• In vivo · Sep 2017

    Lymph Node Size on Computed Tomography Images Is a Predictive Indicator for Lymph Node Metastasis in Patients with Colorectal Neuroendocrine Tumors.

    • Toshiaki Tanaka, Hiroaki Nozawa, Kazushige Kawai, Keisuke Hata, Tomomichi Kiyomatsu, Takeshi Nishikawa, Kensuke Otani, Kazuhito Sasaki, Koji Murono, and Toshiaki Watanabe.
    • Department of Surgical Oncology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan toshi-t@venus.dti.ne.jp.
    • In Vivo. 2017 Sep 1; 31 (5): 1011-1017.

    BackgroundColorectal neuroendocrine tumors (NET) are a rare manifestation of colorectal neoplasia, requiring for radical dissection of the regional lymph nodes along with colorectal resection similar to that required for colorectal cancer. However, thus far, no reports have described the ability of computed tomography (CT) to predict lymph node involvement. In this study, we revealed the prediction rate of lymph node metastasis using contrast-enhanced CT.Patients And MethodsA total of 21 patients with colorectal NET undergoing colorectal resection were recruited from January 2010 to June 2016. We compared the CT findings between samples with or without pathologically proven lymph node metastasis, in each field (pericolic/perirectal and intermediate nodes).ResultsWithin the pericolic/perirectal field, any lymph node larger than 5 mm in the CT images was a predictive indicator of lymph node metastasis with a sensitivity, specificity, and area under ROC curve (AUC) of 66.7%, 87.5%, and 0.844, respectively. Within the intermediate field, any visible lymph node on the CT was a predictive indicator of lymph node metastasis with a sensitivity, specificity, and AUC of 100%, 76.4%, and 0.890, respectively. In addition, when we observed lymph nodes larger than 3 mm on the CT images, the sensitivity and specificity were 100% and 82.4%, respectively, with an AUC of 0.8971.ConclusionCT images provide predictive information for lymph node metastasis with a high rate of accuracy.Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

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