to multiple regression analysis, the FLR ratio (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.91-0.99, p = 0.040) and LSM (OR 1.72, 95% CI 1.01-2.94, p = 0.047) were independent predictors of major complications. The combined FLR ratio and LSM were predictive of major complications, with an area under the curve (AUC) of 0.818, sensitivity of 68.2%, and specificity of 84.9%. The AUC and specificity for combined FLR ratio and LSM were larger than those for FLR ratio (AUC: 0.711, specificity: 80.2%) and LSM (AUC: 0.793, specificity: 80.2%).

Combined CTV and MRE analysis can improve the AUC and specificity for predicting major complications after anatomical liver resection.

This study investigated whether T1 values in native T1 mapping of 3T magnetic resonance imaging (MRI) of the liver were affected by the fatty component.

This prospective study involved 340 participants from a population-based cohort study between May 8, 2018 and August 8, 2019. Data obtained included: (1) hepatic stiffness according to magnetic resonance elastography (MRE); (2) T1 value according to T1 mapping; (3) fat fraction and iron concentration from multi-echo Dixon; and (4) clinical indices of hepatic steatosis including body mass index, waist circumference, history of diabetes, aspartate aminotransferase, alanine aminotransferase, gamma-glutamyl transpeptidase, and triglycerides. The correlations between T1 value and fat fraction, and between T1 value and liver stiffness were assessed using Pearson's correlation coefficient. The independent two-sample t-test was used to evaluate the differences in T1 values according to the presence or absence of hepatic steatosis, and the one-way analysis of variance was used to evaluate the difference in T1 value by grading of hepatic steatosis according to MRI-based proton density fat fraction (PDFF). In addition, univariate and multivariate linear regression analyses were performed to determine whether other variables influenced the T1 value.

T1 value showed a positive correlation with the fat fraction obtained from PDFF (r = 0.615, P < 0.001) and with the liver stiffness obtained from MRE (r = 0.370, P < 0.001). Regardless of the evaluation method, the T1 value was significantly increased in subjects with hepatic steatosis (P < 0.001). When comparing hepatic steatosis grades based on MRI-PDFF, the mean T1 values were significantly different in all grades, and the T1 value tended to increase as the grade increased (P < 0.001, P for trend <0.001). On multiple linear regression analysis, the T1 value was influenced by MRI-PDFF, calculated liver iron concentration, liver stiffness, and serum aspartate aminotransferase level.

The T1 value obtained by current T1 mapping of 3T MRI was affected by the liver fat component and several other factors such as liver stiffness, iron concentration, and inflammation.

Although MR elastography allows for quantitative evaluation of liver stiffness to assess chronic liver diseases, it has associated drawbacks related to additional scanning time, patient discomfort, and added costs.

To develop a machine learning model that can categorically classify the severity of liver stiffness using both anatomical T2-weighted MRI and clinical data for children and young adults with known or suspected pediatric chronic liver diseases.

We included 273 subjects with known or suspected chronic liver disease. We extracted data including axial T2-weighted fast spin-echo fat-suppressed images, clinical data (e.g., demographic/anthropomorphic data, particular medical diagnoses, laboratory values) and MR elastography liver stiffness measurements. We propose DeepLiverNet (a deep transfer learning model) to classify patients into one of two groups: no/mild liver stiffening (<3 kPa) or moderate/severe liver stiffening (≥3 kPa). We conducted internal cross-validation using 178 subjects, and external validation using an independent cohort of 95 subjects. We assessed diagnostic performance using accuracy, sensitivity, specificity and area under the receiver operating characteristic curve (AuROC).

In the internal cross-validation experiment, the combination of clinical and imaging data produced the best performance (AuROC=0.86) compared to clinical (AuROC=0.83) or imaging (AuROC=0.80) data alone. Using both clinical and imaging data, the DeepLiverNet correctly classified patients with accuracy of 88.0%, sensitivity of 74.3% and specificity of 94.6%. In our external validation experiment, this same deep learning model achieved an accuracy of 80.0%, sensitivity of 61.1%, specificity of 91.5% and AuROC of 0.79.

A deep learning model that incorporates clinical data and anatomical T2-weighted MR images might provide a means of risk-stratifying liver stiffness and directing the use of MR elastography.

