BACKGROUND:Quantitative ultrasound techniques enable noninvasive assessment of hepatic steatosis, fibrosis, and inflammation in metabolic dysfunction-associated steatotic liver disease (MASLD). This study performed a head-to-head comparison of dual-elastography and 2D shear wave elastography (2D-SWE) for comprehensive histologic evaluation. METHODS:A total of 186 biopsy proven MASLD patients were enrolled. Dual-elastography provided attenuation imaging (ATI), fibrosis (F-index), and inflammatory activity (A-index), while 2D-SWE offered attenuation coefficient (ATT), shear wave elasticity (SWE), and shear wave dispersion (SWD). Histologic grades of steatosis (S0-S3), fibrosis (F0-F3), and inflammation (A0-A3) served as the reference standard. Diagnostic performance was assessed using receiver operating characteristic (ROC) analysis. RESULTS:ATI outperformed ATT for detecting ≥S1 steatosis (AUROC 0.90 vs. 0.81, P = 0.036), while their performance for ≥S2 and ≥S3 was comparable. For significant fibrosis (≥F2), the F-index showed higher accuracy than SWE (AUROC 0.87 vs. 0.80, P = 0.046) with greater sensitivity (73.7%) and balanced specificity (85.3%). SWD demonstrated moderate diagnostic ability for inflammatory activity (AUROC 0.75 for ≥A2; 0.84 for ≥A3), and the A-index achieved AUROC 0.73 for detecting lobular inflammation grade ≥2. CONCLUSIONS:ATI and ATT are reliable for assessing steatosis, the F-index provides superior accuracy for significant fibrosis, and SWD and A-index reflect overall and lobular inflammation, respectively. These multiparametric ultrasound techniques enable comprehensive, noninvasive evaluation of key histologic features in MASLD.

To develop and validate a machine learning (ML) model integrating dual elastography, clinical features, and serum biomarkers for noninvasive prediction of severe drug-induced liver injury (DILI). This prospective multicenter study enrolled consecutive DILI patients undergoing liver biopsy and dual elastography. Severe DILI was defined as Scheuer inflammation grade plus fibrosis stage ≥ 5 (G + S ≥ 5). Dual elastography-derived activity index (A index) and fibrosis index (F index) correlated with pathological inflammation (G0–4) and fibrosis (S0–4) stages. The dataset was stratified and split 7:3 into training and test sets. LASSO regression was applied for feature selection. Eight ML models were constructed and compared, optimized using 5-fold cross-validation and Bayesian methods. Performance was evaluated by area under the curve (AUC), sensitivity, and specificity. SHapley Additive exPlanations (SHAP) were used to interpret the models. A total of 305 participants were included (median age 49 years, IQR 40–56; 98 male), comprising 55 with severe DILI and 250 without. A and F indices increased with inflammation grade and fibrosis stage, respectively (p < 0.01). Combining clinical and dual elastography features with serum biomarkers, the optimized regularized regression model performed best in the test set (AUC 0.862 [95 https://wznng666.shinyapps.io/RR55555/ .

