Journal of Gastric Cancer

The Korean Gastric Cancer Association (대한위암학회)
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Preoperative N Staging of Gastric Cancer by Stomach Protocol Computed Tomography

  • Kim, Se Hoon (Department of Surgery, Jeju National University School of Medicine) ;
  • Kim, Jeong Jae (Department of Radiology, Jeju National University School of Medicine) ;
  • Lee, Jeong Sub (Department of Radiology, Jeju National University School of Medicine) ;
  • Kim, Seung Hyoung (Department of Radiology, Jeju National University School of Medicine) ;
  • Kim, Bong Soo (Department of Radiology, Jeju National University School of Medicine) ;
  • Maeng, Young Hee (Department of Pathology, Jeju National University School of Medicine) ;
  • Hyun, Chang Lim (Department of Pathology, Jeju National University School of Medicine) ;
  • Kim, Min Jeong (Department of Surgery, Jeju National University School of Medicine) ;
  • Jeong, In Ho (Department of Surgery, Jeju National University School of Medicine)
  • Received : 2013.08.07
  • Accepted : 2013.09.03
  • Published : 2013.09.30
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Abstract

Purpose: Clinical stage of gastric cancer is currently assessed by computed tomography. Accurate clinical staging is important for the tailoring of therapy. This study evaluated the accuracy of clinical N staging using stomach protocol computed tomography. Materials and Methods: Between March 2004 and November 2012, 171 patients with gastric cancer underwent preoperative stomach protocol computed tomography (Jeju National University Hospital; Jeju, Korea). Their demographic and clinical characteristics were reviewed retrospectively. Two radiologists evaluated cN staging using axial and coronal computed tomography images, and cN stage was matched with pathologic results. The diagnostic accuracy of stomach protocol computed tomography for clinical N staging and clinical characteristics associated with diagnostic accuracy were evaluated. Results: The overall accuracy of stomach protocol computed tomography for cN staging was 63.2%. Computed tomography images of slice thickness 3.0 mm had a sensitivity of 60.0%; a specificity of 89.6%; an accuracy of 78.4%; and a positive predictive value of 78.0% in detecting lymph node metastases. Underestimation of cN stage was associated with larger tumor size (P<0.001), undifferentiated type (P=0.003), diffuse type (P=0.020), more advanced pathologic stage (P<0.001), and larger numbers of harvested and metastatic lymph nodes (P<0.001 each). Tumor differentiation was an independent factor affecting underestimation by computed tomography (P=0.045). Conclusions: Computed tomography with a size criterion of 8 mm is highly specific but relatively insensitive in detecting nodal metastases. Physicians should keep in mind that computed tomography may not be an appropriate tool to detect nodal metastases for choosing appropriate treatment.

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References

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