Non-invasive assessment of esophageal varices: Status of today

With increasing burden of compensated cirrhosis, we desperately need non-invasive methods for assessment of clinically significant portal hypertension. The use of liver and spleen stiffness measurement helps in deferring unnecessary endoscopies for low risk esophageal varices. This would reduce cost and patient discomfort. However, these special techniques may not be feasible at remote areas where still we need only biochemical parameters. More prospective studies validating the non-invasive risk prediction models are definitely needed.

Letter to editor ‘Non-invasive model for predicting high-risk esophageal varices based on liver and spleen stiffness’

This letter to the editor relates to the study entitled "Non-invasive model for predicting high-risk esophageal varices based on liver and spleen stiffness". Acute bleeding caused by esophageal varices is a life-threatening complication in patients with liver cirrhosis. Due to the discomfort, contraindications, and associated complications of upper gastrointestinal endoscopy screening, it is crucial to identify an imaging-based non-invasive model for predicting high-risk esophageal varices in patients with cirrhosis.

Non-invasive model for predicting high-risk esophageal varices based on liver and spleen stiffness

BACKGROUND

Acute bleeding due to esophageal varices (EVs) is a life-threatening complication in patients with cirrhosis. The diagnosis of EVs is mainly through upper gastrointestinal endoscopy, but the discomfort, contraindications and complications of gastrointestinal endoscopic screening reduce patient compliance. According to the bleeding risk of EVs, the Baveno VI consensus divides varices into high bleeding risk EVs (HEVs) and low bleeding risk EVs (LEVs). We sought to identify a non-invasive prediction model based on spleen stiffness measurement (SSM) and liver stiffness measurement (LSM) as an alternative to EVs screening.

AIM

To develop a safe, simple and non-invasive model to predict HEVs in patients with viral cirrhosis and identify patients who can be exempted from upper gastrointestinal endoscopy.

METHODS

Data from 200 patients with viral cirrhosis were included in this study, with 140 patients as the modelling group and 60 patients as the external validation group, and the EVs types of patients were determined by upper gastrointestinal endoscopy and the Baveno VI consensus. Those patients were divided into the HEVs group (66 patients) and the LEVs group (74 patients). The effect of each parameter on HEVs was analyzed by univariate and multivariate analyses, and a non-invasive prediction model was established. Finally, the discrimination ability, calibration ability and clinical efficacy of the new model were verified in the modelling group and the external validation group.

RESULTS

Univariate and multivariate analyses showed that SSM and LSM were associated with the occurrence of HEVs in patients with viral cirrhosis. On this basis, logistic regression analysis was used to construct a prediction model: Ln [P/(1-P)] = -8.184 -0.228 × SSM + 0.642 × LSM. The area under the curve of the new model was 0.965. When the cut-off value was 0.27, the sensitivity, specificity, positive predictive value and negative predictive value of the model for predicting HEVs were 100.00%, 82.43%, 83.52%, and 100%, respectively. Compared with the four prediction models of liver stiffness-spleen diameter to platelet ratio score, variceal risk index, aspartate aminotransferase to alanine aminotransferase ratio, and Baveno VI, the established model can better predict HEVs in patients with viral cirrhosis.

CONCLUSION

Based on the SSM and LSM measured by transient elastography, we established a non-invasive prediction model for HEVs. The new model is reliable in predicting HEVs and can be used as an alternative to routine upper gastrointestinal endoscopy screening, which is helpful for clinical decision making.

Non-invasive prediction model for high-risk esophageal varices in the Chinese population

BACKGROUND

There are two types of esophageal varices (EVs): high-risk EVs (HEVs) and low-risk EVs, and HEVs pose a greater threat to patient life than low-risk EVs. The diagnosis of EVs is mainly conducted by gastroscopy, which can cause discomfort to patients, or by non-invasive prediction models. A number of non-invasive models for predicting EVs have been reported; however, those that are based on the formula for calculation of liver and spleen volume in HEVs have not been reported.

AIM

To establish a non-invasive prediction model based on the formula for liver and spleen volume for predicting HEVs in patients with viral cirrhosis.

METHODS

Data from 86 EV patients with viral cirrhosis were collected. Actual liver and spleen volumes of the patients were determined by computed tomography, and their calculated liver and spleen volumes were calculated by standard formulas. Other imaging and biochemical data were determined. The impact of each parameter on HEVs was analyzed by univariate and multivariate analyses, the data from which were employed to establish a non-invasive prediction model. Then the established prediction model was compared with other previous prediction models. Finally, the discriminating ability, calibration ability, and clinical efficacy of the new model was verified in both the modeling group and the external validation group.

RESULTS

Data from univariate and multivariate analyses indicated that the liver-spleen volume ratio, spleen volume change rate, and aspartate aminotransferase were correlated with HEVs. These indexes were successfully used to establish the non-invasive prediction model. The comparison of the models showed that the established model could better predict HEVs compared with previous models. The discriminating ability, calibration ability, and clinical efficacy of the new model were affirmed.

CONCLUSION

The non-invasive prediction model for predicting HEVs in patients with viral cirrhosis was successfully established. The new model is reliable for predicting HEVs and has clinical applicability.

High-risk esophageal varices in patients treated with locoregional therapy for hepatocellular carcinoma: Assessment with liver computed tomography

AIM: To assess the diagnostic performance of follow-up liver computed tomography (CT) for the detection of high-risk esophageal varices in patients treated with locoregional therapy for hepatocellular carcinoma (HCC).

METHODS: We prospectively enrolled 100 patients with cirrhosis who underwent transcatheter arterial chemoembolization, radiofrequency ablation or both procedures for HCCs. All patients underwent upper endoscopy and subsequently liver CT. Three radiologists independently evaluated the presence of high-risk esophageal varices with transverse images alone and with three orthogonal multiplanar reformation (MPR) images, respectively. With endoscopic grading as the reference standard, diagnostic performance was assessed by using receiver operating characteristic (ROC) curve analysis.

RESULTS: The diagnostic performances (areas under the ROC curve) of three observers with transverse images alone were 0.947 ± 0.031, 0.969 ± 0.024, and 0.916 ± 0.038, respectively. The mean sensitivity, specificity, positive predicative value (PPV), and negative predicative value (NPV) with transverse images alone were 90.1%, 86.39%, 70.9%, and 95.9%, respectively. The diagnostic performances, mean sensitivity, specificity, PPV, and NPV with three orthogonal MPR images (0.965 ± 0.025, 0.959 ± 0.027, 0.938 ± 0.033, 91.4%, 89.5%, 76.3%, and 96.6%, respectively) were not superior to corresponding values with transverse images alone (P > 0.05), except for the mean specificity (P = 0.039).

CONCLUSION: Our results showed excellent diagnostic performance, sensitivity and NPV to detect high-risk esophageal varices on follow-up liver CT after locoregional therapy for HCC.