Liver Stiffness Measured with Two-dimensional Shear-Wave Elastography                    Is Predictive of Liver-related Events in Patients with Chronic Liver Disease Due                    to Hepatis B Viral Infection

Wu, Manli; Wu, Lili; Jin, Jieyang; Wang, Jinfen; Li, Shuoyang; Zeng, Jie; H, Guo; Zheng, Jian; Chen, Shigao; Zheng, Rongqin

doi:10.1148/radiol.2020191481

Cited by 26 publications

(26 citation statements)

References 33 publications

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“…TE was recommended as a first-line examination for liver fibrosis and cirrhosis (31). Previous studies found that 2D SWE had comparable diagnostic accuracy to TE (8,11,12). Moreover, it is inappropriate for hospitalized patients with liver cirrhosis to perform TE because of ascites and liver atrophy.…”

Section: Discussionmentioning

confidence: 98%

“…Furthermore, when measuring 2D SWE values, we can simultaneously measure PVv and monitor ascites and liver tumors. Wu et al (12) demonstrated that 2D SWE could predict liverrelated events in patients with compensated liver cirrhosis. Jin et al (10) found that 2D SWE improved the predictive performance of MELD in ACLF patients.…”

Section: Discussionmentioning

confidence: 99%

“…2D SWE can be applied to patients with ascites, and performed with B-mode image guidance. Previous studies (9,10,12,13) determined that 2D SWE values were significantly associated with liver fibrosis, liver-related events and prognosis. Few prior studies used 2D SWE to predict ACLF development among patients with acutely decompensated hepatitis B cirrhosis (AD-HBV).…”

Section: Introductionmentioning

confidence: 99%

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A model based on two-dimensional shear wave elastography for acute-on-chronic liver failure development in patients with acutely decompensated hepatitis B cirrhosis

Yuan¹,

Huang²,

Wu³

et al. 2022

Quant Imaging Med Surg

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Background: To evaluate the accuracy of two-dimensional (2D) shear wave elastography (SWE), develop and validate a novel prognostic model in predicting acute-on-chronic liver failure (ACLF) development in patients with acutely decompensated hepatitis B cirrhosis. Methods: This prospective cohort study enrolled 221 patients in the First Affiliated Hospital of Nanchang University from September 2019 to January 2021, and randomly assigned them to the derivation and validation cohorts (7:3 ratio). Ultrasound, 2D SWE, clinical and laboratory data were collected, and outcome (ACLF developed) was recorded during a 90-day follow-up period. We evaluated the ability of 2D SWE to predict the outcome, developed a model for predicting ACLF development in the derivation cohort, and assessed the model in the validation cohort. Results: 2D SWE values were significantly higher in patients with ACLF development (P<0.05). The accuracy of 2D SWE in predicting the outcome was better than that of serum parameters of liver fibrosis (all P<0.05). The SWE model for ACLF development had good calibration and discrimination [concordance index (C-index): 0.855 and 0.840 respectively] in derivation and validation cohorts, outperforming serum prognostic scores (all P<0.05). Conclusions: The SWE model, superior to serum prognostic scores in predicting ACLF development, could be a noninvasive tool to guide the individual management of patients with acutely decompensated hepatitis B cirrhosis.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A model based on two-dimensional shear wave elastography for acute-on-chronic liver failure development in patients with acutely decompensated hepatitis B cirrhosis

Yuan¹,

Huang²,

Wu³

et al. 2022

Quant Imaging Med Surg

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“…Remarkably, the post-treatment LSM of 2D-SWE, but not the pre-treatment level or dynamic changes in LSM, appeared to be a superior predictor of LRE in our study. In patients without decompensated cirrhosis, the baseline levels of 2D-SWE or quick liver stiffness response seemed to be useful markers for predicting LREs or remission of disease (8,18). This may be because pre-treatment 2D-SWE simply reflects the baseline status, whereas the post-treatment LSM level may represent the combination of baseline and the treatment response, and the treatment response has been reported to have high heterogeneity (23,24).…”

Section: Discussionmentioning

confidence: 99%

“…A meta-analysis covering 13 studies and 1,143 patients demonstrated that 2D-SWE has a better performance for the noninvasive staging of liver fibrosis in patients with CHB, with the area under the receiver operating characteristic (ROC) curve (AUC) increasing by 0.003-0.034 when diagnosing cirrhosis (P=0.022) (7). However, in a recent report of a 4-year follow-up with rare liver-related events (LREs) (6.7%), baseline LSM of 2D-SWE showed an AUC similar to that of transient elastography (AUC, 0.86 vs. 0.88, P=0.71) for the prediction of liver-related outcomes in patients with CHB, which may ignore the value of dynamic changes of 2D-SWE (8). Therefore, it would be necessary to explore the predictive value of baseline and dynamic changes in 2D-SWE in hepatic complications for those with decompensated cirrhosis receiving antiviral therapy.…”