OBJECTIVE:Renal microvascular rarefaction is an early pathological event in chronic kidney disease (CKD) that may precede a measurable decline in renal function. However, currently available non-invasive tools remain limited in detecting these early structural alterations. This study aimed to evaluate the value of super-resolution contrast-enhanced ultrasound (SR-CEUS) for assessing renal cortical microvascular impairment in early CKD with preserved estimated glomerular filtration rate (eGFR), and to compare its performance with conventional contrast-enhanced ultrasound (CEUS) and serum biomarkers. METHODS:In this prospective study, 39 patients with early CKD scheduled for renal biopsy and 41 healthy controls were enrolled. All participants underwent CEUS and SR-CEUS imaging during the same contrast-enhanced examination. Quantitative SR-CEUS parameters, including vessel density (VD), mean velocity (MV) and perfusion index (PI), as well as conventional CEUS time-intensity curve parameters, were analyzed. Logistic regression models were constructed based on variables with significant between-group differences, and diagnostic performance was assessed using receiver operating characteristic analysis. DeLong tests were used to compare model performance. Correlations between imaging-derived parameters and renal functional biomarkers across all participants, as well as histopathological interstitial fibrosis and tubular atrophy scores in the CKD group, were evaluated. RESULTS:Compared with healthy controls, patients with early CKD showed significantly lower VD, MV and PI (all p < 0.001). Among CEUS-derived time-intensity curve parameters, peak enhancement and wash-in perfusion were also significantly reduced (both p < 0.001), whereas time-related parameters showed no significant between-group differences. Among individual variables, VD yielded the best diagnostic performance (area under the receiver operating characteristic curve [AUC] = 0.86; 95% confidence interval [CI]: 0.74-0.95). The SR-CEUS model (VD + MV + PI) achieved the highest diagnostic accuracy (AUC = 0.94; 95% CI: 0.88-0.99), significantly outperforming the CEUS model (AUC = 0.82, p = 0.030) and eGFR (AUC = 0.75, p = 0.003). Across all participants, VD showed the strongest positive correlation with eGFR (r = 0.58, p < 0.001). In the CKD group, VD (r = -0.61), MV (r = -0.44), peak enhancement (r = -0.44) and wash-in perfusion (r = -0.36) were significantly negatively correlated with interstitial fibrosis and tubular atrophy scores. CONCLUSION:SR-CEUS enables non-invasive visualization and quantitative assessment of renal cortical microvascular alterations in early CKD. Compared with conventional CEUS and serum biomarkers, SR-CEUS demonstrated superior diagnostic performance for detecting microvascular impairment in patients with preserved eGFR. These findings suggest that SR-CEUS may serve as a sensitive imaging biomarker for the early non-invasive assessment of CKD-related microvascular injury.

Background:Immunoglobulin A nephropathy (IgAN) has heterogeneous clinical and pathological manifestations. Renal biopsy is the invasive diagnostic standard, and crescents mark active glomerular injury. Quantitative contrast-enhanced ultrasound (CEUS) can characterize renal microvascular perfusion. We aimed to develop a non-invasive nomogram integrating quantitative CEUS parameters and routine serological biomarkers to diagnose IgAN and predict crescent formation. Methods:In this retrospective single-center study, 184 patients with chronic kidney disease (CKD) underwent CEUS within 7 days before renal biopsy. Patients were classified into IgAN (n=94) and non-IgAN (n=90) groups, and the IgAN cohort was further stratified by crescent status (n=47 in each subgroup). Quantitative time-intensity curve (TIC) parameters were extracted from regions of interest (ROIs) using VueBox 7.0 software. Elliptical ROIs of approximately 4 mm × 3 mm were placed in the mid renal cortex and medulla closest to the probe to generate cortical and medullary TICs. Cortex-to-medulla normalization was applied. The analyzed parameters included peak enhancement (PE), wash-in rate (WiR), and wash-in perfusion index (WiP). Logistic regression models were constructed for IgAN diagnosis, crescent prediction in IgAN, and crescent prediction in the entire cohort. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to evaluate discrimination, calibration, and clinical net benefit. DeLong tests compared the combined model (CEUS parameters plus serological indicators), clinical-only model, and CEUS-only model to assess the incremental diagnostic value of CEUS. Subgroup analysis based on estimated glomerular filtration rate (eGFR) was performed for crescent prediction in IgAN to examine the influence of renal function on model performance. Results:IgAN patients showed significantly altered renal perfusion characteristics compared with non-IgAN patients. The combined model incorporating age, eGFR, urine albumin-to-creatinine ratio (UACR), and WiR achieved moderate discrimination for IgAN diagnosis, with an area under the curve (AUC) of 0.78 [95% confidence interval (CI): 0.72-0.85]. For crescent prediction in IgAN, the combined model based on age and WiP achieved an AUC of 0.74 (95% CI: 0.64-0.85). For crescent prediction in the entire cohort, the combined model based on age and rise time (RT) showed an AUC of 0.72 (95% CI: 0.64-0.81). DeLong tests showed that the combined models outperformed the corresponding clinical-only and CEUS-only models (all P<0.05), supporting the incremental but moderate diagnostic value of CEUS. Subgroup analysis showed stronger predictive performance in patients with preserved renal function. Conclusions:CEUS-derived microvascular information, when combined with clinical biomarkers, provides incremental diagnostic information and may assist pre-biopsy risk stratification and crescent formation prediction in CKD. These findings should be interpreted as exploratory and require external validation before routine clinical implementation.

