CT esophagography: Non invasive screening and grading of esophageal varices in cirrhosis

Computed tomography for the diagnosis of gastroesophageal varices and risk assessment in patients with cirrhosis: a systematic review and meta-analysis

PURPOSE

This meta-analysis aimed to evaluate the diagnostic accuracy of computed tomography (CT) for detecting gastroesophageal varices (GEVs) and identify high-risk GEVs in patients with cirrhosis.

METHODS

A comprehensive search of databases identified 28 studies reporting on CT-based diagnosis for GEVs confirmed via endoscopy. Meta-analyses were conducted to calculate pooled sensitivity (SEN) and pooled specificity (SPE), positive likelihood ratio (PLR) and negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the curve (AUC).

RESULTS

Based on the number of patients (or varices), the pooled SEN, SPE, PLR, NLR, DOR, and AUC of CT-based diagnosis were estimated at 0.91 (0.92), 0.81 (0.45), 4.82 (1.67), 0.11 (0.17), 42.47 (10.26), and 0.93 (0.94), respectively, for any GEV and at 0.89 (0.89), 0.90 (0.79), 8.86 (4.28), 0.12 (0.14), 75.71 (30.19), and 0.95 (0.85), respectively, for high-risk GEVs. Subgroup analyses indicated that CT had a higher diagnostic accuracy for esophageal varices compared with gastric varices (AUC: 0.93 vs. 0.89, P < 0.05), and the 64-slice CT yielded superior SEN compared with 16-slice and <16-slice CT (AUC: 0.97 vs. 0.92 and 0.82, respectively, P < 0.05). Prospective studies demonstrated higher diagnostic accuracy than retrospective studies (AUC: 0.95 vs. 0.90, P < 0.05). Regarding variceal size, a cut-off of 3 mm and 5 mm discriminated between low- and high-risk individuals, respectively, with high diagnostic accuracy (AUC: 0.992 vs. 0.997, P > 0.05).

CONCLUSION

CT demonstrates promising diagnostic accuracy for identifying gastroesophageal varices and distinguishing high-risk GEVs in patients with cirrhosis. Further research to validate optimal variceal size cut-offs is warranted to enhance clinical utility.

CLINICAL SIGNIFICANCE

Such a high diagnostic accuracy of CT scans for predicting varices is clinically meaningful for patients with cirrhosis accompanied by portal hypertension. If high-risk varices are identified at CT scans, early intervention would be helpful to reduce the risk of variceal bleeding.

The diagnostic accuracy of triphasic abdominal CT in detecting esophageal varices

BACKGROUND

In Tanzania, triphasic abdominal Computed Tomography (CT) is a more accessible and non-invasive alternative for diagnosing esophageal varices, though its accuracy has not been thoroughly evaluated, therefore this study aimed to determine the diagnostic accuracy of triphasic abdominal CT in detecting esophageal varices using esophagogastroduodenoscopy (OGD) as the gold standard among patients with upper gastrointestinal bleeding at Muhimbili National Hospital (MNH).

METHODS

This cross-sectional study was conducted at MNH from January 2021 to May 2023. We sampled upper gastrointestinal bleeding patients who underwent both OGD and triphasic abdominal CT using non-probability consecutive sampling. The sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and accuracy of triphasic abdominal CT were assessed against OGD findings.

RESULTS

In a study of 200 participants, esophageal varices were detected in 54% by OGD and 53.5% by CT. We observed 105 true positives, 2 false positives, 90 true negatives, and 3 false negatives. Triphasic abdominal CT demonstrated a sensitivity of 97.2%, specificity of 97.8%, PPV of 98.1%, NPV of 96.8%, and an accuracy of 97.5%. Extraluminal findings included portal venous thrombosis in (22%), splenic collateral (51.5%), ascites (32%), hepatocellular carcinoma (13%), and periportal fibrosis (32%).

CONCLUSION

Triphasic abdominal Computed Tomography can be used as a reliable and non-invasive alternative modality for diagnosing and screening esophageal varices in resource-limited settings.

Computed tomography vs liver stiffness measurement and magnetic resonance imaging in evaluating esophageal varices in cirrhotic patients: A systematic review and meta-analysis

BACKGROUND

Computed tomography (CT), liver stiffness measurement (LSM), and magnetic resonance imaging (MRI) are non-invasive diagnostic methods for esophageal varices (EV) and for the prediction of high-bleeding-risk EV (HREV) in cirrhotic patients. However, the clinical use of these methods is controversial.

AIM

To evaluate the accuracy of LSM, CT, and MRI in diagnosing EV and predicting HREV in cirrhotic patients.

METHODS

We performed literature searches in multiple databases, including PubMed, Embase, Cochrane, CNKI, and Wanfang databases, for articles that evaluated the accuracy of LSM, CT, and MRI as candidates for the diagnosis of EV and prediction of HREV in cirrhotic patients. Summary sensitivity and specificity, positive likelihood ratio and negative likelihood ratio, diagnostic odds ratio, and the areas under the summary receiver operating characteristic curves were analyzed. The quality of the articles was assessed using the quality assessment of diagnostic accuracy studies-2 tool. Heterogeneity was examined by Q-statistic test and I 2 index, and sources of heterogeneity were explored using meta-regression and subgroup analysis. Publication bias was evaluated using Deek's funnel plot. All statistical analyses were conducted using Stata12.0, MetaDisc1.4, and RevMan5.3.

