Tumor thickness and paralingual distance of coronal MR imaging predicts cervical node metastases in oral tongue carcinoma

Masaya Okura, S. Iida, T. Aikawa, T. Adachi, N. Yoshimura, T. Yamada, M. Kogo

Research output: Contribution to journalArticle

41 Citations (Scopus)

Abstract

BACKGROUND AND PURPOSE: The presence of cervical lymph node metastases is an important prognostic factor for oral tongue cancer. The accurate preoperative assessment is essential for treatment. Several studies have suggested that histologic tumor thickness is related to the metastases. The aim of this study was to determine whether MR images of oral tongue tumor have the potential to predict cervical lymph node metastases. MATERIALS AND METHODS: A total of 43 patients with squamous cell carcinoma of the oral tongue were investigated. Tumor thickness, sublingual distance between tumor and sublingual space, and paralingual distance between tumor and paralingual space, as determined from coronal MR imaging, were preoperatively estimated. Logistic regression analysis was used to identify independent predictors of lymph node metastases. RESULTS: Univariate logistic regression analysis showed that T classification, N classification, and 3 measured MR imaging distances (millimeters) were significantly associated with lymph node metastases. Multivariate logistic regression analysis showed that tumor thickness (odds ratio, 1.34; 95% confidence interval [CI], 1.11-1.63; P < .005) and paralingual distance (odds ratio, 0.53; 95% CI, 0.35-0.82; P < .005) were significant predictors for lymph node metastases. The probability of metastases was estimated with these models. The preoperative decision (20% probability) as to whether to perform neck dissection could be based on tumor thickness of >9.7 mm and paralingual distance of <5.2 mm. CONCLUSION: MR images provide satisfactory accuracy for the preoperative estimation of the tumor thickness and the paralingual distance, which are valuable for predicting cervical lymph node metastases.

Original languageEnglish
Pages (from-to)45-50
Number of pages6
JournalAmerican Journal of Neuroradiology
Volume29
Issue number1
DOIs
Publication statusPublished - Jan 1 2008

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

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