A Study of the Relationship between USG and MRCP Findings in Biliary and Pancreatic Pathologies

  • Rajender Kumar Assistant Professor, Department of Radiology, World College of Medical Sciences Research and Hospital, Jhajjar Haryana, India
Keywords: Pancreatic duct, Malignant, Benign, USG & MRCP

Abstract

Introduction: The most common type of hepato-biliary pathology is obstructive jaundice. The aim of this study was to assess the diagnostic accuracy of two non-invasive modalities, ultrasound (USG) and magnetic resonance cholangiopancreatography (MRCP). Cases were investigated further. ERCP, surgical findings, and histopathology correlation all contributed to the diagnosis. Subjects and Methods: A total of 45 patients, 23 male and 22 female, ranging in age from 5 to 74 years, came with epigastric pain, decreased appetite, nausea, vomiting, fever with chills, and yellow skin and sclera. Ultrasound was performed on the patients, followed by MRCP. This study comprised patients of all ages, genders, and professions who had USG and MRCP and had strong clinical and lab evidence of biliary blockage. Results: In the study population, the accuracy of diagnosis of USG versus MRCP results in biliary and pancreatic diseases. In 31 (68.9%) cases, the reason of biliary blockage was benign, while in 14 cases, the cause was malignant (31.1%). Choledocholithiasis (26.9%) was the most prevalent benign obstruction, while periampullary carcinoma was the most common malignant obstruction (42.9%). Conclusion: In pancreaticobiliary diseases, MRCP is a better noninvasive approach than ultrasound. MRCP is a non-invasive, radiation-free method of evaluating the pancreaticobiliary tree. Multiplanar imaging and 3D reproduction are both possible with MRCP. Ultrasound is a non-invasive, non-radioactive technique.

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Published
2017-06-15
How to Cite
Kumar, R. (2017). A Study of the Relationship between USG and MRCP Findings in Biliary and Pancreatic Pathologies. Asian Journal of Medical Radiological Research, 5(2), 9-12. Retrieved from https://aijournals.com/index.php/ajmrr/article/view/2186