Nonalcoholic fatty liver disease (NAFLD) affects 25% of the global population. The standard of diagnosis, biopsy, is invasive and affected by sampling error and inter-reader variability. We hypothesized that widely available rapid MRI techniques could be used to predict nonalcoholic steatohepatitis (NASH) noninvasively by measuring liver stiffness, with magnetic resonance elastography (MRE), and liver fat, with chemical shift-encoded (CSE) MRI. Besides, we validate an automated image analysis technique to maximize the utility of these methods.

To implement and test an automated system for analyzing CSE-MRI and MRE data coupled with model-based prediction of NASH.

Prospective.

Eighty-three patients with suspected NAFLD.

A 1.5 T using a flow-compensated motion-encoded gradient echo MRE sequence and a multiecho CSE-MRI sequence.

The MRE and CSE-MRI data were analyzed by two readers (5+ and 1 years of experience) and an automated algorithm. A logistic regression model to predict pathology-diagnosed NASH was trained based on stiffness and proton density fat fraction, and the area under the receiver operating characteristic curve (AUROC) was calculated using 10-fold cross validation for models based on both automated and manual measurements. A separate model was trained to predict the NASH severity score (NAS).

Pearson's correlation, Bland-Altman, AUROC, C-statistic.

The agreement between automated measurements and the more experienced reader (R²  = 0.87 for stiffness and R²  = 0.99 for proton density fat fraction [PDFF]) was slightly better than the agreement between readers (R²  = 0.85 and 0.98). The model for predicting biopsy-diagnosed NASH had an AUROC of 0.87. The NAS-prediction model had a C-statistic of 0.85.

We demonstrated a workflow that used a limited MRI acquisition protocol and fully automated analysis to predict NASH with high accuracy. These methods show promise to provide a reliable noninvasive alternative to biopsy for NASH-screening in populations with NAFLD.

2 TECHNICAL EFFICACY STAGE: 2.

To evaluate the diagnostic efficacy of intravoxel incoherent motion (IVIM) parameters in hepatitis B virus (HBV)-induced hepatic fibrosis using different calculation methods and to investigate histopathologic origins.

Liver biopsies from 37 prospectively recruited chronic hepatitis B patients were obtained. Twelve b-value (0-1000 s/mm²) diffusion-weighted imaging (DWI) was performed with a 1.5 T scanner and was followed by blinded percutaneous liver biopsy. All biopsy specimens were evaluated with Ishak staging, and the microvascular density (MVD) was calculated. Patients were classified as having no/mild (F0-1), moderate (F2-3), or marked (F4-5) fibrosis. Pseudodiffusion (D*), the perfusion fraction (f), and the apparent diffusion coefficient (ADC) were calculated using all b-values, while true diffusion (D) was calculated using all b-values [D_0-1000] and b-values greater than 200 s/mm² [D_200-1000]. Three concentric regions of interest (ROIs) (5, 10, and 20 mm) centered on the biopsy site were used.

D* was correlated with the MVD (p = 0.015, Pearson's r = 0.415), but f was not (p = 0.119). D_0-1000 was inversely correlated with Ishak stage (p = 0.000, Spearman's r_s =  - 0.685) and was significantly decreased in all the fibrosis groups; however, only the no/mild and marked fibrosis groups had significantly different D_200-1000 values. A pairwise comparison of receiver operating characteristic (ROC) curves of D_0-1000 and D_200-1000 showed significant differences (p = 0.039). D* was the best at discriminating early fibrosis (AUC = 0.861), while the ADC best discriminated advanced fibrosis (AUC = 0.964).

D* was correlated with the MVD and is a powerful parameter to discriminate early hepatic fibrosis. D significantly decreased with advanced fibrosis stage when using b-values less than 200 s/mm² in calculations.

Early and accurate detection of liver fibrosis are important for clinical treatment.

To compare the diagnostic accuracy of liver diffusion kurtosis imaging (DKI) and conventional diffusion-weighted imaging (cDWI) in differentiating patients with mild and substantial fibrosis from normal individuals.

Twenty-seven healthy volunteers with no fibrosis (S0) and 45 patients with mild (S1) or substantial (S2) liver fibrosis underwent DWI with multiple b-values. Liver mean apparent diffusion (MD) and mean kurtosis (MK) values derived from DKI and apparent diffusion coefficient (ADC) derived from cDWI were measured and compared. Their discriminative abilities were analyzed and compared by receiver operating characteristic (ROC) curve analysis.