OBJECTIVES:This study sought to design and verify a nomogram that utilizes ultrasonographic and clinical indicators to differentiate between intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC). METHODS:From November 2022 to September 2024, 136 patients with confirmed ICC or HCC were enrolled and randomly assigned to training and validation groups in a 7:3 ratio. Preoperative B-mode ultrasound, contrast-enhanced ultrasound, two-dimensional shear wave elastography features, and clinical indicators were retrieved and compared. Least Absolute Shrinkage and Selection Operator regression and multivariate logistic regression analysis were used to identify independent factors and develop a predictive nomogram. The model's evaluation focused on discrimination, calibration, and clinical utility. RESULTS:Significant predictive factors for ICC include a history of hepatitis, levels of alpha-fetoprotein and carbohydrate antigen 19-9, rim-like arterial phase hyperenhancement, and the stiffness ratio between the lesion and liver parenchyma. With AUC values of 0.987 (95% CI: 0.969, 1.000) for the training set and 0.926 (95% CI: 0.813, 1.000) for the validation set, the nomogram exhibited strong differentiation capabilities between the two entities. CONCLUSIONS:The nomogram combining multimodal indicators achieved high AUC values in both the validation and test sets (AUC = 0.926-0.987), demonstrating robust diagnostic accuracy for distinguishing ICC from HCC. This tool could aid in clinical decision-making for these challenging diagnoses.

Immunogenic programmed cell death effectively triggers acute inflammatory responses, thereby enhancing antitumor immunity. The advancement of biodegradable nonmetallic dual inducers represents a promising strategy. Herein, a biodegradable organomolecular ferroelectric nanoplatform (C60-TCNQ, CT) is designed to facilitate effective ferroelectric catalysis, thereby augmenting tumor immunotherapy through apoptosis and ferroptosis. CT-mediated ultrasound-triggered ferroelectric catalysis promotes ferroelectric polarization and significantly increases the production of reactive oxygen species, leading to substantial tumor cell apoptosis. Moreover, the polycyano group of CT nanoparticles selectively reacts with cysteine under mild conditions, resulting in redox imbalances and the accumulation of lipid peroxides, which contribute to the induction of ferroptosis in tumor cells. Additionally, the apoptosis and ferroptosis induced by CT stimulate immunogenic cell death progression, eliciting robust immune responses. In vivo evaluation using a bilateral tumor model demonstrates the capacity of CT to sensitize anti-PD-L1 therapy under ultrasound irradiation, achieving an impressive antitumor response rate of 96.2% against malignant melanoma and an 80% inhibition of tumor metastasis. RNA sequencing analysis revealed that treatment with CT resulted in a downregulation of gene signatures associated with the immune-related Jak-Stat signaling pathway. This study opens a novel avenue to developing organomolecular ferroelectric nanomedicines for effective tumor immunotherapy.

