Portal vein computed tomography imaging characteristics and their relationship with bleeding risk in patients with

Xue-Jing Song1, Jing-Lei Liu2, Shu-Ya Jia3

  • 1Department of Medical Oncology, Shijiazhuang People's Hospital, Shijiazhuang 050000, Hebei Province, China.

PubMed

Insights

Multi-slice spiral CT perfusion imaging effectively predicts upper gastrointestinal bleeding in cirrhotic portal hypertension patients. Key indicators include gastric coronary vein diameter and vascular area, with vascular area showing the highest predictive power.

Area of Science:

  • Radiology
  • Gastroenterology
  • Medical Imaging

Background:

  • Cirrhotic portal hypertension poses a significant risk for upper gastrointestinal bleeding.
  • Accurate prediction of bleeding is crucial for timely intervention and improved patient outcomes.

Purpose of the Study:

  • To evaluate the predictive accuracy of multi-slice spiral CT perfusion imaging for upper gastrointestinal bleeding.
  • To identify specific imaging parameters that correlate with bleeding risk in patients with cirrhotic portal hypertension.

Main Methods:

  • A comparative study involving 62 patients with cirrhotic portal hypertension and 28 healthy controls.
  • Multi-slice spiral CT perfusion imaging was performed, analyzing parameters like vascular area, vessel count, and gastric coronary vein diameter (GCVD).
  • Statistical analysis identified predictors of upper gastrointestinal bleeding.

Main Results:

  • Vascular area, number of blood vessels, and GCVD were significantly higher in patients with bleeding compared to those without and controls.
  • All three parameters demonstrated a strong association with upper gastrointestinal bleeding.
  • Vascular area exhibited the highest predictive value (AUC = 0.831).

Conclusions:

  • Multi-slice spiral CT perfusion imaging is a valuable tool for predicting upper gastrointestinal bleeding in patients with cirrhotic portal hypertension.
  • GCVD, number of blood vessels, and vascular area are significant predictors.
  • Vascular area offers the strongest predictive capability for identifying bleeding risk.
Abstract

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