Computed Tomographic Portography with Esophageal Variceal Measurements in the Evaluation of Esophageal Variceal Severity and Assessment of Esophageal Variceal Volume Efficacy

3D slicer-based calculation of hematoma irregularity index for predicting hematoma expansion in intracerebral hemorrhage

BACKGROUND

Irregular hematoma is considered as a risk sign of hematoma expansion. The aim of this study was to quantify hematoma irregularity with computed tomography based on 3D Slicer.

METHODS

Patients with spontaneous intracerebral hemorrhage who underwent an initial and subsequent non-contrast computed tomography (CT) at a single medical center between January 2019 to January 2020 were retrospectively identified. The Digital Imaging and Communication in Medicine (DICOM) standard images were loaded into the 3D Slicer, and the surface area (S) and volume (V) of hematoma were calculated. The hematoma irregularity index (HII) was defined as [Formula: see text]. Logistic regression analyses and receiver operating characteristic (ROC) curve analysis were performed to assess predictive performance of HII.

RESULTS

The enrolled patients were divided into those with hematoma enlargement (n = 36) and those without the enlargement (n = 57). HII in hematoma expansion group was 130.4 (125.1-140.0), and the index in non-enlarged hematoma group was 118.6 (113.5-122.3). There was significant difference in HII between the two groups (P < 0.01). Multivariate logistic regression analysis revealed that the HII was significantly associated with hematoma expansion before (odds ratio = 1.203, 95% confidence interval [CI], 1.115-1.298; P < 0.001) and after adjustment for age, hematoma volume, Glasgow Coma Scale score (odds ratio = 1.196, 95% CI, 1.102-1.298, P < 0.001). The area under the ROC curve was 0.86 (CI, 0.78-0.93, P < 0.01), and the best cutoff of HII for predicting hematoma growth was 123.8.

CONCLUSION

As a quantitative indicator of irregular hematoma, HII can be calculated using the 3D Slicer. And the HII was independently correlated with hematoma expansion.

Assessment of variceal bleeding in cirrhotic patients: accuracy of multi-detector computed tomography

Background

Esophageal variceal hemorrhage (EVH) has been shown to be a leading cause of mortality in patients with portal hypertension. Our purpose was to assess the utility of multi-detector computed tomography (MDCT) features in the assessment of esophageal varices (EVs) and esophageal variceal hemorrhage (EVH). This prospective study included 85 cirrhotic patients who underwent MDCT and Upper Gastrointestinal Tract (UGIT) endoscopy within 2 weeks. Four radiologists evaluated the presence of EVs and the presence and size of different collaterals. Multivariable logistic regression analysis was calculated to investigate the significant predictors influencing EV and EVH.

Results

Findings of EV with MDCT were the best predictor of EV or EVH. The presence (and/or size) of following collaterals had significant association with both EV and EVH: paraesophageal (p < 0.001, < 0.001), short gastric (p = 0.024, 0.010), gastric varicosities (p < 0.001, < 0.001), coronary (p < 0.001, < 0.001), and main coronary vein (MCV) (p < 0.001, = 0.011). We proposed an imaging-based model (presence of coronary collaterals, main coronary vein size > 3.5 mm, presence of short gastric collaterals, presence of gastric varicosities, size > 1.5 mm) with 97% sensitivity, 91% specificity, and 94% accuracy to predict EVs. We suggested another model (presence of paraesophageal collaterals, presence of short gastric vein (SGC), SGC size > 2.5 mm, main coronary vein size > 3.5 mm, gastric varicosities size > 1.5 mm, size of EVs > 4 mm, and Child C score) to predict EVH with 98% sensitivity, 81% specificity, and 89.5% accuracy. Inter-observer agreement was high in the detection of EVs (W. Kappa = 0.71–0.88).

Conclusion

MDCT is an effective modality in the diagnosis of EVs. At MDCT, the presence and/or size of various collaterals including para-esophageal, short gastric, coronary collaterals, and gastric varicosities are accurate predictors for either EVs existence or EVH. We suggested two computed tomography imaging-based models with high reproducibility and acceptable accuracy for the prediction of EV and EVH. With cirrhotic patients, we recommend that radiologists report collaterals in their daily practice.

Quantitative measurements of esophageal varices using computed tomography for prediction of severe varices and the risk of bleeding: a preliminary study

BACKGROUND

We aimed to assess whether the quantitative parameters of esophageal varices (EV) based on computed tomography (CT) can noninvasively predict severe EV and the risk of esophageal variceal bleeding (EVB).

METHODS

A total of 136 endoscopically confirmed EV patients were included in this retrospective study and were divided into a non-conspicuous (mild-to-moderate EV, n = 30) and a conspicuous EV group (severe EV, n = 106), a bleeding (n = 89) and a non-bleeding group (n = 47). EV grade (EVG), EV diameter (EVD), cross-sectional surface area (CSA), EV volume (EVV), spleen volume (SV), splenic vein (SNV), portal vein (PV), diameter of left gastric vein (DLGV), and the opening type of LGV were measured independently using 3D-slicer. Univariate and multivariate logistic analysis were used to determine the independent factors and the receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic performance.

