Oral surgery, oral medicine, oral pathology and oral radiology · 2020
Depth of invasion determined by magnetic resonance imaging in tongue cancer can be a predictor of cervical lymph node metastasis.
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Haraguchi Kazuya, Yoshiga Daigo, Oda Masafumi, Tabe Shirou, Mitsugi Sho, Takahashi Osamu, Habu Manabu, Sasaguri Masaaki, Morimoto Yasuhiro, Yoshioka Izumi, Tominaga Kazuhiro
Аннотация
OBJECTIVES: We evaluated the relationships between depth of invasion (DOI) of tongue cancer, as measured with preoperative T1- and T2-weighted magnetic resonance imaging (MRI) and postoperative histopathologic (Path) specimens, with cervical lymph node metastasis (CLNM) and tumor stage. We also calculated the correlation of MRI and Path DOI measurements.
STUDY DESIGN: This retrospective study included 101 patients who had squamous cell carcinoma of the tongue and were treated surgically. Two observers measured DOI on all 3 modalities.
RESULTS: DOI thresholds for predicting CLNM with high diagnostic efficacy were 6.99 mm and 8.32 mm for MRI and 5 mm for Path. DOI values from all modalities were significantly different for tumors with and without CLNM (P < .01) and for the 4 TNM stages (P ≤ .05), with increasing values corresponding to advancement in tumor stage. Addition of DOI changed the T level of many tumors based on the new TNM (tumor-node-metastasis) classification. The correlation coefficient between DOI calculated on each MRI sequence and Path was 0.90.
CONCLUSIONS: MRI-derived DOI accurately reflected the subsequent metastatic status and degree of progression of tumor stages, with a strong positive correlation to Path values, and may be considered a predictor of tumor stage and CLNM.
STUDY DESIGN: This retrospective study included 101 patients who had squamous cell carcinoma of the tongue and were treated surgically. Two observers measured DOI on all 3 modalities.
RESULTS: DOI thresholds for predicting CLNM with high diagnostic efficacy were 6.99 mm and 8.32 mm for MRI and 5 mm for Path. DOI values from all modalities were significantly different for tumors with and without CLNM (P < .01) and for the 4 TNM stages (P ≤ .05), with increasing values corresponding to advancement in tumor stage. Addition of DOI changed the T level of many tumors based on the new TNM (tumor-node-metastasis) classification. The correlation coefficient between DOI calculated on each MRI sequence and Path was 0.90.
CONCLUSIONS: MRI-derived DOI accurately reflected the subsequent metastatic status and degree of progression of tumor stages, with a strong positive correlation to Path values, and may be considered a predictor of tumor stage and CLNM.