OBJECTIVE:This study aimed to investigate the reproducibility of ultrasound-derived fat fraction (UDFF) among operators with different experience levels. Furthermore, it seeks to validate the performance of UDFF in detecting hepatic steatosis. MATERIALS AND METHODS:The study was conducted at three hospitals and involved patients suspected of having metabolic dysfunction-associated steatotic liver disease (MASLD). Two radiologists took UDFF measurements from each participant to find the best place to measure and evaluate reproducibility. Subsequently, the performance of the UDFF measurements from the left and right liver lobes in detecting hepatic steatosis was compared with magnetic resonance proton density fat fraction (MRI-PDFF) results. RESULTS:A total of 163 patients were examined for UDFF in both left and right liver lobes. The measurement failure rates were 28.8% for the left lobe and 6.5% for the right lobe. The inter-observer reproducibility was high in the right lobe, with intraclass correlation coefficient (ICCs) of 0.89-0.96. Additionally, 80 participants underwent magnetic MRI-PDFF and UDFF examinations, revealing an area under the curve (AUC) of 0.97 for the right lobe and 0.84 for the left lobe. CONCLUSION:UDFF measurements in the left lobe exhibited a higher failure rate and less consistency, while measurements in the right lobe had a higher success rate and excellent reproducibility. For suspected MASLD patients, at least two measurements were recommended. Additionally, UDFF from the right lobe is more reliable for detecting fatty liver. However, the study had a small sample size, and future research should include larger, multi-center studies. CRITICAL RELEVANCE STATEMENT:Ultrasound-derived fat fraction (UDFF) represents an objective technique characterized by high stability and reproducibility that accurately assesses liver fat content, which is suitable for the screening of metabolic dysfunction-associated steatotic liver disease (MASLD). KEY POINTS:Ultrasound-derived fat fraction (UDFF) obtained from the right lobe demonstrates strong repeatability and reproducibility. UDFF has good diagnostic performance in grading steatosis. UDFF is suitable for the screening of metabolic dysfunction-associated steatotic liver disease (MASLD).

OBJECTIVE:To evaluate the diagnostic performance of ultrasound-derived fat fraction (UDFF) and automated point shear wave elastography (auto-pSWE) for detecting hepatic steatosis and fibrosis in suspected steatotic liver disease (SLD) patients. METHODS:This prospective multicenter study enrolled 259 suspected SLD patients (including bariatric surgery candidates and those with abnormal liver function). All participants underwent liver biopsy, UDFF and auto-pSWE. Comparative and subgroup analyses evaluated their performance in patients with SLD, with or without concurrent viral hepatitis. Liner regression identified factors affecting UDFF/auto-pSWE. LASSO and stepwise models predicted significant fibrosis (≥ F2). RESULTS:UDFF demonstrated high diagnostic accuracy in SLD (n = 221) and SLD & viral hepatitis (n = 38), especially in SLD, with AUCs of 0.94, 0.88, and 0.91 for diagnosing ≥S1, ≥S2, and S3, respectively (p < 0.001). BMI (β = 0.44; 95% CI: 0.31-0.57; p < 0.001), HDL (β = -6.73; 95% CI: -11.06- -2.39; p = 0.002) and auto-pSWE (β = -0.57; 95% CI: -0.10- -0.14; p = 0.009) were identified as significant predictors of UDFF. Auto-pSWE alone showed limited diagnostic performance for fibrosis in both groups, and UDFF was a negative predictor (β = -0.04; 95% CI: -0.07- -0.01; p = 0.028). The LASSO and stepwise models showed good diagnostic performance for ≥ F2 (AUC = 0.80; 95% CI: 0.74-0.86; p < 0.001). CONCLUSIONS:UDFF is an effective method for diagnosing hepatic steatosis in SLD, unaffected by concomitant viral hepatitis. Auto-pSWE's accuracy can be substantially enhanced when combined with clinical-laboratory parameters.

