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The Effectiveness of Ultrasonography in Diagnosis of Cervical Lymph Node Metastasis in Preoperative Esophageal Cancer

  • Shigenobu Asakura
  • Kin-Ichi Nabeya
  • Tateo Hanaoka
  • Tetsuya Nyumura
  • Yoshitaka Nakata
  • Choo Kaku
  • Osamu Kimura
  • Noboru Suzuki
  • Shojirou Koido
  • Masaru Asami
  • Takeyuki Asakura
Conference paper

Abstract

In determining treatment procedures, it is most important to diagnose cervical lymph node metastasis of esophageal cancer preoperatively. Heretofore, the conventional criteria for ultrasonography (US) in metastatic lymph nodes, as designated in the Guidelines for the Clinical and Pathologic Studies on Carcinoma of the Esophagus [1] were: (1) Well defined margins, (2) irregular inner echo images, and (3) longitudinal diameter over 5 mm. Lymph nodes satisfying all three criteria were diagnosed as metastatic. Investigations were made along these lines and it was found that sensitivity was 58.3%; specificity, 97.0%; accuracy, 80.7%; false positive, 17.5%; and false negative, 1.8%. In other words, with the current diagnostic criteria, anticipated delineation ratios could not be obtained. Therefore, keeping in mind the results of occupancy ratios of cancerous lesions within metastatic lymph nodes, new criteria that would be minimally influenced by the examination apparatus or by the examinee’s subjective point of view was established: (1) Ratio of longitudinal diameter to short axis over 0.5, and (2) lymph node longitudinal diameter over 0.5 cm. Lymph nodes satisfying these two criteria were considered to be metastatic. Investigations were made along these lines and it was found that sensitivity was 71.4%; specificity, 100%; accuracy, 87.7%; false positive, 10.5%; and false negative 0%. A satisfying delineation ratio was obtained.

Keywords

Lymph Node Esophageal Cancer Metastatic Lymph Node Cervical Lymph Node Cervical Lymph Node Metastasis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Tokyo 1993

Authors and Affiliations

  • Shigenobu Asakura
  • Kin-Ichi Nabeya
  • Tateo Hanaoka
  • Tetsuya Nyumura
  • Yoshitaka Nakata
  • Choo Kaku
  • Osamu Kimura
  • Noboru Suzuki
  • Shojirou Koido
  • Masaru Asami
  • Takeyuki Asakura
    • 1
  1. 1.Second Department of SurgeryKyorin University School of MedicineMitaka, Tokyo, 181Japan

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