Objective: Diagnosing benign vs. malignant extrahepatic cholestasis is challenging despite the currently available advanced imaging and endoscopic techniques. This study aims to determine the predictive accuracy of initial biochemical data and bile duct dilatation findings in transabdominal ultrasound (US) to differentiate between benign and malignant disease in patients with extrahepatic cholestasis.
Patients And Methods: We reviewed the case records of 814 patients who had undergone endoscopic retrograde cholangiopancreatography (ERCP) or percutaneous transhepatic cholangiography (in cases of unsuccessful ERCP) for extrahepatic cholestasis. The etiology of biliary obstruction was determined based on ERCP, endoscopic ultrasonography, radiology, cytology, biopsy, and/or clinical follow-up at one year. The patients were divided into benign and malignant groups according to the underlying etiology of biliary obstruction. A complete biochemical profile, transabdominal ultrasonography at presentation, and other demographic data were recorded.
Results: Alkaline phosphatase (p = 0.002), aspartate aminotransferase (p = 0.038), and bilirubin levels were significantly higher in malignant patients. The mean age of patients with malignancy was 69.5 years, vs. 60.6 years in benign patients (p < 0.001). The likelihood of malignancy increased with the increased bilirubin levels (> 200 µmol/l: 30.0% sensitivity, 97.6% specificity). The total bilirubin level predicting malignancy as the best cut-off value was 111 mmol/L with optimum sensitivity and specificity (61.8% and 83.8%, respectively) and area under the curve = 0.756, (p < 0.001). Intrahepatic bile duct (IHBD) dilatation was significantly higher in malignant patients (p < 0.001).
Conclusions: A serum bilirubin level of 111 µmol/L or higher and the detection of IHBD dilatation on abdominal ultrasonography are important predictors in the differential diagnosis of benign and malignant causes of extrahepatic cholestasis.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.26355/eurrev_202312_34584 | DOI Listing |
Med Image Anal
January 2025
Department of Electrical and Computer Engineering, College of Information and Communication Engineering, Sungkyunkwan University, Suwon, 440-746, South Korea. Electronic address:
This study introduces HCC-Net, a novel wavelet-based approach for the accurate diagnosis of hepatocellular carcinoma (HCC) from abdominal ultrasound (US) images using artificial neural networks. The HCC-Net integrates the discrete wavelet transform (DWT) to decompose US images into four sub-band images, a lesion detector for hierarchical lesion localization, and a pattern-augmented classifier for generating pattern-enhanced lesion images and subsequent classification. The lesion detection uses a hierarchical coarse-to-fine approach to minimize missed lesions.
View Article and Find Full Text PDFHepatology
February 2025
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA.
Am J Case Rep
December 2024
Department of Otolaryngology, Military Institute of Aviation Medicine, Warsaw, Poland.
BACKGROUND The thyroglossal duct cyst, which develops from the midline migratory tract between the foramen cecum and the anatomic location of the thyroid, is the most prevalent congenital abnormality of the neck, accounting for about 70% of all cervical neck masses in children and 7% in adults. Only up to 1% of these abnormalities contain malignant thyroid tissue, with 90% of those cases being papillary thyroid carcinoma. Thyroglossal duct cyst is rarely linked to carcinoma.
View Article and Find Full Text PDFCureus
January 2025
College of Dentistry, King Saud University, Riyadh, SAU.
Oral melanocytic nevi (OMN) are rare benign tumors originating from melanocytes with an unclear pathogenesis. The current theory suggests that OMN originate from dormant dendritic melanocytes that become enclosed in the dermis during the embryonic migration of melanoblasts - the precursors of melanocytes - from the neural crest to the epidermis. OMN can be congenital or acquired, with acquired nevi being more common.
View Article and Find Full Text PDFAdv Appl Bioinform Chem
January 2025
Department of Information Technology, Mutah University, Al-Karak, Jordan.
Purpose: The incidence of cancer, which is a serious public health concern, is increasing. A predictive analysis driven by machine learning was integrated with haematology parameters to create a method for the simultaneous diagnosis of several malignancies at different stages.
Patients And Methods: We analysed a newly collected dataset from various hospitals in Jordan comprising 19,537 laboratory reports (6,280 cancer and 13,257 noncancer cases).
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!