To prospectively evaluate the diagnostic accuracy of ultrasound-derived fat fraction (UDFF) in quantifying hepatic steatosis, to establish and validate a dual-threshold UDFF classification system, and to investigate its efficacy for risk stratification in body mass index (BMI)-defined subgroups. This prospective multicenter study involved 790 suspected metabolic dysfunction-associated steatotic liver disease (MASLD) participants from April 2023 to November 2024 (derivation: n = 553; validation: n = 237). Liver biopsy histopathology (n = 342), MRI proton density fat fraction (MRI-PDFF) (n = 396), or proton magnetic resonance spectroscopy (1H-MRS) (n = 52) was used as the reference standard. UDFF was compared to noninvasive test Hepatic Steatosis Index (HSI) and Fatty Liver Index (FLI) using area under the curve (AUC). The diagnostic thresholds were optimized to maintain at least 90

ABSTRACT Objectives Diabetic peripheral neuropathy (DPN) may affect the biomechanical properties and morphology of the plantar tissue. This study aimed to compare plantar stiffness and thickness in individuals with diabetes with and without DPN and develop a novel explanatory model for DPN risk assessment by integrating these measures with clinical parameters. Materials & Methods Thirty‐two healthy controls and 84 people with diabetes (41 with DPN and 43 without DPN) were included. Shear wave elastography evaluated plantar thickness and stiffness at the heel, hallux, and first and fifth metatarsal heads (1st MTH, 5th MTH). An integrated thickness or stiffness index was generated at multiple locations by principal component analysis (PCA). Results People with DPN showed a significant increase in plantar thickness (heel, 1st MTH) (p < 0.001) and stiffness (all tested locations) compared to healthy controls (p < 0.05). Moreover, plantar thickness at 1st MTH, plantar stiffness at 5th MTH, and integrated stiffness index generated by PCA were significantly higher in DPN than in the non‐DPN group (p < 0.05). A DPN explanatory model was developed using multivariate logistic regression, incorporating the integrated plantar stiffness index, diabetes duration, and gender. The model showed high discriminative ability (AUROC: 97.7%), with an optimal cutoff of 0.56 yielding 92.7% sensitivity and 95.3% specificity. Conclusion The integrated plantar stiffness index, combined with gender and diabetes duration, offers a novel approach for DPN, providing a noninvasive tool for DPN risk assessment.

BACKGROUND Hepatic steatosis, characterized by fat accumulation in hepatocytes, can result from metabolic dysfunction-associated steatotic liver disease (MASLD), infections, alcoholism, chemotherapy, and toxins. MASLD is diagnosed via imaging or biopsy with metabolic criteria and may progress to metabolic dysfunction–associated steatohepatitis, potentially leading to fibrosis, cirrhosis, or cancer. The coexistence of hepatic steatosis with chronic hepatitis B (CHB) is mainly related to metabolic factors and increases mortality and cancer risks. As a noninvasive method, attenuation imaging (ATI) shows promise in quantifying liver fat, demonstrating strong correlation with liver biopsy. AIM To investigate the disparity of ATI for assessing biopsy-based hepatic steatosis in CHB patients and MASLD patients. METHODS The study enrolled 249 patients who underwent both ATI and liver biopsy, including 78 with CHB and 171 with MASLD. Hepatic steatosis was classified into grades S0 to S3 according to the proportion of fat cells present. Liver fibrosis was staged from 0 to 4 according to the meta-analysis of histological data in viral hepatitis scoring system. The diagnostic performance of attenuation coefficient (AC) values across different groups was compared for each grade of steatosis. Factors associated with the AC values were determined through linear regression analysis. A multivariate logistic regression model was established to predict ≥ S2 within the MASLD group. RESULTS In both the CHB and the MASLD groups, AC values increased significantly with higher steatosis grade (P < 0.001). In the CHB group, the areas under the curve (AUCs) of AC for predicting steatosis grades ≥ S1, ≥ S2 and S3 were 0.918, 0.960 and 0.987, respectively. In contrast, the MASLD group showed AUCs of 0.836, 0.774, and 0.688 for the same steatosis grades. The diagnostic performance of AC for detecting ≥ S2 and S3 indicated significant differences between the two groups (both P < 0.001). Multivariate linear regression analysis identified body mass index, triglycerides, and steatosis grade as significant factors for AC. When the steatosis grade is ≥ S2, it can progress to more serious liver conditions. A clinical model integrating blood biochemical parameters and AC was developed in the MASLD group to enhance the prediction of ≥ S2, achieving an AUC of 0.848. CONCLUSION The AC could effectively discriminate the degree of steatosis in both the CHB and MASLD groups. In the MASLD group, when combined with blood biochemical parameters, AC exhibited better predictive ability for moderate to severe steatosis.