RESULTS

Overall, 18, 17, and 7 relevant articles on the accuracy of LSM, CT, and MRI in evaluating EV and HREV were retrieved. A significant heterogeneity was observed in all analyses (P < 0.05). The areas under the summary receiver operating characteristic curves of LSM, CT, and MRI in diagnosing EV and predicting HREV were 0.86 (95% confidence interval [CI]: 0.83-0.89), 0.91 (95%CI: 0.88-0.93), and 0.86 (95%CI: 0.83-0.89), and 0.85 (95%CI: 0.81-0.88), 0.94 (95%CI: 0.91-0.96), and 0.83 (95%CI: 0.79-0.86), respectively, with sensitivities of 0.84 (95%CI: 0.78-0.89), 0.91 (95%CI: 0.87-0.94), and 0.81 (95%CI: 0.76-0.86), and 0.81 (95%CI: 0.75-0.86), 0.88 (95%CI: 0.82-0.92), and 0.80 (95%CI: 0.72-0.86), and specificities of 0.71 (95%CI: 0.60-0.80), 0.75 (95%CI: 0.68-0.82), and 0.82 (95%CI: 0.70-0.89), and 0.73 (95%CI: 0.66-0.80), 0.87 (95%CI: 0.81-0.92), and 0.72 (95%CI: 0.62-0.80), respectively. The corresponding positive likelihood ratios were 2.91, 3.67, and 4.44, and 3.04, 6.90, and2.83; the negative likelihood ratios were 0.22, 0.12, and 0.23, and 0.26, 0.14, and 0.28; the diagnostic odds ratios were 13.01, 30.98, and 19.58, and 11.93, 49.99, and 10.00. CT scanner is the source of heterogeneity. There was no significant difference in diagnostic threshold effects (P > 0.05) or publication bias (P > 0.05).

CONCLUSION

Based on the meta-analysis of observational studies, it is suggested that CT imaging, a non-invasive diagnostic method, is the best choice for the diagnosis of EV and prediction of HREV in cirrhotic patients compared with LSM and MRI.

Computed tomography for the diagnosis of varices in liver cirrhosis: a systematic review and meta-analysis of observational studies

OBJECTIVES

This systematic review and meta-analysis aimed to evaluate the diagnostic accuracy of contrast-enhanced computed tomography (CT) for varices in liver cirrhosis.

METHODS

PubMed and EMBASE databases were searched for the literature identification. The area under the summary receiver operating characteristic curve (AUSROC), sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR), and diagnostic odds ratio (DOR) were calculated. We performed the subgroup analyses according to the location of varices, CT technique, and study design. The study quality was assessed according to the QUADAS-2 tool.

RESULTS

Seventeen papers were eligible. The study quality was modest. The AUSROC was 0.8975 and 0.9494 for predicting any size and high-risk varices, respectively. Summary sensitivity, specificity, PLR, NLR, and DOR of CT for predicting any size and high-risk varices were 0.87/0.80/3.67/0.18/22.70 and 0.87/0.88/7.52/0.12/65.55, respectively. According to the location of varices, the AUSROC was 0.9127 for predicting any size gastric varices alone; and the AUSROC was 0.8958 and 0.9461 for predicting any size and high-risk esophageal varices alone, respectively. According to the CT technique, the AUSROC of multi-detector CT (MDCT) was 0.9047 and 0.9490 for predicting any size and high-risk varices, respectively; and the AUSROC of MDCT esophagograms for predicting any size and high-risk varices was 0.8735 and 0.9664, respectively. In the subgroup analysis of prospective studies, the AUSROC was 0.9122 and 0.9507 for predicting any size and high-risk varices, respectively.

CONCLUSION

CT had a high accuracy for the diagnosis of varices in liver cirrhosis.

Computed tomography in evaluating gastroesophageal varices in patients with portal hypertension: A meta-analysis

AIMS

Gastroesophageal varices (GOV) is a common complication in patients with portal hypertension. We conducted a meta-analysis in attempt to evaluate the diagnostic accuracy of computed tomography (CT) as a noninvasive imaging tool for identifying GOV in reference to esophagogastroduodenoscopy (EGD).

METHODS

A systemic literature search of multiple databases were conducted to identify articles that investigated the diagnostic performance of CT for GOV, while employing EGD as reference standard. A 2×2 table was conducted according to the available published data for both esophageal varices (EV) and gastric varices (GV) as individual subgroups. The following indices were calculated: pooled sensitivity and specificity, positive and negative likelihood ratio, diagnostic odds ratio, and area under receiver operating characteristics. All statistical analyses were conducted via STATA13.0 and RevMan5.3.

RESULTS

A total of 11 studies were included in this meta-analysis, 10 articles evaluated the diagnostic accuracy of CT for EV (807 subjects) and 7 articles for GV (583 subjects). The pooled sensitivity and specificity for identifying EV were 0.896 (95% CI, 0.841-0.934) and 0.723 (95% CI, 0.644-0.791), respectively, with an AUROC of 0.86. The pooled sensitivity and specificity for identifying GV were 0.955 (95% CI, 0.903-0.980) and 0.658 (95% CI, 0.433-0.829), respectively, with an AUROC of 0.95. A subgroup analysis suggested varying CT technology could serve as a potential source of heterogeneity between included studies. A Deek's funnel plot indicated a low probability for publication bias.

CONCLUSION

Computed tomography could potentially replace EGD as a primary screening tool for diagnosing GOV, however results should be interpreted with caution given its suboptimal specificity.