The value of MRI texture analysis based on gray level co-occurrence matrix to predict cervical lymph node metastasis in tongue carcinoma patients

Abstract

Objective To evaluate the value of MRI texture analysis based on gray level co-occurrence matrix to predict cervical lymph node metastasis in patients with tongue carcinoma. Methods A total of 70 patients with tongue carcinoma confirmed by pathology were analyzed retrospectively. The patients were divided into cervical lymph node (LN) metastasis group (unilateral LN+,n=18; bilateral LN+,n=22) and no cervical lymph node metastasis(LN-,n=30). T1W, T2W and contrast-enhanced T1W images of the largest section of tumor were selected. ROI of the lesion was manually drew and GLCM texture parameters (energy, contrast, correlation, inverse difference and entropy) were extracted. The tumor length, thickness and para-lingual distance between tumor and tongue midline were also measured. Differences of all parameters were compared between LN+ group and LN- group, unilateral and bilateral cervical lymph node metastasis group, the parameters with statistically significant difference in predicting the efficiency of cervical lymph node metastasis were analyzed. The diagnostic efficiency of lymph node metastasis was calculated. Results The correlation, inverse difference and entropy based on T2WI showed significant difference (Zcorrelation=2.97, tinverse difference=5.14, tentropy=2.41; P 0.05). The diagnostic sensitivity of radiologists was 65.0% (26/40), the specificity was 80.0% (24/32) on cervical lymph node metastasis. Conclusion Texture analysis based on T2WI can predict cervical lymph node metastasis in patients with tongue carcinoma. Entropy has certain value in predicting bilateral cervical lymph node metastasis. Key words: Tongue neoplasms; Lymphatic metastasis; Magnetic resonance imaging; Gray level co-occurrence matrix; Texture analysis