Immune checkpoint blockade (ICB) is combined with sonodynamic therapy (SDT) to increase response rates and enhance anticancer efficacy. However, the "always on" property of most sonosensitizers in reducing tumor microenvironment (TME) compromises the therapeutic outcome of sonoimmunotherapy and exacerbates adverse side effects. Precisely controllable strategies combining sulfur dioxide (SO2) gas therapy with cancer immunotherapy can address these issues but remain lacking. Herein an "activatable SO2 nanosonosensitizer" for precise sono-gaseous checkpoint trimodal therapy of orthotopic hepatocellular carcinoma (HCC) is reported, whose full activity is initiated by ultrasound (US) irradiation in the reducing TME. This "activatable SO2 nanosonosensitizer," Aza-DNBS nanoparticles (NPs), are established by self-assembling Aza-boron-dipyrromethene based sonosensitizer molecules and 2,4-dinitrobenzenesulfonate (DNBS)-caged SO2 prodrug. The activity of Aza-DNBS NPs is initially silenced, and the sonodynamic, gaseous, and immunosuppressive TME reprogramming activities are precisely awakened under US irradiation. Due to the glutathione-responsiveness of Aza-DNBS NPs, Aza-DNBS NPs can generate large amounts of SO2 for gas therapy-enhanced SDT, which triggers robust immunogenic cell death activation and reprogramming of the immunosuppressive TME, thereby significantly suppressing orthotopic tumor growth and delaying lung metastasis. Thus, this study represents a strategy for designing a generic nanoplatform for precisely combined immunotherapy of orthotopic HCC.

The undesirable efficacy of immunotherapy in cancer patients is associated with the inactivation of immune responses in tumor immunosuppressive microenvironment (TIME). The pivotal roles of nitric oxide (NO) and peroxynitrite (ONOO-) in immunoregulation can augment anticancer immunotherapy. Here, ultrasound (US)-responsive nanoparticles (NPs), denoted as Cu-PG NPs, are elaborately constructed to achieve incremental NO release for gas therapy and controlled generation of superoxide anion (O2 center dot-) for sonodynamic therapy (SDT), thereby leading to synergistic in situ ONOO- generation and TIME reprogramming. In vitro and in vivo experimental results collectively confirm that US-activated Cu-PG NPs effectively regulate immune circulation, which involves multiple steps to ameliorate compromise immunogenicity without systemic toxicity. These steps comprise the initiation of immunogenic cell death in cancer cells, induction of dendritic cells maturation, promotion of cytotoxic T lymphocytes infiltration, and polarization of macrophages toward the pro-inflammatory M1 phenotype. Importantly, this therapeutic approach reinforces systemic immunity and elicits immune memory to inhibit the proliferation of distant tumors, particularly integration with anti-PD-L1 antibodies. This work proposes the synergistic gas therapy and SDT strategy for generating ONOO-, which holds enormous potential in potentiating immunotherapy sensitivity by further facilitating the coordinated remodeling of TIME. The innovative Cu-PG NPs facilitate the controlled release of nitric oxide and reactive oxygen species, enabling the on-demand generation of peroxynitrite through a combination of copper ion-catalyzed S-nitrosoglutathione and sonosensitizer-mediated sonodynamic therapy. This strategy initiates immunogenic cell death in tumor cells and drives M1 macrophages polarization, effectively reprogramming the tumor immunosuppressive microenvironment to enhance the efficacy of immunotherapy. image