Section: Introductionmentioning

confidence: 97%

Dynamic monitoring with shear wave elastography predicts outcomes of chronic hepatitis B patients with decompensated cirrhosis

Ye¹,

Huang²,

Sun³

et al. 2021

Ann Transl Med

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Background: Two-dimensional shear wave elastography (2D-SWE) can be used to accurately assess significant liver fibrosis in chronic hepatitis B (CHB). However, whether those with decompensated cirrhosis could benefit from surveillance with 2D-SWE remains unclear. We aimed to evaluate the association between dynamic changes in 2D-SWE measurements and the prognosis of CHB-related decompensated cirrhosis.Methods: We prospectively enrolled 149 consecutive treatment-naive CHB patients with decompensated cirrhosis from a clinical trial (registration number: ChiCTR-DCD-15006000) from February 2015 to December 2018. 2D-SWE was performed at 48-week intervals until December 2020. Liver-related events (LREs) were recorded through electronic medical records and telephone interviews. Results:The liver stiffness measurement (LSM) levels persistently reduced after antiviral therapy in patients who did not develop LREs, while patients with LREs showed a fluctuating trend of LSM alterations.Low pre-treatment 2D-SWE LSM, ∆% 2D-SWE LSM pre-virus control, and ∆% 2D-SWE LSM prepost treatment were characterized by similar prognostic abilities as high levels of these parameters. Posttreatment 2D-SWE LSM was independently correlated with LREs in multivariate Cox regression models after antiviral treatments [hazard ratio (HR) =1.05; 95% confidence interval (CI): 1.02-1.08, P=0.0007 and 1.11; 95% CI: 1.04-1.18, P=0.0026]. Receiver operating characteristic (ROC) curve analysis identified that post-treatment 2D-SWE LSM exhibited the best predictive power for LREs among all the other variables, including parameters of 2D-SWE and serum fibrosis markers (area under the curve =0.75, P<0.001). Conclusions:The last follow-up LSM, rather than pre-treatment or dynamic changes in 2D-SWE serves as a powerful predictor of LREs, suggesting that sequential monitoring may be beneficial to predicting prognosis.

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Shear wave elastography‐based deep learning model for prognosis of patients with acutely decompensated cirrhosis

Huang,

Li,

Yuan

et al. 2023

J of Clinical Ultrasound

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PurposeThis study aimed to develop and validate a deep learning model based on two‐dimensional (2D) shear wave elastography (SWE) for predicting prognosis in patients with acutely decompensated cirrhosis.MethodsWe prospectively enrolled 288 acutely decompensated cirrhosis patients with a minimum 1‐year follow‐up, divided into a training cohort (202 patients, 1010 2D SWE images) and a test cohort (86 patients, 430 2D SWE images). Using transfer learning by Resnet‐50 to analyze 2D SWE images, a SWE‐based deep learning signature (DLswe) was developed for 1‐year mortality prediction. A combined nomogram was established by incorporating deep learning SWE information and laboratory data through a multivariate Cox regression analysis. The performance of the nomogram was evaluated with respect to predictive discrimination, calibration, and clinical usefulness in the training and test cohorts.ResultsThe C‐index for DLswe was 0.748 (95% CI 0.666–0.829) and 0.744 (95% CI 0.623–0.864) in the training and test cohorts, respectively. The combined nomogram significantly improved the C‐index, accuracy, sensitivity, and specificity of DLswe to 0.823 (95% CI 0.763–0.883), 86%, 75%, and 89% in the training cohort, and 0.808 (95% CI 0.707–0.909), 83%, 74%, and 85% in the test cohort (both p < 0.05). Calibration curves demonstrated good calibration of the combined nomogram. Decision curve analysis indicated that the nomogram was clinically valuable.ConclusionsThe 2D SWE‐based deep learning model holds promise as a noninvasive tool to capture valuable prognostic information, thereby improving outcome prediction in patients with acutely decompensated cirrhosis.

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Liver Stiffness Measured with Two-dimensional Shear-Wave Elastography Is Predictive of Liver-related Events in Patients with Chronic Liver Disease Due to Hepatis B Viral Infection

Cited by 26 publications

References 33 publications

A model based on two-dimensional shear wave elastography for acute-on-chronic liver failure development in patients with acutely decompensated hepatitis B cirrhosis

A model based on two-dimensional shear wave elastography for acute-on-chronic liver failure development in patients with acutely decompensated hepatitis B cirrhosis

Dynamic monitoring with shear wave elastography predicts outcomes of chronic hepatitis B patients with decompensated cirrhosis

Shear wave elastography‐based deep learning model for prognosis of patients with acutely decompensated cirrhosis

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