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

研究成果: ジャーナルへの寄稿記事

33 引用 (Scopus)

抄録

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.

元の言語英語
ページ(範囲)45-50
ページ数6
ジャーナルAmerican Journal of Neuroradiology
29
発行部数1
DOI
出版物ステータス出版済み - 1 1 2008

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Tongue
Neoplasm Metastasis
Carcinoma
Lymph Nodes
Neoplasms
Logistic Models
Regression Analysis
Tongue Neoplasms
Mouth Neoplasms
Squamous Cell Carcinoma
Odds Ratio
Confidence Intervals

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

これを引用

Tumor thickness and paralingual distance of coronal MR imaging predicts cervical node metastases in oral tongue carcinoma. / Okura, Masaya; Iida, S.; Aikawa, T.; Adachi, T.; Yoshimura, N.; Yamada, T.; Kogo, M.

:: American Journal of Neuroradiology, 巻 29, 番号 1, 01.01.2008, p. 45-50.

研究成果: ジャーナルへの寄稿記事

Okura, Masaya ; Iida, S. ; Aikawa, T. ; Adachi, T. ; Yoshimura, N. ; Yamada, T. ; Kogo, M. / Tumor thickness and paralingual distance of coronal MR imaging predicts cervical node metastases in oral tongue carcinoma. :: American Journal of Neuroradiology. 2008 ; 巻 29, 番号 1. pp. 45-50.
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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.",
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N2 - 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.

AB - 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.

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