Prediction of Location of the Parotid Tumors that Cross Over Anatomical Criteria for Facial Nerve on Computed Tomography
10.3342/kjorl-hns.2018.00577
- Author:
Gyu Ho JANG
1
;
Deok Su KIM
;
Young Do JUNG
;
Youn Tae SEO
;
Bo Mun KIM
;
Bu Kwan KIL
;
Dong Won LEE
;
Ho Kyun KIM
;
Jeong Kyu KIM
Author Information
1. Department of Otolaryngology-Head and Neck Surgery, Catholic University of Daegu School of Medicine, Daegu, Korea. doctorjkkim@cu.ac.kr
- Publication Type:Original Article
- From:Korean Journal of Otolaryngology - Head and Neck Surgery
2019;62(3):176-181
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
BACKGROUND AND OBJECTIVES:To find more accurate way to determine the location of parotid tumors that cross anatomical criteria for the facial nerve (FN).SUBJECTS AND METHOD: Two hundred patients were included in the study and retrospectively studied. Five anatomical criteria were used to predict the location of parotid tumors on computed tomography (CT). Deep portion of tumors was measured and then, cut-off value was obtained after receiver operator curve analysis. The location of tumor was predicted by using the cut-off value and by the conventional way, in which the side where most of the tumor is located is determined as the tumor site.
RESULTS:The parotid tumors were located in superficial lobes in 148 cases, and in deep lobes in 52 cases by operative record. The tumors that cross the anatomical criteria were defined as ââ¬Ëcrossing tumor.ââ¬â¢ The cut-off values for prediction of ââ¬Ëcrossing tumorââ¬â¢ location on CT were 6.7 mm for anatomical line, 6.4 mm for FN line, 11.2 mm for retromandibular vein, 4.9 mm for Utrecht line and 3.8 mm for Conn's arc. The accuracy of 5 anatomical criteria for ââ¬Ëcrossing tumorââ¬â¢ was between 55.9% and 81.6% when the cut-off value was used, whereas the accuracy was between 25.7% and 68.9% when conventional way was used.
CONCLUSION:In cases of ââ¬Ëcrossing tumor,ââ¬â¢ the cut-off value obtained by measurement of deep portion of tumor can be applied to improve the diagnostic performance for the prediction of tumor location.
