Analysis of Extrahepatic Obstructive Jaundice Based on Multislice Spiral Computed Tomography
Objective: To evaluate the value of multislice spiral Computed Tomography in the diagnosis and differential diagnosis of extrahepatic obstructive jaundice. Methods: A retrospective analysis was performed on 78 cases of extrahepatic obstructive jaundice confirmed by surgery
and clinical analysis. All cases were divided into two groups according to benign and malignant, 41 in benign and 37 in malignant. Twenty of them performed enhanced scanning, and image post-processing was performed. We observe the quantitative and qualitative indicators of CT: the inner diameter
of the common bile duct, the extent of intrahepatic bile duct dilation, the length of the obstruction site from the hilar region; the presence or absence of stones, the location of the mass and the mass, the relationship between the mass and the common bile duct, and the degree of mass enhancement. Results: All cases clearly showed the obstruction site, and the difference between the obstruction site and the hepatic hilar length was significant between the benign and malignant groups (P < 0.01); while in the malignant group, there was also a statistical difference between
cholangiocarcinoma and pancreatic head cancer and ampulla (P < 0.05). There was no significant difference in the common bile duct inner diameter among the groups (P > 0.05). Conclusions: Multi-slice spiral CT is more accurate in distinguishing the location, etiology,
and malignancy of extrahepatic obstructive jaundice. It is of great value in the diagnosis and differential diagnosis of extrahepatic obstructive jaundice.
Keywords: CANCER; MEDICAL IMAGING; MULTISLICE SPIRAL COMPUTED TOMOGRAPHY; OBSTRUCTIVE JAUNDICE
Document Type: Research Article
Publication date: 01 December 2020
- Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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