PURPOSE:Posthepatectomy liver failure (PHLF) is a major cause of postoperative mortality in hepatocellular carcinoma (HCC) patients. The study aimed to develop a method based on the two-dimensional shear wave elastography and clinical data to evaluate the risk of PHLF in HCC patients with chronic hepatitis B. METHODS:This multicenter study proposed a deep learning model (PHLF-Net) incorporating dual-modal ultrasound features and clinical indicators to predict the PHLF risk. The datasets were divided into a training cohort, an internal validation cohort, an internal independent testing cohort, and three external independent testing cohorts. Based on ResNet50 pretrained on ImageNet, PHLF-Net used a progressive training strategy with images of varying granularity and incorporated conventional B-mode and elastography images and clinical indicators related to liver reserve function. RESULTS:In total, 532 HCC patients who underwent hepatectomy at five hospitals were enrolled. PHLF occurred in 147 patients (27.6%, 147/532). The PHLF-Net combining dual-modal ultrasound and clinical indicators demonstrated high effectiveness for predicting PHLF, with AUCs of 0.957 and 0.923 in the internal validation and testing sets, and AUCs of 0.950, 0.860, and 1.000 in the other three independent external testing sets. The performance of PHLF-Net outperformed models of single- and dual-modal US. CONCLUSIONS:Preoperative ultrasound imaging combining clinical indicators can effectively predict the PHLF probability in patients with HCC. In the internal and external validation sets, PHLF-Net demonstrated its usefulness in predicting PHLF.

Objective Drug-induced liver injury (DILI) is one of the most challenging forms of liver disorder. We aimed to use ultrasound dual elastography, by combining strain and shear wave imaging, to noninvasively assess liver inflammation and injury severity of DILI. Methods 291 DILI patients were included in the prospective multicenter study and divided into training and validation cohorts. All patients received liver biopsy and dual elastography examination. Liver inflammation grading (G0-4) and fibrosis staging (F0-4) were considered as the gold standard of liver injury and G+F u2265 5 was defined as severe liver injury. Indexes of dual elastography and serological indicators (DESI) were selected and analyzed with multivariable logistic regression to build DESI models for evaluating liver inflammation, and the C score model was built with the same method for diagnosing severe liver injury. Results Areas under the receiver operating characteristic curve (AUCs) of the DESI model to assess liver inflammation u2265 G2 were 0.887 and 0.868 in training and validation cohorts, respectively. AUCs of the DESI model in diagnosing u2265 G3 were 0.893 and 0.896 in the two cohorts, respectively. The C score accurately assessed severe liver injury with AUCs of 0.909 and 0.885 in two cohorts. Of the 87 patients with mild clinical severity, 10 (11.49%) had severe pathological injury, which could be identified by C score. Conclusion Dual elastography demonstrated high performance in diagnosing liver inflammation and identifying severe pathological liver injury of DILI, making up for the deficiency of serological indicators alone for evaluating DILI severity.

