Efficacy Analysis of Double‐Low Dynamic Contrast‐Enhanced CT and Hepatic Extracellular Volume Fraction in the Diagnosis of Liver Fibrosis

Liang, Zhandong; Liu, Yanxia; Nie, Yuan-Wen

doi:10.1155/2022/8089914

Cited by 2 publications

(1 citation statement)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Actually, in China, there were no FibroScan or FibroTouch in many hospitals. In China, for patients with liver cirrhosis, CT was used as a routine examination to determine the degree of liver cirrhosis and exclude malignant lesions[ 18 ].…”

Section: Discussionmentioning

confidence: 99%

Non-invasive model for predicting esophageal varices based on liver and spleen volume

Yang¹,

Zhao²,

Tantai³

et al. 2022

World J Clin Cases

View full text Add to dashboard Cite

BACKGROUND Upper endoscopy is the gold standard for predicting esophageal varices in China. Guidelines and consensus suggest that patients with liver cirrhosis should undergo periodic upper endoscopy, most patients undergo their first upper endoscopy when esophageal variceal bleeds. Therefore, it is important to develop a non-invasive model to early diagnose esophageal varices. AIM To develop a non-invasive predictive model for esophageal varices based on liver and spleen volume in viral cirrhosis patients. METHODS We conducted a cross-sectional study based on viral cirrhosis crowd in the Second Affiliated Hospital of Xi'an Jiaotong University. By collecting the basic information and clinical data of the participants, we derived the independent risk factors and established the prediction model of esophageal varices. The established model was compared with other models. Area under the receiver operating characteristic curve, calibration plot and decision curve analysis were used to test the discriminating ability, calibration ability and clinical practicability in both the internal and external validation. RESULTS The portal vein diameter, the liver and spleen volume, and volume change rate were the independent risk factors of esophageal varices. We successfully used the factors to establish the predictive model [area under the curve (AUC) 0.87, 95%CI: 0.80-0.95], which showed better predictive value than other models. The model showed good discriminating ability, calibration ability and the clinical practicability in both modelling group and external validation group. CONCLUSION The developed non-invasive predictive model can be used as an effective tool for predicting esophageal varices in viral cirrhosis patients.

show abstract

Section: Discussionmentioning

confidence: 99%

Non-invasive model for predicting esophageal varices based on liver and spleen volume

Yang¹,

Zhao²,

Tantai³

et al. 2022

World J Clin Cases

View full text Add to dashboard Cite

show abstract

Advancements of non‐invasive imaging technologies for the diagnosis and staging of liver fibrosis: Present and future

Huang,

Peng,

Kang

2024

VIEW

View full text Add to dashboard Cite

Liver fibrosis is a reparative response triggered by liver injury. Non‐invasive assessment and staging of liver fibrosis in patients with chronic liver disease are of paramount importance, as treatment strategies and prognoses depend significantly on the degree of fibrosis. Although liver fibrosis has traditionally been staged through invasive liver biopsy, this method is prone to sampling errors, particularly when biopsy sizes are inadequate. Consequently, there is an urgent clinical need for an alternative to biopsy, one that ensures precise, sensitive, and non‐invasive diagnosis and staging of liver fibrosis. Non‐invasive imaging assessments have assumed a pivotal role in clinical practice, enjoying growing popularity and acceptance due to their potential for diagnosing, staging, and monitoring liver fibrosis. In this comprehensive review, we first delved into the current landscape of non‐invasive imaging technologies, assessing their accuracy and the transformative impact they have had on the diagnosis and management of liver fibrosis in both clinical practice and animal models. Additionally, we provided an in‐depth exploration of recent advancements in ultrasound imaging, computed tomography imaging, magnetic resonance imaging, nuclear medicine imaging, radiomics, and artificial intelligence within the field of liver fibrosis research. We summarized the key concepts, advantages, limitations, and diagnostic performance of each technique. Finally, we discussed the challenges associated with clinical implementation and offer our perspective on advancing the field, hoping to provide alternative directions for the future research.

show abstract

Efficacy Analysis of Double‐Low Dynamic Contrast‐Enhanced CT and Hepatic Extracellular Volume Fraction in the Diagnosis of Liver Fibrosis

Cited by 2 publications

References 24 publications

Non-invasive model for predicting esophageal varices based on liver and spleen volume

Non-invasive model for predicting esophageal varices based on liver and spleen volume

Advancements of non‐invasive imaging technologies for the diagnosis and staging of liver fibrosis: Present and future

Contact Info

Product

Resources

About