ArticleFrontiers in medicine2022
Computed Tomography-Based Texture Features for the Risk Stratification of Portal Hypertension and Prediction of Survival in Patients With Cirrhosis: A Preliminary Study.
Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 9 citations in OpenAlex.
- Development of a clinical-CT-radiomics nomogram for predicting endoscopic red color sign in cirrhotic patients with esophageal varices.Abdominal radiology (New York) · 2026Article
- Computed tomography-based multi-organ radiomics nomogram model for predicting the risk of esophagogastric variceal bleeding in cirrhosis.World journal of gastroenterology · 2024Article
- Hepatic venous pressure gradient: Inaccurately estimates portal venous pressure gradient in alcoholic cirrhosis and portal hypertension.World journal of gastrointestinal surgery · 2023Article
- Surgomics: personalized prediction of morbidity, mortality and long-term outcome in surgery using machine learning on multimodal data.Surgical endoscopy · 2022Article
- Bibliometric-analysis visualization and review of non-invasive methods for monitoring and managing the portal hypertension.Frontiers in medicine · 2022Review
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Clinical evidence suggests that the risk stratification of portal hypertension (PH) plays a vital role in disease progression and patient outcomes. However, the gold standard for stratifying PH [portal vein pressure (PVP) measurement] is invasive and therefore not suitable for routine clinical practice. This study is aimed to stratify PH and predict patient outcomes using liver or spleen texture features based on computed tomography (CT) images non-invasively. Methods: A total of 114 patients with PH were included in this retrospective study and divided into high-risk PH (PVP ≥ 20 mm Hg, Results: Five texture features (one first-order feature from the liver and four wavelet features from the spleen) and the international normalized ratio (INR) were identified as statistically significant for stratifying PH ( Conclusion: CT-based texture features from the liver or spleen may have the potential to stratify PH and predict patient survival.
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