A simple morphological classification to estimate the malignant potential of pancreatic neuroendocrine tumors

Background A novel morphological classification using resected specimens predicted malignant potential and prognosis in patients with pancreatic neuroendocrine tumors (P-NETs). The aim of this study was to examine the predictive ability of morphological diagnoses made using non-invasive multi-detector computed tomography (MDCT) in P-NETs. Methods Between 2002 and 2015, 154 patients were diagnosed with P-NETs at the Tokyo Medical and Dental University, and 82 patients who underwent surgical treatment were enrolled. The primary tumors were classified by MDCT into three types: Type I, simple nodular tumor; Type II, simple nodular tumor with extra-nodular growth; and Type III, confluent multinodular tumor. Patients were stratified by 15 clinical specialists according to classification and without any other clinical or pathological information. Clinicopathological features and patient survival were reviewed retrospectively. Results The mean observation time was 1004 days. Forty-six, 22, and 14 patients had Type I, II, and III tumors, respectively. Morphological classification was significantly correlated with advanced features such as tumor size, Ki-67 index, and synchronous liver metastasis ( p