Negative predictive value of preoperative computed tomography in determining pathologic local invasion, nodal disease, and abdominal metastases in gastric cancer

D. J. Kagedan, F. Frankul, A. El-Sedfy, C. McGregor, M. Elmi, B. Zagorski, M. E. Dixon, A. L. Mahar, J. Vasilevska-Ristovska, L. Helyer, C. Rowsell, C. J. Swallow, C. H. Law, Natalie Groce Coburn

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Background Before undergoing curative-intent resection of gastric adenocarcinoma (ga), most patients undergo abdominal computed tomography (ct) imaging to determine contraindications to resection (local invasion, distant metastases). However, the ability to detect contraindications is variable, and the literature is limited to single-institution studies. We sought to assess, on a population level, the clinical relevance of preoperative ct in evaluating the resectability of ga tumours in patients undergoing surgery. Methods In a provincial cancer registry, 2414 patients with ga diagnosed during 2005–2008 at 116 institutions were identified, and a primary chart review of radiology, operative, and pathology reports was performed for all patients. Preoperative abdominal ct reports were compared with intraoperative findings and final pathology reports (reference standard) to determine the negative predictive value (npv) of ct in assessing local invasion, nodal involvement, and intra-abdominal metastases. Results Among patients undergoing gastrectomy, the npv of ct imaging in detecting local invasion was 86.9% (n = 536). For nodal metastasis, the npv of ct was 43.3% (n = 450). Among patients undergoing surgical exploration, the npv of ct for intra-abdominal metastases was 52.3% (n = 407). Conclusions Preoperative abdominal ct imaging reported as negative is most accurate in determining local invasion and least accurate in nodal assessment. The poor npv of ct should be taken into account when selecting patients for staging laparoscopy.

Original languageEnglish (US)
Pages (from-to)273-279
Number of pages7
JournalCurrent Oncology
Issue number4
Publication statusPublished - Jan 1 2016


All Science Journal Classification (ASJC) codes

  • Oncology

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