BACKGROUND Liver stiffness (LS) measurement with two-dimensional shear wave elastography (2D-SWE) correlates with the degree of liver fibrosis and thus indirectly reflects liver function reserve. The size of the spleen increases due to tissue proliferation, fibrosis, and portal vein congestion, which can indirectly reflect the situation of liver fibrosis/cirrhosis. It was reported that the size of the spleen was related to posthepatectomy liver failure (PHLF). So far, there has been no study combining 2D-SWE measurements of LS with spleen size to predict PHLF. This prospective study aimed to investigate the utility of 2D-SWE assessing LS and spleen area (SPA) for the prediction of PHLF in hepatocellular carcinoma (HCC) patients and to develop a risk prediction model. AIM To investigate the utility of 2D-SWE assessing LS and SPA for the prediction of PHLF in HCC patients and to develop a risk prediction model. METHODS This was a multicenter observational study prospectively analyzing patients who underwent hepatectomy from October 2020 to March 2022. Within 1 wk before partial hepatectomy, ultrasound examination was performed to measure LS and SPA, and blood was drawn to evaluate the patient’s liver function and other conditions. Least absolute shrinkage and selection operator logistic regression and multivariate logistic regression analysis was applied to identify independent predictors of PHLF and develop a nomogram. Nomogram performance was validated further. The diagnostic performance of the nomogram was evaluated with receiver operating characteristic curve compared with the conventional models, including the model for end-stage liver disease (MELD) score and the albumin-bilirubin (ALBI) score. RESULTS A total of 562 HCC patients undergoing hepatectomy (500 in the training cohort and 62 in the validation cohort) were enrolled in this study. The independent predictors of PHLF were LS, SPA, range of resection, blood loss, international normalized ratio, and total bilirubin. Better diagnostic performance of the nomogram was obtained in the training [area under receiver operating characteristic curve (AUC): 0.833; 95% confidence interval (95%CI): 0.792-0.873; sensitivity: 83.1%; specificity: 73.5%] and validation (AUC: 0.802; 95%CI: 0.684-0.920; sensitivity: 95.5%; specificity: 52.5%) cohorts compared with the MELD score and the ALBI score. CONCLUSION This PHLF nomogram, mainly based on LS by 2D-SWE and SPA, was useful in predicting PHLF in HCC patients and presented better than MELD score and ALBI score.

Objective:To investigate the clinical value of multiparameteric quantitative ultrasound combined with a non-invasive prediction model for assessing high-risk steatohepatitis.Methods:One hundred and ninety-four cases with metabolic-associated fatty liver disease (MAFLD) who underwent liver biopsy in Huashan Hospital, Fudan University, from June 2021 to September 2022 were selected. Shear wave elastography (SWE), shear wave dispersion (SWD) imaging, and attenuation imaging (ATI) examinations were conducted in all patients before biopsy. High-risk steatohepatitis was defined as a total activity score of ≥4 in patients with steatohepatitis, hepatocellular ballooning, and liver lobular inflammation based on pathological hepatic steatosis, inflammatory activity, and fibrosis scoring system (SAF), and fibrosis stage≥F2. Binary logistic regression analysis was used to identify the factors influencing high-risk steatohepatitis. A predictive model for diagnosing high-risk steatohepatitis was constructed using R language. The DeLong test was used to compare the area under the curve between groups. Measurement data was compared between groups using the t-test or rank-sum test, and count data were compared between groups using the χ2 test. Results:There were 46 cases (23.7%) with high-risk steatohepatitis. The quantitative ultrasound parameters included elastic modulus ( OR=2.958, 95% CI: 1.889-4.883, P<0.001), dispersion coefficient ( OR=1.786, 95% CI: 1.424-2.292, P<0.001) and attenuation coefficient ( OR=42.642, 95% CI: 3.463-640.451, P=0.004). Serological indexes of fasting blood glucose ( OR=1.196, 95% CI: 1.048-1.392, P=0.011), alanine aminotransferase ( OR=1.012, 95% CI: 1.006-1.019, P<0.001), aspartate aminotransferase ( OR=1.027, 95% CI: 1.014-1.042, P<0.001), γ-glutamyl transferase ( OR=1.008, 95% CI: 1.001-1.017, P=0.041) and HDL cholesterol ( OR=0.087, 95% CI: 0.016-0.404, P=0.003) were the factors influencing its progression. The AUCs of elastic modulus, dispersion coefficient, attenuation coefficient, multiparametric ultrasound model, serological index model, and ultrasound combined with serology model for the diagnosis of high-risk steatohepatitis were 0.764, 0.758, 0.634, 0.786, 0.773 and 0.825, respectively. The results of the DeLong test showed that the ultrasound combined with the serological model was significantly better than the serological index model and the elastic modulus, dispersion coefficient, and attenuation coefficient alone ( P=0.024, 0.027, 0.038 and <0.001). Conclusion:The combination of multiparametric quantitative ultrasound is helpful for the non-invasive diagnosis of high-risk steatohepatitis and possesses great clinical significance.