Diagnosing pancreatic cancer: the role of percutaneous biopsy and CT

Autor: C.V. House, B. Theis, R.C.G. Russell, William R. Lees, M. Novelli, Zahir Amin
Rok vydání: 2006
Předmět:
Zdroj: Clinical Radiology. 61:996-1002
ISSN: 0009-9260
DOI: 10.1016/j.crad.2006.07.005
Popis: Aims To determine the sensitivity and complications of percutaneous biopsy of pancreatic masses, and whether typical computed tomography (CT) features of adenocarcinoma can reliably predict this diagnosis. Materials and methods A 5 year retrospective analysis of percutaneous core biopsies of pancreatic masses and their CT features was undertaken. Data were retrieved from surgical/pathology databases; medical records and CT reports and images. Results Three hundred and three patients underwent 372 biopsies; 56 of 87 patients had repeat biopsies. Malignancy was diagnosed in 276 patients, with ductal adenocarcinoma in 259 (85%). Final sensitivity of percutaneous biopsy for diagnosing pancreatic neoplasms was 90%; for repeat biopsy it was 87%. Complications occurred in 17 (4.6%) patients, in three of whom the complications were major (1%): one abscess, one duodenal perforation, one large retroperitoneal bleed. CT features typical of ductal adenocarcinoma were: hypovascular pancreatic mass with bile and/or pancreatic duct dilatation. Atypical CT features were: isodense or hypervascular mass, calcification, non-dilated ducts, cystic change, and extensive lymphadenopathy. Defining typical CT features of adenocarcinoma as true-positives, CT had a sensitivity of 68%, specificity of 95%, positive predictive value (PPV) of 98%, and negative predictive value of 41% for diagnosing pancreatic adenocarcinoma. Conclusion Final sensitivity of percutaneous biopsy for establishing the diagnosis was 90%. CT features typical of pancreatic adenocarcinoma had high specificity and PPV. On some occasions, especially in frail patients with co-morbidity, it might be reasonable to assume a diagnosis of pancreatic cancer if CT features are typical, and biopsy only if CT shows atypical features.
Databáze: OpenAIRE