RESULTS

The difference of EVG, EVD, CSA, EVV, DLGV, SNV between the conspicuous and non-conspicuous EV group were statistically significant (p < 0.05), area under the curves (AUCs) of them for predicting severe EV were 0.72, 0.772, 0.704, 0.768, 0.707, 0.65, with corresponding sensitivities of 70.3%, 63.5%, 50%, 74.3%, 52.7%, 48.6%, specificities of 71.4%, 85.7%, 100%, 71.4%, 81%, 81%, respectively. EVG, CSA (odds ratio 3.258, 95% CI 1.597-6.647; 1.029, 95% CI 1.008-1.050) were found to be independent predictive factors. However, there was no significant difference of the included indices between the bleeding and non-bleeding group (p > 0.05).

CONCLUSIONS

CT can be used as a noninvasive method to predict the severity of EV, which may reduce the invasive screening of endoscopy.

CT-derived quantitative liver volumetric parameters for prediction of severe esophageal varices and the risk of first variceal hemorrhage

PURPOSE

To assess whether CT (computed tomography)-derived quantitative parameters of liver lobe volume can predict severe esophageal varices (EV) and the risk of first varicealhemorrhage (FVH) in patients with liver cirrhosis.

METHODS

A total of 217 endoscopically confirmed EV patients were included in this retrospective study and were divided into a low-risk EV group (mild-to-moderate EV, n = 83) and a high-risk EV group (severe EV, n = 134), a FVH group (n = 17) and a non-FVH group (n = 27), patients' clinical findings were recorded. The left, right, caudate lobe, total liver volume and the corresponding functional volume were measured respectively, and the ratio of caudate volume/total volume (CV/TV), caudate functional volume/total functional volume (CFV/TFV) were calculated. Univariate and multivariate logistic analysis were used to determine the independent factors and the receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic performance.

RESULTS

CV, CFV, CV/TV, CFV/TFV were significantly different in the EV severity study and FVH study (p < 0.05). Multivariate analysis indicated that CV/TV and ascites were independent predictive factors for severe EV, a predictive model combing those two factors revealed a satisfactory diagnostic performance (area under the curve (AUC), 0.853, 95 %CI 0.797-0.905). Furthermore, CV/TV and the presence of red color sign under endoscopy were found to be independent predictive factors for FVH, and the former showed a better discriminative performance than the latter (AUC, 0.851 vs 0.779).

CONCLUSIONS

CT-derived quantitative parameters of CV, CFV, CV/TV, CFV/TFV may be used as an alternative to endoscopy in predicting severe varices and the risk of bleeding.

Multiparametric radiomics nomogram may be used for predicting the severity of esophageal varices in cirrhotic patients

Background

To explore whether a multiparametric radiomics nomogram on computed tomography (CT) images based on radiomics and relevant parameters of esophageal varices (EV) can be used for predicting the EV severity in patients with cirrhotic livers.

Methods

From January 2016 to August 2018, 136 consecutive patients with clinicopathologically confirmed liver cirrhosis were included for the development of a predictive model. The patients were then divided into two groups, including non-conspicuous EV group (mild-to-moderate EV, n=30) and conspicuous EV group (severe EV, n=106) by using the endoscopic validation as the reference standard. The radiomic scores (Rad scores) were constructed using the binary logistic regression model from the radiomics features of regions of interest (ROIs) in the left liver (LL) and right liver (RL), respectively. The multiparametric nomogram combined the best performance Rad-score and EV-relevant factors, and the calibration, discrimination, and clinical usefulness of developed nomogram were evaluated using calibration curves, decision curve analysis (DCA) and net reclassification index (NRI) analysis respectively.

Results

The LL Rad-score calculated from radiomics features was selected with a relatively higher area under the curve (AUC) (AUC; 0.88, training cohort; 0.87, the validation cohort) compared with RL Rad-score (AUC; 0.86, training cohort; 0.83, the validation cohort). In addition, cross-sectional surface area (CSA) was identified as the important predictor (P<0.05), the multiparametric nomogram containing LL Rad-score and CSA was shown to have a better predictive performance and good calibration in the training model (C-index, 0.953, 95% CI, 0.892 to 0.973) and the validation cohort (C-index, 0.938, 95% CI, 0.841 to 0.961), resulting in an improved NRI (categorical NRI of 25.9%, P=0.0128; continuous NRI of 120%, P<0.001) and integrated discriminatory improvement (IDI) (IDI =13.9%, P<0.001). DCA demonstrated that the multiparametric radiomics nomogram was clinically useful.

Conclusions

A multiparametric radiomics nomogram, which incorporates the liver radiomics signature and EV-relevant indices, is a useful tool for noninvasively predicting EV severity and may complement the standard endoscopy for evaluating EV severity in patients with cirrhosis.