Significant differences in MD and ADC values were found between groups (P < 0.05). MD value was statistically different between S0 and S1 (P = 0.028) and S0 and S2 (P = 0.005). ADC value was statistically different between S0 and S2 (P = 0.012). MK value was similar between groups (P = 0.646). MD and ADC values significantly correlated with fibrosis stages (r_s = -0.668, -0.341; P < 0.01). MK values had no correlation with fibrosis stages (r_s = 0.180; P = 0.130). The area under ROC curves (AUC) for MD and ADC was 0.937 and 0.707 for characterization of S1-2 and 0.817 and 0.658 for S2, respectively. MD performed better than ADC for characterization of S1-2 and S2 (P < 0.05).

Differentiating patients with mild or substantial fibrosis from normal individuals is feasible using DKI, which performs better than cDWI.

The early diagnosis of liver fibrosis is crucial for the prevention of liver cirrhosis and liver cancer. As gold standard for staging liver fibrosis, liver biopsy is an invasive procedure that carries the risk of serious complications. The aim of this study was to evaluate the performance of the residual neural network (ResNet), a non-invasive methods, for staging liver fibrosis using plain CT images.

This retrospective study involved 347 patients subjected to liver CT scanning and liver biopsy. For each patient, we selected three axial images adjacent to the puncture location in the eighth or ninth inter-space on the right side. After processing and enhancement (rotation, translation, and amplification), these images were used as input data for the ResNet model. The model used a fivefold cross-validation method. In each fold, the images of approximately 80% of the total sample size (278 patients) were used for training the ResNet model, the other 20% (69 patients) were used for testing the trained network, with the liver biopsy pathology results as gold standard. The proportion of patients in each fibrosis stage was equal for training and test groups. The final result was the mean of the fivefold cross-validation in the test group. The performance of the ResNet model was evaluated for the test group by receiver operating characteristic (ROC) analysis.

For the ResNet model, the area under the ROC curve (AUC) for assessing cirrhosis (F4), advanced fibrosis (F3 or higher), significant fibrosis (F2 or higher), and mild fibrosis (F1 or higher) was 0.97, 0.94, 0.90, and 0.91, respectively.

The ResNet model analysis of plain CT images exhibited high diagnostic efficiency for liver fibrosis staging. As a convenient, fast, and economical non-invasive diagnostic method, the ResNet model can be used to assist radiologists and clinicians in liver fibrosis evaluations.

Magnetic resonance elastography (MRE) is the most accurate noninvasive technique in diagnosing fibrosis and cirrhosis in patients with chronic liver disease (CLD). The accuracy of hepatic MRE in distinguishing the severity of disease has been validated in studies of patients with various CLDs. Advanced hepatic MRE is a reliable, comfortable, and inexpensive alternative to liver biopsy for disease diagnosing, progression monitoring, and clinical decision making in patients with CLDs. This article summarizes current knowledge of the technical advances and innovations in hepatic MRE, and the clinical applications in various hepatic diseases.

The aim of this study was to pre-operatively investigate the diagnostic performance of 2D shear wave elastography (2D-SWE) for staging liver fibrosis and inflammation in patients with hepatocellular carcinoma (HCC) who then undergo surgery and to determine the optimal locations for measurement. In total, 106 patients were enrolled in this prospective study from March 2017 to May 2018. Two-dimensional SWE was used to measure liver stiffness (LS) in each patient 0-1, 1-2 and 2-5 cm from the tumor border (groups 1, 2 and 3, respectively). Spearman's correlation was used to evaluate the relationships between LS and hepatic fibrosis and between LS and inflammation. Receiver operating characteristic curve (ROC) analysis was used to evaluate the diagnostic accuracy of 2D-SWE. The technical success rate of SWE in tissue distant from the tumor (group 3) was significantly higher than that in peri-tumoral tissue (groups 1 and 2) (p < 0.001). Moreover, the area under the ROC for diagnosing cirrhosis (F4) and severe inflammation (A3) was higher for group 3 than for groups 1 and 2. Our results suggest that 2D-SWE is a helpful approach to assessment of hepatic fibrosis in HCC patients before hepatic resection. We found that to achieve a superior success rate and preferable diagnosis accuracy for patients with HCC, LS measurement should be performed 2-5 cm from the tumor margin.